**4. Epileptogenic spreading and neurostimulation affect higher order, global oscillations**

Significantly, recent studies demonstrate that epileptic activity affects longdistance oscillatory associations in the brain, including those influencing higher order cognitive activity [26]. A key finding has been the detection of coupling between epileptic electrical activity and slow brain oscillations—posited to mediate interareal coordination of brain activity—in loci distant from seizure origins. Using a biomarker of experimental epileptogenesis, fast ripples (FRs) (high-frequency waveforms that can be induced by kainite injection) the study demonstrated the presence of nonrandom brain activity specifically associated with slow oscillations. Fast ripples were shown to couple with two bandwidths, a slow oscillation in the 3- to 5-Hz range and one involving interictal epileptic episodes in the 20- to 30-Hz range. Phase-amplitude coupling during these events aligned at 4.5 Hz frequency for phase and 27 Hz frequency for amplitude and was 2.1 times higher than during baseline. Domain-specific analyses additionally revealed that the frontal cortex and left and right hippocampi specifically increased in power at 3–5 Hz in all three regions indicating that the ripples were synchronized across these brain domains. Furthermore, the increase in synchronization converged toward a common value, revealing that distribution of phase differences tended to converge and to coincide with the slow oscillation. Additionally, frontal cortex synchronization was delayed with respect to the two hippocampi, demonstrating that functional connectivity was oriented from the hippocampi to the frontal cortices, a finding also confirmed by Grainger analysis. Altogether, the data revealed a strong influence of structured brain activity on epileptogenesis, with cross-frequency coupling between the slow oscillation and FRs shaping the latter's temporal pattern and directionality in the brain.

Critically, epileptic coupling with slow oscillations has been shown to modify memory consolidation, a higher order brain function [27]. Memory consolidation is known to require three patterns of network activity (and their corresponding physiological coupling): hippocampal ripples, neocortical slow oscillations, and neocortical sleep spindles. By selectively eliminating ripples, for instance, memory performance can be greatly impaired in laboratory animals. In normal functioning, the coupling of the three patterns between the hippocampi and prefrontal cortices during NREM sleep leads to consolidation. Experimentally, accordingly, these studies examined how epileptogenesis interfered with the temporal coupling between these events. Specifically, the introduction of experimentally induced, interictal episodes was used to reduce fast ripples. Multivariate correlations between experimentally induced IEDs and fast ripples and spindles then showed that the reduction in FR resulted in significant declines in task-related memory performance, demonstrating a direct effect between the epileptogenic event, the brain patterning, and the inability to recall learned tasks. Significantly, the experimentally induced IEDs modified structured, global activity involving slow oscillations. In all cases, the hippocampal IEDs induced a marked decrease in neuronal firing (relative to baseline firing) within 200 ms, a time window known to be correlated with neuronal hyperpolarization and reduced spiking during NREM sleep and anesthesia that corresponded to slow oscillation, delta waves.

*Neurostimulation and Neuromodulation in Contemporary Therapeutic Practice*

overlap range).

overlap range where oscillator frequency differences are minimal, mathematically described by the sine of the phase angle difference between oscillators. As a result, the oscillators continue to experience frequency modulation throughout the cycle, which is manifest in the continual change in their precession rates (**Figure 1**). (Frequency modulation is posited to lead to information transfer in the maximal

Moreover, increasing coupling strength by neurostimulation for the purpose of improving synchronization with a neural oscillator is intrinsically limited and possesses an upper bound [25]. Neural oscillations exhibit stochastic behavior with intermittent synchronization, where neural signals go in and out of synchrony [23] revealing that synchronization (of weakly coupled oscillators) represents a statistical median where a predominant fraction of "micro" oscillating circuits determine the behavior of the population oscillator. Thus, the overall oscillatory distribution may be considered to have a certain phase variance range. Increases in coupling strength, accordingly, can be expected to shift only a proportion of the individual cycling circuits into a non-oscillatory range as increases in the strength of coupling progressively shift the population to a phase lock value near one (**Figure 2**).

