Addiction: Brain and Cognitive Stimulation for Better Cognitive Control and Far Beyond

*Xavier Noël, Antoine Bechara, Mélanie Saeremans, Charles Kornreich, Clémence Dousset, Salvatore Campanella, Armand Chatard, Nemat Jaafari and Macha Dubuson*

## **Abstract**

Addiction behaviors are characterized by conditioned responses responsible for craving and automatic actions as well as disturbances within the supervisory network, one of the key elements of which is the inhibition of prepotent response. Interventions such as brain stimulation and cognitive training targeting this imbalanced system can potentially be a positive adjunct to treatment as usual. The relevance of several invasive and noninvasive brain stimulation techniques in the context of addiction as well as several cognitive training protocols is reviewed. By reducing cue-induced craving and modifying the pattern of action, memory associations, and attention biases, these interventions produced significant but still limited clinical effects. A new refined definition of response inhibition, including automatic inhibition of response and a more consistent approach to cue exposure capitalizing on the phase of reconsolidation of pre-activated emotional memories, all associated with brain and cognitive stimulation, opens new avenues for clinical research.

**Keywords:** addiction, inhibition, brain stimulation, memory reconsolidation, cue exposure

## **1. Introduction**

Despite considerable progress in detoxification, pharmacology, and psychological interventions in addictive behaviors, clinical outcomes remain suboptimal (e.g., high relapse rate or poor quality of life) [1]. The main reason of the poor clinical outcomes is likely to be related to multiple interacting determinants of social, psychological, and biological mechanisms involved in the addiction risk and the relapse, a view that is not compatible with pure essentialism and simplistic approaches of addiction [2].

Inter-individual variations within the addiction group in respect to neurobiological mechanisms of addiction were highlighted by influential theorizations [3–9]. Indeed, addictive behaviors can be viewed as the product of an imbalance between separate, but interacting, neural systems: an impulsive, largely amygdalastriatum-dependent, neural system that promotes automatic, habitual, and salient behaviors; a reflective, mainly prefrontal cortex-dependent, neural system for decision-making, forecasting the future consequences of a behavior, and inhibitory control; and the insula that integrates interoception states into conscious feelings and decision-making processes that are involved in uncertain risk and reward. Any imbalance in the dynamics of these systems can account for poor decision-making (i.e., prioritizing short-term consequences of a decisional option), and the lack of willpower [10–12], which heightens the risk for addiction and relapse.

As part of the "executive network" involving ventrolateral prefrontal cortex and dorsolateral prefrontal cortex, response inhibition interacts with automatic behavioral ("habit network") and motivational responses ("reward network") to produce flexible actions and adaptive choices. Indeed, the inhibition of a prepotent response has become an important element of the responsible braking system and limiting the expression of spontaneous motivation and emotion signals [13]. Indeed, successful self-regulation requires the ability to inhibit impulses that are not compatible with one's goals [14].

Importantly, psychostimulant dependence, alcohol dependence, and gambling disorders have been consistently associated with a response inhibition deficit [5]. However, the deficit in inhibition observed in addiction population is generally of low or moderate effect size [15, 16]. Nevertheless, even a small effect size can have clinically relevant effects, as evidenced by the impact of impaired response inhibition on the risk of dependence and response to treatment [9, 17–19]. Indeed, response inhibition is considered as a primary candidate for cognitive remediation that can potentially reduce the risk of addiction and the relapse [20]. As an alternative way consistent with dual-process theories, to limit these risks is to reduce the need for inhibitory control, for instance, by dampening automatic conditioned responses (e.g., craving, attentional and memory biases) triggered by contextual (e.g., the sight of a bottle of beer) or internal (e.g., negative effects) cues. In addition, more automatic forms of response inhibition could be trained in the hope of enabling individuals to generate appropriate alcohol-stop associations without too much of an effortful process [21].

In this chapter, we investigate the manner the risk associated with too limited response inhibition can be reduced by implementing multiple forms of cognitive training, invasive and noninvasive brain stimulation techniques, and neurofeedback (NF). It should be noted that an overwhelming majority of neuroscientists engaged in brain stimulation in psychopathology has truly viewed brain-based interventions as complementary interventions to clinical treatments such as cognitive-behavioral therapy and motivational enhancement intervention [22, 23]. Indeed, the beliefs, desires, emotions, and intentions of patients are essential elements to take into account [2], which can be modulated by brain- and cognitive-based interventions.

After a brief presentation of response inhibition theories and methods, we summarize cognitive training intervention in the context of addictive behaviors as well as three brain stimulation techniques (i.e., deep brain stimulation, electric and magnetic brain stimulation) and finally protocols of neurofeedback. We then develop more complex clinical and research concepts (e.g., combined cognitive training and brain stimulation along with cue exposure interventions).

## **2. Executive functioning, response inhibition, and self-regulation: terminological and theoretical clarifications**

Numerous terms have often been used to describe similar concepts. For example, concepts such as self-regulation, inhibition, executive function, cognitive control, effortful processes, impulsivity, risk-taking, and disinhibition are sometimes clearly

**29**

*Addiction: Brain and Cognitive Stimulation for Better Cognitive Control and Far Beyond*

delineated but sometimes are used as synonyms or closely related concepts [24]. Attempts to clarify those concepts (e.g., the degree that some of those constructs overlap) have been scarce but mostly suggest that intrinsic aspects of regulation, self-regulation, serve as an umbrella concept that encompasses top-down and bottom-up processes that mutually influence one another [24–26]. Naturally, the influence of extrinsic aspects of regulation, that is, facilitated or hindered selfregulation due to others' mind and action, is far to be negligible and should be considered to fully apprehend the determinants of dysregulated actions, such as

As suggested by William James, "Voluntary action, then, is at all times a resultant of the compounding of our impulsions with our inhibitions" [29]. In order to control the desire, the reason takes place as represented like Plato seeing the will as a charioteer attempting to control two horses (one of desire and one of reason) in Phaedrus. For both Hippocrates and Aristotle, the body and mind are not independent, but each influences the other. Long after, the fundamental duality between reason and emotion conferred to will the essence to control (or inhibit) action and emotion. A few decades later, Sherrington was awarded the 1932 Nobel Prize for Physiology and Medicine for his contribution to our understanding of inhibition in

Although creating a sense of comfort in theorizing, the explanation (e.g., brain structure in the frog that inhibits a spinal reflex) based on similarity to excitatory or inhibitory functions of the nervous system (i.e., neurons can serve either functions) that strong impulses can be impeded through the implementation of inhibition

Because of this warning, presenting an operational definition of "inhibition" remains an adventurous venture, not only because of the weight of its intuitive load (e.g., cognitive inhibition is equivalent to neural inhibition sometimes as metaphor) but also because of the phenomenon and explanation conflation or a confusion

In most cases, response inhibition mainly refers to the suppression of actions that are no longer required or that are inappropriate, which supports flexible and goal-directed behavior in ever-changing environments [32]. As such, given its role in supervising ongoing thoughts and action in working memory, response inhibition has been considered as a hallmark of executive functions [33, 34]. As a form of top-down (intentional) inhibition process, prepotent response inhibition refers to deliberate inhibition operating on basic and reactive elements of action, which is essentially non-automatic and represents a cost. Intentional control depends on motivation and capacity [35]; it is subjectively deliberate, slow, and sequential; and

However, a growing amount of data challenged this strictly hierarchical view [36, 37]. Indeed, executive control emerges from an interactive and competitive network generating biases in advance and is strongly influenced by personal recent and past experiences. Indeed, humans automatize as much as possible; hence apparent intentional inhibition can in fact operate automatically for particular contexts, due to context-inhibition associations made through learning. For instance, on the stop-signal task [32], when people are informed that they may have to stop a response in the near future, they typically slow down operation through altering activity in lower-level systems that are involved in stimulus detection, action selection, and action execution [38]. Put differently, instead of relying only on executive functioning, low-level and high-level systems work together for self-regulation.

*DOI: http://dx.doi.org/10.5772/intechopen.88869*

addictive behaviors [27, 28].

**2.1 Inhibition in definition**

remains a debated matter [30].

neurophysiology, which consolidated the concept.

between a causal process and a functional relationship [31].

it requires working memory and is capacity-limited.

*Addiction: Brain and Cognitive Stimulation for Better Cognitive Control and Far Beyond DOI: http://dx.doi.org/10.5772/intechopen.88869*

delineated but sometimes are used as synonyms or closely related concepts [24]. Attempts to clarify those concepts (e.g., the degree that some of those constructs overlap) have been scarce but mostly suggest that intrinsic aspects of regulation, self-regulation, serve as an umbrella concept that encompasses top-down and bottom-up processes that mutually influence one another [24–26]. Naturally, the influence of extrinsic aspects of regulation, that is, facilitated or hindered selfregulation due to others' mind and action, is far to be negligible and should be considered to fully apprehend the determinants of dysregulated actions, such as addictive behaviors [27, 28].

## **2.1 Inhibition in definition**

*Inhibitory Control Training - A Multidisciplinary Approach*

compatible with one's goals [14].

much of an effortful process [21].

behaviors; a reflective, mainly prefrontal cortex-dependent, neural system for decision-making, forecasting the future consequences of a behavior, and inhibitory control; and the insula that integrates interoception states into conscious feelings and decision-making processes that are involved in uncertain risk and reward. Any imbalance in the dynamics of these systems can account for poor decision-making (i.e., prioritizing short-term consequences of a decisional option), and the lack of

As part of the "executive network" involving ventrolateral prefrontal cortex and dorsolateral prefrontal cortex, response inhibition interacts with automatic behavioral ("habit network") and motivational responses ("reward network") to produce flexible actions and adaptive choices. Indeed, the inhibition of a prepotent response has become an important element of the responsible braking system and limiting the expression of spontaneous motivation and emotion signals [13]. Indeed, successful self-regulation requires the ability to inhibit impulses that are not

Importantly, psychostimulant dependence, alcohol dependence, and gambling disorders have been consistently associated with a response inhibition deficit [5]. However, the deficit in inhibition observed in addiction population is generally of low or moderate effect size [15, 16]. Nevertheless, even a small effect size can have clinically relevant effects, as evidenced by the impact of impaired response inhibition on the risk of dependence and response to treatment [9, 17–19]. Indeed, response inhibition is considered as a primary candidate for cognitive remediation that can potentially reduce the risk of addiction and the relapse [20]. As an alternative way consistent with dual-process theories, to limit these risks is to reduce the need for inhibitory control, for instance, by dampening automatic conditioned responses (e.g., craving, attentional and memory biases) triggered by contextual (e.g., the sight of a bottle of beer) or internal (e.g., negative effects) cues. In addition, more automatic forms of response inhibition could be trained in the hope of enabling individuals to generate appropriate alcohol-stop associations without too

In this chapter, we investigate the manner the risk associated with too limited response inhibition can be reduced by implementing multiple forms of cognitive training, invasive and noninvasive brain stimulation techniques, and neurofeedback (NF). It should be noted that an overwhelming majority of neuroscientists engaged in brain stimulation in psychopathology has truly viewed brain-based interventions as complementary interventions to clinical treatments such as cognitive-behavioral therapy and motivational enhancement intervention [22, 23]. Indeed, the beliefs, desires, emotions, and intentions of patients are essential elements to take into account [2], which can be modulated by brain- and cognitive-based interventions. After a brief presentation of response inhibition theories and methods, we summarize cognitive training intervention in the context of addictive behaviors as well as three brain stimulation techniques (i.e., deep brain stimulation, electric and magnetic brain stimulation) and finally protocols of neurofeedback. We then develop more complex clinical and research concepts (e.g., combined cognitive

training and brain stimulation along with cue exposure interventions).

**terminological and theoretical clarifications**

**2. Executive functioning, response inhibition, and self-regulation:** 

Numerous terms have often been used to describe similar concepts. For example, concepts such as self-regulation, inhibition, executive function, cognitive control, effortful processes, impulsivity, risk-taking, and disinhibition are sometimes clearly

willpower [10–12], which heightens the risk for addiction and relapse.

**28**

As suggested by William James, "Voluntary action, then, is at all times a resultant of the compounding of our impulsions with our inhibitions" [29]. In order to control the desire, the reason takes place as represented like Plato seeing the will as a charioteer attempting to control two horses (one of desire and one of reason) in Phaedrus. For both Hippocrates and Aristotle, the body and mind are not independent, but each influences the other. Long after, the fundamental duality between reason and emotion conferred to will the essence to control (or inhibit) action and emotion. A few decades later, Sherrington was awarded the 1932 Nobel Prize for Physiology and Medicine for his contribution to our understanding of inhibition in neurophysiology, which consolidated the concept.

Although creating a sense of comfort in theorizing, the explanation (e.g., brain structure in the frog that inhibits a spinal reflex) based on similarity to excitatory or inhibitory functions of the nervous system (i.e., neurons can serve either functions) that strong impulses can be impeded through the implementation of inhibition remains a debated matter [30].

Because of this warning, presenting an operational definition of "inhibition" remains an adventurous venture, not only because of the weight of its intuitive load (e.g., cognitive inhibition is equivalent to neural inhibition sometimes as metaphor) but also because of the phenomenon and explanation conflation or a confusion between a causal process and a functional relationship [31].

In most cases, response inhibition mainly refers to the suppression of actions that are no longer required or that are inappropriate, which supports flexible and goal-directed behavior in ever-changing environments [32]. As such, given its role in supervising ongoing thoughts and action in working memory, response inhibition has been considered as a hallmark of executive functions [33, 34]. As a form of top-down (intentional) inhibition process, prepotent response inhibition refers to deliberate inhibition operating on basic and reactive elements of action, which is essentially non-automatic and represents a cost. Intentional control depends on motivation and capacity [35]; it is subjectively deliberate, slow, and sequential; and it requires working memory and is capacity-limited.

However, a growing amount of data challenged this strictly hierarchical view [36, 37]. Indeed, executive control emerges from an interactive and competitive network generating biases in advance and is strongly influenced by personal recent and past experiences. Indeed, humans automatize as much as possible; hence apparent intentional inhibition can in fact operate automatically for particular contexts, due to context-inhibition associations made through learning. For instance, on the stop-signal task [32], when people are informed that they may have to stop a response in the near future, they typically slow down operation through altering activity in lower-level systems that are involved in stimulus detection, action selection, and action execution [38]. Put differently, instead of relying only on executive functioning, low-level and high-level systems work together for self-regulation.

#### **Figure 1.**

*Executive function classification proposed by [33].*

Although closely related to executive functioning, response inhibition can be distinct from other forms of executive functions such as working memory update (i.e., the ability to replace information stored in working memory with new information) and switching (i.e., the ability to shift attention to other tasks or perceptual dimensions) [33] (see **Figure 1**).

Based on latent variable analysis, several forms of response inhibition could be distinguished [39–42]. A first distinction has been made between the inhibition of prepotent response and the resistance to distracter interference. However, the robustness of this two-factor solution remains questionable in light of low correlations between inhibition measures, when the contribution of memory processes was intentionally reduced [41]. It follows from this discussion that studies using a single laboratory paradigm for assessing or investigating inhibition do not warrant generalization beyond the specific paradigm studied.

More fine-grained forms of inhibition have been put forward across the years [39, 41]. Indeed, resistance to proactive interference consists of resisting memory intrusions from information that was previously relevant to the task but has since become irrelevant.

A second categorization relies on the degree of anticipation and preparation of response inhibition [43, 44]. Reactive inhibition (or reflexive inhibition) is a form of inhibition that one can implement without anticipation (e.g., stopping the car when an animal unexpectedly jumps on to the road). Proactive inhibition refers to the impact of inhibition preparation on the inhibitory performance (e.g., keeping one's foot close to the brake after passing a warning sign for animals on the road). Possibly because proactive form of response inhibition requires much more than just inhibition, as attested by shared brain contribution of both forms of inhibition (the right inferior frontal gyrus, supplementary motor area and striatum) and also specific engagement of working memory-related regions (i.e., dorsolateral prefrontal region) [45], proactive inhibition may be more ecologically valid than reactive inhibition [46].

Sufficient agreement can be found on the contributions of these different inhibitory control mechanisms as measured by a variety of cognitive tasks described by Friedman and Miyake [39]. The list of tasks includes the color Stroop, anti-saccade,

**31**

alcohol use [71].

*Addiction: Brain and Cognitive Stimulation for Better Cognitive Control and Far Beyond*

repetition costs tend to assess resistance to distracter interference.

influence behavioral and substance addictions later in life [17, 61].

stop-signal, simon, global-local, and negative compatibility tasks that could share a component of inhibition of prepotent response; the letter flanker, the number Stroop, arrow flanker, and negative compatibility as well as the task assessing n-2

Consistent with the previous discussion, response disinhibition is an important element of modern addiction models [6, 9], and empirical data support this claim, particularly for gambling, psychostimulant, and alcohol addiction [5]. By conferring a central position to response inhibition, brain imaging and behavioral studies demonstrated abnormal functioning in individuals at risk to develop an addictive behavior, in addicted people, and in individuals who relapsed [9, 47, 48]. Indeed, a variety of response inhibition deficits are present in numerous forms of reinforcement pathologies (e.g., tobacco dependence [49, 50], alcohol disorder [51, 52], eating disorders [53, 54], gambling disorder [55] (but see [56])). Second, those deficits can predict relapse in drug and behavioral addiction [18, 57, 58], and research suggests that recently abstinent addicts experience heightened difficulties with response inhibition [59, 60]. Thirdly, the inability to stop one's actions, due notably to early stressful life events and negative parent–child interaction [61], can

In addition, it should be noted that impaired response inhibition has a strong impact in important aspects of decision-making. For instance, impaired prepotent response inhibition in alcoholics was associated with poorer performance on the Iowa gambling task [62], which requires participants to deal with uncertainty in a context of punishment and reward, with some choices being advantageous in the short term (high reward) but disadvantageous in the long run (higher punishment) and known for its ecological validity of decision-making [63–65]. Risk-taking could also be modulated through inhibitory control engagement, with participants being more cautious once anticipating to suppress their response [66]. Unfortunately, the benefit of this form of inhibitory training is fragile and transitory [67]. Besides, data from a sample of pathological gamblers revealed no effect of this procedure on risk-taking [68]. Finally, prepotent response inhibition can moderate the behavioral expression of implicit cognition [69]. Indeed, the impact of implicit cognitive processes on drinking behavior should be stronger in individuals with relatively weaker executive control than in individuals with relatively good executive control, as shown by using the classical Stroop interference scores [70]. Conversely, among adolescents with relatively good executive control, explicit expectancies were the best predictor of

In theory, prepotent response inhibition can directly be involved in *myopic* decision, that is, a preference for dominant sooner-smaller at the detriment of less salient larger-later decisions [72]. Steeper delay discounting rate is indubitable in individuals with addiction [73], which concurs to the risk of addiction and treatment response [74, 75]. In support of the existence of a relationship between prepotent response inhibition and short-termism, decreased gray matter volume in lateral prefrontal regions is associated with greater impatience [72, 76]. However, the level of inhibitory control, as typified by the stop-signal reaction time of the stop-signal task [32], and preference for large delayed rewards, as assessed using delay-discounting paradigms, are generally *not* correlated in both healthy participants [77] and clinical populations (e.g., in patients with attention deficit/and hyperactivity disorder) [78], which suggests that response inhibition and delay discounting are

independent factors, each of them contributing to addiction.

*DOI: http://dx.doi.org/10.5772/intechopen.88869*

**3. Response inhibition and addiction**

stop-signal, simon, global-local, and negative compatibility tasks that could share a component of inhibition of prepotent response; the letter flanker, the number Stroop, arrow flanker, and negative compatibility as well as the task assessing n-2 repetition costs tend to assess resistance to distracter interference.

## **3. Response inhibition and addiction**

*Inhibitory Control Training - A Multidisciplinary Approach*

dimensions) [33] (see **Figure 1**).

*Executive function classification proposed by [33].*

become irrelevant.

**Figure 1.**

inhibition [46].

generalization beyond the specific paradigm studied.

Although closely related to executive functioning, response inhibition can be distinct from other forms of executive functions such as working memory update (i.e., the ability to replace information stored in working memory with new information) and switching (i.e., the ability to shift attention to other tasks or perceptual

Based on latent variable analysis, several forms of response inhibition could be distinguished [39–42]. A first distinction has been made between the inhibition of prepotent response and the resistance to distracter interference. However, the robustness of this two-factor solution remains questionable in light of low correlations between inhibition measures, when the contribution of memory processes was intentionally reduced [41]. It follows from this discussion that studies using a single laboratory paradigm for assessing or investigating inhibition do not warrant

More fine-grained forms of inhibition have been put forward across the years [39, 41]. Indeed, resistance to proactive interference consists of resisting memory intrusions from information that was previously relevant to the task but has since

A second categorization relies on the degree of anticipation and preparation of response inhibition [43, 44]. Reactive inhibition (or reflexive inhibition) is a form of inhibition that one can implement without anticipation (e.g., stopping the car when an animal unexpectedly jumps on to the road). Proactive inhibition refers to the impact of inhibition preparation on the inhibitory performance (e.g., keeping one's foot close to the brake after passing a warning sign for animals on the road). Possibly because proactive form of response inhibition requires much more than just inhibition, as attested by shared brain contribution of both forms of inhibition (the right inferior frontal gyrus, supplementary motor area and striatum) and also specific engagement of working memory-related regions (i.e., dorsolateral prefrontal region) [45], proactive inhibition may be more ecologically valid than reactive

Sufficient agreement can be found on the contributions of these different inhibitory control mechanisms as measured by a variety of cognitive tasks described by Friedman and Miyake [39]. The list of tasks includes the color Stroop, anti-saccade,

**30**

Consistent with the previous discussion, response disinhibition is an important element of modern addiction models [6, 9], and empirical data support this claim, particularly for gambling, psychostimulant, and alcohol addiction [5]. By conferring a central position to response inhibition, brain imaging and behavioral studies demonstrated abnormal functioning in individuals at risk to develop an addictive behavior, in addicted people, and in individuals who relapsed [9, 47, 48]. Indeed, a variety of response inhibition deficits are present in numerous forms of reinforcement pathologies (e.g., tobacco dependence [49, 50], alcohol disorder [51, 52], eating disorders [53, 54], gambling disorder [55] (but see [56])). Second, those deficits can predict relapse in drug and behavioral addiction [18, 57, 58], and research suggests that recently abstinent addicts experience heightened difficulties with response inhibition [59, 60]. Thirdly, the inability to stop one's actions, due notably to early stressful life events and negative parent–child interaction [61], can influence behavioral and substance addictions later in life [17, 61].

In addition, it should be noted that impaired response inhibition has a strong impact in important aspects of decision-making. For instance, impaired prepotent response inhibition in alcoholics was associated with poorer performance on the Iowa gambling task [62], which requires participants to deal with uncertainty in a context of punishment and reward, with some choices being advantageous in the short term (high reward) but disadvantageous in the long run (higher punishment) and known for its ecological validity of decision-making [63–65]. Risk-taking could also be modulated through inhibitory control engagement, with participants being more cautious once anticipating to suppress their response [66]. Unfortunately, the benefit of this form of inhibitory training is fragile and transitory [67]. Besides, data from a sample of pathological gamblers revealed no effect of this procedure on risk-taking [68]. Finally, prepotent response inhibition can moderate the behavioral expression of implicit cognition [69]. Indeed, the impact of implicit cognitive processes on drinking behavior should be stronger in individuals with relatively weaker executive control than in individuals with relatively good executive control, as shown by using the classical Stroop interference scores [70]. Conversely, among adolescents with relatively good executive control, explicit expectancies were the best predictor of alcohol use [71].

