**3.1 Evidence for the brain mechanisms involvement in the SCR model**

We have recently found (Branković, 2011) that different types of SCRs (orienting response, SCR to pleasant emotional stimuli, weak movement, and respiratory SCR) have distinct regulation (i.e. different system parameters). This finding raises the question of adequacy of the assumption that mathematical models of the SCR process describe the sudomotor innervation and sweat gland activity (Alexander et al., 2005; Bach et al., 2009, 2010a, 2010b, 2011; Benedek & Kaernbach, 2010). The doubt has been recently expressed by Bach and

 4 The estimation of the duration of *fidelity period* of the SCR system in our sample corresponds well to the empirical data on breaking values of the interstimulus interval in the SCR measurement research (Breska et al., 2011; Benedek & Kaernbach, 2010).

Assessment of Brain Monoaminergic Signaling

secretion (Dementienko et al., 2000).

regulation of SCRs to pleasant emotional stimuli.

(measured as the SCR) (Branković, 2001).

Through Mathematical Modeling of Skin Conductance Response 93

Different types of SCR lend support for the central interpretation of the identified model of the SCR process. This view has potentially significant implications. Namely, it follows that metrics of hidden-input and feedback loops in the SCR process could refer to the brain neurocircuitry

The shift from peripheral to central interpretation of the mathematical models of SCR challenges our understanding of the physiological nature of the SCR. Does the phasic electrodermal response reflect sweat secretion, passive diffusion, and reabsorption process? It would be difficult to explain precise influence and transmission of the central neural events on the distinct, stimulus specific SCR form if it would be realized through sluggish processes such as secretion, diffusion, and reabsorption. But there is evidence that formation of SCR could be better explained as determined by constriction of myoepithelial cells of ducts of the sweat glands (associated with vasomotor activity) on activation of the sympathetic nervous system than by long-time secretion, spreading and reabsorption of

Considering the results of the system identification studies of SCR (Branković, 2008, 2011) in the context of the data regarding the functional neuroanatomy of the SCR and emotional processing we suggest the following scenario during the process of generation and

The initial step (generation of the initial neural event, i.e. the input neural signal for the SCR system) takes place in the interaction amygdala–hippocampus: "*Outcome* of the specific patterning of the match-mismatch process in the hippocampus/amygdala complex determines the precise constellation of signals to be either routed onward to the hypothalamus or aborted, and shapes the affective response or lack thereof to any stimulus event" (Hadley, 1989, p. 346; Laine et al., 2009; Phelps, 2004). In the amygdala-hippocampus interplay the role of the hippocampus is to detect novelty and unexpectedness of the stimulus (Kumaran & Maguire, 2007a, 2007b, 2008; Vinogradova, 1975). On the other hand, 'attachment of significance [emotional meaning] to a stimulus is critically dependent on the amygdala" (Mishkin & Aggleton, 1981, p. 412). We assumed that only unexpected pleasant emotional stimuli could elicit initial neural signal for pleasant emotional excitement

It is tempting to hypothesize that some features of the hidden-input to the SCR system could refer to novelty (or unexpectedness) aspect of the stimulus and some other hidden-input measures to significance (or emotional meaning) of the stimulus. It has been already suggested that different features of stimuli were represented through different dimensions of the neural pulse code in one neural system (Masuda & Aihara, 2007). Also, it has been realized that the neural code refers to population activity since individual neurons could not provide sufficient signal-to-noise ratio and speed to transmit information (Lestienne, 2001; Shadlen & Newsome, 1998; Eggermont, 1998). Relying on these findings we suggest that the dimension 'pulse amplitude' in our hidden-inputs metrics could correspond well to the 'population firing rate code' of the neural signal (Masuda & Aihara, 2007). Duration of the pulses in the hidden-input metrics fits the burst duration code (Kepecs & Lisman, 2004).

and neurochemistry rather than to the biophysical properties of the sweat glands.

**3.2 Putative scenario of neural computations during the SCR process** 

Fig. 4. Within-subject distributions of the SCR system parameters of four different subjects

colleagues (2010b) who found a difference of SCRs evoked by aversive pictures in comparison with other applied stimulus classes: "There is no reason why the peripheral output system should exhibit a different response to one stimulus class than to any other... The twist is that it might be possible to estimate characteristics of central nervous function by deconvolving the observed signal." Yet, the spark of this view we can trace back in the Edelberg's work on the so-called recovery limb of the SCR four decades ago. Edelberg (1970) proposed that rapid- and slow-recovery SCRs reflect qualitatively different psychological processes as a result of distinct neural control.

2.7 2.8 2.9 <sup>3</sup> <sup>0</sup>

Input Gain

<sup>0</sup> 0.02 0.04 <sup>0</sup>

log (Input Gain)


2.7 2.8 2.9 <sup>3</sup> <sup>0</sup>

Input Gain

0 2 4 6 x 10-3

log (Input Gain)


Fast Feedback Enhancement


System Gain

<sup>0</sup> <sup>10</sup> <sup>20</sup> <sup>30</sup> <sup>0</sup>

log (System Gain)



System Gain

<sup>0</sup> <sup>20</sup> <sup>40</sup> <sup>60</sup> <sup>0</sup>

log (System Gain)


Feedback Inhibition

0.5 <sup>1</sup> 1.5 <sup>0</sup>

Fidelity Period [seconds]

<sup>12</sup> 12.5 <sup>13</sup> 13.5 <sup>0</sup>

log (Fidelity Period)

1.05 1.1 1.15 1.2 <sup>0</sup>

0.8 0.9 <sup>1</sup> <sup>0</sup>

Fidelity Period [seconds]

<sup>12</sup> 12.5 <sup>13</sup> <sup>0</sup>

log (Fidelity Period)

1.08 1.1 1.12 1.14 <sup>0</sup>

Slow Feedback Enhancement

Slow Feedback Enhancement

1 2 3

> 0.5 1 1.5 2

> > 1 2 3

> > 1 2 3

Feedback Inhibition

1 2 3

> 0.5 1 1.5 2

> > 2 4 6

0.5 1 1.5 2

Fast Feedback Enhancement

1 2 3

2 4 6

2 4 6

> 1 2 3

> 0 1 2

0.5 1 1.5 2

Fig. 4. Within-subject distributions of the SCR system parameters of four different subjects

processes as a result of distinct neural control.