*Effects of varying coupling strength on oscillator attrition. Mathematically, synchronization can be defined in terms of the phase locking value at perfect constancy, that is, equal to 1, minus the influence due to phase precession and the loss of "micro" oscillators due to quenching. Normalized precession influences on synchronization are then described: S(t) = 1 − dΘP/dt (T − t)/dΘP(T) − G((1 − dΘP/dt (T − t)/dΘP(T))), where S(t) is the relative synchronization as a function t of the precession cycle (T). Ahn and Lubchinsky characterize an oscillating population microstructure [23] in terms of the frequency distribution of the phase differences present within the synchronized set. Using this variance, the proportion of oscillators entering a zone of attrition may then be described by a cumulative normal distribution. Thus only the optimally synchronized set will approach a phase lock value leading to quenching, which is expressed as a product of the cumulative normal distribution and the synchronized population, where G, the fraction entering attrition, can be obtained from the cumulative normal distribution, which is bounded, due to phase variance, at phase constancy. (A) Reduction in synchronization due to oscillator attrition. (B) Variation in the coupling strength constant as* 

**10**

*a function of the precession angle.*

**Figure 2.**

### **4.1 Neurostimulation treatments**

The effects of epilepsy on these higher order oscillatory structures suggest that neurostimulation could restore normal function by reversing these effects. Work in this area remains preliminary, but consistent with this hypothesis.

### *4.1.1 Vagal nerve stimulation*

Therapeutic approaches using neurostimulation for epilepsy primarily involve vagal nerve stimulation (VNS), although other techniques such as deep brain stimulation and repetitive transcranial magnetic stimulation (rTMS) have seen limited use. Existing studies suggest that neurostimulation influences mechanisms of consciousness, which are altered during epilepsy [28]. For afferent vagal nerve fibers, the brainstem nucleus of the solitary tract (NST) is the main relay station. This nucleus has widespread projections to numerous areas in the forebrain, brainstem, thalamus, and areas involved in learning and memory formation (amygdala, hippocampus). Additionally, learning, memory encoding and recall are known to be modulated by arousal, an integral feature of consciousness. Consistent with the observations on the effect of epilepsy on memory consolidation, animal models of vagal nerve stimulation showed that it positively influenced hippocampal longterm potentiation (HLP). In humans, for instance, a chronic increased alertness is observed in VNS-implanted subjects with acute effects on memory consolidation.

### *4.1.2 DBS*

DBS in epilepsy has been applied to a number of targets, including the thalamus (anterior and centromedian nuclei), cerebellum, and basal ganglia (subthalamic nucleus, caudate, substantia nigra pars reticulata). Via the brainstem and basal forebrain arousal systems, the thalamus is hypothesized to underpin consciousness through distributed mechanisms of arousal regulation. Of these, the anterior nucleus of the thalamus appears to underlie limbic seizures and to present in medically resistant seizure formation, whereas the centromedian nucleus of the thalamus is involved in the reticulothalamocortical system that is considered integral to the modulation of vigilance. Significantly, deep brain stimulation of the anterior nucleus of the thalamus has emerged as a promising therapy for drug resistant epilepsy, with recent findings indicating a key mechanistic role for brain oscillations. A study by Chang, for example, showed that desynchronization of the ipsilateral hippocampal background electrical activity over a broad frequency range influenced epileptic discharges, including interictal spikes and high-frequency oscillations [29]. Furthermore, high-frequency stimulation of the anterior nucleus of the thalamus appeared to decouple large-scale neural activity between the hippocampus and regionally distant cortical areas.

### **5. Summary and conclusion**

Singer's discovery in the 1990s of patterned electrical activity for brain communication provided the conceptual basis for moving beyond temporal sequencing for encoded representations [30]. It also overcame the most significant theoretical limitation of Hubel and Wiesel's abstraction thesis for coding, which had been premised on their discovery of motion and edge detector cells in the occipital cortex. The use of rhythmic, typically oscillatory, activity for communication and the ordering of cognition has since been confirmed in a wide variety of studies. This understanding

**13**

**Author details**

Denis Larrivee1,2

1 Loyola University Chicago, USA

\*Address all correspondence to: sallar1@aol.com

provided the original work is properly cited.

2 Mind and Brain Institute, University of Navarra Medical School, Spain

© 2020 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,

*Introductory Chapter: Neurostimulation and the Structural Basis of Brain Activity*

applications now revolutionizing treatment for brain disease.

has enabled a sounder strategy for investigating the structure of brain operation and how the impairment of this structure might lead to brain dysfunction and disease. It has also opened a window to the new therapeutic modes of neuromodulation and neurostimulation. These recent forms of therapy, many described in this volume, are exploiting such understanding to yield the current profusion of medical

*DOI: http://dx.doi.org/10.5772/intechopen.93061*

*Introductory Chapter: Neurostimulation and the Structural Basis of Brain Activity DOI: http://dx.doi.org/10.5772/intechopen.93061*

has enabled a sounder strategy for investigating the structure of brain operation and how the impairment of this structure might lead to brain dysfunction and disease. It has also opened a window to the new therapeutic modes of neuromodulation and neurostimulation. These recent forms of therapy, many described in this volume, are exploiting such understanding to yield the current profusion of medical applications now revolutionizing treatment for brain disease.