In theory, prepotent response inhibition can directly be involved in *myopic* decision, that is, a preference for dominant sooner-smaller at the detriment of less salient larger-later decisions [72]. Steeper delay discounting rate is indubitable in individuals with addiction [73], which concurs to the risk of addiction and treatment response [74, 75]. In support of the existence of a relationship between prepotent response inhibition and short-termism, decreased gray matter volume in lateral prefrontal regions is associated with greater impatience [72, 76]. However, the level of inhibitory control, as typified by the stop-signal reaction time of the stop-signal task [32], and preference for large delayed rewards, as assessed using delay-discounting paradigms, are generally *not* correlated in both healthy participants [77] and clinical populations (e.g., in patients with attention deficit/and hyperactivity disorder) [78], which suggests that response inhibition and delay discounting are independent factors, each of them contributing to addiction.

## **4. Cognitive training**

As mentioned earlier, several findings argued in favor of cognitive-based interventions aimed at targeting response inhibition as an assistant in preventing relapse in addicted population.

Amending those deficits is a huge endeavor and ways to achieve it is still a debated matter [79]. This section elaborates on several cognitive training interventions (CTI) that potentially impact positively on inhibition-related processes in individuals with reinforcement pathologies.

### **4.1 Restoring inhibitory control**

Two contrasting approaches have been used to evaluate response inhibition training on substance use disorders and behavioral addiction: general stop inhibition with classical paradigms assessing prepotent response inhibition or with versions adapted to the type of addictive behaviors (e.g., *alcohol* Stroop test or *cocaine* go/no-go task).

Although there is no conclusive evidence of true increase in inhibitory control in response to extensive training with standard go/no-go or SST tasks in adults [80], training of inhibitory control reduced monetary risk-taking [66] and alcohol-seeking [81]; even this effect is small and short-lived [67, 68], which could potentially explain why some studies failed to observe far-transfer effects [82].

In contrast to some studies using formal training of working memory (e.g., [83]) to evaluate their direct impact on unhealthy behaviors (e.g., alcohol abuse), which can be positive in nonclinical samples [84], but not clinical population [85], modified versions of response inhibition tasks have served as training paradigms [79, 86–90].

During "inhibitory control training" (ICT), participants complete an inhibitory control task (go/no-go task, stop-signal task, anti-saccade task) in which the requirement to exercise inhibitory control is paired with cues related to healthy behaviors, before the effects of this training on the target behavior are measured (for reviews, see [79, 89, 91]). For example, when a group of participants in whom inhibition was paired with neutral cues was compared, participants who completed a stop-signal task in which alcohol images were paired with inhibition subsequently led to reduced ad libitum alcohol consumption in the laboratory, but not self-reported drinking in the week after training [90]. In the same vein, participants who learned to associate food images with inhibition on a go/no-go task subsequently consumed less of those foods when given access to them [88]. In contrast, training of oculomotor inhibition in the presence of alcohol-related cues led to slowed eye movements toward target cues on catch trials, but this manipulation failed to influence the proportion of inhibitory failures and had no influence on alcohol consumption in the laboratory [90]. Initial results indicated that the relationship between behavioral inhibition and alcohol intake may be causal, possibly to the ecological value of alcohol motor response inhibition paradigms (e.g., picking up a glass of alcohol beverage may be directly targeted by motor inhibition training), and training of oculomotor inhibitory control is far less convincing.

Meta-analytic approach [89, 91, 92] demonstrated that the effect of ICT on behavior was dependent on the task used. In theory, research on inhibition have led to the recognition that there are at least two types of inhibitory control: action restraint in which the decision to inhibit is made from the onset (go/no-go tasks) and action cancelation in which the decision to inhibit occurs after implementation of the prepotent response (stop-signal task) [93, 94]. However, the meta-analyses reveal that the higher the proportion of successful inhibitions of appetitive signals, the greater the magnitude of the effect of ICTs. Indeed, studies found a larger and

**33**

into regular therapy [109].

*Addiction: Brain and Cognitive Stimulation for Better Cognitive Control and Far Beyond*

more statistically robust ICT effect size when go/no-go rather than stop-signal tasks are used. One reason for the superiority of training action restrain on action cancelation [95, 96] is that compared to go/no-go tasks, stop-signal tasks have a lower rate of overall stop success that ends up hindering the development of strong stimulus-stop associations [53, 95]. Instead, go/no-go tasks feature strong stimulus-stop association due to the rate of successful inhibitions reflected in the number and proportion of stop-stimulus pairings, which in turn moderate the effects of training on unhealthy behavior. It is still in debate to ascertain what repeated stop-stimulus pairings could cause: better intentional inhibitory control over impulsive action [97], facilitated automatic retrieval of stimulus-stop associations [21, 37, 98], or diminished motivational properties of target information [99–101]. The issue of which mechanisms mediate the relationship between cognitive training paradigms and behavioral changes remains highly complex for several reasons. First, the size of behavioral change is at best rather small and does not survive more than a couple of hours [67]. Besides, it remains to be seen whether the control condition used in most of the studies where participants are required to rapidly respond to appetitive stimuli as often as inhibiting responses contributes to inflated effect size of ICT [89]. Second, there is no clear consensus on theoretical constructs such as motivation, where generally there is a weak relationship between implicit and explicit measures of stimulus evaluation [102]. Indeed, whereas a majority of studies using implicit motivational measures demonstrate no effect of inhibition of cognitive training on stimulus devaluation, other studies using Likert scale or other explicit procedures [101] demonstrated devaluation

To sum up, general or cue-specific inhibition training has yielded only modest

Cognitive bias modification consists of pairing alcohol-related content with action tendencies, classically pushing a joystick in response the alcohol-related images and pulling the same joystick in response to soft drinks [106, 107]. Cognitive and clinical effects of this procedure have been compared to sham training conditions requiring an equal number of approach and avoidance movements to both alcohol and soft drinks pictures (i.e., no stimulus-response contingency). Main original outcomes are (a) reduced alcohol approach-related biases indicated with the implicit association task and (b) reduced alcohol relapse up to 1 year after the training. As suggested, an important mediating effect was the building of an alcohol-avoidance bias [106]. The clinical efficacy of this approach regardless of patients' characteristics (age, number of prior detoxifications, etc.) has shown to be too limited to be integrated as such in clinical settings. Indeed, on a meta-analysis of 14 studies (mainly for alcohol and tobacco use problems) involving 2435 participants [22], the authors found a small, nonsignificant overall effect on cognitive bias assessed directly after the completion of the training intervention. In addition, neither smoking nor alcohol reduction was found in response to training intervention. In the same vein, a recent meta-analysis "cast serious doubts on the clinical utility of CBM interventions for addiction" [108]. In response to this assertion, influential researchers in the field, Wiers et al., argued that this analysis combined the results of laboratory and randomized controlled trials, which may underestimate CBM's actual effectiveness when incorporated

In addition to those theoretical and methodological limitations, several moderators could hinder yet existing ICT effects. It is the case of the degree of

*DOI: http://dx.doi.org/10.5772/intechopen.88869*

effects following this sort of intervention [103–105].

**4.2 Cognitive bias modification**

clinical results, and mechanisms remain to be elucidated.

#### *Addiction: Brain and Cognitive Stimulation for Better Cognitive Control and Far Beyond DOI: http://dx.doi.org/10.5772/intechopen.88869*

more statistically robust ICT effect size when go/no-go rather than stop-signal tasks are used. One reason for the superiority of training action restrain on action cancelation [95, 96] is that compared to go/no-go tasks, stop-signal tasks have a lower rate of overall stop success that ends up hindering the development of strong stimulus-stop associations [53, 95]. Instead, go/no-go tasks feature strong stimulus-stop association due to the rate of successful inhibitions reflected in the number and proportion of stop-stimulus pairings, which in turn moderate the effects of training on unhealthy behavior. It is still in debate to ascertain what repeated stop-stimulus pairings could cause: better intentional inhibitory control over impulsive action [97], facilitated automatic retrieval of stimulus-stop associations [21, 37, 98], or diminished motivational properties of target information [99–101]. The issue of which mechanisms mediate the relationship between cognitive training paradigms and behavioral changes remains highly complex for several reasons. First, the size of behavioral change is at best rather small and does not survive more than a couple of hours [67]. Besides, it remains to be seen whether the control condition used in most of the studies where participants are required to rapidly respond to appetitive stimuli as often as inhibiting responses contributes to inflated effect size of ICT [89]. Second, there is no clear consensus on theoretical constructs such as motivation, where generally there is a weak relationship between implicit and explicit measures of stimulus evaluation [102]. Indeed, whereas a majority of studies using implicit motivational measures demonstrate no effect of inhibition of cognitive training on stimulus devaluation, other studies using Likert scale or other explicit procedures [101] demonstrated devaluation effects following this sort of intervention [103–105].

To sum up, general or cue-specific inhibition training has yielded only modest clinical results, and mechanisms remain to be elucidated.

### **4.2 Cognitive bias modification**

Cognitive bias modification consists of pairing alcohol-related content with action tendencies, classically pushing a joystick in response the alcohol-related images and pulling the same joystick in response to soft drinks [106, 107]. Cognitive and clinical effects of this procedure have been compared to sham training conditions requiring an equal number of approach and avoidance movements to both alcohol and soft drinks pictures (i.e., no stimulus-response contingency). Main original outcomes are (a) reduced alcohol approach-related biases indicated with the implicit association task and (b) reduced alcohol relapse up to 1 year after the training. As suggested, an important mediating effect was the building of an alcohol-avoidance bias [106]. The clinical efficacy of this approach regardless of patients' characteristics (age, number of prior detoxifications, etc.) has shown to be too limited to be integrated as such in clinical settings. Indeed, on a meta-analysis of 14 studies (mainly for alcohol and tobacco use problems) involving 2435 participants [22], the authors found a small, nonsignificant overall effect on cognitive bias assessed directly after the completion of the training intervention. In addition, neither smoking nor alcohol reduction was found in response to training intervention. In the same vein, a recent meta-analysis "cast serious doubts on the clinical utility of CBM interventions for addiction" [108]. In response to this assertion, influential researchers in the field, Wiers et al., argued that this analysis combined the results of laboratory and randomized controlled trials, which may underestimate CBM's actual effectiveness when incorporated into regular therapy [109].

In addition to those theoretical and methodological limitations, several moderators could hinder yet existing ICT effects. It is the case of the degree of

*Inhibitory Control Training - A Multidisciplinary Approach*

individuals with reinforcement pathologies.

**4.1 Restoring inhibitory control**

As mentioned earlier, several findings argued in favor of cognitive-based interventions aimed at targeting response inhibition as an assistant in preventing relapse

Two contrasting approaches have been used to evaluate response inhibition training on substance use disorders and behavioral addiction: general stop inhibition with classical paradigms assessing prepotent response inhibition or with versions adapted to the type of addictive behaviors (e.g., *alcohol* Stroop test or *cocaine* go/no-go task). Although there is no conclusive evidence of true increase in inhibitory control in response to extensive training with standard go/no-go or SST tasks in adults [80], training of inhibitory control reduced monetary risk-taking [66] and alcohol-seeking [81]; even this effect is small and short-lived [67, 68], which could potentially

In contrast to some studies using formal training of working memory (e.g., [83])

During "inhibitory control training" (ICT), participants complete an inhibitory control task (go/no-go task, stop-signal task, anti-saccade task) in which the requirement to exercise inhibitory control is paired with cues related to healthy behaviors, before the effects of this training on the target behavior are measured (for reviews, see [79, 89, 91]). For example, when a group of participants in whom inhibition was paired with neutral cues was compared, participants who completed a stop-signal task in which alcohol images were paired with inhibition subsequently led to reduced ad libitum alcohol consumption in the laboratory, but not self-reported drinking in the week after training [90]. In the same vein, participants who learned to associate food images with inhibition on a go/no-go task subsequently consumed less of those foods when given access to them [88]. In contrast, training of oculomotor inhibition in the presence of alcohol-related cues led to slowed eye movements toward target cues on catch trials, but this manipulation failed to influence the proportion of inhibitory failures and had no influence on alcohol consumption in the laboratory [90]. Initial results indicated that the relationship between behavioral inhibition and alcohol intake may be causal, possibly to the ecological value of alcohol motor response inhibition paradigms (e.g., picking up a glass of alcohol beverage may be directly targeted by motor inhibition training), and training of oculomotor inhibitory control is far less convincing. Meta-analytic approach [89, 91, 92] demonstrated that the effect of ICT on behavior was dependent on the task used. In theory, research on inhibition have led to the recognition that there are at least two types of inhibitory control: action restraint in which the decision to inhibit is made from the onset (go/no-go tasks) and action cancelation in which the decision to inhibit occurs after implementation of the prepotent response (stop-signal task) [93, 94]. However, the meta-analyses reveal that the higher the proportion of successful inhibitions of appetitive signals, the greater the magnitude of the effect of ICTs. Indeed, studies found a larger and

explain why some studies failed to observe far-transfer effects [82].

to evaluate their direct impact on unhealthy behaviors (e.g., alcohol abuse), which can be positive in nonclinical samples [84], but not clinical population [85], modified versions of response inhibition tasks have served as training paradigms

Amending those deficits is a huge endeavor and ways to achieve it is still a debated matter [79]. This section elaborates on several cognitive training interventions (CTI) that potentially impact positively on inhibition-related processes in

**4. Cognitive training**

in addicted population.

[79, 86–90].

**32**

readiness to change, that is, the goal to gain control over harmful behaviors that make the ICT intervention more congruent with the participant's mindset, hence potentiating its effects [110]. Another source of variation in the effect of ICT could be the strength of appetitive responses to food cues [111], with the effects of ICT on behavior being proportional to the strength of appetitive responses to cues before ICT [112, 113]. Whether individual differences in attempts to limit drinking, smoking, or gambling moderate the effects of ICT on alcohol intake is a promising avenue for future research. Put together with current literature revealing substance-specific relapse (and vulnerability)-related impairments, it is recommended to investigate cognitive training programs based on a patienttailored protocol [114].

## **5. Brain neurostimulation techniques**

## **5.1 Brain stimulations: noninvasive and invasive techniques**

Effects of brain stimulation of basic processes, neurochemical regulation, and cognitive and affective processes at the system level have revealed promising results when applied to addiction treatment (for reviews and meta-analyses, see [23, 115, 116]). The most used stimulation techniques include deep brain stimulation, repetitive transcranial magnetic stimulation, and transcranial direct current stimulation known for their effect on self-regulatory processes and possibly acting on several forms of response inhibition.

### **5.2 Invasive brain stimulations**

### *5.2.1 Deep brain stimulation*

Despite ethical concerns due to potential serious side effects [117], deep brain stimulation has expanded from successful thalamic stimulation for Parkinsonian tremor (for a review, see [118]) to psychiatric conditions including addiction [23, 115, 116]. DBS is a neurosurgical procedure involving the placement of a neurostimulator, often called "brain pacemaker," which delivers electrical impulses through implanted electrodes to specific brain regions related to abnormal functioning characterizing neurological and psychiatric conditions.

Back in the 1980s, BDS was introduced as treatment for movement disorders and became well known for treating the tremor of patients with Parkinson disease [119]. During the 2000s, it started to be applied in psychiatric disorders when the pathology is treatment-refractory: in obsessive-compulsive disorder (OCD) [120] and in major depression [121]. DBD gained interest as a means to treat addiction as soon as studies reported unintended alleviation of comorbid alcohol [115], nicotine [122], and gambling [123] addictions.

As reviewed by Luigjes et al. [124], based on a total of eight studies, bilateral high-frequency NAc stimulation in heroine dependence came with reduced craving and prolonged abstinence. In addition, animal studies have provided evidence that NAc DBS dampens impulsivity [125, 126], which represents a core aspect of addictive behaviors [127].

However, because of the absence of double-blind controlled trials in addiction, the cost and the invasiveness of the procedure, as well as the lack of consensus regarding its clinical efficacy and the encountered difficulties to recruit motivated participants [128], DBS to treat addiction could suffer from feasibility issues.

**35**

ing conclusion [23].

*Addiction: Brain and Cognitive Stimulation for Better Cognitive Control and Far Beyond*

Because they offer a safe economical way to modulate brain activity, techniques such as repetitive transcranial magnetic stimulation and transcranial direct current stimulation are growing in popularity for interventions in psychiatric disorder [129, 130]. They are so-called noninvasive to reflect the fact that the magnetic pulses are delivered from a coil placed over the scalp, without a surgical intervention (in contrast to DBS), which contributed to its popularity as techniques for modulating brain activity over the past two decades. Although recent reviews repeatedly recommended more clinical trials before firm conclusions about their efficacy could be drawn [124], their effects on key addictive-related phenomena

Repetitive transcranial magnetic stimulation delivers in a time interval a magnetic pulse through the skull via a stimulating coil. The magnetic field involves a focal electrical current, depolarizing underlying cortical neurons. The intensity, duration, properties, localization, and frequency directly influence the effects. Low frequency (1–5 Hz) tends to produce inhibitory effects and fits well the intention of downregulating activity in the targeted regions [132, 133]. High frequency (10–20 Hz) tends to produce excitatory effects on the stimulated brain area. However, substantial inter-individual responses to both low- and high-frequency stimulation have been reported [134]. By using either figure-of-eight coils or H-coils known to produce highly focal stimulation in superficial cortex or deeper intracranial penetration to a more central target, respectively [135], the clinical influence of a

*rTMS and addictive behaviors*: The most frequently used rTMS setup has been 10 sessions of stimulation on either the right DLPFC with a high frequency or the left DLPFC with lower frequency. In nicotine addiction, frequently reported findings include reduced transitory (no longer than several weeks following the intervention) cue-induced craving for cigarette as well as lower nicotine consumption [136, 137]. Interestingly, an important placebo effect has been repeatedly found in rTMS studies. Indeed, a reduction in the daily consumption of alcohol [138] or cocaine [139] has been found in response to both active and sham stimulation. In the same vein, although a reduced attentional bias toward alcohol cues has been found in response to high-frequency left DLPFC rTMS, all participants (irrespective of their stimulation condition) reported a reduced craving [140]. The placebo response should be due to a concurrent treatment regimen, which too often is missing from these studies, and better study designs should involve participant blinding. Regarding the clinical impact of rTMS in behavioral addiction (e.g., gambling addiction, binge eating), the insufficient number of controlled trials prevents draw-

An important issue to be discussed is the potential cognitive mediators of rTMS effects in addicted subjects. In theory, a reduction in craving intensity and in substance use could be mediated by improved response inhibition or mental flexibility or a change in salience or automatization. No effects above sham stimulation were found on prepotent response inhibition evaluated by a go/no-go task [141].

Although DLPFC is critical for cognitive-executive functions, stimulation of medial regions tends to influence affective-motivational functions [142]. This region along with others such as the insula is important for the selection of longterm over short-term reward, an interplay that may be abnormal in individuals with addictive behaviors [143, 144]. Magnetic stimulation of the medial prefrontal

*DOI: http://dx.doi.org/10.5772/intechopen.88869*

(e.g., craving, impulsivity) are noteworthy [131].

*5.3.1 Repetitive transcranial magnetic stimulation*

variety of clinical phenomena has been investigated.

**5.3 Noninvasive brain stimulations**

## **5.3 Noninvasive brain stimulations**

*Inhibitory Control Training - A Multidisciplinary Approach*

tailored protocol [114].

**5. Brain neurostimulation techniques**

**5.1 Brain stimulations: noninvasive and invasive techniques**

tioning characterizing neurological and psychiatric conditions.

sibly acting on several forms of response inhibition.

**5.2 Invasive brain stimulations**

and gambling [123] addictions.

tive behaviors [127].

feasibility issues.

*5.2.1 Deep brain stimulation*

readiness to change, that is, the goal to gain control over harmful behaviors that make the ICT intervention more congruent with the participant's mindset, hence potentiating its effects [110]. Another source of variation in the effect of ICT could be the strength of appetitive responses to food cues [111], with the effects of ICT on behavior being proportional to the strength of appetitive responses to cues before ICT [112, 113]. Whether individual differences in attempts to limit drinking, smoking, or gambling moderate the effects of ICT on alcohol intake is a promising avenue for future research. Put together with current literature revealing substance-specific relapse (and vulnerability)-related impairments, it is recommended to investigate cognitive training programs based on a patient-

Effects of brain stimulation of basic processes, neurochemical regulation, and cognitive and affective processes at the system level have revealed promising results when applied to addiction treatment (for reviews and meta-analyses, see [23, 115, 116]). The most used stimulation techniques include deep brain stimulation, repetitive transcranial magnetic stimulation, and transcranial direct current stimulation known for their effect on self-regulatory processes and pos-

Despite ethical concerns due to potential serious side effects [117], deep brain stimulation has expanded from successful thalamic stimulation for Parkinsonian tremor (for a review, see [118]) to psychiatric conditions including addiction [23, 115, 116]. DBS is a neurosurgical procedure involving the placement of a neurostimulator, often called "brain pacemaker," which delivers electrical impulses through implanted electrodes to specific brain regions related to abnormal func-

Back in the 1980s, BDS was introduced as treatment for movement disorders and became well known for treating the tremor of patients with Parkinson disease [119]. During the 2000s, it started to be applied in psychiatric disorders when the pathology is treatment-refractory: in obsessive-compulsive disorder (OCD) [120] and in major depression [121]. DBD gained interest as a means to treat addiction as soon as studies reported unintended alleviation of comorbid alcohol [115], nicotine [122],

As reviewed by Luigjes et al. [124], based on a total of eight studies, bilateral high-frequency NAc stimulation in heroine dependence came with reduced craving and prolonged abstinence. In addition, animal studies have provided evidence that NAc DBS dampens impulsivity [125, 126], which represents a core aspect of addic-

However, because of the absence of double-blind controlled trials in addic-

tion, the cost and the invasiveness of the procedure, as well as the lack of consensus regarding its clinical efficacy and the encountered difficulties to recruit motivated participants [128], DBS to treat addiction could suffer from

**34**

Because they offer a safe economical way to modulate brain activity, techniques such as repetitive transcranial magnetic stimulation and transcranial direct current stimulation are growing in popularity for interventions in psychiatric disorder [129, 130]. They are so-called noninvasive to reflect the fact that the magnetic pulses are delivered from a coil placed over the scalp, without a surgical intervention (in contrast to DBS), which contributed to its popularity as techniques for modulating brain activity over the past two decades. Although recent reviews repeatedly recommended more clinical trials before firm conclusions about their efficacy could be drawn [124], their effects on key addictive-related phenomena (e.g., craving, impulsivity) are noteworthy [131].

## *5.3.1 Repetitive transcranial magnetic stimulation*

Repetitive transcranial magnetic stimulation delivers in a time interval a magnetic pulse through the skull via a stimulating coil. The magnetic field involves a focal electrical current, depolarizing underlying cortical neurons. The intensity, duration, properties, localization, and frequency directly influence the effects. Low frequency (1–5 Hz) tends to produce inhibitory effects and fits well the intention of downregulating activity in the targeted regions [132, 133]. High frequency (10–20 Hz) tends to produce excitatory effects on the stimulated brain area. However, substantial inter-individual responses to both low- and high-frequency stimulation have been reported [134]. By using either figure-of-eight coils or H-coils known to produce highly focal stimulation in superficial cortex or deeper intracranial penetration to a more central target, respectively [135], the clinical influence of a variety of clinical phenomena has been investigated.