2.7 2.8 2.9 <sup>3</sup> <sup>0</sup>

Input Gain

<sup>0</sup> 0.02 0.04 <sup>0</sup>

log (Input Gain)


Fast Feedback Enhancement

<sup>2</sup> 2.5 <sup>3</sup> <sup>0</sup>

Input Gain

<sup>0</sup> 0.02 0.04 0.06 <sup>0</sup>

log (Input Gain)



System Gain

<sup>0</sup> <sup>5</sup> <sup>10</sup> <sup>15</sup> <sup>0</sup>

log (System Gain)


Feedback Inhibition


System Gain

<sup>0</sup> <sup>10</sup> <sup>20</sup> <sup>0</sup>

log (System Gain)


0.7 0.8 0.9 <sup>1</sup> <sup>0</sup>

Fidelity Period [seconds]

<sup>12</sup> <sup>13</sup> <sup>14</sup> <sup>0</sup>

log (Fidelity Period)

1.05 1.1 1.15 <sup>0</sup>

Slow Feedback Enhancement

0.4 0.6 0.8 <sup>1</sup> <sup>0</sup>

Fidelity Period [seconds]

<sup>12</sup> <sup>14</sup> <sup>16</sup> <sup>18</sup> <sup>0</sup>

log (Fidelity Period)

<sup>1</sup> 1.2 1.4 <sup>0</sup>

Slow Feedback Enhancement

1 2 3

1 2 3

1 2 3

0.5 1 1.5 2

0.5 1 1.5 2

> 1 2 3

Feedback Inhibition

1 2 3

2 4 6

0.5 1 1.5 2

0.5 1 1.5 2

> 1 2 3

> 1 2 3

Fast Feedback Enhancement

1 2 3

0.5 1 1.5 2

0.5 1 1.5 2

0.5 1 1.5 2

> 1 2 3

colleagues (2010b) who found a difference of SCRs evoked by aversive pictures in comparison with other applied stimulus classes: "There is no reason why the peripheral output system should exhibit a different response to one stimulus class than to any other... The twist is that it might be possible to estimate characteristics of central nervous function by deconvolving the observed signal." Yet, the spark of this view we can trace back in the Edelberg's work on the so-called recovery limb of the SCR four decades ago. Edelberg (1970) proposed that rapid- and slow-recovery SCRs reflect qualitatively different psychological Different types of SCR lend support for the central interpretation of the identified model of the SCR process. This view has potentially significant implications. Namely, it follows that metrics of hidden-input and feedback loops in the SCR process could refer to the brain neurocircuitry and neurochemistry rather than to the biophysical properties of the sweat glands.

The shift from peripheral to central interpretation of the mathematical models of SCR challenges our understanding of the physiological nature of the SCR. Does the phasic electrodermal response reflect sweat secretion, passive diffusion, and reabsorption process? It would be difficult to explain precise influence and transmission of the central neural events on the distinct, stimulus specific SCR form if it would be realized through sluggish processes such as secretion, diffusion, and reabsorption. But there is evidence that formation of SCR could be better explained as determined by constriction of myoepithelial cells of ducts of the sweat glands (associated with vasomotor activity) on activation of the sympathetic nervous system than by long-time secretion, spreading and reabsorption of secretion (Dementienko et al., 2000).

### **3.2 Putative scenario of neural computations during the SCR process**

Considering the results of the system identification studies of SCR (Branković, 2008, 2011) in the context of the data regarding the functional neuroanatomy of the SCR and emotional processing we suggest the following scenario during the process of generation and regulation of SCRs to pleasant emotional stimuli.

The initial step (generation of the initial neural event, i.e. the input neural signal for the SCR system) takes place in the interaction amygdala–hippocampus: "*Outcome* of the specific patterning of the match-mismatch process in the hippocampus/amygdala complex determines the precise constellation of signals to be either routed onward to the hypothalamus or aborted, and shapes the affective response or lack thereof to any stimulus event" (Hadley, 1989, p. 346; Laine et al., 2009; Phelps, 2004). In the amygdala-hippocampus interplay the role of the hippocampus is to detect novelty and unexpectedness of the stimulus (Kumaran & Maguire, 2007a, 2007b, 2008; Vinogradova, 1975). On the other hand, 'attachment of significance [emotional meaning] to a stimulus is critically dependent on the amygdala" (Mishkin & Aggleton, 1981, p. 412). We assumed that only unexpected pleasant emotional stimuli could elicit initial neural signal for pleasant emotional excitement (measured as the SCR) (Branković, 2001).

It is tempting to hypothesize that some features of the hidden-input to the SCR system could refer to novelty (or unexpectedness) aspect of the stimulus and some other hidden-input measures to significance (or emotional meaning) of the stimulus. It has been already suggested that different features of stimuli were represented through different dimensions of the neural pulse code in one neural system (Masuda & Aihara, 2007). Also, it has been realized that the neural code refers to population activity since individual neurons could not provide sufficient signal-to-noise ratio and speed to transmit information (Lestienne, 2001; Shadlen & Newsome, 1998; Eggermont, 1998). Relying on these findings we suggest that the dimension 'pulse amplitude' in our hidden-inputs metrics could correspond well to the 'population firing rate code' of the neural signal (Masuda & Aihara, 2007). Duration of the pulses in the hidden-input metrics fits the burst duration code (Kepecs & Lisman, 2004).

Assessment of Brain Monoaminergic Signaling

**monoaminergic signaling** 

chain during the SCR process.

brain.

1999).

Through Mathematical Modeling of Skin Conductance Response 95

Considering the neurochemical meaning of the system parameters in the SCR model (e.g. feedback loops' gains) the following important issue should be clarified. Although the nodes in our dynamic model (Figure 2) could be realized as principal points on the path of integration and feedback regulation of the central neural signal conveying the information for emotional sweating we do not expect that the SCR signal which we measure at the skin surface and which figures as the slow positive feedback loop in the SCR model is actually transmitted back to the brain through some receptors and ascending neural pathways and takes part in the regulation of arousal. Rather, we suppose that in the central regulation of the arousal appears some neural signal (we assume a brain stem monoaminergic activity) with the similar and coherent temporal characteristics as the measured SCR which is the real slow positive feedback signal in the process of the SCR.6 We hold the similar view on the fast positive feedback signal and the negative feedback signal in our SCR model. Mathematically they appear as the first and the second derivative of the measured SCR signal but neurobiologically they correspond to two earlier nodes in the neural integration

Keeping in mind this notion we are equipped with a broader and more flexible perspective which could yield to a more accurate identification of the neurochemical meaning of the SCR system parameters than it would be the case if we would persist in trying to find real neuroanatomical pathways which convey the SCR signal (which we measure) back to the

In order to reveal neurochemical meaning of the parameters obtained through mathematical modeling of the SCR process we have conducted a psychopharmacological intervention study. The basic idea had been to detect and follow the changes in the SCR system parameters in psychiatric patients receiving medication with well defined influence on certain brain neurotransmitter systems. The idea corresponds to that what Humble (2000) has assigned as "the psychopharmacological dissection". Although antidepressant exerts neither a single neurotransmitter effect nor a single action on a neurotransmission system (Leonard, 2000) there are differences among them. They differ in selectivity for both reuptake inhibition and receptor blockade. Among the most selective drugs for "the psychopharmacological dissection" are citalopram (the purest serotonin reuptake inhibitor available), reboxetin (the purest noradrenaline reuptake inhibitor), and maprotiline (which exerts considerably more receptor-blocking activity but also less inhibition of serotonin

In agreement with the thesis that identified control process of SCR takes place in the neurocircuitry located between amygdala and brain stem speaks comparability of spectral characteristics of the signal components of the SCR system (SCR signal, its derivatives, and periodicity of the hidden input) on one side, with dominant oscillatory activity of the brain structures engaged in arousal process in that section of the neuroaxis (Branković, 2011). 6 Similarity in temporal patterns displayed by a central measure of brain function (the N200 component of event-related potentials) and the measured peripheral SCR signal has been already detected, demonstrating dynamic relationship between the SCR signal and a brain neural process (Lim et al.,

reuptake than other noradrenaline reuptake inhibitors) (Humble, 2000).