*rTMS and addictive behaviors*: The most frequently used rTMS setup has been 10 sessions of stimulation on either the right DLPFC with a high frequency or the left DLPFC with lower frequency. In nicotine addiction, frequently reported findings include reduced transitory (no longer than several weeks following the intervention) cue-induced craving for cigarette as well as lower nicotine consumption [136, 137]. Interestingly, an important placebo effect has been repeatedly found in rTMS studies. Indeed, a reduction in the daily consumption of alcohol [138] or cocaine [139] has been found in response to both active and sham stimulation. In the same vein, although a reduced attentional bias toward alcohol cues has been found in response to high-frequency left DLPFC rTMS, all participants (irrespective of their stimulation condition) reported a reduced craving [140]. The placebo response should be due to a concurrent treatment regimen, which too often is missing from these studies, and better study designs should involve participant blinding.

Regarding the clinical impact of rTMS in behavioral addiction (e.g., gambling addiction, binge eating), the insufficient number of controlled trials prevents drawing conclusion [23].

An important issue to be discussed is the potential cognitive mediators of rTMS effects in addicted subjects. In theory, a reduction in craving intensity and in substance use could be mediated by improved response inhibition or mental flexibility or a change in salience or automatization. No effects above sham stimulation were found on prepotent response inhibition evaluated by a go/no-go task [141].

Although DLPFC is critical for cognitive-executive functions, stimulation of medial regions tends to influence affective-motivational functions [142]. This region along with others such as the insula is important for the selection of longterm over short-term reward, an interplay that may be abnormal in individuals with addictive behaviors [143, 144]. Magnetic stimulation of the medial prefrontal cortex may bias the preference for delayed, over sooner, rewards [145]. However, this encouraging view has been recently tempered by a study reporting the absence of effect of rTMS targeting the medial prefrontal cortex on impulsive choice on the delay discounting task in pathological gamblers [146].

In contrast to rTMS that requires 20–30 min of stimulation time to achieve its full effect, theta burst stimulation (TBS) protocols could achieve similar efficiency by employing protocols lasting between 20 s and 3 min that induce NMDA receptor-dependent long-term potentiation and long-term depression [147]. A recent meta-analytic review [148] that focused on healthy participants on the prefrontal cortex with theoretically linked cognitive test performance as the outcome revealed that uninterrupted train of TBS decreases performances on measures of inhibitory control, attentional control, and working memory, whereas intermittent TBS has positive effects on executive functions (but not likely ceiling effects). Future studies comparing different magnetic stimulation protocols should be conducted in the context of addictive behaviors.

#### *5.3.2 Transcranial direct current stimulation*

Transcranial direct current stimulation involves delivering low-intensity electric current (typically 0.5–2 mA) via electrodes placed on the scalp and/or upper body. Cortical excitability is modulated by a polarity-dependent shift of the neuronal membrane potential [149, 150]. On the macroscopic level, anodal stimulation enhances cortical excitability via depolarization and long-term potentiation, whereas cathodal stimulation inhibits excitability via hyperpolarization and long-term depression [149]. The density, duration, and direction of the current that comes into contact with underlying neurons determine the strength and direction of neuromodulation [149, 150]. After an initial subthreshold depolarization or hyperpolarization of neuronal membrane potentials that increases or decreases the likelihood of spontaneous neural firing, facilitation of long-term potentials or longterm depression occurs [151]. tDCS modulation of the action potentials even lasts beyond the stimulation period [149, 150], and several neuromodulation sessions could increase the duration of the effects [152].

*tDCS as an intervention in addictive disorders*: a recent review [23] showed that seven published studies have focused on the impact of tDCS on various measures related to substance addiction. Despite important inter-individual differences in response to tDCS [153], most preeminent effects were found on craving reduction [154]. In addition, mixed results were found with respect to executive control functions [124, 131, 155, 156]. Importantly, in healthy controls no improvement was found after tDCS stimulation of bilateral DLPFC stimulation of either right anodal/ left cathodal or left anodal/right cathodal on decision-making under risk (e.g., balloon analogue task), an absence of effect possibly due to a ceiling effect [157].

The benefit from reducing cue-induced craving for clinical population could be pertinent. Indeed, pressing, urgent, and irrepressible desire to drink or to smoke has been strongly associated with *loss of control*, leading to a high relapse rate [158]. However, the mediating effect of craving variation in response to tDCS on relapse is not obvious. For instance, in a tDCS study in patients with alcohol dependence (two daily stimulations 5 consecutive days on left cathodal/right anodal over the dorsolateral prefrontal cortex), no differences with regard to changes on scores of craving were found despite an improved overall perception of quality of life and reduced relapse probability in several alcoholics [159]. In nicotine addiction, right anodal stimulation on the DLPFC reduces craving with minimal heterogeneity, whereas cathodal tDCS on this region showed the most positive effect on cue-provoked craving and smoking intake [154]. However, this craving reduction, which may be due

**37**

behaviors.

*5.3.3 Neurofeedback*

*Addiction: Brain and Cognitive Stimulation for Better Cognitive Control and Far Beyond*

to increased control on cue reactivity, could be too small to positively impact cigarette use. Indeed, as compared to sham, active tDCS significantly reduced smoking craving and increased brain reactivity to smoking cues within the right posterior cingulate, as measured with a functional magnetic resonance imaging event-related paradigm, but failed to diminish the number of cigarettes smoked (see also [160]) and the exhaled carbon monoxide 1 month following the stimulation [161].

Regarding the association between tDCS and food, reduction of food craving [162–164] and calorie intake [97] in healthy subjects and reduced craving for food

Mediating processes involved in brain stimulation of the PFC is likely to be more complex than previously expected. It was demonstrated that anodal tDCS applied over frontoparietal regions has previously been shown to enhance attention and executive control functions [166–168], but the effects are limited and non-lasting. Working memory, depending on the stimulation modalities, can be a valid candidate mediator [169]. As a multicomponent system responsible for temporary storage and manipulation of information, working memory sustained emotional regulation [14]. Because many psychiatric disorders are associated with working memory impairments, it may be useful to improve the transient "online" manipula-

Response inhibition is another good candidate mediator of the relationship between tDCS and clinical change. For instance, a recent study showed that tDCS over the right inferior frontal cortex made healthy participants more efficient in proactive, but not reactive, inhibition [170]. In another study, tDCS over the pre SMA during a stop-signal task increases activity in the pre SMA after anodal stimulation during stop trials and was associated with improved inhibitory control [171]. Finally, after applying tDCS over the rIFG, two studies [170, 172] observed a decrease in P3 amplitude during no-go and/or stop trials in anodal compared to inactive stimulation. The clinical value of those results in the case of addictive behaviors remains to be seen. One possibility is that a reduction of P3 amplitude during successful response inhibition on a go/no-go task in response to tDCS could be a protective factor for the risk of relapse in vulnerable alcoholics, that is, those

The clinical impact of tDCS on substance use can be still more subtle. For instance, in obese participants, electric brain stimulation on the DLPFC facilitated the transition between unconscious and conscious perception of appetitive stimuli, a phenomenon particularly pronounced in participants with higher body mass index [174]. Those findings could have an impact on craving regulation, via augmented awareness of implicit determinants of craving, enhancing the risk of relapse.

Although the proposed cognitive mediators presented in this section showed promising results, their clinical relevance is still tentative. Much more data is needed to achieve a better comprehension of the impact of tDCS on addictive

In neurofeedback, participants learn to modulate their own brain activity through feedback. The main goal is for participants to develop effective self-regulation strategies to increase desired brain activity. Functional magnetic resonance imaging neurofeedback (fMRI-NF) and electroencephalography neurofeedback (EEG-NF) are the most developed configurations [175], each with its strengths and weaknesses [176, 177]. Higher spatial resolution and broad brain coverage characterize fMRI-NF [178], while EEG-NF has very good timing but low spatial accuracy. In EEG-NF, it is possible to modify neuronal oscillations in specific frequency

*DOI: http://dx.doi.org/10.5772/intechopen.88869*

in overweight subjects [165] have been reported.

tion of emotional thoughts in treatment rehabilitation.

with greater amplitude of P3 [173].

#### *Addiction: Brain and Cognitive Stimulation for Better Cognitive Control and Far Beyond DOI: http://dx.doi.org/10.5772/intechopen.88869*

to increased control on cue reactivity, could be too small to positively impact cigarette use. Indeed, as compared to sham, active tDCS significantly reduced smoking craving and increased brain reactivity to smoking cues within the right posterior cingulate, as measured with a functional magnetic resonance imaging event-related paradigm, but failed to diminish the number of cigarettes smoked (see also [160]) and the exhaled carbon monoxide 1 month following the stimulation [161].

Regarding the association between tDCS and food, reduction of food craving [162–164] and calorie intake [97] in healthy subjects and reduced craving for food in overweight subjects [165] have been reported.

Mediating processes involved in brain stimulation of the PFC is likely to be more complex than previously expected. It was demonstrated that anodal tDCS applied over frontoparietal regions has previously been shown to enhance attention and executive control functions [166–168], but the effects are limited and non-lasting.

Working memory, depending on the stimulation modalities, can be a valid candidate mediator [169]. As a multicomponent system responsible for temporary storage and manipulation of information, working memory sustained emotional regulation [14]. Because many psychiatric disorders are associated with working memory impairments, it may be useful to improve the transient "online" manipulation of emotional thoughts in treatment rehabilitation.

Response inhibition is another good candidate mediator of the relationship between tDCS and clinical change. For instance, a recent study showed that tDCS over the right inferior frontal cortex made healthy participants more efficient in proactive, but not reactive, inhibition [170]. In another study, tDCS over the pre SMA during a stop-signal task increases activity in the pre SMA after anodal stimulation during stop trials and was associated with improved inhibitory control [171]. Finally, after applying tDCS over the rIFG, two studies [170, 172] observed a decrease in P3 amplitude during no-go and/or stop trials in anodal compared to inactive stimulation. The clinical value of those results in the case of addictive behaviors remains to be seen. One possibility is that a reduction of P3 amplitude during successful response inhibition on a go/no-go task in response to tDCS could be a protective factor for the risk of relapse in vulnerable alcoholics, that is, those with greater amplitude of P3 [173].

The clinical impact of tDCS on substance use can be still more subtle. For instance, in obese participants, electric brain stimulation on the DLPFC facilitated the transition between unconscious and conscious perception of appetitive stimuli, a phenomenon particularly pronounced in participants with higher body mass index [174]. Those findings could have an impact on craving regulation, via augmented awareness of implicit determinants of craving, enhancing the risk of relapse.

Although the proposed cognitive mediators presented in this section showed promising results, their clinical relevance is still tentative. Much more data is needed to achieve a better comprehension of the impact of tDCS on addictive behaviors.

#### *5.3.3 Neurofeedback*

In neurofeedback, participants learn to modulate their own brain activity through feedback. The main goal is for participants to develop effective self-regulation strategies to increase desired brain activity. Functional magnetic resonance imaging neurofeedback (fMRI-NF) and electroencephalography neurofeedback (EEG-NF) are the most developed configurations [175], each with its strengths and weaknesses [176, 177]. Higher spatial resolution and broad brain coverage characterize fMRI-NF [178], while EEG-NF has very good timing but low spatial accuracy. In EEG-NF, it is possible to modify neuronal oscillations in specific frequency

*Inhibitory Control Training - A Multidisciplinary Approach*

delay discounting task in pathological gamblers [146].

context of addictive behaviors.

*5.3.2 Transcranial direct current stimulation*

could increase the duration of the effects [152].

cortex may bias the preference for delayed, over sooner, rewards [145]. However, this encouraging view has been recently tempered by a study reporting the absence of effect of rTMS targeting the medial prefrontal cortex on impulsive choice on the

In contrast to rTMS that requires 20–30 min of stimulation time to achieve its full effect, theta burst stimulation (TBS) protocols could achieve similar efficiency by employing protocols lasting between 20 s and 3 min that induce NMDA receptor-dependent long-term potentiation and long-term depression [147]. A recent meta-analytic review [148] that focused on healthy participants on the prefrontal cortex with theoretically linked cognitive test performance as the outcome revealed that uninterrupted train of TBS decreases performances on measures of inhibitory control, attentional control, and working memory, whereas intermittent TBS has positive effects on executive functions (but not likely ceiling effects). Future studies comparing different magnetic stimulation protocols should be conducted in the

Transcranial direct current stimulation involves delivering low-intensity electric current (typically 0.5–2 mA) via electrodes placed on the scalp and/or upper body. Cortical excitability is modulated by a polarity-dependent shift of the neuronal membrane potential [149, 150]. On the macroscopic level, anodal stimulation enhances cortical excitability via depolarization and long-term potentiation, whereas cathodal stimulation inhibits excitability via hyperpolarization and

long-term depression [149]. The density, duration, and direction of the current that comes into contact with underlying neurons determine the strength and direction of neuromodulation [149, 150]. After an initial subthreshold depolarization or hyperpolarization of neuronal membrane potentials that increases or decreases the likelihood of spontaneous neural firing, facilitation of long-term potentials or longterm depression occurs [151]. tDCS modulation of the action potentials even lasts beyond the stimulation period [149, 150], and several neuromodulation sessions

*tDCS as an intervention in addictive disorders*: a recent review [23] showed that seven published studies have focused on the impact of tDCS on various measures related to substance addiction. Despite important inter-individual differences in response to tDCS [153], most preeminent effects were found on craving reduction [154]. In addition, mixed results were found with respect to executive control functions [124, 131, 155, 156]. Importantly, in healthy controls no improvement was found after tDCS stimulation of bilateral DLPFC stimulation of either right anodal/ left cathodal or left anodal/right cathodal on decision-making under risk (e.g., balloon analogue task), an absence of effect possibly due to a ceiling effect [157].

The benefit from reducing cue-induced craving for clinical population could be pertinent. Indeed, pressing, urgent, and irrepressible desire to drink or to smoke has been strongly associated with *loss of control*, leading to a high relapse rate [158]. However, the mediating effect of craving variation in response to tDCS on relapse is not obvious. For instance, in a tDCS study in patients with alcohol dependence (two daily stimulations 5 consecutive days on left cathodal/right anodal over the dorsolateral prefrontal cortex), no differences with regard to changes on scores of craving were found despite an improved overall perception of quality of life and reduced relapse probability in several alcoholics [159]. In nicotine addiction, right anodal stimulation on the DLPFC reduces craving with minimal heterogeneity, whereas cathodal tDCS on this region showed the most positive effect on cue-provoked craving and smoking intake [154]. However, this craving reduction, which may be due

**36**

domains associated with functions such as attention or relaxation. fMRI-NF and its variant, real-time fMRI [179], provide direct feedback to modulate (increase or decrease) neuronal activity in the regions of interest [180]. With fMRI-NF, brain regions of interest are defined a priori on the basis of consensual articles describing which neurocognitive networks are altered and predictive of low use of controlled substances [181]. In EEG-NF, critical oscillations in certain frequency bands have been associated with mental states (e.g., alpha and theta frequencies for a relaxed or meditative state, beta rhythm, or sensorimotor for inhibition).

In the context of addictive behaviors, alpha-theta and the alpha-theta augmented with SMR training represent the two main protocols of EEG-NF. As pointed out by [23], only a few studies have reached a reasonable quality (only one study used a control condition matched in time) [182], which makes it difficult to determine which protocol provides the best results. However, in two studies [182, 183], a reduction in the number of false alarms (i.e., response to no-go trials) on a go/no-go task was observed in participants who received EEG-NF rather than an alternative treatment. It is interesting to note that sensorimotor interferences can be reduced in healthy participants who undergo SMR neurofeedback training, which they have learned to voluntarily increase, resulting in better cognitive performance [184].

With respect to fMRI-NF, an analysis based on eight studies [23] revealed that six of them performed on nicotine addiction showed better regulation at the level of the anterior part of the cingulate gyrus directly associated with a decrease in the desire to smoke [185]. In alcohol addiction, reduced craving was achieved by modifying activity in the ACC, PFC, and insula [186]. Further studies should explore reward (e.g., ventral striatum) and control processing before the clinical relevance in addiction could be confirmed and mediating factors (e.g., prepotent response inhibition) identified.

## **6. A step forward: combined interventions with retrieval-extinction techniques**

Coupling brain stimulation with other pharmacological and non-pharmacological interventions may provide further knowledge about individual brain oscillation states across several montages and voltages as well as long-term structural and functional effects of brain stimulation on addicted patients [187]. These proposals will certainly make better use of brain stimulation techniques and therefore optimize their clinical effects (**Table 1)**.

Here we focused more on the effects of combined interventions to improve clinical efficacy. Combined methodologies have provided positive clinical results in a variety of psychiatric conditions [188]. From a broad perspective, the use of neuromodulation techniques to promote brain plasticity [189, 190] while exerting response inhibition, extinction learning, or cognitive restructuration may help regain control over prepotent actions.

As shown in **Table 2**, only five studies used several combined approaches in the context of substance use disorders. The results are rather disappointing. Indeed, in five out of five studies, no interaction between brain stimulation and cognitive manipulation was found, indicating that tDCS did not add any clinical value to behavioral training. However, two studies have examined the combined effects of left anodal tDCS on DLPFC and cognitive-behavioral modification (CBM) in high-risk drinkers undergoing or not treatment. In the high-risk drinker sample, 1.0 mA was administered on left DLPFC during three CBM sessions for 3 to 4 days. No effect of CBM or tDCS was observed on approach bias or alcohol consumption. However, participants reported a reduced craving during a signal responsiveness task [191]. In treatment seekers, 2.0 mA over left DLPFC over the course of four

**39**

**Learning-related concepts**

*Addiction: Brain and Cognitive Stimulation for Better Cognitive Control and Far Beyond*

cortical activity

blood oxygenation

words or alcohol-related content)

Cognitive biases These refer generally to unidentified or inaccurately identified

Cognitive deficits Describes a deviation from the normal functioning of general

Executive functions Partially independent, top-down processes reflecting goal cognitive

shifting are core functions Proactive control Refers to expectancy-based activation of cognitive control

Working memory The ability to hold multiple things in mind at once while mentally

Prepotent inhibition response Refers to the suppression of actions that are no longer required or that

in ever-changing environments Self-regulation Encompasses cognitive control, emotion regulation, and top-down

Interference control Ignoring (inhibiting, suppressing, or deactivating) internal or

goal or goal state)

previous learning

Conditioned stimulus A previously neutral stimulus that has been learned to predict an

Event-related potentials (ERP) By means of electrodes placed at various points on the scalp and

Deep brain stimulation (DBS) A small device, similar to a pacemaker, is surgically implanted to

deliver electrical stimulation to targeted areas of the brain

low-intensity (1–2 mA) current in the brain

Allows changes in cortical activity to be generated by inducing a direct

Induces repeated single magnetic pulses in the brain to modulate

amplified through an EEG machine, the ERP measures electrical potentials generated by the brain in response to specific internal or external events (e.g., sensory, cognitive, or motor stimuli)

To detect regional and time-varying changes in brain metabolism and

A structured practice of mental abilities that are used to solve complex

A structured practice of mental abilities where the semantic content of the processed information is controlled (e.g., negative emotional

tasks regardless of their content (e.g., working memory)

attitudes or stereotypes, but in the present essay, we reported attentional, memory, and action tendency biases as normal and abnormal manifestations of domain-specific processing (e.g., attentional engagement toward smoking cues in deprived smokers)

cognitive domains (e.g., episodic memory, executive functioning)

corresponding to an internal goal are involved in the control of behavior, emotions, and cognition. The updating of the relevant information, the inhibition of prepotent impulses, and the mental set

(maintaining goal activation to bias responding) prior to an anticipated conflict or challenge. In contrast, reactive control refers to the activation of cognitive control after a change or conflict is detected

external competing information to protect working memory or to

are inappropriate, which supports flexible and goal-directed behavior

and bottom-up processes that alter emotion, behavior, or cognition to attempt to enhance adaptation (or to achieve an explicit or implicit

outcome; the presentation of the stimulus evokes the memory of the

manipulating one or more of them (e.g., updating)

focus attention on goal-relevant information

*DOI: http://dx.doi.org/10.5772/intechopen.88869*

**Brain stimulation and investigation techniques**

Transcranial direct current stimulation (tDCS) and its variant, the transcranial alternating current or random

Repetitive transcranial magnetic

Function magnetic resonance

Domain-general cognitive

Domain-specific cognitive

Cognitive training and related cognitive functions

noise stimulation

stimulation (rTMS)

imagery (fMRI)

training

training


*Inhibitory Control Training - A Multidisciplinary Approach*

meditative state, beta rhythm, or sensorimotor for inhibition).

domains associated with functions such as attention or relaxation. fMRI-NF and its variant, real-time fMRI [179], provide direct feedback to modulate (increase or decrease) neuronal activity in the regions of interest [180]. With fMRI-NF, brain regions of interest are defined a priori on the basis of consensual articles describing which neurocognitive networks are altered and predictive of low use of controlled substances [181]. In EEG-NF, critical oscillations in certain frequency bands have been associated with mental states (e.g., alpha and theta frequencies for a relaxed or

In the context of addictive behaviors, alpha-theta and the alpha-theta augmented with SMR training represent the two main protocols of EEG-NF. As pointed out by [23], only a few studies have reached a reasonable quality (only one study used a control condition matched in time) [182], which makes it difficult to determine which protocol provides the best results. However, in two studies [182, 183], a reduction in the number of false alarms (i.e., response to no-go trials) on a go/no-go task was observed in participants who received EEG-NF rather than an alternative treatment. It is interesting to note that sensorimotor interferences can be reduced in healthy participants who undergo SMR neurofeedback training, which they have learned to voluntarily increase, resulting in better cognitive performance [184]. With respect to fMRI-NF, an analysis based on eight studies [23] revealed that six of them performed on nicotine addiction showed better regulation at the level of the anterior part of the cingulate gyrus directly associated with a decrease in the desire to smoke [185]. In alcohol addiction, reduced craving was achieved by modifying activity in the ACC, PFC, and insula [186]. Further studies should explore reward (e.g., ventral striatum) and control processing before the clinical relevance in addiction could be confirmed and mediating factors (e.g., prepotent response inhibition) identified.

**6. A step forward: combined interventions with retrieval-extinction** 

Coupling brain stimulation with other pharmacological and non-pharmacological interventions may provide further knowledge about individual brain oscillation states across several montages and voltages as well as long-term structural and functional effects of brain stimulation on addicted patients [187]. These proposals will certainly make better use of brain stimulation techniques and therefore opti-

Here we focused more on the effects of combined interventions to improve clinical efficacy. Combined methodologies have provided positive clinical results in a variety of psychiatric conditions [188]. From a broad perspective, the use of neuromodulation techniques to promote brain plasticity [189, 190] while exerting response inhibition, extinction learning, or cognitive restructuration may help

As shown in **Table 2**, only five studies used several combined approaches in the context of substance use disorders. The results are rather disappointing. Indeed, in five out of five studies, no interaction between brain stimulation and cognitive manipulation was found, indicating that tDCS did not add any clinical value to behavioral training. However, two studies have examined the combined effects of left anodal tDCS on DLPFC and cognitive-behavioral modification (CBM) in high-risk drinkers undergoing or not treatment. In the high-risk drinker sample, 1.0 mA was administered on left DLPFC during three CBM sessions for 3 to 4 days. No effect of CBM or tDCS was observed on approach bias or alcohol consumption. However, participants reported a reduced craving during a signal responsiveness task [191]. In treatment seekers, 2.0 mA over left DLPFC over the course of four

**38**

**techniques**

mize their clinical effects (**Table 1)**.

regain control over prepotent actions.


#### **Table 1.**

*Definitions and glossary of major terms as relevant in the current essay.*

training sessions in 4 consecutive days was used [192]. No significant interaction effect for the full sample was found. However, in this study, there were some indications of a boosting effect of tDCS and CBM, such that relapse was lower in this group at the 1-year follow-up.

More encouraging evidence for the usefulness of a combined approach comes from research on patients with mood disorders. For instance, participants with social anxiety disorder had a significant decrease in attention bias for threatening signals during single anodal stimulation as opposed to simulated stimulation [196]. In obsessive-compulsive disorder, exposure to information aimed at generating a conditioned response (e.g., increase anxiety in response to a risk of contamination) has been tested in combination with tDCS [197] or rTMS [198]. Indeed, by using a personalized provocation of symptoms aimed at generating an appropriate level of distress, the goal was to activate the corresponding neural circuit. During brain stimulation, people were asked to think about provocation ("Please keep thinking about your dirty hands"). Positive results were found in this combined setting (brief exposure therapy + tDCS or rTMS). In the field of nicotine addiction, one study has shown that it is advantageous to use a challenge with actual exposure to tobacco signals just prior to the rTMS high-frequency stimulation treatment [199]. It should be noted that this approach requires that the interventions be individualized according to the conditioned responses involved in the addictive process.

Brain stimulation techniques could also be advantageously coupled with interventions targeting the learning process of extinction in addictive disorder. Extinction refers to the disappearance of a conditioned behavior in the absence of positive or negative reinforcement [200]. Extinction is the basis for an intervention based on exposure, a primary treatment for a variety of psychiatric conditions, including addiction [201]. Unfortunately, the extinguishing procedures did not simply wipe out the conditioned responses of the past, as shown by the return of the targeted behavior by extinction which is again apparent after the passage of time, after the presentation of the unconditioned stimulus, and when extinguished signals are encountered outside the extinction context [201]. Instead, extinction may be a new form of learning that exists with extinction memories in distinct neural

**41**

**Studies** den Uyl

Electrophysiological

Heavy drinkers

tDCS criteria\* 78

21.8 (3.2)

51/27

2 × 2 factorial design:

• training

• training

• training

•

Sham tDCS

during sham training

Three groups in parallel

Four sessions of

3-month,

No effect of

repeated CBM

and/or tDCS

on 3 months

of abstinence

duration,

AABR

while

1-year

abstinence

follow-ups,

craving

intensity,

approach bias

craving, and

alcohol biases,

except a trendlevel effect of

active tDCS

during active

training on

relapse rate at 1

year only when

comparing to

sham tDCS

(p = .07)

receiving tDCS

over DLPFC (20

min, 2 mA; 35 cm2

anode F3 and

100 m2 cathode F4)

\*\*

design:

• training

• training

•

Active tDCS separate

from active training

Sham tDCS during active

Active tDCS during active

Active tDCS during sham

Sham tDCS during active

Active tDCS during active

want to reduce

drinking

Dutch-speaking

18–35 years

AUDIT > 8

and behavioral

effects of combined

tDCS and Alcohol

Approach Bias

Retraining (AABR) in

hazardous drinkers

den Uyl

A clinical trial with

Individuals

tDCS criteria\* 91

47 (8.8)

30/91

with AUD

under a

3-month

hospital

treatment

combined tDCS and

Alcohol Approach

Bias Retraining in

alcohol-dependent

patients

et al. [191]

et al. [191]

**Condition**

**Inclusion criteria**

**Exclusion criteria**

**N**

**Mean age** 

**Female/**

**Design**

**Experimental** 

**Outcome** 

**Results**

**measures**

**condition**

Three sessions

Alcohol use,

No effects

on EEG and

behavioral

measures of

repeated CBM

and/or tDCS,

except for an

effect of tDCS

on induced

craving

craving, AAT,

IAT, EEG P300

Quantity of

alcohol use

at month

follow-up

of AABR\*\* while

receiving tDCS

over DLPFC (1 mA

for 15 min; 35 cm2

anode F3 and

100 cm2 cathode

over contralateral

supraorbital

region)

**(SD)**

**male**

*Addiction: Brain and Cognitive Stimulation for Better Cognitive Control and Far Beyond*

*DOI: http://dx.doi.org/10.5772/intechopen.88869*


*Addiction: Brain and Cognitive Stimulation for Better Cognitive Control and Far Beyond DOI: http://dx.doi.org/10.5772/intechopen.88869*

*Inhibitory Control Training - A Multidisciplinary Approach*

group at the 1-year follow-up.

Reactivation-extinction (retrieval-extinction)

**Table 1.**

training sessions in 4 consecutive days was used [192]. No significant interaction effect for the full sample was found. However, in this study, there were some indications of a boosting effect of tDCS and CBM, such that relapse was lower in this

Extinction The presentation of a conditioned/learned stimulus now in the

Reactivation Re-exposure to memory reminders, which may result in

memory

memory

extinction

*Definitions and glossary of major terms as relevant in the current essay.*

Learning The behavioral changes of an organism are the result of regularities in the environment of that organism

Retrieval A reminder results in recollection of the previously learned memory;

reconsolidation into an updated memory

Reconsolidation The active process that is necessary to restabilize a reactivated/

absence of the previously associated outcome; this results in the temporary decline of subsequent memory expression

destabilization of the previously learned neural representation of

the term encompasses the multiple processes from reactivation of the neural memory representation to behavioral expression of the

destabilized memory; disruption of reconsolidation results in memory impairment, while new information is incorporated during

The combination of memory reactivation (usually via a reminder that results in memory retrieval) and, after a brief interval, subsequent

More encouraging evidence for the usefulness of a combined approach comes from research on patients with mood disorders. For instance, participants with social anxiety disorder had a significant decrease in attention bias for threatening signals during single anodal stimulation as opposed to simulated stimulation [196]. In obsessive-compulsive disorder, exposure to information aimed at generating a conditioned response (e.g., increase anxiety in response to a risk of contamination) has been tested in combination with tDCS [197] or rTMS [198]. Indeed, by using a personalized provocation of symptoms aimed at generating an appropriate level of distress, the goal was to activate the corresponding neural circuit. During brain stimulation, people were asked to think about provocation ("Please keep thinking about your dirty hands"). Positive results were found in this combined setting (brief exposure therapy + tDCS or rTMS). In the field of nicotine addiction, one study has shown that it is advantageous to use a challenge with actual exposure to tobacco signals just prior to the rTMS high-frequency stimulation treatment [199]. It should be noted that this approach requires that the interventions be individualized according to the conditioned responses involved in the addictive process. Brain stimulation techniques could also be advantageously coupled with interventions targeting the learning process of extinction in addictive disorder. Extinction refers to the disappearance of a conditioned behavior in the absence of positive or negative reinforcement [200]. Extinction is the basis for an intervention based on exposure, a primary treatment for a variety of psychiatric conditions, including addiction [201]. Unfortunately, the extinguishing procedures did not simply wipe out the conditioned responses of the past, as shown by the return of the targeted behavior by extinction which is again apparent after the passage of time, after the presentation of the unconditioned stimulus, and when extinguished signals are encountered outside the extinction context [201]. Instead, extinction may be a new form of learning that exists with extinction memories in distinct neural

**40**


**43**

**Studies** Claus et al.

Effect of combining

At-risk alcohol

History of

79

24.5 (2.7)

Not

2 × 2 factorial design:

indicated

• training

• training

•

Active tDCS

during sham

training

•

Sham tDCS

during sham

training

Sham tDCS during active

Active tDCS during active

treatment

for AUD or

desire for

treatment

Alcohol

withdrawal

Brain injury

Psychotropic

medications

Pregnancy

Illicit drug

use

Metal in the

body

*\*tDCS criteria: epilepsy, multiple sclerosis or other neurological illness, previous brain injury/infection, metal in the brain, pacemaker, pregnancy, claustrophobia, recent fainting/panic attack, frequent* 

*headaches or dizziness, and eczema or other skin conditions*

*\*\*Alcohol Approach Bias Retraining: pull or push alcohol or soft drink pictures with joystick.*

*\*\*\*Attentional Bias Modification: dot-probe training task with alcohol, nonalcohol, or object pictures*

*\*\*\*\*Inhibitory control training: a go/no-go training task with fatty food, healthy food, and close pictures*

**Table 2.**

*Effect of tDCS and behavioral interventions combined in substance use disorder.*

drinkers

AUDIT > 8

CBM and tDCS on

reduction of alcohol

approach biases and

alcohol consumption

[195]

**Condition**

**Inclusion criteria**

**Exclusion criteria**

**N**

**Mean age** 

**Female/**

**Design**

**Experimental** 

**Outcome** 

**Results**

**measures**

**condition**

Four sessions (of

Drinks per

Significant

alcohol

drinking day

(DDD) and

approach

biases at

percent heavy

drinking days

baseline;

neither CBM,

tDCS, nor the

interaction

reduced the

bias at the

(PHDD) at

baseline, the

follow-up

visits at 1-week

and 1-month

follow-ups,

follow-up

No significant

effect of

intervention

on either DDD

or PHDD

alcohol

approach bias

at baseline

1 h per week, 4

consecutive weeks)

of AABR\*\* while

tDCS right inferior

frontal gyrus (2

mA; 20 min; 11 cm2

anode F10 and the

cathode arm)

**(SD)**

**male**

*Addiction: Brain and Cognitive Stimulation for Better Cognitive Control and Far Beyond*

*DOI: http://dx.doi.org/10.5772/intechopen.88869*


*\*\*Alcohol Approach Bias Retraining: pull or push alcohol or soft drink pictures with joystick. \*\*\*Attentional Bias Modification: dot-probe training task with alcohol, nonalcohol, or object pictures*

 *\*\*\*\*Inhibitory control training: a go/no-go training task with fatty food, healthy food, and close pictures*

## **Table 2.**

*Effect of tDCS and behavioral interventions combined in substance use disorder.*

*Inhibitory Control Training - A Multidisciplinary Approach*

**42**

**Studies** den Uyl

Clinical trial with

Individuals

tDCS criteria\* 83

48.6 (0.9)

21/62

2 × 2 factorial design:

• ABM

•

Sham tDCS

during active ABM

•

Active tDCS

during sham

ABM

• training

Sham tDCS during sham

Active tDCS during active

with AUD

under a

3-month

hospital

treatment

combined tDCS and

Attentional Bias

Modification (ABM)

in alcohol-dependent

patients

Sedgmond

Effect of tDCS on

Healthy

In diet to lose

172

20.81

141/172

2 × 2 factorial design:

One session of

Food craving,

No evidence

for the effect

snack buffet

consumption,

of tDCS

on food

consumption

or food craving

with Bayesian.

No effect

of tDCS on

inhibitory

control

inhibitory

control

ICT

while

receiving tDCS

over DLPFC (2 mA

for 20 min; 35 cm2

anode F4 and

cathode F3)

\*\*\*\*

(0.26)

• training

•

Sham tDCS

during active training

•

Active tDCS

during sham

training

• training

Sham tDCS during sham

Active tDCS during active

participants

weight

History

of eating

disorders

Previously

participated

in this type of

study

food consumption or

food craving when

combined with

inhibitory control

training in healthy

subjects

et al. [194]

et al. [193]

**Condition**

**Inclusion** 

**Exclusion** 

**N**

**Mean age** 

**Female/**

**Design**

**Experimental** 

**Outcome** 

**Results**

**measures**

**condition**

Four sessions of

1-year

Stronger

avoidance bias

only during

ABM

combined

abstinence

follow-up,

alcohol bias,

training

session in

active tDCS

with active

ABM

(p < 0.05)

No effects

of tDCS and

ABM on the

bias scores,

craving, or

relapse

craving

intensity

with tDCS (20 min,

2 mA, over DLPFC,

35 cm2 anode F3,

and 100 m2 cathode

F4)

\*\*\*

**(SD)**

**male**

**criteria**

**criteria**

circuits [202]. Therefore, increased extinction with new approaches has been extensively studied in animals and, more recently, in humans with aversive responses (e.g., fear) and appetite disorders (e.g., addiction) [203]. The extinction of the conditioned response may be more effective if it is preceded by a brief exposure to the conditioned response, that is to say, a phase of reactivation of the memory [204–206]. This approach, often named *super-extinction*, gave rise to theories of synaptic consolidation [207], which brought a fresh look at memory processes involved in flexible actions. Briefly, once activated, conditioned responses are rendered labile and unstable that interfering intervention (e.g., propranolol administration [208], non-pharmacological manipulation [209, 210]) ensuing during the reconsolidation window could update original memory traces [204]. Reduced involvement of the inhibitory networks [211] and induced plasticity [209] during extinction following reactivation could represent some of the key mechanisms in play. Importantly, whereas in extinction amygdala's representation remains intact, the prefrontal activated reconsolidation would eliminate the necessity of such inhibition [211]. Additionally, as shown in animal studies, one factor that may initiate memory destabilization and reconsolidation is the detention of prediction errors (*surprise effect*) [212, 213]. In humans, some procedures combining prediction errors and memory reconsolidation interference have yielded interesting results in subjects with high alcohol consumption ([214, 215], p. 20; [216]). Although the clinical impact of those essays was not overwhelming, subtle changes of alcohol attractiveness have already been highlighted, such as a reduction of craving for alcohol [216] and significant reductions in verbal fluency for positive alcohol-related words [215]. In theory, conditioned stimuli could be erased with a single treatment, which could solve the compliance problems necessary to continue treatment, promoting abstinence [217]. Although promising and extremely relevant in the context of the prevention and treatment of addictive behaviors, the precise recovery conditions required to successfully destabilize memory remain unclear (e.g., role of prediction error, type of intervention post-activation, counter-conditioning, interference, extinction).

We suggest here that the *super-extinction* procedure can be implemented in combination with brain stimulation techniques and cognitive response inhibition training, for example, which may lead to stronger and more prolonged clinical effects in drug and behavioral addictions. Indeed, not only is the activation of relevant brain circuitry important before the application of brain stimulation [197–199], but it is also possible to capitalize on the lability of memory during reconsolidation. Indeed, reactivated memory becomes labile after retrieval through a process known as memory reconsolidation. Memory reconsolidation after retrieval may be used to maintain or update long-term memories, reinforcing or integrating new information into them [204–206, 209], a phenomenon that would underlie change in psychotherapy [218]. Interestingly, decreasing DLPFC activity has been observed in repeated encounters with memories (e.g., [115]), resulting in a stabilization of memory. Consistently, the stimulation of the control network via an anodal TDCS applied to the right DLPFC during repeated access to acquired information disrupts the long-term retention of these memories [219]. Based on these findings, it is likely that stimulating the control network during reconsolidation of emotional memories associated with addictive behaviors could result in disrupted storage, particularly in circumstances that generate interferences (e.g., training *alcohol-stop* associations). Future research is needed to test these hypotheses and shed new light on this theoretical reasoning.

Another promising possibility is that cognitive training works better when combined with other forms of clinical intervention aimed at enhancing motivation, self-esteem, family functioning, social support, etc. [220]. In other words, a very interesting line of research is to study the interaction between the mechanisms

**45**

*Addiction: Brain and Cognitive Stimulation for Better Cognitive Control and Far Beyond*

involved in clinical interventions that lead to positive outcomes and the aforementioned cognitive interventions. Too often, clinical interventions have been described simply as a set of technical tools (e.g., CBT, family therapy) instead of mechanisms and processes of clinical interventions (e.g., compensatory skills, selfunderstanding) [221], which is a problem when we consider that each participant does not respond in the same way to a given intervention. For this reason, it may be that only the participants who benefit most in some way from a given clinical intervention are those for whom cognitive training and brain stimulation work best. It is obvious that the weakness of this hypothesis is precisely the problem encountered by research in identifying central mechanisms and methods related to psychological

Finally, some studies have found that addicted participants have preserved automatic inhibitory resources [52]. In this study, recently detoxified alcoholics and healthy participants performed a modified stop-signal task that consisted of a training phase in which a subset of the stimuli was consistently associated with stopping or going and a test phase in which this mapping was reversed. In the training phase, stop performance improved for the consistent stop stimuli, compared with control stimuli that were not associated with going or stopping. In the test phase, go performance tended to be impaired for old stop stimuli. Combined, these findings support the automatic inhibition hypothesis. Importantly, performance was similar in both groups, which indicates that automatic inhibitory control develops normally in individuals with alcoholism. Furthermore, clinical interventions aimed at potentiating the automatic suppression of alcohol-going associations combined with procedures encouraging the automatic selection of alternative responses (e.g., intention implementation [223]). This approach has the merit to promote better inhibitory control of the action without saturating the resources of effortful self-regulation. Whether intensive addiction cues/stop associations could benefit from reactivation of craving or negative emotions is an important hypothesis to be tested in further experiments.

Many efforts have been made to modify the acquired motivational properties of addiction cues and to reinforce the control of prepotent responses via cognitive training, brain stimulation, and neurofeedback protocols. To date, our review has highlighted some of the promises as well as the obstacles that we need to overcome. In keeping with recent narrative critiques and the meta-analytic approach, the current state of the art appears to be like a half-empty or half-full glass. On the one side, an important limitation is the absence of a robust consensus about methods and mechanisms of brain stimulation techniques (but see for a recent consensus, article [224]) and recent findings calling into question inhibition as a psychometric construct [41]. The main consequence of this is the high level of variation between subjects in response to brain stimulation as well as a poor understanding of the precise cognitive mechanisms that mediate the efficacy of brain stimulation. On the other side, the glass could be considered half-filled because a reduction in the state of cue-induced craving is now feasible and the ongoing research on possible moderators could add important information. Indeed, the motivation for change of participants that refers to personal goals and values is a clinical target requiring specific psychological interventions before cognitive and brain enhancement can turn into robust clinical effects [109]. Clearly, the brain (e.g., using EEG or fMRI) and cognitive (e.g., impaired executive functions, exacerbated approach tendencies toward addiction cues) profiles of patients sensitive to cognitive improvement are

*DOI: http://dx.doi.org/10.5772/intechopen.88869*

change in response to clinical interventions [222].

**7. Concluding remarks**

important factors to identify [114, 225].

*Addiction: Brain and Cognitive Stimulation for Better Cognitive Control and Far Beyond DOI: http://dx.doi.org/10.5772/intechopen.88869*

involved in clinical interventions that lead to positive outcomes and the aforementioned cognitive interventions. Too often, clinical interventions have been described simply as a set of technical tools (e.g., CBT, family therapy) instead of mechanisms and processes of clinical interventions (e.g., compensatory skills, selfunderstanding) [221], which is a problem when we consider that each participant does not respond in the same way to a given intervention. For this reason, it may be that only the participants who benefit most in some way from a given clinical intervention are those for whom cognitive training and brain stimulation work best. It is obvious that the weakness of this hypothesis is precisely the problem encountered by research in identifying central mechanisms and methods related to psychological change in response to clinical interventions [222].

Finally, some studies have found that addicted participants have preserved automatic inhibitory resources [52]. In this study, recently detoxified alcoholics and healthy participants performed a modified stop-signal task that consisted of a training phase in which a subset of the stimuli was consistently associated with stopping or going and a test phase in which this mapping was reversed. In the training phase, stop performance improved for the consistent stop stimuli, compared with control stimuli that were not associated with going or stopping. In the test phase, go performance tended to be impaired for old stop stimuli. Combined, these findings support the automatic inhibition hypothesis. Importantly, performance was similar in both groups, which indicates that automatic inhibitory control develops normally in individuals with alcoholism. Furthermore, clinical interventions aimed at potentiating the automatic suppression of alcohol-going associations combined with procedures encouraging the automatic selection of alternative responses (e.g., intention implementation [223]). This approach has the merit to promote better inhibitory control of the action without saturating the resources of effortful self-regulation. Whether intensive addiction cues/stop associations could benefit from reactivation of craving or negative emotions is an important hypothesis to be tested in further experiments.

## **7. Concluding remarks**

*Inhibitory Control Training - A Multidisciplinary Approach*

circuits [202]. Therefore, increased extinction with new approaches has been extensively studied in animals and, more recently, in humans with aversive responses (e.g., fear) and appetite disorders (e.g., addiction) [203]. The extinction of the conditioned response may be more effective if it is preceded by a brief exposure to the conditioned response, that is to say, a phase of reactivation of the memory [204–206]. This approach, often named *super-extinction*, gave rise to theories of synaptic consolidation [207], which brought a fresh look at memory processes involved in flexible actions. Briefly, once activated, conditioned responses are rendered labile and unstable that interfering intervention (e.g., propranolol administration [208], non-pharmacological manipulation [209, 210]) ensuing during the reconsolidation window could update original memory traces [204]. Reduced involvement of the inhibitory networks [211] and induced plasticity [209] during extinction following reactivation could represent some of the key mechanisms in play. Importantly, whereas in extinction amygdala's representation remains intact, the prefrontal activated reconsolidation would eliminate the necessity of such inhibition [211]. Additionally, as shown in animal studies, one factor that may initiate memory destabilization and reconsolidation is the detention of prediction errors (*surprise effect*) [212, 213]. In humans, some procedures combining prediction errors and memory reconsolidation interference have yielded interesting results in subjects with high alcohol consumption ([214, 215], p. 20; [216]). Although the clinical impact of those essays was not overwhelming, subtle changes of alcohol attractiveness have already been highlighted, such as a reduction of craving for alcohol [216] and significant reductions in verbal fluency for positive alcohol-related words [215]. In theory, conditioned stimuli could be erased with a single treatment, which could solve the compliance problems necessary to continue treatment, promoting abstinence [217]. Although promising and extremely relevant in the context of the prevention and treatment of addictive behaviors, the precise recovery conditions required to successfully destabilize memory remain unclear (e.g., role of prediction error, type of intervention post-activation, counter-conditioning, interference, extinction).

We suggest here that the *super-extinction* procedure can be implemented in combination with brain stimulation techniques and cognitive response inhibition training, for example, which may lead to stronger and more prolonged clinical effects in drug and behavioral addictions. Indeed, not only is the activation of relevant brain circuitry important before the application of brain stimulation [197–199], but it is also possible to capitalize on the lability of memory during reconsolidation. Indeed, reactivated memory becomes labile after retrieval through a process known as memory reconsolidation. Memory reconsolidation after retrieval may be used to maintain or update long-term memories, reinforcing or integrating new information into them [204–206, 209], a phenomenon that would underlie change in psychotherapy [218]. Interestingly, decreasing DLPFC activity has been observed in repeated encounters with memories (e.g., [115]), resulting in a stabilization of memory. Consistently, the stimulation of the control network via an anodal TDCS applied to the right DLPFC during repeated access to acquired information disrupts the long-term retention of these memories [219]. Based on these findings, it is likely that stimulating the control network during reconsolidation of emotional memories associated with addictive behaviors could result in disrupted storage, particularly in circumstances that generate interferences (e.g., training *alcohol-stop* associations). Future research is needed to test these hypotheses and shed new light on this

Another promising possibility is that cognitive training works better when combined with other forms of clinical intervention aimed at enhancing motivation, self-esteem, family functioning, social support, etc. [220]. In other words, a very interesting line of research is to study the interaction between the mechanisms

**44**

theoretical reasoning.