**4. Revealing the neurochemical meaning of the parameters in the model of the SCR process: Foundation for the psychophysiological probing of brain** 

Finally, temporal distribution of the pulses in the 'hidden-input for the SCR' could refer to the temporal neural code (e.g. inter-burst interval) (Lestienne, 2001). Further work should be done to explore the statistics and semantics of the 'hidden-input code'. Probably, the neural code of the amigdalohippocampal circuit converts some subjective features (estimations) of stimuli ("stimulus attributes arrived at by computational process", and not physical attributes of stimuli (Eggermont, 1998)) into emotional (sympathetic) response. In other words, different dimensions of the hidden-input metrics could relate to different features (e.g. novelty vs. intensity (Barry, 2006)) of the stimulus that evokes the SCR.

The amigdalo-hippocampal interplay (resulting in the generation of neural input for the emotional SCR) is probably realized through the rhythmic, theta-related (5-11 Hz) modulation of neuronal activities in the amigdalo-hippocampal circuit which may provide adequate recurring time windows when synaptic interaction will be facilitated in this limbic network (Seidenbecher et al., 2003; Paré & Gaudreau, 1996). The theta selfsynchronization of hippocampal and amygdala neurons (suggesting functional connectivity between those neurons) is not continuous but periodic process, which occurs both spontaneously every 5-30 seconds (mean 12.9 s) in brain slices maintained *in vitro* (Kano et al., 2005) and confronted with emotion-inducing stimuli (Pape et al., 2005; Seidenbecher et al., 2003). Interestingly, the periodicity of the amigdalo-hippocampal theta synchronization fits well with the fidelity period of the emotional SCR system – about 13 seconds (see 2.3.2). Moreover, the periodic theta amigdalo-hippocampal neural synchronizations last up to 2.5 seconds (Kano et al., 2005) what corresponds to the duration of the hidden-input pulses for the emotional SCR (see 2.3.1).

Along with the large amplitude theta synchronous oscillations both amygdala and hippocampal neurons generate action potentials at 24-45 Hz during the initial component of the periodic amigdalo-hippocampal synchronization (Kano et al., 2005). We speculate that postsynaptic integration of this early high frequency component of synchronous periodic events could be responsible for the strength (amplitude, height) of the "hidden" neural input for the emotional SCR (see 2.3.1). With this ends the first phase in the SCR process – generation of the neural input (the trigger of the emotional response).

The next phase is transmission and regulation of the SCR. This phase is realized through bidirectional connections among amygdala, hypothalamus, and the brain stem (cf. Pfaff, et al., 2005). In his neurobiological model of emotion regulation Lewis (2005) emphasized multiple positive and negative feedback components originating from brain stem which back up to amygdala and other cortical and subcortical systems increasing the activation of some systems while decreasing it in others. In the identified (central) control process of the SCR we detected three feedback loops (see 2.3.2). According to the known neurobiology of arousal the first candidates for the neurochemical substrate of the feedback loops could be brainstem originating monoaminergic inervation of amygdala and hippocampus: i.e. dopaminergic, noradrenergic, and serotonergic system.5

<sup>5</sup> "The activation of structures at different levels of the neuroaxis drives the brain into vertical integration. Reciprocal influences among brain stem, hypothalamic, and corticolimbic regions become coupled, perhaps through synchronization of independent oscillators, and this coupling may give rise to an emergent meta-synchronization that coordinates all lower-order couplings" (Lewis, 2005, p. 192).

Finally, temporal distribution of the pulses in the 'hidden-input for the SCR' could refer to the temporal neural code (e.g. inter-burst interval) (Lestienne, 2001). Further work should be done to explore the statistics and semantics of the 'hidden-input code'. Probably, the neural code of the amigdalohippocampal circuit converts some subjective features (estimations) of stimuli ("stimulus attributes arrived at by computational process", and not physical attributes of stimuli (Eggermont, 1998)) into emotional (sympathetic) response. In other words, different dimensions of the hidden-input metrics could relate to different features

The amigdalo-hippocampal interplay (resulting in the generation of neural input for the emotional SCR) is probably realized through the rhythmic, theta-related (5-11 Hz) modulation of neuronal activities in the amigdalo-hippocampal circuit which may provide adequate recurring time windows when synaptic interaction will be facilitated in this limbic network (Seidenbecher et al., 2003; Paré & Gaudreau, 1996). The theta selfsynchronization of hippocampal and amygdala neurons (suggesting functional connectivity between those neurons) is not continuous but periodic process, which occurs both spontaneously every 5-30 seconds (mean 12.9 s) in brain slices maintained *in vitro* (Kano et al., 2005) and confronted with emotion-inducing stimuli (Pape et al., 2005; Seidenbecher et al., 2003). Interestingly, the periodicity of the amigdalo-hippocampal theta synchronization fits well with the fidelity period of the emotional SCR system – about 13 seconds (see 2.3.2). Moreover, the periodic theta amigdalo-hippocampal neural synchronizations last up to 2.5 seconds (Kano et al., 2005) what corresponds to the

Along with the large amplitude theta synchronous oscillations both amygdala and hippocampal neurons generate action potentials at 24-45 Hz during the initial component of the periodic amigdalo-hippocampal synchronization (Kano et al., 2005). We speculate that postsynaptic integration of this early high frequency component of synchronous periodic events could be responsible for the strength (amplitude, height) of the "hidden" neural input for the emotional SCR (see 2.3.1). With this ends the first phase in the SCR process –

The next phase is transmission and regulation of the SCR. This phase is realized through bidirectional connections among amygdala, hypothalamus, and the brain stem (cf. Pfaff, et al., 2005). In his neurobiological model of emotion regulation Lewis (2005) emphasized multiple positive and negative feedback components originating from brain stem which back up to amygdala and other cortical and subcortical systems increasing the activation of some systems while decreasing it in others. In the identified (central) control process of the SCR we detected three feedback loops (see 2.3.2). According to the known neurobiology of arousal the first candidates for the neurochemical substrate of the feedback loops could be brainstem originating monoaminergic inervation of amygdala and hippocampus: i.e.