Many efforts have been made to modify the acquired motivational properties of addiction cues and to reinforce the control of prepotent responses via cognitive training, brain stimulation, and neurofeedback protocols. To date, our review has highlighted some of the promises as well as the obstacles that we need to overcome. In keeping with recent narrative critiques and the meta-analytic approach, the current state of the art appears to be like a half-empty or half-full glass. On the one side, an important limitation is the absence of a robust consensus about methods and mechanisms of brain stimulation techniques (but see for a recent consensus, article [224]) and recent findings calling into question inhibition as a psychometric construct [41]. The main consequence of this is the high level of variation between subjects in response to brain stimulation as well as a poor understanding of the precise cognitive mechanisms that mediate the efficacy of brain stimulation. On the other side, the glass could be considered half-filled because a reduction in the state of cue-induced craving is now feasible and the ongoing research on possible moderators could add important information. Indeed, the motivation for change of participants that refers to personal goals and values is a clinical target requiring specific psychological interventions before cognitive and brain enhancement can turn into robust clinical effects [109]. Clearly, the brain (e.g., using EEG or fMRI) and cognitive (e.g., impaired executive functions, exacerbated approach tendencies toward addiction cues) profiles of patients sensitive to cognitive improvement are important factors to identify [114, 225].

In this chapter, we also strongly recommend that conditioned stimuli and conditioned responses that lead to the loss and recovery of control of addictive behavior be better identified and used with retrieval-extinction techniques in combination with brain and cognitive stimulations. If ethical questions arise when unpleasant sensations are felt by people seeking care and when an intervention alters the substance of a memory, as it may disrupt a sense of self, we must remember the lack of effectiveness of contemporary clinical and experimental treatments in an intolerable situation which we have become too accustomed. We hope to have convinced the reader that in reconsolidation-based treatments, even if boundary conditions begin to be discovered [226, 227], the potential benefits may far outweigh the risks.

It is difficult to obtain better cognitive control, such as improving executive functions in adults, as shown by considerable data [80], but capitalizing on preserved automatic inhibitory resources could prove useful for promoting better inhibitory control of the action without saturating the resources of effortful selfregulation [21, 52].

In sum, these are exciting days where a number of key elements useful to change addictive behaviors have now been identified, yet their perfect fit remains to be done. What is also promising is the undeniable need to bridge the gap between experimental studies and clinical issues in taking into account motivation, relevant personal conditioned responses, acute and chronic stress, memory, response inhibition, and brain and cognitive stimulation to provide addicts with better control of their impulse and obsessions because it is often a prerequisite to return to a satisfactory quality of life.

## **Author details**

Xavier Noël1 \*, Antoine Bechara2 , Mélanie Saeremans1 , Charles Kornreich1 , Clémence Dousset1 , Salvatore Campanella1 , Armand Chatard3 , Nemat Jaafari4 and Macha Dubuson1

1 Psychological Medicine Laboratory, Faculty of Medicine, Université Libre de Bruxelles, Belgium


\*Address all correspondence to: xnoel@ulb.ac.be

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**47**

*Addiction: Brain and Cognitive Stimulation for Better Cognitive Control and Far Beyond*

response inhibition and salience attribution in human drug addiction:

[10] Bechara A, Noel X, Crone EA. Loss

[11] Noël X, Bechara A, Brevers D, Verbanck P, Campanella S. Alcoholism

and the loss of willpower: A neurocognitive perspective. Journal of Psychophysiology.

[12] Noël X, Van Der Linden M, Bechara A. The neurocognitive mechanisms of decision-making, impulse control, and loss of willpower to resist drugs. Psychiatry (Edgmont (Pa.: Township)). 2006;**3**(5):30-41

[13] Evans JSBT. Dual-processing accounts of reasoning, judgment, and social cognition. Annual Review of Psychology. 2008;**59**:255-278

[14] Hofmann W, Schmeichel BJ, Baddeley AD. Executive functions and self-regulation. Trends in Cognitive Sciences. 2012;**16**(3):174-180

[15] Argyriou E, Davison CB, Lee TTC. Response inhibition and internet gaming disorder: A meta-analysis. Addictive Behaviors. 2017;**71**:54-60

[16] Lipszyc J, Schachar R. Inhibitory control and psychopathology: A meta-analysis of studies using the stop signal task. Journal of the International Neuropsychological Society: JINS.

[17] Nigg JT, Wong MM, Martel MM, Jester JM, Puttler LI, Glass JM, et al.

2010;**16**(6):1064-1076

2010;**24**(4):240-248

A systematic review. Neuron.

of willpower: Abnormal neural mechanisms of impulse control and decision making in addiction. In: Handbook of Implicit Cognition and Addiction. Thousand Oaks, California: Sage publications, Inc., 2006. pp. 215-232

2018;**98**(5):886-903

*DOI: http://dx.doi.org/10.5772/intechopen.88869*

[1] Miller PM, Book SW, Stewart SH. Medical treatment of alcohol dependence: A systematic review. International Journal of Psychiatry in

Kalis A. Brain disorders? Not really… why network structures block reductionism in psychopathology research. The Behavioral and Brain

[3] Goldstein RZ, Volkow ND. Drug addiction and its underlying

neurobiological basis: Neuroimaging evidence for the involvement of the frontal cortex. The American Journal of Psychiatry. 2002;**159**(10):1642-1652

Dysfunction of the prefrontal cortex in addiction: Neuroimaging findings and clinical implications. Nature Reviews. Neuroscience. 2011;**12**(11):652-669

[4] Goldstein RZ, Volkow ND.

[5] Lee RSC, Hoppenbrouwers S, Franken I. A systematic meta-review of impulsivity and compulsivity in addictive behaviors. Neuropsychology

[6] Noël X, Brevers D, Bechara A. A neurocognitive approach to understanding the neurobiology of addiction. Current Opinion in Neurobiology. 2013;**23**(4):632-638

[7] Redish AD, Jensen S, Johnson A. A unified framework for addiction: Vulnerabilities in the decision process. The Behavioral and Brain Sciences. 2008;**31**(4):415-437 discussion 437-487

[8] Tang Y-Y, Posner MI, Rothbart MK, Volkow ND. Circuitry of self-control and its role in reducing addiction. Trends in Cognitive Sciences. 2015;**19**(8):439-444

[9] Zilverstand A, Huang AS, Alia-Klein N, Goldstein RZ. Neuroimaging impaired

Review. 2019;**29**(1):14-26

Medicine. 2011;**42**(3):227-266

**References**

[2] Borsboom D, Cramer A,

Sciences. 2018;**24**:1-54

*Addiction: Brain and Cognitive Stimulation for Better Cognitive Control and Far Beyond DOI: http://dx.doi.org/10.5772/intechopen.88869*

## **References**

*Inhibitory Control Training - A Multidisciplinary Approach*

regulation [21, 52].

tory quality of life.

**Author details**

Clémence Dousset1

Bruxelles, Belgium

Macha Dubuson1

\*, Antoine Bechara2

, Salvatore Campanella1

2 Department of Psychology, Southern California University, USA

3 Faculty of Psychology, University of Poitiers, France

4 Faculty of Medicine, University of Poitiers, France

\*Address all correspondence to: xnoel@ulb.ac.be

provided the original work is properly cited.

Xavier Noël1

In this chapter, we also strongly recommend that conditioned stimuli and conditioned responses that lead to the loss and recovery of control of addictive behavior be better identified and used with retrieval-extinction techniques in combination with brain and cognitive stimulations. If ethical questions arise when unpleasant sensations are felt by people seeking care and when an intervention alters the substance of a memory, as it may disrupt a sense of self, we must remember the lack of effectiveness of contemporary clinical and experimental treatments in an intolerable situation which we have become too accustomed. We hope to have convinced the reader that in reconsolidation-based treatments, even if boundary conditions begin to be discovered [226, 227], the potential benefits may far outweigh the risks. It is difficult to obtain better cognitive control, such as improving executive functions in adults, as shown by considerable data [80], but capitalizing on preserved automatic inhibitory resources could prove useful for promoting better inhibitory control of the action without saturating the resources of effortful self-

In sum, these are exciting days where a number of key elements useful to change

, Mélanie Saeremans1

1 Psychological Medicine Laboratory, Faculty of Medicine, Université Libre de

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

, Armand Chatard3

, Charles Kornreich1

,

and

, Nemat Jaafari4

addictive behaviors have now been identified, yet their perfect fit remains to be done. What is also promising is the undeniable need to bridge the gap between experimental studies and clinical issues in taking into account motivation, relevant personal conditioned responses, acute and chronic stress, memory, response inhibition, and brain and cognitive stimulation to provide addicts with better control of their impulse and obsessions because it is often a prerequisite to return to a satisfac-

**46**

[1] Miller PM, Book SW, Stewart SH. Medical treatment of alcohol dependence: A systematic review. International Journal of Psychiatry in Medicine. 2011;**42**(3):227-266

[2] Borsboom D, Cramer A, Kalis A. Brain disorders? Not really… why network structures block reductionism in psychopathology research. The Behavioral and Brain Sciences. 2018;**24**:1-54

[3] Goldstein RZ, Volkow ND. Drug addiction and its underlying neurobiological basis: Neuroimaging evidence for the involvement of the frontal cortex. The American Journal of Psychiatry. 2002;**159**(10):1642-1652

[4] Goldstein RZ, Volkow ND. Dysfunction of the prefrontal cortex in addiction: Neuroimaging findings and clinical implications. Nature Reviews. Neuroscience. 2011;**12**(11):652-669

[5] Lee RSC, Hoppenbrouwers S, Franken I. A systematic meta-review of impulsivity and compulsivity in addictive behaviors. Neuropsychology Review. 2019;**29**(1):14-26

[6] Noël X, Brevers D, Bechara A. A neurocognitive approach to understanding the neurobiology of addiction. Current Opinion in Neurobiology. 2013;**23**(4):632-638

[7] Redish AD, Jensen S, Johnson A. A unified framework for addiction: Vulnerabilities in the decision process. The Behavioral and Brain Sciences. 2008;**31**(4):415-437 discussion 437-487

[8] Tang Y-Y, Posner MI, Rothbart MK, Volkow ND. Circuitry of self-control and its role in reducing addiction. Trends in Cognitive Sciences. 2015;**19**(8):439-444

[9] Zilverstand A, Huang AS, Alia-Klein N, Goldstein RZ. Neuroimaging impaired

response inhibition and salience attribution in human drug addiction: A systematic review. Neuron. 2018;**98**(5):886-903

[10] Bechara A, Noel X, Crone EA. Loss of willpower: Abnormal neural mechanisms of impulse control and decision making in addiction. In: Handbook of Implicit Cognition and Addiction. Thousand Oaks, California: Sage publications, Inc., 2006. pp. 215-232

[11] Noël X, Bechara A, Brevers D, Verbanck P, Campanella S. Alcoholism and the loss of willpower: A neurocognitive perspective. Journal of Psychophysiology. 2010;**24**(4):240-248

[12] Noël X, Van Der Linden M, Bechara A. The neurocognitive mechanisms of decision-making, impulse control, and loss of willpower to resist drugs. Psychiatry (Edgmont (Pa.: Township)). 2006;**3**(5):30-41

[13] Evans JSBT. Dual-processing accounts of reasoning, judgment, and social cognition. Annual Review of Psychology. 2008;**59**:255-278

[14] Hofmann W, Schmeichel BJ, Baddeley AD. Executive functions and self-regulation. Trends in Cognitive Sciences. 2012;**16**(3):174-180

[15] Argyriou E, Davison CB, Lee TTC. Response inhibition and internet gaming disorder: A meta-analysis. Addictive Behaviors. 2017;**71**:54-60

[16] Lipszyc J, Schachar R. Inhibitory control and psychopathology: A meta-analysis of studies using the stop signal task. Journal of the International Neuropsychological Society: JINS. 2010;**16**(6):1064-1076

[17] Nigg JT, Wong MM, Martel MM, Jester JM, Puttler LI, Glass JM, et al.

Poor response inhibition as a predictor of problem drinking and illicit drug use in adolescents at risk for alcoholism and other substance use disorders. Journal of the American Academy of Child and Adolescent Psychiatry. 2006;**45**(4):468-475

[18] Noël X, Sferrazza R, Van Der Linden M, Paternot J, Verhas M, Hanak C, et al. Contribution of frontal cerebral blood flow measured by (99m)Tc-Bicisate spect and executive function deficits to predicting treatment outcome in alcohol-dependent patients. Alcohol and Alcoholism. 2002;**37**(4):347-354

[19] Whelan R, Watts R, Orr CA, Althoff RR, Artiges E, Banaschewski T, et al. Neuropsychosocial profiles of current and future adolescent alcohol misusers. Nature. 2014;**512**(7513):185-189

[20] Noël X, Brevers D, Bechara A. A triadic neurocognitive approach to addiction for clinical interventions. Frontiers in Psychiatry. 2013;**4**:179

[21] Verbruggen F, Best M, Bowditch WA, Stevens T, McLaren IPL. The inhibitory control reflex. Neuropsychologia. 2014;**65**:263-278

[22] Boffo M, Zerhouni O, Gronau QF, van Beek RJJ, Nikolaou K, Marsman M, et al. Cognitive bias modification for behavior change in alcohol and smoking addiction: Bayesian metaanalysis of individual participant data. Neuropsychology Review. 2019;**29**(1):52-78

[23] Luigjes J, Segrave R, de Joode N, Figee M, Denys D. Efficacy of invasive and non-invasive brain modulation interventions for addiction. Neuropsychology Review. 2019;**29**(1):116-138

[24] Nigg JT. Annual research review: On the relations among self-regulation, self-control, executive functioning, effortful control, cognitive control, impulsivity, risk-taking, and inhibition for developmental psychopathology. Journal of Child Psychology and Psychiatry, and Allied Disciplines. 2017;**58**(4):361-383

[25] Diamond A. Executive functions. Annual Review of Psychology. 2013;**64**:135-168

[26] Zhou Q, Chen SH, Main A. Commonalities and differences in the research on Children's effortful control and executive function: A call for an integrated model of self-regulation. Child Development Perspectives. 2012;**6**(2):112-121

[27] Fals-Stewart W, O'Farrell TJ, Hooley JM. Relapse among married or cohabiting substance-abusing patients: The role of perceived criticism. Behavior Therapy. 2001;**32**(4):787-801

[28] Sripada CS, Angstadt M, McNamara P, King AC, Phan KL. Effects of alcohol on brain responses to social signals of threat in humans. NeuroImage. 2011;**55**(1):371-380

[29] James W. Talks to Teachers on Psychology: And to Students on Some of Life's Ideals. New York: H. Holt; 1899

[30] MacLeod C, Dodd M, Sheard E, Wilson D, Bibi U. In opposition to inhibition. In: The Psychology of Learning and Motivation. Vol. 43. San Diego, CA: B.H. Ross; 2003. pp. 163-214

[31] Smith R. Inhibition: History and Meaning in the Sciences of Mind and Brain. Berkeley: University of California Press; 1992

[32] Logan GD, Cowan WB, Davis KA. On the ability to inhibit simple and choice reaction time responses: A model and a method. Journal of Experimental

**49**

*Addiction: Brain and Cognitive Stimulation for Better Cognitive Control and Far Beyond*

resolution. Psychology and Aging.

Oberauer K. Should we stop thinking about inhibition? Searching for individual and age differences in inhibition ability. Journal of Experimental Psychology. Learning, Memory, and Cognition.

[41] Rey-Mermet A, Gade M,

[42] Stahl C, Voss A, Schmitz F,

Nuszbaum M, Tüscher O, Lieb K, et al. Behavioral components of impulsivity. Journal of Experimental Psychology. General. 2014;**143**(2):850-886

[43] Aron AR. From reactive to proactive and selective control: Developing a richer model for stopping inappropriate

responses. Biological Psychiatry.

[44] Braver TS. The variable nature of cognitive control: A dual mechanisms framework. Trends in Cognitive Sciences. 2012;**16**(2):106-113

[45] Zandbelt BB, Bloemendaal M, Neggers SFW, Kahn RS, Vink M.

the neural network of proactive inhibitory control. Human Brain Mapping. 2013;**34**(9):2015-2024

[46] Schall JD, Godlove DC. Current advances and pressing problems in studies of stopping. Current Opinion in Neurobiology. 2012;**22**(6):1012-1021

[47] Fillmore MT, Weafer J. Behavioral

[48] Verdejo-Garcia A, Chong TT-J, Stout JC, Yücel M, London ED. Stages of dysfunctional decision-making in

inhibition and addiction. In: MacKillop J, de Wit H, editors. The Wiley-Blackwell Handbook of Addiction Psychopharmacology. Chichester, West Sussex; Malden, MA: Wiley-Blackwell;

2013. pp. 135-164

Expectations and violations: Delineating

2011;**69**(12):e55-e68

2014;**29**(2):187-204

2018;**44**(4):501-526

*DOI: http://dx.doi.org/10.5772/intechopen.88869*

[33] Miyake A, Friedman NP, Emerson MJ, Witzki AH, Howerter A, Wager TD. The

Psychology. Human Perception and Performance. 1984;**10**(2):276-291

unity and diversity of executive functions and their contributions to complex "frontal lobe" tasks: A latent variable analysis. Cognitive Psychology.

[34] Miyake A, Friedman NP. The nature and organization of individual differences in executive functions: Four general conclusions. Current Directions in Psychological Science.

[35] Botvinick M, Braver T. Motivation and cognitive control: From behavior to neural mechanism. Annual Review of

[36] Ridderinkhof KR. Neurocognitive mechanisms of perception-action coordination: A review and theoretical

[37] Verbruggen F. Executive control of actions across time and space. Current Directions in Psychological Science.

[38] Verbruggen F, Logan GD. Proactive adjustments of response strategies in the stop-signal paradigm. Journal of Experimental Psychology. Human

Perception and Performance.

[39] Friedman NP, Miyake A. The relations among inhibition and interference control functions: A latent-variable analysis. Journal of Experimental Psychology. General.

[40] Pettigrew C, Martin RC. Cognitive declines in healthy aging: Evidence from multiple aspects of interference

Psychology. 2015;**66**:83-113

integration. Neuroscience and Biobehavioral Reviews. 2014;

2000;**41**(1):49-100

2012;**21**(1):8-14

**46**(Pt 1):3-29

2016;**25**(6):399-404

2009;**35**(3):835-854

2004;**133**(1):101-135

*Addiction: Brain and Cognitive Stimulation for Better Cognitive Control and Far Beyond DOI: http://dx.doi.org/10.5772/intechopen.88869*

Psychology. Human Perception and Performance. 1984;**10**(2):276-291

*Inhibitory Control Training - A Multidisciplinary Approach*

self-control, executive functioning, effortful control, cognitive control, impulsivity, risk-taking, and inhibition for developmental psychopathology. Journal of Child Psychology and Psychiatry, and Allied Disciplines.

[25] Diamond A. Executive functions. Annual Review of Psychology.

[26] Zhou Q, Chen SH, Main A. Commonalities and differences in the research on Children's effortful control and executive function: A call for an integrated model of self-regulation. Child Development Perspectives.

[27] Fals-Stewart W, O'Farrell TJ, Hooley JM. Relapse among married or cohabiting substance-abusing patients: The role of perceived criticism. Behavior

Therapy. 2001;**32**(4):787-801

[28] Sripada CS, Angstadt M,

of alcohol on brain responses to social signals of threat in humans. NeuroImage. 2011;**55**(1):371-380

[29] James W. Talks to Teachers on Psychology: And to Students on Some of Life's Ideals. New York: H. Holt; 1899

[30] MacLeod C, Dodd M, Sheard E, Wilson D, Bibi U. In opposition to inhibition. In: The Psychology of Learning and Motivation. Vol. 43. San Diego, CA: B.H. Ross; 2003.

[31] Smith R. Inhibition: History and Meaning in the Sciences of Mind and Brain. Berkeley: University of California

[32] Logan GD, Cowan WB, Davis KA. On the ability to inhibit simple and choice reaction time responses: A model and a method. Journal of Experimental

pp. 163-214

Press; 1992

McNamara P, King AC, Phan KL. Effects

2017;**58**(4):361-383

2013;**64**:135-168

2012;**6**(2):112-121

Poor response inhibition as a predictor of problem drinking and illicit drug use in adolescents at risk for alcoholism and other substance use disorders. Journal of the American Academy of Child and Adolescent Psychiatry.

[18] Noël X, Sferrazza R, Van Der Linden M, Paternot J, Verhas M, Hanak C, et al. Contribution of frontal cerebral blood flow measured by (99m)Tc-Bicisate spect and executive function deficits to predicting treatment

outcome in alcohol-dependent patients. Alcohol and Alcoholism.

[19] Whelan R, Watts R, Orr CA, Althoff RR, Artiges E, Banaschewski T, et al. Neuropsychosocial profiles of current and future adolescent alcohol misusers. Nature. 2014;**512**(7513):185-189

[20] Noël X, Brevers D, Bechara A. A triadic neurocognitive approach to addiction for clinical interventions. Frontiers in Psychiatry. 2013;**4**:179

[21] Verbruggen F, Best M, Bowditch WA, Stevens T, McLaren IPL. The inhibitory control reflex. Neuropsychologia.

[22] Boffo M, Zerhouni O, Gronau QF, van Beek RJJ, Nikolaou K, Marsman M, et al. Cognitive bias modification for behavior change in alcohol and smoking addiction: Bayesian metaanalysis of individual participant data. Neuropsychology Review.

[23] Luigjes J, Segrave R, de Joode N, Figee M, Denys D. Efficacy of invasive and non-invasive brain modulation

[24] Nigg JT. Annual research review: On the relations among self-regulation,

interventions for addiction. Neuropsychology Review. 2019;**29**(1):116-138

2006;**45**(4):468-475

2002;**37**(4):347-354

2014;**65**:263-278

2019;**29**(1):52-78

**48**

[33] Miyake A, Friedman NP, Emerson MJ, Witzki AH, Howerter A, Wager TD. The unity and diversity of executive functions and their contributions to complex "frontal lobe" tasks: A latent variable analysis. Cognitive Psychology. 2000;**41**(1):49-100

[34] Miyake A, Friedman NP. The nature and organization of individual differences in executive functions: Four general conclusions. Current Directions in Psychological Science. 2012;**21**(1):8-14

[35] Botvinick M, Braver T. Motivation and cognitive control: From behavior to neural mechanism. Annual Review of Psychology. 2015;**66**:83-113

[36] Ridderinkhof KR. Neurocognitive mechanisms of perception-action coordination: A review and theoretical integration. Neuroscience and Biobehavioral Reviews. 2014; **46**(Pt 1):3-29

[37] Verbruggen F. Executive control of actions across time and space. Current Directions in Psychological Science. 2016;**25**(6):399-404

[38] Verbruggen F, Logan GD. Proactive adjustments of response strategies in the stop-signal paradigm. Journal of Experimental Psychology. Human Perception and Performance. 2009;**35**(3):835-854

[39] Friedman NP, Miyake A. The relations among inhibition and interference control functions: A latent-variable analysis. Journal of Experimental Psychology. General. 2004;**133**(1):101-135

[40] Pettigrew C, Martin RC. Cognitive declines in healthy aging: Evidence from multiple aspects of interference

resolution. Psychology and Aging. 2014;**29**(2):187-204

[41] Rey-Mermet A, Gade M, Oberauer K. Should we stop thinking about inhibition? Searching for individual and age differences in inhibition ability. Journal of Experimental Psychology. Learning, Memory, and Cognition. 2018;**44**(4):501-526

[42] Stahl C, Voss A, Schmitz F, Nuszbaum M, Tüscher O, Lieb K, et al. Behavioral components of impulsivity. Journal of Experimental Psychology. General. 2014;**143**(2):850-886

[43] Aron AR. From reactive to proactive and selective control: Developing a richer model for stopping inappropriate responses. Biological Psychiatry. 2011;**69**(12):e55-e68

[44] Braver TS. The variable nature of cognitive control: A dual mechanisms framework. Trends in Cognitive Sciences. 2012;**16**(2):106-113

[45] Zandbelt BB, Bloemendaal M, Neggers SFW, Kahn RS, Vink M. Expectations and violations: Delineating the neural network of proactive inhibitory control. Human Brain Mapping. 2013;**34**(9):2015-2024

[46] Schall JD, Godlove DC. Current advances and pressing problems in studies of stopping. Current Opinion in Neurobiology. 2012;**22**(6):1012-1021

[47] Fillmore MT, Weafer J. Behavioral inhibition and addiction. In: MacKillop J, de Wit H, editors. The Wiley-Blackwell Handbook of Addiction Psychopharmacology. Chichester, West Sussex; Malden, MA: Wiley-Blackwell; 2013. pp. 135-164

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addiction. Pharmacology, Biochemistry, and Behavior. 2018;**164**:99-105

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*Inhibitory Control Training - A Multidisciplinary Approach*

Learning to stop responding to

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[88] Houben K, Jansen A. Training inhibitory control. A recipe for resisting sweet temptations. Appetite.

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of mechanisms of action and

Robinson E, Christiansen P, Nolan S, Tudur-Smith C, et al. Inhibitory control training for appetitive behaviour change: A meta-analytic investigation

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[90] Jones A, Field M. The effects of cue-specific inhibition training on alcohol consumption in heavy social drinkers. Experimental and Clinical Psychopharmacology. 2013;**21**(1):8-16

[91] Allom V, Mullan B, Hagger M. Does inhibitory control training improve health behaviour? A meta-analysis.

[92] Turton R, Bruidegom K, Cardi V, Hirsch CR, Treasure J. Novel methods to help develop healthier eating habits for eating and weight disorders: A systematic review and meta-analysis. Neuroscience and Biobehavioral

[93] Eagle DM, Bari A, Robbins TW. The neuropsychopharmacology of action inhibition: Cross-species translation of the stop-signal and go/ no-go tasks. Psychopharmacology.

Health Psychology Review.

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2008;**199**(3):439-456

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2016;**10**(2):168-186

2011;**56**(2):345-349

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[81] Jones A, Guerrieri R, Fernie G, Cole J, Goudie A, Field M. The effects of priming restrained versus disinhibited behaviour on alcohol-seeking in social drinkers. Drug and Alcohol Dependence. 2011;**113**(1):55-61

[82] Redick TS, Shipstead Z, Harrison TL, Hicks KL, Fried DE, Hambrick DZ, et al. No evidence of intelligence improvement after working memory training: A randomized, placebo-controlled study. Journal of Experimental Psychology. General.

2013;**142**(2):359-379

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Cognitive Sciences. 2010;**14**(7):317-324

Jansen A. Getting a grip on drinking behavior: Training working memory to reduce alcohol abuse. Psychological

[85] Wanmaker S, Leijdesdorff SMJ, Geraerts E, van de Wetering BJM, Renkema PJ, Franken IHA. The efficacy of a working memory training in substance use patients: A randomized double-blind placebo-controlled clinical trial. Journal of Clinical and Experimental Neuropsychology.

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[87] Houben K, Havermans RC, Nederkoorn C, Jansen A. Beer à no-go:

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[84] Houben K, Wiers RW,

Science. 2011;**22**(7):968-975

2018;**40**(5):473-486

2014;**40**(4):987-1001

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[98] Veling H, Aarts H, Papies EK. Using stop signals to inhibit chronic dieters' responses toward palatable foods. Behaviour Research and Therapy. 2011;**49**(11):771-780

[99] Hare TA, Camerer CF, Rangel A. Self-control in decision-making involves modulation of the vmPFC valuation system. Science. New York, N.Y. 2009;**324**(5927):646-648

[100] Veling H, Aarts H, Stroebe W. Stop signals decrease choices for palatable foods through decreased food evaluation. Frontiers in Psychology. 2013;**4**:875

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[196] Heeren A, Billieux J, Philippot P, De Raedt R, Baeken C, de Timary P, et al. Impact of transcranial direct current stimulation on attentional bias for threat: A proof-of-concept study among individuals with social anxiety disorder. Social Cognitive and Affective Neuroscience. 2017;**12**(2):251-260

[197] Carmi L, Tendler A, Bystritsky A, Hollander E, Blumberger DM, Daskalakis J, et al. Efficacy and safety of deep transcranial magnetic stimulation for obsessive-compulsive disorder: A prospective multicenter randomized double-blind placebo-controlled trial. The American Journal of Psychiatry. 21 May 2019

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[212] Pedreira ME, Pérez-Cuesta LM, Maldonado H. Mismatch between what is expected and what actually occurs triggers memory reconsolidation or extinction. Learning & Memory

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[213] Sevenster D, Beckers T, Kindt M. Prediction error governs pharmacologically induced amnesia for learned fear. Science.

2013;**339**(6121):830-833

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2016;**233**(5):851-861

2018;**235**(3):695-708

[214] Das RK, Lawn W, Kamboj SK. Rewriting the valuation and salience of alcohol-related stimuli via memory

[215] Hon T, Das RK, Kamboj SK. The effects of cognitive reappraisal following retrieval-procedures

[216] Kaag AM, Goudriaan AE, De Vries TJ, Pattij T, Wiers RW. A high working memory load prior to memory retrieval reduces craving in non-treatment seeking problem drinkers. Psychopharmacology.

[217] Everitt BJ, Giuliano C, Belin D. Addictive behaviour in experimental

reconsolidation. Translational Psychiatry. 2015;**5**:e645

2004;**11**(5):579-585

2012;**336**(6078):241-245

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[210] Xue Y-X, Luo Y-X, Wu P, Shi H-S, Xue L-F, Chen C, et al. A memory retrieval-extinction procedure to prevent drug craving and relapse. Science (New York, N.Y.). 2012;**336**(6078):241-245

*Inhibitory Control Training - A Multidisciplinary Approach*

[200] Pavlov I. Conditioned Reflexes. USA: Oxford University

[201] Conklin CA, Tiffany ST. Applying extinction research and theory to cue-exposure addiction

[202] Dunsmoor JE, Niv Y, Daw N, Phelps EA. Rethinking extinction.

[203] Milton AL, Everitt BJ. The psychological and neurochemical mechanisms of drug memory reconsolidation: Implications for the treatment of addiction. The European Journal of Neuroscience.

[204] Lee JLC, Nader K, Schiller D. An update on memory reconsolidation updating. Trends in Cognitive Sciences.

[206] Sandrini M, Cohen LG, Censor N. Modulating reconsolidation: A link to causal systems-level dynamics of human memories. Trends in Cognitive Sciences.

[207] McGaugh JL. Time-dependent processes in memory storage. Science (New York, N.Y.). 1966;**153**(3742):1351-1358

[208] Soeter M, Kindt M. An abrupt transformation of phobic behavior after a post-retrieval amnesic agent. Biological

Psychiatry. 2015;**78**(12):880-886

[209] Monfils M-H, Cowansage KK, Klann E, LeDoux JE. Extinctionreconsolidation boundaries: Key to persistent attenuation of fear memories.

Science. 2009;**324**(5929):951-955

treatments. Addiction. 2002;**97**(2):155-167

Neuron. 2015;**88**(1):47-63

2010;**31**(12):2308-2319

2017;**21**(7):531-545

[205] Nader K, Schafe GE, Le Doux JE. Fear memories require protein synthesis in the amygdala for reconsolidation after retrieval. Nature.

2000;**406**(6797):722-726

2015;**19**(8):475-482

Press; 1927

[194] Sedgmond J, Lawrence NS, Verbruggen F, Morrison S,

Science. 2019;**6**(1):181186

2019;**43**(7):1591-1599

Chambers CD, Adams RC. Prefrontal brain stimulation during food-related inhibition training: Effects on food craving, food consumption and inhibitory control. Royal Society Open

[195] Claus ED, Klimaj SD, Chavez R, Martinez AD, Clark VP. A randomized trial of combined tDCS over right inferior frontal cortex and cognitive bias modification: Null effects on drinking and alcohol approach bias. Alcoholism, Clinical and Experimental Research.

[196] Heeren A, Billieux J, Philippot P, De Raedt R, Baeken C, de Timary P, et al. Impact of transcranial direct current stimulation on attentional bias for threat: A proof-of-concept study among individuals with social anxiety disorder. Social Cognitive and Affective Neuroscience. 2017;**12**(2):251-260

[197] Carmi L, Tendler A, Bystritsky A,

Daskalakis J, et al. Efficacy and safety of deep transcranial magnetic stimulation for obsessive-compulsive disorder: A prospective multicenter randomized double-blind placebo-controlled trial. The American Journal of Psychiatry.

[198] Carmi L, Alyagon U, Barnea-Ygael N, Zohar J, Dar R, Zangen A. Clinical and electrophysiological outcomes of deep TMS over the medial prefrontal and anterior cingulate cortices in OCD patients. Brain Stimulation.

[199] Dinur-Klein L, Dannon P, Hadar A, Rosenberg O, Roth Y, Kotler M, et al. Smoking cessation induced by deep repetitive transcranial magnetic

stimulation of the prefrontal and insular cortices: A prospective, randomized controlled trial. Biological Psychiatry.

Hollander E, Blumberger DM,

21 May 2019

2018;**11**(1):158-165

2014;**76**(9):742-749

**60**

[211] Schiller D, Kanen JW, LeDoux JE, Monfils M-H, Phelps EA. Extinction during reconsolidation of threat memory diminishes prefrontal cortex involvement. Proceedings of the National Academy of Sciences of the United States of America. 2013;**110**(50):20040-20045

[212] Pedreira ME, Pérez-Cuesta LM, Maldonado H. Mismatch between what is expected and what actually occurs triggers memory reconsolidation or extinction. Learning & Memory (Cold Spring Harbor, N.Y.). 2004;**11**(5):579-585

[213] Sevenster D, Beckers T, Kindt M. Prediction error governs pharmacologically induced amnesia for learned fear. Science. 2013;**339**(6121):830-833

[214] Das RK, Lawn W, Kamboj SK. Rewriting the valuation and salience of alcohol-related stimuli via memory reconsolidation. Translational Psychiatry. 2015;**5**:e645

[215] Hon T, Das RK, Kamboj SK. The effects of cognitive reappraisal following retrieval-procedures designed to destabilize alcohol memories in high-risk drinkers. Psychopharmacology. 2016;**233**(5):851-861

[216] Kaag AM, Goudriaan AE, De Vries TJ, Pattij T, Wiers RW. A high working memory load prior to memory retrieval reduces craving in non-treatment seeking problem drinkers. Psychopharmacology. 2018;**235**(3):695-708

[217] Everitt BJ, Giuliano C, Belin D. Addictive behaviour in experimental animals: Prospects for translation. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences. 2018;**373**:1742

[218] Lane RD, Ryan L, Nadel L, Greenberg L. Memory reconsolidation, emotional arousal, and the process of change in psychotherapy: New insights from brain science. The Behavioral and Brain Sciences. 2015;**38**:e1

[219] Marián M, Szőllősi Á, Racsmány M. Anodal transcranial direct current stimulation of the right dorsolateral prefrontal cortex impairs long-term retention of reencountered memories. Cortex; A Journal Devoted to the Study of the Nervous System and Behavior. 2018;**108**:80-91

[220] Gladwin TE, Wiers CE, Wiers RW. Interventions aimed at automatic processes in addiction: Considering necessary conditions for efficacy. Current Opinion in Behavioral Sciences. 2017;**13**:19-24

[221] Connolly Gibbons MB, Crits-Christoph P, Barber JP, Stirman SW, Gallop R, Goldstein LA, et al. Unique and common mechanisms of change across cognitive and dynamic psychotherapies. Journal of Consulting and Clinical Psychology. 2009;**77**(5):801-813

[222] Connolly Gibbons MB, Crits-Christoph P, Barber JP, Schamberger M. Insight in psychotherapy: A review of empirical literature. In: Castonguay LG, Hill C, editors. Insight in Psychotherapy. 2007. pp. 143-165

[223] Gollwitzer P, Sheeran P. Implementation intentions and goal achievement: A meta-analysis of effects and processes. In: Zanna MP, editor. Advances in Experimental Social Psychology. Vol. 38. Academic Press; 2006. pp. 69-119

**Chapter 4**

**Abstract**

**1. Introduction**

17–18 years [4].

**63**

Binge Drinking and Memory in

Adolescents and Young Adults

The binge drinking (BD) pattern of alcohol consumption, characterized by intermittent consumption of large quantities of alcohol in short periods, is currently prevalent during adolescence and early youth. This period is characterized by critical changes to the structural and functional development of brain areas related with memory, as well as other executive functions. As a result, BD has been associated with undermined learning and memory ability in adolescents and youths of both sexes. One distinctive contribution of this chapter is to evaluate, together, the impact of an acute BD episode, the sample's history of consumption, and its effect on learning and memory performance and as potential gender differences. The main findings of the published research show that BD has differential effects on several types of memory and confirm that women are more vulnerable to these detrimental effects of alcohol than are men. These cognitive differences between men and women seem to be overridden as the blood alcohol concentration progressively increases. As BD pattern of consumption has been associated with inhibitory control deficits, future research also should investigate long-term implementation of inhibitory control training, emphasizing the importance of this training as part of

*Concepción Vinader-Caerols and Santiago Monleón*

the intervention strategies focused on this at-risk group.

**Keywords:** binge drinking, memory, adolescence, youth, gender

Alcohol is one of the most widely consumed psychoactive substances in the world, especially among adolescents and young adults [1, 2]. Many of these develop a pattern of alcohol consumption known as binge drinking (BD). BD has been defined by The National Institute on Alcohol Abuse and Alcoholism (NIAAA) as a pattern of drinking that elevates a person's blood alcohol concentration (BAC) to 0.8 g/L or above [3]. This pattern involves the intake of large quantities of alcohol in a short period (about 2 h), followed by a period of abstinence, with a variability between 1 week and 1 month (see **Figure 1**). BD is the most common pattern of alcohol use among adolescents and young adults in Western countries. In Spain, the prevalence of BD pattern is similar in both sexes among 14–16 year-old adolescents and is more widespread among men than women in the age range of

Individuals engaging in frequent BD have an increased risk to develop an alcohol

use disorder (AUD) later in life. This risk has been suggested to be linked to

[224] Ekhtiari H, Tavakoli H, Addolorato G, Baeken C, Bonci A, Campanella S, et al. Transcranial electrical and magnetic stimulation (tES and TMS) for addiction medicine: A consensus paper on the present state of the science and the road ahead. Neuroscience and Biobehavioral Reviews. 2019;**104**:118-140

[225] Campanella S, Schroder E, Kajosch H, Noel X, Kornreich C. Why cognitive event-related potentials (ERPs) should have a role in the management of alcohol disorders. Neuroscience and Biobehavioral Reviews. San Diego, California. 21 Jun 2018

[226] Dunbar AB, Taylor JR. Reconsolidation and psychopathology: Moving towards reconsolidation-based treatments. Neurobiology of Learning and Memory. 2017;**142**(Pt A):162-171

[227] Monfils MH, Holmes EA. Memory boundaries: Opening a window inspired by reconsolidation to treat anxiety, trauma-related, and addiction disorders. The Lancet. Psychiatry. 2018;**5**(12):1032-1042

## **Chapter 4**

*Inhibitory Control Training - A Multidisciplinary Approach*

Campanella S, et al. Transcranial electrical and magnetic stimulation (tES and TMS) for addiction medicine: A consensus paper on the present state of the science and the road ahead. Neuroscience and Biobehavioral Reviews. 2019;**104**:118-140

[224] Ekhtiari H, Tavakoli H, Addolorato G, Baeken C, Bonci A,

[225] Campanella S, Schroder E, Kajosch H, Noel X, Kornreich C. Why cognitive event-related potentials (ERPs) should have a role in the management of alcohol disorders. Neuroscience and Biobehavioral Reviews. San Diego,

California. 21 Jun 2018

[226] Dunbar AB, Taylor JR.

Reconsolidation and psychopathology: Moving towards reconsolidation-based treatments. Neurobiology of Learning and Memory. 2017;**142**(Pt A):162-171

[227] Monfils MH, Holmes EA. Memory

boundaries: Opening a window inspired by reconsolidation to treat anxiety, trauma-related, and addiction disorders. The Lancet. Psychiatry.

2018;**5**(12):1032-1042

**62**

## Binge Drinking and Memory in Adolescents and Young Adults

*Concepción Vinader-Caerols and Santiago Monleón*

## **Abstract**

The binge drinking (BD) pattern of alcohol consumption, characterized by intermittent consumption of large quantities of alcohol in short periods, is currently prevalent during adolescence and early youth. This period is characterized by critical changes to the structural and functional development of brain areas related with memory, as well as other executive functions. As a result, BD has been associated with undermined learning and memory ability in adolescents and youths of both sexes. One distinctive contribution of this chapter is to evaluate, together, the impact of an acute BD episode, the sample's history of consumption, and its effect on learning and memory performance and as potential gender differences. The main findings of the published research show that BD has differential effects on several types of memory and confirm that women are more vulnerable to these detrimental effects of alcohol than are men. These cognitive differences between men and women seem to be overridden as the blood alcohol concentration progressively increases. As BD pattern of consumption has been associated with inhibitory control deficits, future research also should investigate long-term implementation of inhibitory control training, emphasizing the importance of this training as part of the intervention strategies focused on this at-risk group.

**Keywords:** binge drinking, memory, adolescence, youth, gender

## **1. Introduction**

Alcohol is one of the most widely consumed psychoactive substances in the world, especially among adolescents and young adults [1, 2]. Many of these develop a pattern of alcohol consumption known as binge drinking (BD). BD has been defined by The National Institute on Alcohol Abuse and Alcoholism (NIAAA) as a pattern of drinking that elevates a person's blood alcohol concentration (BAC) to 0.8 g/L or above [3]. This pattern involves the intake of large quantities of alcohol in a short period (about 2 h), followed by a period of abstinence, with a variability between 1 week and 1 month (see **Figure 1**). BD is the most common pattern of alcohol use among adolescents and young adults in Western countries. In Spain, the prevalence of BD pattern is similar in both sexes among 14–16 year-old adolescents and is more widespread among men than women in the age range of 17–18 years [4].

Individuals engaging in frequent BD have an increased risk to develop an alcohol use disorder (AUD) later in life. This risk has been suggested to be linked to

*Inhibitory Control Training - A Multidisciplinary Approach*

these skills [10]. For example, the superior associative cortex (e.g., prefrontal cortex) undergoes myelination, pruning, and synaptic reorganization [11, 12], among other alterations. Significant changes in the volume and shape of the hippocampal complex, a brain region that plays an important role in memory functions, are also

Due to this plasticity, the adolescent brain seems to be especially vulnerable to the neurotoxic effects of alcohol. In fact, alcohol-related performance deficits in tasks assessing cognitive processes, such as attention, memory, and executive functions, in the not-yet-adult brain are more evident during adolescence [16, 17] and

The intermittence between BD episodes seems to be the most important factor involved, as the repeated alternation between intoxication and withdrawal is particularly deleterious for the brain, due to the excitotoxic cell death it provokes [19, 20]. Thus, it has been demonstrated that BD episodes can be more harmful for the brain

Therefore, the BD adolescent population constitutes a cohort at risk of brain damage, and any disruptive effects of alcohol on learning and memory abilities in

*Preferred reporting items for systematic reviews and meta-analyses (PRISMA) flow diagram showing how*

become more pronounced with a BD pattern of consumption [12, 18].

than an equivalent amount of alcohol without withdrawal episodes [20, 21].

observed during this developmental period [13–15].

*Binge Drinking and Memory in Adolescents and Young Adults*

*DOI: http://dx.doi.org/10.5772/intechopen.88485*

**Figure 2.**

**65**

*articles were selected for review.*

**Figure 1.**

*(a) Binge drinking pattern criteria. Quantity: intake of 50–56 g of pure alcohol in women and 60–70 g in men, in 2 h. Frequency: at least one BD episode per month. Intermittency: abstinence between BD episodes over time (minimum 1 week, maximum 1 month). (b) Number of drinks (1 drink = SDU, standard drink unit) in the USA and Europe for binge drinking's BAC levels.*

executive deficits (e.g., [5]). The BD pattern of consumption seems to be especially associated with increased impulsivity and inhibitory control deficits (e.g., [6–8]). At the same time, this seems to be due to an attenuated frontal activation (e.g., [8, 9]). Thus, a higher incidence of BD has been related to decreased activation of dorsolateral prefrontal cortex, dorsomedial prefrontal cortex, and anterior cingulate cortex, brain regions strongly implicated in executive functioning [9]. The neurotoxic effects of BD on these regions can be less evident throughout adolescence, but if this alcohol consumption pattern persists, the executive dysfunction could be exacerbated. While individuals with AUD typically exhibit inhibitory control dysfunction, evidence of impaired inhibitory control among binge drinkers, who are at increased risk of developing an AUD, is mixed. Despite the variability in the literature, some findings point to mechanisms that may confer vulnerability for transition from binge drinking to AUD [6]. Therefore, inhibitory control deficits must be considered as an important factor that contributes to alcohol abuse.

On the other hand, important physical, social, and cognitive skills are acquired during adolescence and early youth. This period is also characterized by critical changes to the structural and functional development of brain areas related with

these skills [10]. For example, the superior associative cortex (e.g., prefrontal cortex) undergoes myelination, pruning, and synaptic reorganization [11, 12], among other alterations. Significant changes in the volume and shape of the hippocampal complex, a brain region that plays an important role in memory functions, are also observed during this developmental period [13–15].

Due to this plasticity, the adolescent brain seems to be especially vulnerable to the neurotoxic effects of alcohol. In fact, alcohol-related performance deficits in tasks assessing cognitive processes, such as attention, memory, and executive functions, in the not-yet-adult brain are more evident during adolescence [16, 17] and become more pronounced with a BD pattern of consumption [12, 18].

The intermittence between BD episodes seems to be the most important factor involved, as the repeated alternation between intoxication and withdrawal is particularly deleterious for the brain, due to the excitotoxic cell death it provokes [19, 20]. Thus, it has been demonstrated that BD episodes can be more harmful for the brain than an equivalent amount of alcohol without withdrawal episodes [20, 21].