<sup>5</sup> "The activation of structures at different levels of the neuroaxis drives the brain into vertical integration. Reciprocal influences among brain stem, hypothalamic, and corticolimbic regions become coupled, perhaps through synchronization of independent oscillators, and this coupling may give rise to an emergent meta-synchronization that coordinates all lower-order couplings" (Lewis, 2005, p. 192).

(e.g. novelty vs. intensity (Barry, 2006)) of the stimulus that evokes the SCR.

duration of the hidden-input pulses for the emotional SCR (see 2.3.1).

generation of the neural input (the trigger of the emotional response).

dopaminergic, noradrenergic, and serotonergic system.5

#### **4. Revealing the neurochemical meaning of the parameters in the model of the SCR process: Foundation for the psychophysiological probing of brain monoaminergic signaling**

Considering the neurochemical meaning of the system parameters in the SCR model (e.g. feedback loops' gains) the following important issue should be clarified. Although the nodes in our dynamic model (Figure 2) could be realized as principal points on the path of integration and feedback regulation of the central neural signal conveying the information for emotional sweating we do not expect that the SCR signal which we measure at the skin surface and which figures as the slow positive feedback loop in the SCR model is actually transmitted back to the brain through some receptors and ascending neural pathways and takes part in the regulation of arousal. Rather, we suppose that in the central regulation of the arousal appears some neural signal (we assume a brain stem monoaminergic activity) with the similar and coherent temporal characteristics as the measured SCR which is the real slow positive feedback signal in the process of the SCR.6 We hold the similar view on the fast positive feedback signal and the negative feedback signal in our SCR model. Mathematically they appear as the first and the second derivative of the measured SCR signal but neurobiologically they correspond to two earlier nodes in the neural integration chain during the SCR process.

Keeping in mind this notion we are equipped with a broader and more flexible perspective which could yield to a more accurate identification of the neurochemical meaning of the SCR system parameters than it would be the case if we would persist in trying to find real neuroanatomical pathways which convey the SCR signal (which we measure) back to the brain.

In order to reveal neurochemical meaning of the parameters obtained through mathematical modeling of the SCR process we have conducted a psychopharmacological intervention study. The basic idea had been to detect and follow the changes in the SCR system parameters in psychiatric patients receiving medication with well defined influence on certain brain neurotransmitter systems. The idea corresponds to that what Humble (2000) has assigned as "the psychopharmacological dissection". Although antidepressant exerts neither a single neurotransmitter effect nor a single action on a neurotransmission system (Leonard, 2000) there are differences among them. They differ in selectivity for both reuptake inhibition and receptor blockade. Among the most selective drugs for "the psychopharmacological dissection" are citalopram (the purest serotonin reuptake inhibitor available), reboxetin (the purest noradrenaline reuptake inhibitor), and maprotiline (which exerts considerably more receptor-blocking activity but also less inhibition of serotonin reuptake than other noradrenaline reuptake inhibitors) (Humble, 2000).

In agreement with the thesis that identified control process of SCR takes place in the neurocircuitry located between amygdala and brain stem speaks comparability of spectral characteristics of the signal components of the SCR system (SCR signal, its derivatives, and periodicity of the hidden input) on one side, with dominant oscillatory activity of the brain structures engaged in arousal process in that section

of the neuroaxis (Branković, 2011). 6 Similarity in temporal patterns displayed by a central measure of brain function (the N200 component of event-related potentials) and the measured peripheral SCR signal has been already detected, demonstrating dynamic relationship between the SCR signal and a brain neural process (Lim et al., 1999).

Assessment of Brain Monoaminergic Signaling

input, i.e. the inter-pulse interval remained unchanged.

regarding the effect on the hidden-input pulse prolongation.

**Pulse Amplitude Change [%]** 

**Pulse Duration Change [%]** 

**Inter-Pulse Pause Change [%]** 

**system parameters** 

**Hidden-input feature Citalopram Venlafaxin/** 

125.55 (19.98)

6.74 (36.64)

28.53 (30.92)

Table 1. Effects of a serotonergic agent (citalopram), dual acting agents (venlafaxin or clomipramine), and a noradrenergic antidepressant (maprotiline) on the hidden-input characteristics. The values represent means of the relative change in percents (SD).

**4.2 Tonic and phasic functions of the brain monoaminergic signaling and the SCR** 

Relying on our neurobiological model of the SCR process (see 3.2) it follows that the parameter *input gain* appears as an indicator of the tonic function of the brain monoaminergic signaling. On the other hand, feedback loops' gains seem to refer to phasic

Through Mathematical Modeling of Skin Conductance Response 97

antidepressant treatment phase. We tested the hypothesis that serotonergic and noradrenergic agents influence the process of generation of the initial neural input for the SCR system examining if there is any pattern of change in the amplitude and duration of the hidden-input in depressed patients before and during the treatment with antidepressants. The t-tests for dependent samples (using Bonferroni correction for multiple tests) revealed significant increase of the hidden-input amplitude and prolongation of the input pulse after four weeks of antidepressant treatment considering all applied agents together. The chronic antidepressant treatment did not significantly affect the timing of the pulses in the hidden-

In order to test if the monoaminergic agents show distinctive effect on the features of the hidden-input the following multivariate analysis of variance has been performed. We compared the relative change (in percents) of the hidden-input measures in the three groups of patients underwent to three different four weeks treatments: 1) citalopram group, 2) venlafaxin or clomipramine treated group, and 3) maprotiline group. The MANOVA revealed significant difference on the overall model between the treatment groups (Wilks' lambda=0.463, F(6, 82)=6.42, p<0.0005, multivariate eta-squared=0.32). The univariate analyses of variance revealed significant differences among the treatment groups regarding the hiddeninput amplitude (eta-squared=0.438) and hidden-input duration (eta-squared=0.143) and nonsignificant differences regarding the inter-pulse pause. Pairwise comparisons revealed a stronger increasing effect on the hidden-input amplitude of the serotonergic agent (citalopram) than it was the case after venlafaxin or clomipramine treatment (Table 1). Interestingly, chronic treatment with maprotiline brought to lessening of the hidden-input amplitude. On the other hand, all three kinds of applied monoaminergic agents brought to prolongation of the hiddeninput pulse but citalopram was significantly less effective than both venlafaxin/clomipramine and maprotiline. The last two kinds of treatment were not mutually significantly different

**Clomipramine Maprotiline** 


41.18 (13.31)


39.91 (22.89)

36.64 (9.98)

79.68 (35.425)

The neurochemical agents which we used to perform a kind of "the psychopharmacological dissection" of the SCR system were: (1) citalopram (daily dose 20 mg), a selective serotonin reuptake inhibitor (SSRI) – in revealing the serotonergic components of the SCR system (in 21 depressed patients); (2) maprotiline (daily dose 150 mg) – in revealing the noradrenergic SCR system's components (in 20 depressed patients); and (3) venlafaxin (daily dose 225 mg) or clomipramine (daily dose 150 mg) as dual acting (both serotonergic and noradrenergic) agents (in 18 depressed patients). The patients were diagnosed according to the DSM-IV criteria (American Psychiatric Association, 1994) for major depressive disorder currently in depressive episode. The mean score on the Hamilton (1960) rating scale for depression (HAMD) with 17 items was 21.4 (SD=6.7) on the day of the first psychophysiological measurement (the day before starting the pharmacological treatment) with non-significant differences among the treatment groups. All patients manifested significant clinical improvement after four weeks of the inter-trial period assessed as reduction of the HAMD score for more than 50 %.

One concept of the modern neuroscience should be mentioned before we continue with the results of the pharmacological intervention study. It deals with the distinction between the tonic and the phasic neurotransmitters' function. We find this distinction essentially for understanding the observed SCR system parameters' change in patients under psychopharmacological treatment. In the following we explain how some of the parameters refer to the tonic and others indicate the phasic function of serotonin and noradrenaline.

#### **4.1 The hidden-input measures and the brain monoaminergic systems**

According to the suggested scenario of neural computations during the SCR process (see 3.2) two features of the hidden input – pulse *amplitude* and *duration* – could be supposed as dependent not only on the characteristics of the encountering stimulus but also on the tonic monoaminergic innervation of the amygdalo-hippocampal circuit. For instance, it was shown that both dopamine agonists and antagonists alter the amygdala response to emotional stimuli (Salgado-Pineda et al., 2005; Takahashi et al., 2005; Exner et al., 2004). It is also known that noradrenaline modulates the filter function in the hippocampus causing an increase in the signal-to-noise ratio of the pyramidal cells such that the cells' response to stimuli near action potential threshold are inhibited, whereas the responses to larger stimuli are enhanced (Nicoll et al., 1987; Segal & Bloom, 1976).

Comparison between healthy subjects and acutely depressed patients of our sample regarding the amplitude and duration of the hidden-input and inter-pulse interval was performed using the t-test for independent samples with Bonferroni adjustment for multiple tests. The tests revealed significant lower amplitude of the hidden-input in depression and no difference regarding the duration and inter-pulse interval between healthy and depressed participants.

In order to test whether the diminution of the hidden-input amplitude in depression is due to deviant brain monoaminergic function we conducted an intervention study with antidepressants and probed the SCR system of the patients at the three times: 1) the day 0, i.e. the day before starting the antidepressant treatment, 2) the day 7, corresponding to the acute antidepressant treatment phase, and 3) the day 28, corresponding to the chronic

The neurochemical agents which we used to perform a kind of "the psychopharmacological dissection" of the SCR system were: (1) citalopram (daily dose 20 mg), a selective serotonin reuptake inhibitor (SSRI) – in revealing the serotonergic components of the SCR system (in 21 depressed patients); (2) maprotiline (daily dose 150 mg) – in revealing the noradrenergic SCR system's components (in 20 depressed patients); and (3) venlafaxin (daily dose 225 mg) or clomipramine (daily dose 150 mg) as dual acting (both serotonergic and noradrenergic) agents (in 18 depressed patients). The patients were diagnosed according to the DSM-IV criteria (American Psychiatric Association, 1994) for major depressive disorder currently in depressive episode. The mean score on the Hamilton (1960) rating scale for depression (HAMD) with 17 items was 21.4 (SD=6.7) on the day of the first psychophysiological measurement (the day before starting the pharmacological treatment) with non-significant differences among the treatment groups. All patients manifested significant clinical improvement after four weeks of the inter-trial period assessed as reduction of the HAMD

One concept of the modern neuroscience should be mentioned before we continue with the results of the pharmacological intervention study. It deals with the distinction between the tonic and the phasic neurotransmitters' function. We find this distinction essentially for understanding the observed SCR system parameters' change in patients under psychopharmacological treatment. In the following we explain how some of the parameters refer to the tonic and others indicate the phasic function of serotonin and noradrenaline.

According to the suggested scenario of neural computations during the SCR process (see 3.2) two features of the hidden input – pulse *amplitude* and *duration* – could be supposed as dependent not only on the characteristics of the encountering stimulus but also on the tonic monoaminergic innervation of the amygdalo-hippocampal circuit. For instance, it was shown that both dopamine agonists and antagonists alter the amygdala response to emotional stimuli (Salgado-Pineda et al., 2005; Takahashi et al., 2005; Exner et al., 2004). It is also known that noradrenaline modulates the filter function in the hippocampus causing an increase in the signal-to-noise ratio of the pyramidal cells such that the cells' response to stimuli near action potential threshold are inhibited, whereas the responses to larger stimuli

Comparison between healthy subjects and acutely depressed patients of our sample regarding the amplitude and duration of the hidden-input and inter-pulse interval was performed using the t-test for independent samples with Bonferroni adjustment for multiple tests. The tests revealed significant lower amplitude of the hidden-input in depression and no difference regarding the duration and inter-pulse interval between healthy and

In order to test whether the diminution of the hidden-input amplitude in depression is due to deviant brain monoaminergic function we conducted an intervention study with antidepressants and probed the SCR system of the patients at the three times: 1) the day 0, i.e. the day before starting the antidepressant treatment, 2) the day 7, corresponding to the acute antidepressant treatment phase, and 3) the day 28, corresponding to the chronic

**4.1 The hidden-input measures and the brain monoaminergic systems** 

are enhanced (Nicoll et al., 1987; Segal & Bloom, 1976).

score for more than 50 %.

depressed participants.

antidepressant treatment phase. We tested the hypothesis that serotonergic and noradrenergic agents influence the process of generation of the initial neural input for the SCR system examining if there is any pattern of change in the amplitude and duration of the hidden-input in depressed patients before and during the treatment with antidepressants. The t-tests for dependent samples (using Bonferroni correction for multiple tests) revealed significant increase of the hidden-input amplitude and prolongation of the input pulse after four weeks of antidepressant treatment considering all applied agents together. The chronic antidepressant treatment did not significantly affect the timing of the pulses in the hiddeninput, i.e. the inter-pulse interval remained unchanged.