Therefore, the BD adolescent population constitutes a cohort at risk of brain damage, and any disruptive effects of alcohol on learning and memory abilities in

**Figure 2.**

*Preferred reporting items for systematic reviews and meta-analyses (PRISMA) flow diagram showing how articles were selected for review.*

executive deficits (e.g., [5]). The BD pattern of consumption seems to be especially associated with increased impulsivity and inhibitory control deficits (e.g., [6–8]). At the same time, this seems to be due to an attenuated frontal activation (e.g., [8, 9]). Thus, a higher incidence of BD has been related to decreased activation of dorsolateral prefrontal cortex, dorsomedial prefrontal cortex, and anterior cingulate cortex, brain regions strongly implicated in executive functioning [9]. The neurotoxic effects of BD on these regions can be less evident throughout adolescence, but if this alcohol consumption pattern persists, the executive dysfunction could be exacerbated. While individuals with AUD typically exhibit inhibitory control dysfunction, evidence of impaired inhibitory control among binge drinkers, who are at increased risk of developing an AUD, is mixed. Despite the variability in the literature, some findings point to mechanisms that may confer vulnerability for transition from binge drinking to AUD [6]. Therefore, inhibitory control deficits must be

*(a) Binge drinking pattern criteria. Quantity: intake of 50–56 g of pure alcohol in women and 60–70 g in men, in 2 h. Frequency: at least one BD episode per month. Intermittency: abstinence between BD episodes over time (minimum 1 week, maximum 1 month). (b) Number of drinks (1 drink = SDU, standard drink unit) in the*

On the other hand, important physical, social, and cognitive skills are acquired during adolescence and early youth. This period is also characterized by critical changes to the structural and functional development of brain areas related with

considered as an important factor that contributes to alcohol abuse.

**Figure 1.**

**64**

*USA and Europe for binge drinking's BAC levels.*

*Inhibitory Control Training - A Multidisciplinary Approach*

this age group could have a particularly deep impact and last through to adulthood. Moreover, females would seem to be more vulnerable to these detrimental effects of alcohol [22].

alcohol use [22]. There is evidence suggesting that female adolescents are more vulnerable to the neurotoxic effects of alcohol on cognition [22, 26, 27], since the cognitive tolerance effect of alcohol on IVM develops in BD women but not in BD men [24]. Other authors have found that men generally report lower sensitivity to alcohol (individuals need more alcohol to experience the same sensations or impairments) than women, and reactivity to alcohol-related cues is more pronounced in male than in female binge drinkers (e.g., [11]). These results might at least partially explain why men typically show a higher prevalence of alcohol consumption than women. However, in Spain at least, the incidence of alcohol consumption in 14–18-year-old adolescents is higher among females than males [4], while the BD pattern during adolescence is similar in 14–16-year-old adolescents and is more common among men than women in the age range of 17–18 years [4]. Gender differences in WM have also been reported in healthy young subjects, showing an advantage in this memory among males, with females exhibiting disadvantages manifested by a small effect size in both verbal and visuospatial WM [28]. This male advantage could be due to the activating effects of testosterone [29], though age and specific task modulate the magnitude and direction of the effects (e.g., [28, 30]). However, there are reviews in literature that explore the history of BD consumption but not the acute effects it exerts and which does not support the existence of gender differences in the effects of alcohol on this type of memory

*Binge Drinking and Memory in Adolescents and Young Adults*

*DOI: http://dx.doi.org/10.5772/intechopen.88485*

In the light of these data, it would seem crucial to consider (a) including both sexes, men and women, in any studies carried out and (b) evaluating potential gender differences in the relationship between BD and memory in adolescents and

Selected subjects were invited to participate in our studies if they reported refraining from alcohol consumption (or having indulged in very sporadic consumption) or a history of alcohol use classified as a BD pattern according to the NIAAA criteria for Spain (see [12]). Subsequently, the participants were classified as fulfilling a BD pattern if they had drunk six or more standard drink units (SDU) in the case of men or five or more SDU in the case of women on a minimum of two or three occasions per month throughout the 12 months prior to the survey. In Spain

a SDU = 10 g of alcohol of distilled spirits (alcohol content ≥40% vol.). It is

Therefore, in the studies reviewed in this chapter, including ours:

A. The experimental subjects were nondependent individuals indulging in alcohol use, usually evaluated by the Alcohol Use Disorders Identification Test (AUDIT) or others, such as the brief Michigan Alcoholism Screening test

B. A very noticeable factor is the variability both in the samples' history

(refrainers, habitual consumers, binge drinkers, light binge drinkers, etc.) and in the acute administration of alcohol that leads to a BAC of 0.8 g/L (see

important to clarify that a stable BD pattern maintained over the time (12 months in the case of our studies) is a crucial criterion, because repeated alternation between intoxication and abstinence has been shown to be particularly harmful to the developing brain [19, 20]. Participants were classified as refrainers if they had never consumed alcoholic beverages or had drunk very sporadically (<1 SDU on <3 occasions per year, for example, 250 ml of beer, per occasion) since the onset of

(e.g., [31]).

young adults.

their alcohol use.

(e.g., [25]).

**67**

**2.3 Pattern alcohol consumption**

In the following sections, the main insights provided by studies performed by our group and other researchers about the effects of BD on learning and memory performance will be discussed. We focus on the types of memory that are most damaged by alcohol: immediate visual memory (IVM) and working memory (WM). One distinctive contribution of this chapter is to evaluate, together, the impact of an acute BD episode and the sample's history of consumption on learning and memory performance, as well as the possible gender differences at play.

For this review, we conducted a literature search of three databases: *Web of Science*, *PsycINFO*, and *PubMed*. The following combination of key terms was used: binge/heavy/social OR adolescent/young OR blood alcohol OR immediate/working/ memory OR alcohol/ethanol OR cognitive AND acute alcohol. These keywords were examined in the "title" section for *Web of Science* and *PsycINFO* and "title/abstract" sections for *PubMed*. We considered studies published in English since 2000 (1 January 2000–30 November 2018) in humans. The total number of studies identified through the initial database searching was 677 (*Web of Science*, 284 records; *PsycINFO*, 215 records; *PubMed*, 178 records). Duplicated records were removed, and other articles were excluded using strict exclusion criteria: no BD pattern, out of age range (18–35 years old), psychiatric disorders, and other criteria described in the "methods" section. Eventually, 15 full-text articles were included in this review (see **Figure 2** and **Table 1**). This review is limited by the publication bias (databases not included), procedure of selection bias, and unavailable data.

## **2. Methods**

#### **2.1 Subjects**

The experimental subjects in our studies (e.g., [23, 24]) were adolescent university students, who filled in a self-report questionnaire about consumption of drugs, frequency and level of alcohol consumption, hours and quality of sleep, and physical and psychological health. They were recruited based on strict inclusion and exclusion criteria. The inclusion criteria used were 18–19 years old, a healthy body mass index (between 20 and 25), and good health (without major medical problems). The subjects had to be refrainers (or very occasional alcohol consumers) or binge drinkers. The exclusion criteria were as follows: on medication; a history of mental disorders (diagnosed by a health professional according to DSM criteria); an irregular sleep pattern (non-restorative sleep and/or irregular schedule); having consumed, albeit sporadically, any drug (apart from alcohol) or having a history of substance abuse, including caffeine (our criterion: ≤2 stimulant drinks/day), tobacco (our criterion: ≤10 cigarettes/day), and alcohol (except for the BD consumption pattern); and having first-degree relatives with a history of alcoholism.

Other studies reviewed in this chapter included adolescents and young adults (18–35 years old) selected by similar or less restrictive inclusion/exclusion criteria, considering the alcohol use of subjects (history of problems due to alcohol use) and a history of mental health treatment (e.g., [25]).

#### **2.2 Gender**

Gender differences in the effects of alcohol have been reported, supporting the view that the brains of male and female adolescents are differentially affected by

*Binge Drinking and Memory in Adolescents and Young Adults DOI: http://dx.doi.org/10.5772/intechopen.88485*

this age group could have a particularly deep impact and last through to adulthood. Moreover, females would seem to be more vulnerable to these detrimental effects of

*Inhibitory Control Training - A Multidisciplinary Approach*

In the following sections, the main insights provided by studies performed by our group and other researchers about the effects of BD on learning and memory performance will be discussed. We focus on the types of memory that are most damaged by alcohol: immediate visual memory (IVM) and working memory (WM). One distinctive contribution of this chapter is to evaluate, together, the impact of an acute BD episode and the sample's history of consumption on learning and memory performance, as well as the possible gender differences at play. For this review, we conducted a literature search of three databases: *Web of Science*, *PsycINFO*, and *PubMed*. The following combination of key terms was used: binge/heavy/social OR adolescent/young OR blood alcohol OR immediate/working/ memory OR alcohol/ethanol OR cognitive AND acute alcohol. These keywords were examined in the "title" section for *Web of Science* and *PsycINFO* and "title/abstract" sections for *PubMed*. We considered studies published in English since 2000 (1 January 2000–30 November 2018) in humans. The total number of studies identified through the initial database searching was 677 (*Web of Science*, 284 records; *PsycINFO*, 215 records; *PubMed*, 178 records). Duplicated records were removed, and other articles were excluded using strict exclusion criteria: no BD pattern, out of age range (18–35 years old), psychiatric disorders, and other criteria described in the "methods" section. Eventually, 15 full-text articles were included in this review (see **Figure 2** and **Table 1**). This review is limited by the publication bias (databases

not included), procedure of selection bias, and unavailable data.

a history of mental health treatment (e.g., [25]).

The experimental subjects in our studies (e.g., [23, 24]) were adolescent university students, who filled in a self-report questionnaire about consumption of drugs, frequency and level of alcohol consumption, hours and quality of sleep, and physical and psychological health. They were recruited based on strict inclusion and exclusion criteria. The inclusion criteria used were 18–19 years old, a healthy body mass index (between 20 and 25), and good health (without major medical problems). The subjects had to be refrainers (or very occasional alcohol consumers) or binge drinkers. The exclusion criteria were as follows: on medication; a history of mental disorders (diagnosed by a health professional according to DSM criteria); an irregular sleep pattern (non-restorative sleep and/or irregular schedule); having consumed, albeit sporadically, any drug (apart from alcohol) or having a history of substance abuse, including caffeine (our criterion: ≤2 stimulant drinks/day), tobacco (our criterion: ≤10 cigarettes/day), and alcohol (except for the BD consumption pattern); and having first-degree relatives with a history of alcoholism. Other studies reviewed in this chapter included adolescents and young adults (18–35 years old) selected by similar or less restrictive inclusion/exclusion criteria, considering the alcohol use of subjects (history of problems due to alcohol use) and

Gender differences in the effects of alcohol have been reported, supporting the view that the brains of male and female adolescents are differentially affected by

alcohol [22].

**2. Methods**

**2.1 Subjects**

**2.2 Gender**

**66**

alcohol use [22]. There is evidence suggesting that female adolescents are more vulnerable to the neurotoxic effects of alcohol on cognition [22, 26, 27], since the cognitive tolerance effect of alcohol on IVM develops in BD women but not in BD men [24]. Other authors have found that men generally report lower sensitivity to alcohol (individuals need more alcohol to experience the same sensations or impairments) than women, and reactivity to alcohol-related cues is more pronounced in male than in female binge drinkers (e.g., [11]). These results might at least partially explain why men typically show a higher prevalence of alcohol consumption than women. However, in Spain at least, the incidence of alcohol consumption in 14–18-year-old adolescents is higher among females than males [4], while the BD pattern during adolescence is similar in 14–16-year-old adolescents and is more common among men than women in the age range of 17–18 years [4].

Gender differences in WM have also been reported in healthy young subjects, showing an advantage in this memory among males, with females exhibiting disadvantages manifested by a small effect size in both verbal and visuospatial WM [28]. This male advantage could be due to the activating effects of testosterone [29], though age and specific task modulate the magnitude and direction of the effects (e.g., [28, 30]). However, there are reviews in literature that explore the history of BD consumption but not the acute effects it exerts and which does not support the existence of gender differences in the effects of alcohol on this type of memory (e.g., [31]).

In the light of these data, it would seem crucial to consider (a) including both sexes, men and women, in any studies carried out and (b) evaluating potential gender differences in the relationship between BD and memory in adolescents and young adults.

### **2.3 Pattern alcohol consumption**

Selected subjects were invited to participate in our studies if they reported refraining from alcohol consumption (or having indulged in very sporadic consumption) or a history of alcohol use classified as a BD pattern according to the NIAAA criteria for Spain (see [12]). Subsequently, the participants were classified as fulfilling a BD pattern if they had drunk six or more standard drink units (SDU) in the case of men or five or more SDU in the case of women on a minimum of two or three occasions per month throughout the 12 months prior to the survey. In Spain a SDU = 10 g of alcohol of distilled spirits (alcohol content ≥40% vol.). It is important to clarify that a stable BD pattern maintained over the time (12 months in the case of our studies) is a crucial criterion, because repeated alternation between intoxication and abstinence has been shown to be particularly harmful to the developing brain [19, 20]. Participants were classified as refrainers if they had never consumed alcoholic beverages or had drunk very sporadically (<1 SDU on <3 occasions per year, for example, 250 ml of beer, per occasion) since the onset of their alcohol use.

Therefore, in the studies reviewed in this chapter, including ours:


**Table 1** "sample's history of consumption" and "cognitive performance—with (BAC)—" entries for details).

with an alcoholmeter to ensure that they had not previously drunk alcohol on the day in question, and the alcohol use of the BD adolescent subjects was assessed using the AUDIT test (none of the subjects was assessed as alcohol-dependent). Next, refrainers and binge drinkers drank 330 ml of lime- or orange-flavored refreshment (control groups), and binge drinkers' drank a high dose of alcohol. Alcohol was administered in a fixed dose of 120 ml (38.4 g) consisting of vodka mixed with the abovementioned refreshment for both genders or in function of their body weight (0.9 g alcohol/kg body weight in men and 0.8 g alcohol/kg body weight in women). The subjects were instructed to consume their drink within a period of 20 min. After finishing the drink, all subjects rinsed their mouths with water, and BAC was repeatedly measured every 5 min throughout the waiting period, until it reached a peak (approximately 20 min after consuming the drink). This peak of BAC was considered the value with which to classify the participants into the different experimental groups. The subjects performed the IVM and WM tests, while BAC was descendent. BAC was measured once again at the beginning of the tests, between the tests and at the end of the experiment. The BACs registered for the male and female subjects (separately or together) in the different experi-

*Binge Drinking and Memory in Adolescents and Young Adults*

*DOI: http://dx.doi.org/10.5772/intechopen.88485*

A. 0.0 g/L, in refrainers men (*n* = 17) and women (*n* = 24) or BD men (*n* = 23) and women (*n* = 27). These are control groups receiving a nonalcoholic drink.

C. 0.38 g/L, in refrainers men (*n* = 11) and women (*n* = 11) or BD men (n = 11)

E. 0.3–0.5 g/L (mean = 0.4 g/L), in BD men (*n* = 12) and women (*n* = 12).

F. 0.54–1.1 g/L (mean = 0.8 g/L), in BD men (*n* = 14) and women (*n* = 24).

(Note: The A, B, C, and D experimental groups belong to Ref. 23; and the A, E,

All tests were performed between 4:00 pm and 8:00 pm, and the subjects that

Similar procedures were applied in the other reviewed studies, where cognitive performance—with (BAC)—was evaluated after alcohol intake administered in fixed doses or according to body weight. Participants also abstained from alcohol for at least 12 h prior to the experiment, as well as drinking coffee or tea on the mornings prior to the experiment, and were instructed to eat a low-fat breakfast

The main findings obtained in our experimental investigations and those of other groups are summarized in **Table 1**. The effects of acute alcohol consumption—one BD episode with different BACs—on different types of memory are reviewed. A total number of 15 studies are summarized. Only three of them included adolescent male and females (18–20 years old) [23, 24, 33]; the participants in the

received alcohol remained on the premises until their alcohol concentration

and lunch on the day on which tests were performed (e.g., [35]).

B. 0.33 g/L, in refrainers men (*n* = 17) or BD men (*n* = 22).

D.0.5 g/L, in refrainers (*n* = 18) or BD women (*n* = 24).

and F experimental groups belong to Ref. 24).

dropped to legal limits for driving (<0.3 g/L).

mental groups were:

**3. Results**

**69**

and women (*n* = 11).


## **2.4 Memory tests**

In our studies, the third edition of the Wechsler Memory Scale (WMS-III; version adapted for the Spanish population) [32] was used to assess IVM and WM. The IVM subscales require the respondent to recognize faces and remember scenes, while the WM subscales require the respondent to put letter-number sets in order and to reproduce visual-spatial sequences. The literature reports a poorer performance in these types of memory under the acute effects of alcohol (e.g., [24, 33]) and especially in WM associated with a stable BD maintained in time (e.g., [34]).

Other scales used for the evaluation of these or similar types of memory are:


Obviously, the use of different tests/batteries for evaluating memory contributes to the heterogeneity of results in this field of research.

## **2.5 Procedure**

In our procedure, all participants signed an informed consent and a data confidentiality agreement on arrival at the laboratory. BAC was measured in all subjects *Binge Drinking and Memory in Adolescents and Young Adults DOI: http://dx.doi.org/10.5772/intechopen.88485*

**Table 1** "sample's history of consumption" and "cognitive performance—with

C. Depending on the study, performance in the memory task was registered as

D.Taking into account the scarcity of studies evaluating acute alcohol consumption in adolescent and young adult refrainers or occasional consumers (e.g., [23]), the present chapter provides unique insights into this field of research.

In our studies, the third edition of the Wechsler Memory Scale (WMS-III; version adapted for the Spanish population) [32] was used to assess IVM and WM. The IVM subscales require the respondent to recognize faces and remember scenes, while the WM subscales require the respondent to put letter-number sets in order and to reproduce visual-spatial sequences. The literature reports a poorer performance in these types of memory under the acute effects of alcohol (e.g., [24, 33]) and especially in WM associated with a stable BD maintained in time (e.g., [34]). Other scales used for the evaluation of these or similar types of memory are:

• The Cambridge Neuropsychological Test Automated Battery (CANTAB) for evaluating spatial recognition memory. The CANTAB is a computer-based cognitive assessment system consisting of a battery of neuropsychological tests, administered to subjects using a touch screen computer. This battery evaluates several areas of cognitive function using nonverbal stimuli in the majority of its tests, including the pattern recognition memory, a test of visual

recognition memory in a two-choice forced discrimination paradigm.

for evaluating long- and short-term memory, working memory, and

recognition memory, visual working memory, visual processing speed,

• The Wechsler Adult Intelligence Scale (WAIS-R) with the digit symbol substitution test (DSST) for evaluating short-term memory. The WAIS-R (revised form of the WAIS, a test designed to measure intelligence and cognitive ability in adults and older adolescents) consisted of six verbal and five performance subtests, including the DSST. This subtest (DSST-WAIS-R) consists of digit-symbol pairs followed by a list of digits; under each digit the subject must write down the corresponding symbol as fast as possible within

reaction time, and numerical sequencing ability.

to the heterogeneity of results in this field of research.

the allowed time.

**2.5 Procedure**

**68**

• The Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT)

declarative memory. The ImPACT is a computer-based program for assessing neurocognitive function and concussion symptoms. This neurocognitive test battery consists of several modules for evaluating attentional processes, verbal

Obviously, the use of different tests/batteries for evaluating memory contributes

In our procedure, all participants signed an informed consent and a data confidentiality agreement on arrival at the laboratory. BAC was measured in all subjects

(BAC)—" entries for details).

*Inhibitory Control Training - A Multidisciplinary Approach*

either rising or declining BACs.

**2.4 Memory tests**

with an alcoholmeter to ensure that they had not previously drunk alcohol on the day in question, and the alcohol use of the BD adolescent subjects was assessed using the AUDIT test (none of the subjects was assessed as alcohol-dependent). Next, refrainers and binge drinkers drank 330 ml of lime- or orange-flavored refreshment (control groups), and binge drinkers' drank a high dose of alcohol. Alcohol was administered in a fixed dose of 120 ml (38.4 g) consisting of vodka mixed with the abovementioned refreshment for both genders or in function of their body weight (0.9 g alcohol/kg body weight in men and 0.8 g alcohol/kg body weight in women). The subjects were instructed to consume their drink within a period of 20 min. After finishing the drink, all subjects rinsed their mouths with water, and BAC was repeatedly measured every 5 min throughout the waiting period, until it reached a peak (approximately 20 min after consuming the drink). This peak of BAC was considered the value with which to classify the participants into the different experimental groups. The subjects performed the IVM and WM tests, while BAC was descendent. BAC was measured once again at the beginning of the tests, between the tests and at the end of the experiment. The BACs registered for the male and female subjects (separately or together) in the different experimental groups were:


D.0.5 g/L, in refrainers (*n* = 18) or BD women (*n* = 24).

E. 0.3–0.5 g/L (mean = 0.4 g/L), in BD men (*n* = 12) and women (*n* = 12).

F. 0.54–1.1 g/L (mean = 0.8 g/L), in BD men (*n* = 14) and women (*n* = 24).

(Note: The A, B, C, and D experimental groups belong to Ref. 23; and the A, E, and F experimental groups belong to Ref. 24).

All tests were performed between 4:00 pm and 8:00 pm, and the subjects that received alcohol remained on the premises until their alcohol concentration dropped to legal limits for driving (<0.3 g/L).

Similar procedures were applied in the other reviewed studies, where cognitive performance—with (BAC)—was evaluated after alcohol intake administered in fixed doses or according to body weight. Participants also abstained from alcohol for at least 12 h prior to the experiment, as well as drinking coffee or tea on the mornings prior to the experiment, and were instructed to eat a low-fat breakfast and lunch on the day on which tests were performed (e.g., [35]).

## **3. Results**

The main findings obtained in our experimental investigations and those of other groups are summarized in **Table 1**. The effects of acute alcohol consumption—one BD episode with different BACs—on different types of memory are reviewed.

A total number of 15 studies are summarized. Only three of them included adolescent male and females (18–20 years old) [23, 24, 33]; the participants in the rest of the studies were in the 18–35-year-old group, without studies comparing adolescents and young adults.

The sample's history of consumption encompasses a range from refrainers to heavy binge drinkers, including habitual consumers/moderate drinkers and light binge drinkers. This variability in the samples of the reviewed studies gives us a more specific view of the acute effects of alcohol in different types of consumers and not only in binge drinkers.

In general, the results obtained in the evaluated memory tasks confirm the deleterious effects of alcohol use. Significant impairments were observed in spatial recognition memory, WM, associative learning, word fragment completion, free recall, long-term memory, short-term memory, and IVM. However, an absence of effects has also been observed with respect to some of these memories, such as visual memory, short-term memory, WM, and IVM. It is possible that the impairing effects observed are conditioned by BAC (ascendant BAC, BAC peak, descendant BAC) in the case of some types of memory. Thus, in studies in which there were


**71**

*Binge Drinking and Memory in Adolescents and Young Adults*

*DOI: http://dx.doi.org/10.5772/intechopen.88485*


*Binge Drinking and Memory in Adolescents and Young Adults DOI: http://dx.doi.org/10.5772/intechopen.88485*

rest of the studies were in the 18–35-year-old group, without studies comparing

The sample's history of consumption encompasses a range from refrainers to heavy binge drinkers, including habitual consumers/moderate drinkers and light binge drinkers. This variability in the samples of the reviewed studies gives us a more specific view of the acute effects of alcohol in different types of consumers

In general, the results obtained in the evaluated memory tasks confirm the deleterious effects of alcohol use. Significant impairments were observed in spatial recognition memory, WM, associative learning, word fragment completion, free recall, long-term memory, short-term memory, and IVM. However, an absence of effects has also been observed with respect to some of these memories, such as visual memory, short-term memory, WM, and IVM. It is possible that the impairing effects observed are conditioned by BAC (ascendant BAC, BAC peak, descendant BAC) in the case of some types of memory. Thus, in studies in which there were

adolescents and young adults.

*Inhibitory Control Training - A Multidisciplinary Approach*

and not only in binge drinkers.

**70**


ascendant and descendant BACs, impairment was reported in long-term memory, short-term memory, and WM declarative memory with ascendant BAC but not

*Effects of acute alcohol consumption (one BD episode with different BACs) on memory in the studies carried out*

Finally, the values for cognitive performance—with (BAC)—in **Table 1** show the absence of effects or impairing effects in every sample, including for BAC of 0.0 g/L (refrainers and binge drinkers consuming refreshment/placebo). For example, in Vinader-Caerols et al. [23], male IVM performance was refrainers (0.0 g/L) = refrainers (0.33 g/L) = BD (0.0 g/L) = BD (0.33 g/L) and women's

The key findings of this review will now be discussed. Among the types of memory reviewed, word fragment completion, free recall, and IVM appear to be the most sensitive to the effects of acute alcohol, as they are affected by moderate doses of alcohol (BAC = 0.3–0.38 g/L) in adolescents and young adults (e.g., [23, 38]). However, higher doses of alcohol (BAC levels of BD, i.e., around 0.8 g/L) are necessary for a significant impairment in other memories, such as WM (e.g., [24]) and short-term memory (e.g., [40]). A plausible explanation for the lack of effects reported with BACs under 0.8 g/L (e.g., [23, 25, 40, 44, 45]) is that the brain of binge drinkers employs compensatory mechanisms in additional brain areas to

performance was BD (0.0 g/L) < refrainers (0.0 g/L).

*Binge Drinking and Memory in Adolescents and Young Adults*

*DOI: http://dx.doi.org/10.5772/intechopen.88485*

with descendant BAC.

*in this field [37, 39, 42, 43 and 46].*

**Table 1.**

**4. Discussion**

**73**


#### **Table 1.**

*Effects of acute alcohol consumption (one BD episode with different BACs) on memory in the studies carried out in this field [37, 39, 42, 43 and 46].*

ascendant and descendant BACs, impairment was reported in long-term memory, short-term memory, and WM declarative memory with ascendant BAC but not with descendant BAC.

Finally, the values for cognitive performance—with (BAC)—in **Table 1** show the absence of effects or impairing effects in every sample, including for BAC of 0.0 g/L (refrainers and binge drinkers consuming refreshment/placebo). For example, in Vinader-Caerols et al. [23], male IVM performance was refrainers (0.0 g/L) = refrainers (0.33 g/L) = BD (0.0 g/L) = BD (0.33 g/L) and women's performance was BD (0.0 g/L) < refrainers (0.0 g/L).

## **4. Discussion**

The key findings of this review will now be discussed. Among the types of memory reviewed, word fragment completion, free recall, and IVM appear to be the most sensitive to the effects of acute alcohol, as they are affected by moderate doses of alcohol (BAC = 0.3–0.38 g/L) in adolescents and young adults (e.g., [23, 38]). However, higher doses of alcohol (BAC levels of BD, i.e., around 0.8 g/L) are necessary for a significant impairment in other memories, such as WM (e.g., [24]) and short-term memory (e.g., [40]). A plausible explanation for the lack of effects reported with BACs under 0.8 g/L (e.g., [23, 25, 40, 44, 45]) is that the brain of binge drinkers employs compensatory mechanisms in additional brain areas to

**72**

*Inhibitory Control Training - A Multidisciplinary Approach*

perform the tasks adequately and that these resources are undermined at higher BACs (e.g., [24, 33, 36, 40, 41]).

• Variability in the age ranges in the studies. This variability (see **Table 1**), without a neat separation between adolescents and young adults, does not allow to properly compare these periods in order to find potential differences. Actually, there are not studies directly evaluating possible differences in the effects of acute BD on memory, comparing adolescents and young adults.

*Binge Drinking and Memory in Adolescents and Young Adults*

*DOI: http://dx.doi.org/10.5772/intechopen.88485*

Several studies, using different paradigms (e.g., Stroop task, Go/No-Go task), have also shown that BD during adolescence is associated with poor inhibitory control (e.g., [7, 53]). Inhibitory control processes are developing during adolescence and youth, and a poor inhibitory function may predispose the individual to alcohol misuse [53]. Thus, impaired inhibitory control has been related to increased loss of control over drinking (i.e., a greater number of drinks per episode) [7], and this impairment seems to be related to the severity of alcohol-related problems [54, 55]. Likewise, acute and binge alcohol drinking may impair the inhibitory control and compromise the ability to prevent or stop behavior related to alcohol use. Then, poor inhibitory control can be both the cause and the consequence of excessive alcohol use. Adolescence and young adulthood may be a particularly vulnerable period due to the following reasons: (a) the weak or immature inhibitory functioning typical of this stage may contribute to the inability of the individual to control alcohol use and (b) alcohol consumption per se may alter or interrupt the proper development of inhibitory control leading to a reduced ability to regulate alcohol intake [53]. Therefore, inhibitory control training is a potential effective component of a comprehensive protocol for intervention strategies focused on this at-risk group of young adults who continue a BD trajectory into adulthood. Interventions targeting binge-drinking behavior should aim to inhibitory control training. Increasing the knowledge about the effects of BD alcohol consumption pattern on memory and other executive functions in adolescents and young adults is also instrumental to designing programs and policy to reduce the impact of drinking in this highly vulnerable population in order to diminish the likelihood of participation

After reviewing the literature concerning the effects of one BD episode (with different BACs) on learning and memory performance in adolescents and young

• Alcohol BD has differential effects depending on the type of memory. For example, IVM is more sensitive than other memories to the neurotoxic effects of acute doses of alcohol in adolescents and young adults with a BD history (IVM is affected by a moderate BAC, while WM score is undermined only by

• BAC is an important factor to take into account when evaluating the acute effects of BD alcohol on memory performance in this type of studies.

• Women are more vulnerable to some of the detrimental effects of alcohol than men are. For example, an effect of cognitive alcohol tolerance on IVM has been observed in women but not in men. These gender differences emphasize the need to include females in studies when investigating the neurotoxic effects of

in risky behaviors.

**5. Conclusions**

**75**

BAC levels of BD).

adults, the following conclusions can be drawn:

alcohol in adolescents and youths.

In contrast to the present review, others have attempted to provide an overview of affected (and unaffected) neuropsychological functions in adolescents and young binge drinkers, without evaluating the acute effects of alcohol and considering only the subjects' history of BD (e.g., [31]). However, the interaction between a BD history of consumption and the effects of acute alcohol exposure on learning and memory needs to be studied, as some long-term effects of repeated alcohol exposure in adolescents (such as alcohol tolerance or damaged cognitive abilities) are observed more readily—if at all—following an acute dose of alcohol [23].

It is known that tolerance can develop early in adolescents and young adults without alcohol use disorder [47, 48]. Considering the scarcity of studies that have evaluated the phenomenon of tolerance in healthy adolescents and the potential vulnerability of females to the neurotoxic effects of alcohol, we performed a study [23] in which we observed that binge drinkers performed better in IVM than refrainers when given alcohol (showing the development of alcohol tolerance) and binge drinkers performed worse than refrainers after consuming a nonalcoholic control drink (as their memory would have been damaged). Thus, adolescent women are more vulnerable to the neurotoxic effects of alcohol than men, because the cognitive tolerance effect of alcohol on IVM develops in BD women but not in BD men. The phenomenon of women beginning to drink earlier and progressing more rapidly than men from drinking onset to problematic drinking, known as the "telescoping effect" [49–51], would explain why adolescent women develop cognitive tolerance earlier than men.

Although men and women have been included in some of the reviewed studies, only ours [23, 24] were carried out in order to specifically evaluate these gender differences in adolescents. In our second study [24], although the tolerance phenomenon was not evaluated (because refrainers did not consume an acute dose of alcohol), no gender differences were detected in IVM and WM performance with BAC > 0.5 mg/L. We suspect that an increased BAC overrides these cognitive differences between men and women. At the same time, the BAC is dependent on several factors such as rates of absorption, distribution, and elimination, as well as gender, body mass and composition, food effects, and type of alcohol. Therefore, careful extrapolation and interpretation of the BAC is needed [52].

The findings of the present review would be bolstered with a tighter control of factors that contribute to heterogeneity of results, such as:


*Binge Drinking and Memory in Adolescents and Young Adults DOI: http://dx.doi.org/10.5772/intechopen.88485*

• Variability in the age ranges in the studies. This variability (see **Table 1**), without a neat separation between adolescents and young adults, does not allow to properly compare these periods in order to find potential differences. Actually, there are not studies directly evaluating possible differences in the effects of acute BD on memory, comparing adolescents and young adults.

Several studies, using different paradigms (e.g., Stroop task, Go/No-Go task), have also shown that BD during adolescence is associated with poor inhibitory control (e.g., [7, 53]). Inhibitory control processes are developing during adolescence and youth, and a poor inhibitory function may predispose the individual to alcohol misuse [53]. Thus, impaired inhibitory control has been related to increased loss of control over drinking (i.e., a greater number of drinks per episode) [7], and this impairment seems to be related to the severity of alcohol-related problems [54, 55]. Likewise, acute and binge alcohol drinking may impair the inhibitory control and compromise the ability to prevent or stop behavior related to alcohol use. Then, poor inhibitory control can be both the cause and the consequence of excessive alcohol use. Adolescence and young adulthood may be a particularly vulnerable period due to the following reasons: (a) the weak or immature inhibitory functioning typical of this stage may contribute to the inability of the individual to control alcohol use and (b) alcohol consumption per se may alter or interrupt the proper development of inhibitory control leading to a reduced ability to regulate alcohol intake [53]. Therefore, inhibitory control training is a potential effective component of a comprehensive protocol for intervention strategies focused on this at-risk group of young adults who continue a BD trajectory into adulthood. Interventions targeting binge-drinking behavior should aim to inhibitory control training.

Increasing the knowledge about the effects of BD alcohol consumption pattern on memory and other executive functions in adolescents and young adults is also instrumental to designing programs and policy to reduce the impact of drinking in this highly vulnerable population in order to diminish the likelihood of participation in risky behaviors.

## **5. Conclusions**

perform the tasks adequately and that these resources are undermined at higher

In contrast to the present review, others have attempted to provide an overview of affected (and unaffected) neuropsychological functions in adolescents and young binge drinkers, without evaluating the acute effects of alcohol and considering only the subjects' history of BD (e.g., [31]). However, the interaction between a BD history of consumption and the effects of acute alcohol exposure on learning and memory needs to be studied, as some long-term effects of repeated alcohol exposure in adolescents (such as alcohol tolerance or damaged cognitive abilities) are observed more readily—if at all—following an acute dose of alcohol [23].

It is known that tolerance can develop early in adolescents and young adults without alcohol use disorder [47, 48]. Considering the scarcity of studies that have evaluated the phenomenon of tolerance in healthy adolescents and the potential vulnerability of females to the neurotoxic effects of alcohol, we performed a study [23] in which we observed that binge drinkers performed better in IVM than refrainers when given alcohol (showing the development of alcohol tolerance) and binge drinkers performed worse than refrainers after consuming a nonalcoholic control drink (as their memory would have been damaged). Thus, adolescent women are more vulnerable to the neurotoxic effects of alcohol than men, because the cognitive tolerance effect of alcohol on IVM develops in BD women but not in BD men. The phenomenon of women beginning to drink earlier and progressing more rapidly than men from drinking onset to problematic drinking, known as the "telescoping effect" [49–51], would explain why adolescent women develop cogni-

Although men and women have been included in some of the reviewed studies, only ours [23, 24] were carried out in order to specifically evaluate these gender differences in adolescents. In our second study [24], although the tolerance phenomenon was not evaluated (because refrainers did not consume an acute dose of alcohol), no gender differences were detected in IVM and WM performance with BAC > 0.5 mg/L. We suspect that an increased BAC overrides these cognitive differences between men and women. At the same time, the BAC is dependent on several factors such as rates of absorption, distribution, and elimination, as well as gender, body mass and composition, food effects, and type of alcohol. Therefore,

The findings of the present review would be bolstered with a tighter control of

• Not taking into account the gender factor. The inclusion of men and women in

• Variability in the sample's history of consumption, which can encompass a wide range (refrainers, habitual consumers/moderate drinkers, light binge

• The use of different tests/batteries for evaluating similar memories (e.g.,

• The registration of performance in ascendant/descendant BACs. For example, more deleterious effects are observed in ascendant BAC versus descendant BAC. Most of the studies either they evaluate memory performance in descendant BAC or they do not specify whether the BAC is ascendant or

careful extrapolation and interpretation of the BAC is needed [52].

study samples is more representative of the population.

factors that contribute to heterogeneity of results, such as:

drinkers, heavy binge drinkers, etc.).

CANTAB, ImPACT, WAIS-R).

descendant.

**74**

BACs (e.g., [24, 33, 36, 40, 41]).

*Inhibitory Control Training - A Multidisciplinary Approach*

tive tolerance earlier than men.

After reviewing the literature concerning the effects of one BD episode (with different BACs) on learning and memory performance in adolescents and young adults, the following conclusions can be drawn:


• Further research, particularly longitudinal studies, is necessary in order to confirm the abovementioned findings and to consolidate these conclusions.

**References**

[1] Hibell B, Guttormsson U,

Ahlström S, Balakireva O, Bjarnason T, Kokkevi A, Kraus L. Substance use among students in 35 European Countries (The 2007 European School Survey Project on Alcohol and other Drugs, ESPAD, Report). Stockholm: The European Monitoring Center for Drugs and Drug Addiction; 2007

*DOI: http://dx.doi.org/10.5772/intechopen.88485*

*Binge Drinking and Memory in Adolescents and Young Adults*

[8] Herman AM, Critchley HD, Duka T. Binge drinking is associated with attenuated frontal and parietal activation during successful response inhibition in fearful context. The European Journal of Neuroscience. 2018:

1-14. DOI: 10.1111/ejn.14108

[9] Cohen-Gilbert JE, Nickerson LD, Sneider JT, Oot EN, Seraikas AM, Rohan ML, et al. College binge drinking associated with decreased frontal activation to negative emotional distractors during inhibitory control. Frontiers in Psychology. 2017;**8**:1650. DOI: 10.3389/fpsyg.2017.01650

[10] Blakemore SJ. The social brain in

[11] Petit G, Kornreich C, Verbanck P, Campanella S. Gender differences in reactivity to alcohol cues in binge drinkers: A preliminary assessment of event-related potentials. Psychiatry Research. 2013;**209**:494-503. DOI: 10.1016/j.psychres.2013.04.005

[12] López-Caneda E, Mota N, Crego A, Velasquez T, Corral M, Rodríguez Holguín S, et al. Neurocognitive anomalies associated with the binge drinking pattern of alcohol consumption in adolescents and young people: A review. Adicciones. 2014;**26**:334-359.

DOI: 10.20882/adicciones.39

[13] Gogtay N, Nugent TF 3rd,

Herman DH, Ordonez A, Greenstein D, Hayashi KM, et al. Dynamic mapping of normal human hippocampal development. Hippocampus. 2006;**16**: 664-672. DOI: 10.1002/hipo.20193

[14] DeMaster D, Pathman T, Lee JK, Ghetti S. Structural development of the hippocampus and episodic memory: Developmental differences along the anterior/posterior axis. Cerebral Cortex.

adolescence. Nature Reviews. Neuroscience. 2008;**9**:267-277

[2] Chavez PR, Nelson DE, Naimi TS, Brewer RD. Impact of a new genderspecific definition for binge drinking on prevalence estimates for women. American Journal of Preventive Medicine. 2011;**40**:468-471

[3] National Institute of Alcohol Abuse and Alcoholism. NIAAA council approves definition of binge drinking.

[4] Observatorio Español sobre Drogas (OED). Encuesta Escolar sobre Uso de Drogas en Estudiantes de Enseñanzas Secundarias (ESTUDES) 2014–2015. Madrid: Ministerio de Sanidad, Servicios

[5] Gil-Hernandez S, Garcia-Moreno LM. Executive performance and dysexecutive symptoms in binge drinking adolescents. Alcohol. 2016;**51**:

79-87. DOI: 10.1016/j.alcohol.

[6] Poulton A, Mackenzie C, Harrington K, Borg S, Hester R. Cognitive control over immediate reward in binge alcohol drinkers. Alcoholism, Clinical and Experimental Research. 2016;**40**:429-437. DOI:

[7] Carbia C, Corral M, Doallo S, Caamaño-Isorna F. The dual-process

model in young adults with a consistent binge drinking trajectory into adulthood. Drug and Alcohol Dependence. 2018;**186**:113-119. DOI: 10.1016/j.drugalcdep.2018.01.023

2016.01.003

10.1111/acer.12968

**77**

NIAAA Newsletter. 2004;**3**:3

Sociales e Igualdad; 2016

In relation to the inhibitory control in binge drinkers, taking into account the scarcity of studies evaluating inhibitory control training on alcohol consumption (e.g., [56–58]) and the lack of them evaluating this kind of training on BD, future research should investigate long-term implementation of inhibitory control training, emphasizing the importance of this training as part of the intervention strategies focused on this at-risk group.

## **Acknowledgements**

The authors wish to thank the "Generalitat Valenciana" [PROMETEO-II/2015/ 020] and the "Universitat de València" [UV-INV\_AE18-779336] for the funding part of the work reviewed herein. They also wish to thank Mr. Brian Normanly for his editorial assistance.

## **Conflict of interest**

The authors have no conflict of interest to declare.

## **Author details**

Concepción Vinader-Caerols\* and Santiago Monleón Department of Psychobiology, University of Valencia, Valencia, Spain

\*Address all correspondence to: concepcion.vinader@uv.es

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

*Binge Drinking and Memory in Adolescents and Young Adults DOI: http://dx.doi.org/10.5772/intechopen.88485*

## **References**

• Further research, particularly longitudinal studies, is necessary in order to confirm the abovementioned findings and to consolidate these conclusions.

In relation to the inhibitory control in binge drinkers, taking into account the scarcity of studies evaluating inhibitory control training on alcohol consumption (e.g., [56–58]) and the lack of them evaluating this kind of training on BD, future research should investigate long-term implementation of inhibitory control training, emphasizing the importance of this training as part of the intervention strate-

The authors wish to thank the "Generalitat Valenciana" [PROMETEO-II/2015/ 020] and the "Universitat de València" [UV-INV\_AE18-779336] for the funding part of the work reviewed herein. They also wish to thank Mr. Brian Normanly for

The authors have no conflict of interest to declare.

Concepción Vinader-Caerols\* and Santiago Monleón

provided the original work is properly cited.

\*Address all correspondence to: concepcion.vinader@uv.es

Department of Psychobiology, University of Valencia, Valencia, Spain

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

gies focused on this at-risk group.

*Inhibitory Control Training - A Multidisciplinary Approach*

**Acknowledgements**

his editorial assistance.

**Conflict of interest**

**Author details**

**76**

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d-amphetamine: A within-subject study. Alcoholism, Clinical and Experimental Research. 2001;**25**:540-548. DOI: 10.1111/j.1530-0277.2001.tb02248.x

*Inhibitory Control Training - A Multidisciplinary Approach*

alcoholics. The International Journal of

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consequences and gender. The American Journal on Addictions. 2009;**18**:194-197. DOI: 10.1080/10550490902786991

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examination of alcohol-related

and the Law. 2017;**45**:429-438

[53] López-Caneda E, Rodríguez Holguín S, Cadaveira F, Corral M, Doallo S. Impact of alcohol use on inhibitory control (and vice versa) during adolescence and young adulthood: A review. Alcohol and Alcoholism. 2014;**49**:173-181. DOI:

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10.1093/alcalc/agt168

141-151

[43] Luck SJ, Vogel EK. The capacity of visual working memory for features and conjunctions. Nature. 1997;**390**:279-281.

[44] Paulus MP, Tapert SF, Pulido C, Schuckit MA. Alcohol attenuates loadrelated activation during a working memory task: Relation to level of response to alcohol. Alcoholism, Clinical and Experimental Research. 2006;**30**:

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[46] Cash C, Peacock A, Barrington H,

Psychopharmacology. 2015;**29**:436-446. DOI: 10.1177/0269881115570080

continuum using item response theory: Results from the National Epidemiologic

[47] Saha TD, Chou SP, Grant BF. Toward an alcohol use disorder

Survey on alcohol and related conditions. Psychological Medicine. 2006;**36**:931-941. DOI: 10.1017/

[48] Schuckit MA, Smith TL,

young drinkers. The American Journal of Drug and Alcohol Abuse. 2008;**34**:133-149. DOI: 10.1080/

Hesselbrock V, Bucholz KK, Bierut L, Edenberg H, et al. Clinical implications of tolerance to alcohol in nondependent

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S003329170600746X

00952990701877003

**80**

Sinnett N, Bruno R. Detecting impairment: Sensitive cognitive measures of dose-related acute alcohol

intoxication. Journal of

DOI: 10.1038/36846

1363-1371. DOI: 10.1111/ j.1530-0277.2006.00164.x

agm073

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**83**

veterans

**1. Introduction**

**Chapter 5**

**Abstract**

Life Stress and Inhibitory Control

Deficits: Teaching BrainWise as

Vulnerable Populations

*Marilyn Welsh, Patricia Gorman Barry* 

*and Jared M. Greenberg*

inhibitory control in high-risk populations.

a Neurocognitive Intervention in

The chapter describes inhibitory control in the context of broader and related constructs, executive function and self-regulation. We discuss the adaptive functions of inhibitory control, as well as evidence that life stress, such as poverty, maltreatment, homelessness, and mental illness, negatively impacts individuals' inhibitory control and overall self-regulation skills. Moreover, these stressors are known to disrupt the development and functioning of crucial brain systems underlying inhibitory control. Following this review, we discuss a critical thinking skills intervention, BrainWise, which is designed to teach inhibitory and self-regulation skills to children, youth and adults. We describe the implementation of the program, and review evidence for its effectiveness with various populations, including our recent study that demonstrated the success of BrainWise in teaching these skills to homeless men living in transitional housing. Finally, we describe our proposed future applications of this intervention to veterans suffering serious mental health challenges. Our overarching goals are to highlight the importance of inhibitory control and overall self-regulation, the vulnerability of these important skills to life stress, and the promise held by one neurocognitive intervention for improving

**Keywords:** inhibitory control, executive function, self-regulation, stress, poverty, homelessness, childhood maltreatment, mental illness, intervention, BrainWise,

Inhibitory control, as a key component of goal-directed executive function and overall self-regulation, has implications for a range of adaptive behaviors across development. Individual differences in this self-regulatory ability have implications for accomplishing important life tasks such as educational achievement, securing employment, and establishing successful relationships. Failures to achieve these milestones has enormous personal costs, as well as economic costs to society. The contributions to these individual differences are complex covariations and interactions between biological and environmental forces [1], as is true for the wide swath

## **Chapter 5**