In order to test if the monoaminergic agents show distinctive effect on the features of the hidden-input the following multivariate analysis of variance has been performed. We compared the relative change (in percents) of the hidden-input measures in the three groups of patients underwent to three different four weeks treatments: 1) citalopram group, 2) venlafaxin or clomipramine treated group, and 3) maprotiline group. The MANOVA revealed significant difference on the overall model between the treatment groups (Wilks' lambda=0.463, F(6, 82)=6.42, p<0.0005, multivariate eta-squared=0.32). The univariate analyses of variance revealed significant differences among the treatment groups regarding the hiddeninput amplitude (eta-squared=0.438) and hidden-input duration (eta-squared=0.143) and nonsignificant differences regarding the inter-pulse pause. Pairwise comparisons revealed a stronger increasing effect on the hidden-input amplitude of the serotonergic agent (citalopram) than it was the case after venlafaxin or clomipramine treatment (Table 1). Interestingly, chronic treatment with maprotiline brought to lessening of the hidden-input amplitude. On the other hand, all three kinds of applied monoaminergic agents brought to prolongation of the hiddeninput pulse but citalopram was significantly less effective than both venlafaxin/clomipramine and maprotiline. The last two kinds of treatment were not mutually significantly different regarding the effect on the hidden-input pulse prolongation.


Table 1. Effects of a serotonergic agent (citalopram), dual acting agents (venlafaxin or clomipramine), and a noradrenergic antidepressant (maprotiline) on the hidden-input characteristics. The values represent means of the relative change in percents (SD).

#### **4.2 Tonic and phasic functions of the brain monoaminergic signaling and the SCR system parameters**

Relying on our neurobiological model of the SCR process (see 3.2) it follows that the parameter *input gain* appears as an indicator of the tonic function of the brain monoaminergic signaling. On the other hand, feedback loops' gains seem to refer to phasic

Assessment of Brain Monoaminergic Signaling

**FPFL**

Day 0 Day 7 Day 28 **Treatment Phase**

Day 0 Day 7 Day 28 **Treatment Phase**

**SPFL**

2.6 2.65 2.7 2.75 2.8 2.85 2.9

0.7

0.75

0.8

0.85

0.9

reach statistically significant level.

Through Mathematical Modeling of Skin Conductance Response 99

samples with Bonferroni adjustment for multiple tests. The tests revealed significantly weaker gains in all three feedback loops of the SCR system in depression and also a tendency in depression for lessening of the input gain although the found difference did not

In order to test whether the weakening of the feedback loops' gains in depression is influenced by disturbed serotonergic and noradrenergic brain function we compared the SCR system parameters of depressed patients before, after 7 days, and after four weeks of the antidepressant treatment. The repeated measures MANOVA revealed significant effect for time of treatment (Wilks' lambda = 0.035, F(8, 51) = 175.07, p < 0.0005, multivariate eta squared = 0.965). The univariate analyses of variance revealed significant differences among the treatment phases regarding the three feedback loops' gains and also input gain (Figure 5). Pairwise comparisons (with Bonferroni adjustment for multiple tests) revealed significant strengthening of the feedback loops' gains during four weeks of antidepressant treatment. The applied antidepressants also changed the input gain of the SCR system.

**NFL**

Citalopram Dual Agent Maprotiline

Citalopram Dual Agent Maprotiline

Day 0 Day 7 Day 28

**Treatment Phase**

Day 0 Day 7 Day 28 **Treatment Phase**

**Input Gain**

Citalopram Dual Agent Maprotiline

Citalopram Dual Agent Maprotiline

Fig. 5. Change of the SCR system parameters during the antidepressant treatment


> 0 0.01 0.02 0.03 0.04 0.05 0.06

functions of the brainstem monoaminergic systems conveying feedback enhancement and inhibition of the central neural signal which controls the output SCR signal.

Of the three feedback loops in the obtained mathematical model (Figure 2) the first one is proportional to the second derivative of the emotional arousal (SCR'') and it is positive. It refers to some neural signal that backwards enhances the already initiated arousal process. Because of a proximal neuroanatomical position on the amygdala-brainstem axis in comparison with other monoaminergic systems, and similarity of the spectral characteristics of the SCR'' and phasic dopaminergic activity (see Branković, 2011) we speculate that the fast feedback enhancement could relate to the phasic dopaminergic activation (Wanat et al., 2009; Redgrave et al., 2008; Lodge & Grace, 2006; Phillips et al., 2003) and positive feedback regulation of excitability in amygdala neurons through the process of slow afterdepolarization (Yamamoto et al., 2007).

The second feedback loop in the integration chain of our SCR model is negative one. It reflects the feedback inhibition in the arousal process. We speculate that for this feedback inhibition monoaminergic projections to the amygdala coming from the brainstem could be responsible – noradrenergic inhibition from the *locus coeruleus* (Buffalari & Grace, 2007; Schätze et al., 1987) and/or serotonergic inhibition from the raphe nuclei acting both directly on projection neurons and on interneurons (Stein et al., 2000; Rainnie, 1999).

One of the major outputs of the amygdala is the pathway from the medial amygdala to the paraventricular nucleus of the hypothalamus (PVN). This projection plays a critical role in expression of the autonomic response to stimulus (LeDoux, 1992). Beside the sympathetic projections of the PVN for the spinal cord, there is another arm of the PVN output that innervates *locus coeruleus* (LC) both directly (Reyes et al., 2005; Luppi et al., 1995) and indirectly through the innervation of the *nucleus paragigantocellularis*, which is the main input for the LC (Van Bockstaele et al., 1989; Aston-Jones et al., 1986). The majority of the axons of the PVN that directly innervate the LC release corticotrophin releasing factor (CRF) at their endings (Reyes et al., 2005). CRF activates the LC-noradrenergic system and increases the releasing of noradrenaline at the terminal projecting fields of the system (Dunn et al., 2004). The *locus coeruleus* does not innervate intermediolateral column of thoracic cord and, hence, is not directly involved in the transmission of the output of the sympathetic system to the periphery (Valentino & Aston-Jones, 1995; Fritschy et al., 1987). This refers to a different role of the LC activation that could lie in a feedback effect upon the higher brain structures. Indeed, it was shown that the noradrenegic projections from the LC have inhibitory influence on the kindling effect in the amygdala and the hippocampus (Giorgi et al., 2003). Beside that, the neurons in the amygdala that had been inhibited by the stimulation of the carotid sinus and baroreceptors were also inhibited by the stimulation of the LC (Schätze et al., 1987). For these reasons the projections of the hypothalamic PVN that innervate the LC (directly and through the *nucleus paragigantocellularis*) could be assigned as the regulatory output arm of the PVN.

In order to explore the neurochemical nature of the identified feedback loops and the parameter *input gain* in the SCR system we performed the following analyses. Comparison between healthy subjects and acutely depressed patients of our sample regarding the input gain and the three feedback loops gains was performed using the t-test for independent

functions of the brainstem monoaminergic systems conveying feedback enhancement and

Of the three feedback loops in the obtained mathematical model (Figure 2) the first one is proportional to the second derivative of the emotional arousal (SCR'') and it is positive. It refers to some neural signal that backwards enhances the already initiated arousal process. Because of a proximal neuroanatomical position on the amygdala-brainstem axis in comparison with other monoaminergic systems, and similarity of the spectral characteristics of the SCR'' and phasic dopaminergic activity (see Branković, 2011) we speculate that the fast feedback enhancement could relate to the phasic dopaminergic activation (Wanat et al., 2009; Redgrave et al., 2008; Lodge & Grace, 2006; Phillips et al., 2003) and positive feedback regulation of excitability in amygdala neurons through the process of slow

The second feedback loop in the integration chain of our SCR model is negative one. It reflects the feedback inhibition in the arousal process. We speculate that for this feedback inhibition monoaminergic projections to the amygdala coming from the brainstem could be responsible – noradrenergic inhibition from the *locus coeruleus* (Buffalari & Grace, 2007; Schätze et al., 1987) and/or serotonergic inhibition from the raphe nuclei acting both

One of the major outputs of the amygdala is the pathway from the medial amygdala to the paraventricular nucleus of the hypothalamus (PVN). This projection plays a critical role in expression of the autonomic response to stimulus (LeDoux, 1992). Beside the sympathetic projections of the PVN for the spinal cord, there is another arm of the PVN output that innervates *locus coeruleus* (LC) both directly (Reyes et al., 2005; Luppi et al., 1995) and indirectly through the innervation of the *nucleus paragigantocellularis*, which is the main input for the LC (Van Bockstaele et al., 1989; Aston-Jones et al., 1986). The majority of the axons of the PVN that directly innervate the LC release corticotrophin releasing factor (CRF) at their endings (Reyes et al., 2005). CRF activates the LC-noradrenergic system and increases the releasing of noradrenaline at the terminal projecting fields of the system (Dunn et al., 2004). The *locus coeruleus* does not innervate intermediolateral column of thoracic cord and, hence, is not directly involved in the transmission of the output of the sympathetic system to the periphery (Valentino & Aston-Jones, 1995; Fritschy et al., 1987). This refers to a different role of the LC activation that could lie in a feedback effect upon the higher brain structures. Indeed, it was shown that the noradrenegic projections from the LC have inhibitory influence on the kindling effect in the amygdala and the hippocampus (Giorgi et al., 2003). Beside that, the neurons in the amygdala that had been inhibited by the stimulation of the carotid sinus and baroreceptors were also inhibited by the stimulation of the LC (Schätze et al., 1987). For these reasons the projections of the hypothalamic PVN that innervate the LC (directly and through the *nucleus paragigantocellularis*) could be assigned as

In order to explore the neurochemical nature of the identified feedback loops and the parameter *input gain* in the SCR system we performed the following analyses. Comparison between healthy subjects and acutely depressed patients of our sample regarding the input gain and the three feedback loops gains was performed using the t-test for independent

directly on projection neurons and on interneurons (Stein et al., 2000; Rainnie, 1999).

inhibition of the central neural signal which controls the output SCR signal.

afterdepolarization (Yamamoto et al., 2007).

the regulatory output arm of the PVN.

samples with Bonferroni adjustment for multiple tests. The tests revealed significantly weaker gains in all three feedback loops of the SCR system in depression and also a tendency in depression for lessening of the input gain although the found difference did not reach statistically significant level.

In order to test whether the weakening of the feedback loops' gains in depression is influenced by disturbed serotonergic and noradrenergic brain function we compared the SCR system parameters of depressed patients before, after 7 days, and after four weeks of the antidepressant treatment. The repeated measures MANOVA revealed significant effect for time of treatment (Wilks' lambda = 0.035, F(8, 51) = 175.07, p < 0.0005, multivariate eta squared = 0.965). The univariate analyses of variance revealed significant differences among the treatment phases regarding the three feedback loops' gains and also input gain (Figure 5). Pairwise comparisons (with Bonferroni adjustment for multiple tests) revealed significant strengthening of the feedback loops' gains during four weeks of antidepressant treatment. The applied antidepressants also changed the input gain of the SCR system.

Fig. 5. Change of the SCR system parameters during the antidepressant treatment

Assessment of Brain Monoaminergic Signaling

treated with a noradrenergic agent.

**5. Limitations and future research** 

treated with a serotonegic agent (e.g. SSRI type antidepressant).

serotonergic signaling (Best at al., 2011) render the task feasible.

Through Mathematical Modeling of Skin Conductance Response 101

The 125% increase of the hidden-input amplitude after the four weeks citalopram treatment in our study is probably due to the evidenced a 75-80% decrease of serotonin reuptake transporters (SERT) binding site in the amygdala (Gould et al., 2003) and an internalization of SERT proteins from the cell surface, and redistribution of SERT from neurite extensions into the soma after a chronic SSRI treatment (Lau et al., 2008). A corollary of the result could be that depression associated with low hidden-input amplitude would be most effectively

On the contrary, a weaker strengthening effect of citalopram on prolongation of the hiddeninput pulse in comparison with the effect of maprotiline and venlafaxin/clomipramine could suggest a noradrenergic nature of the parameter 'hidden-input pulse duration'. It follows that depression associated with short hidden-input pulse would be most effectively

The strongest increasing effect on the FPFL and NFL gains was shown by venlafaxin and clomipramine (dual acting serotonin/noradrenaline agents). The finding that maprotiline has a weaker strengthening effect on the SPFL gain in comparison with both citalopram and venlafaxin/clomipramine could suggest that the last feedback loop in the SCR control system is more directly associated with the phasic serotonergic than with noradrenergic neurotransmission. Corollary of this would be that depression associated with weakened feedback loops' gains would be most effectively treated with a dual acting agent. There is also possibility to combine knowledge about hidden-input parameters and feedback loops' gains in selecting antidepressant for the treatment of an individual depressed patient.

The approach which we have proposed is supposed to enable an insight into the neural signaling of the monoaminergic systems through measuring and processing of the behavioral variables such as skin conductance response. Although the monoaminergic neural signaling is a net result of the subtle neurochemical processes such as neurotransmitters' release, reuptake, and receptor binding the present method does not allow a direct insight into the relationship between our estimations of the neural signaling and the pharmacological actions such as processes of down- or up-regulation of receptors, inhibition of transporters, and intracellular changes (Leonard, 2000). But there is a possibility to overcome this limitation of the present method. It could be done through an integration of the present model with the existing mathematical models of the cellular mechanisms of the dopaminergic and serotonergic signaling (Best et al., 2009; Best, Nijhout & Reed, 2010; Best, Reed & Nijhout, 2010; Best et al., 2011). The later models are models of the processes of synthesis, release, and reuptake of brainstem monoamines. Establishing the link between the SCR model and these models could bring to a deeper insight into the monoaminergic processes specifying the deviation in the processes through knowing the vales of the SCR system parameters. It could enable even more informed choice of psychotropic drugs (e.g. is it more appropriate to intervene with a postsynaptic receptor agent or with a drug acting on the reuptake transporters). Agreement between our findings on the change of SCR system's indicators of tonic and phasic monoaminergic functions due to serotonergic treatment, and theoretical assumptions derived from the model of

In order to test whether the antidepressants have distinctive effect on the SCR system parameters the multivariate analysis of variance has been performed. We compared the relative increase (in percents) of the feedback loops' gains and of the input gain in the three groups of patients underwent to three different kinds of drug treatment. The MANOVA revealed significant difference on the overall model between the treatment groups (etasquared=0.379). The univariate analyses of variance revealed significant differences among the treatment groups regarding the all three feedback loops' gains and non-significant differences in respect to input gain. Pairwise comparisons showed a stronger increasing effect of dual acting agents (venlafaxin/clomipramine) on the FPFL and the NFL gains than the effect of citalopram and maprotiline (Table 2). Citalopram and dual acting agents have similar strengthening effect on the SPFL gain and their effect is significantly stronger than the effect of maprotiline. The four weeks treatment with all three kinds of antidepressants was associated with similar increase of the input gain in the SCR system.


Table 2. Effects of a serotonergic agent (citalopram), dual acting agents (venlafaxin or clomipramine), and a noradrenergic antidepressant (maprotiline) on the SCR system characteristics. The values represent means of the relative increase in percents (SD).

#### **4.3 Neurochemical meaning of the parameters in the SCR process model suggested by the results**

Relying on the results (summarized in Tables 1 and 2) we suggest the following interpretation of the neurochemical meaning of the SCR model parameters. The finding of the strongest increasing effect of citalopram on the hidden-input amplitude could speak about the serotonergic nature of this hidden-input dimension. Since we assumed influence of the tonic function of the monoaminergic innervation on the strength and duration of the hidden neural input (see 4.1) it follows that the finding of 125% increase of the hidden-input amplitude after selective serotenergic treatment implicates responsibility of the tonic serotonergic function for this increase. Quantitatively this increase is in agreement with the prediction of the mathematical model of the neurochemistry of serotonin system where increase of 90% of the tonic serotonin activity is expected after chronic SSRI treatment (Best et al., 2011). The result is also in accordance with the finding of increased amygdala neural response to happy faces after citalopram treatment in an fMRI study on healthy volunteers (Norbury et al., 2009).

In order to test whether the antidepressants have distinctive effect on the SCR system parameters the multivariate analysis of variance has been performed. We compared the relative increase (in percents) of the feedback loops' gains and of the input gain in the three groups of patients underwent to three different kinds of drug treatment. The MANOVA revealed significant difference on the overall model between the treatment groups (etasquared=0.379). The univariate analyses of variance revealed significant differences among the treatment groups regarding the all three feedback loops' gains and non-significant differences in respect to input gain. Pairwise comparisons showed a stronger increasing effect of dual acting agents (venlafaxin/clomipramine) on the FPFL and the NFL gains than the effect of citalopram and maprotiline (Table 2). Citalopram and dual acting agents have similar strengthening effect on the SPFL gain and their effect is significantly stronger than the effect of maprotiline. The four weeks treatment with all three kinds of antidepressants

was associated with similar increase of the input gain in the SCR system.

**Parameter Citalopram Venlafaxin/** 

2.61 (1.19)

5.79 (2.48)

9.42 (4.01)

(114.58)

Table 2. Effects of a serotonergic agent (citalopram), dual acting agents (venlafaxin or clomipramine), and a noradrenergic antidepressant (maprotiline) on the SCR system characteristics. The values represent means of the relative increase in percents (SD).

**4.3 Neurochemical meaning of the parameters in the SCR process model suggested** 

Relying on the results (summarized in Tables 1 and 2) we suggest the following interpretation of the neurochemical meaning of the SCR model parameters. The finding of the strongest increasing effect of citalopram on the hidden-input amplitude could speak about the serotonergic nature of this hidden-input dimension. Since we assumed influence of the tonic function of the monoaminergic innervation on the strength and duration of the hidden neural input (see 4.1) it follows that the finding of 125% increase of the hidden-input amplitude after selective serotenergic treatment implicates responsibility of the tonic serotonergic function for this increase. Quantitatively this increase is in agreement with the prediction of the mathematical model of the neurochemistry of serotonin system where increase of 90% of the tonic serotonin activity is expected after chronic SSRI treatment (Best et al., 2011). The result is also in accordance with the finding of increased amygdala neural response to happy faces after citalopram treatment in an fMRI study on healthy volunteers

**Clomipramine Maprotiline** 

2.49 (1.82)

4.91 (3.56)

5.12 (4.25)

117.86 (18.37)

4.01 (2.12)

9.59 (5.46)

12.51 (6.73)

83.07 (120.11)

**SCR System** 

**Fast Positive Feedback Loop Gain Increase [%]** 

**Negative Feedback Loop Gain Increase [%]** 

**Slow Positive Feedback Loop Gain Increase [%]** 

**by the results** 

(Norbury et al., 2009).

**Input Gain Increase [%]** 37.50

The 125% increase of the hidden-input amplitude after the four weeks citalopram treatment in our study is probably due to the evidenced a 75-80% decrease of serotonin reuptake transporters (SERT) binding site in the amygdala (Gould et al., 2003) and an internalization of SERT proteins from the cell surface, and redistribution of SERT from neurite extensions into the soma after a chronic SSRI treatment (Lau et al., 2008). A corollary of the result could be that depression associated with low hidden-input amplitude would be most effectively treated with a serotonegic agent (e.g. SSRI type antidepressant).

On the contrary, a weaker strengthening effect of citalopram on prolongation of the hiddeninput pulse in comparison with the effect of maprotiline and venlafaxin/clomipramine could suggest a noradrenergic nature of the parameter 'hidden-input pulse duration'. It follows that depression associated with short hidden-input pulse would be most effectively treated with a noradrenergic agent.

The strongest increasing effect on the FPFL and NFL gains was shown by venlafaxin and clomipramine (dual acting serotonin/noradrenaline agents). The finding that maprotiline has a weaker strengthening effect on the SPFL gain in comparison with both citalopram and venlafaxin/clomipramine could suggest that the last feedback loop in the SCR control system is more directly associated with the phasic serotonergic than with noradrenergic neurotransmission. Corollary of this would be that depression associated with weakened feedback loops' gains would be most effectively treated with a dual acting agent. There is also possibility to combine knowledge about hidden-input parameters and feedback loops' gains in selecting antidepressant for the treatment of an individual depressed patient.
