Gain control through divisive inhibition prevents abrupt transition to chaos in a neural mass model

Moving from phenomenological to predictive modelling: Progress and pitfalls of modelling brain stimulation in-silico

Brain stimulation is an increasingly popular neuromodulatory tool used in both clinical and research settings; however, the effects of brain stimulation, particularly those of non-invasive stimulation, are variable. This variability can be partially explained by an incomplete mechanistic understanding, coupled with a combinatorial explosion of possible stimulation parameters. Computational models constitute a useful tool to explore the vast sea of stimulation parameters and characterise their effects on brain activity. Yet the utility of modelling stimulation in-silico relies on its biophysical relevance, which needs to account for the dynamics of large and diverse neural populations and how underlying networks shape those collective dynamics. The large number of parameters to consider when constructing a model is no less than those needed to consider when planning empirical studies. This piece is centred on the application of phenomenological and biophysical models in non-invasive brain stimulation. We first introduce common forms of brain stimulation and computational models, and provide typical construction choices made when building phenomenological and biophysical models. Through the lens of four case studies, we provide an account of the questions these models can address, commonalities, and limitations across studies. We conclude by proposing future directions to fully realise the potential of computational models of brain stimulation for the design of personalized, efficient, and effective stimulation strategies.

Cholinergic modulation of hierarchical inhibitory control over cortical resting state dynamics: Local circuit modeling of schizophrenia-related hypofrontality

Nicotinic acetylcholine receptors (nAChRs) modulate the cholinergic drive to a hierarchy of inhibitory neurons in the superficial layers of the PFC, critical to cognitive processes. It has been shown that genetic deletions of the various types of nAChRs impact the properties of ultra-slow transitions between high and low PFC activity states in mice during quiet wakefulness. The impact characteristics depend on specific interneuron populations expressing the manipulated receptor subtype. In addition, recent data indicate that a genetic mutation of the α5 nAChR subunit, located on vasoactive intestinal polypeptide (VIP) inhibitory neurons, the rs16969968 single nucleotide polymorphism (α5 SNP), plays a key role in the hypofrontality observed in schizophrenia patients carrying the SNP. Data also indicate that chronic nicotine application to α5 SNP mice relieves the hypofrontality. We developed a computational model to show that the activity patterns recorded in the genetically modified mice can be explained by changes in the dynamics of the local PFC circuit. Notably, our model shows that these altered PFC circuit dynamics are due to changes in the stability structure of the activity states. We identify how this stability structure is differentially modulated by cholinergic inputs to the parvalbumin (PV), somatostatin (SOM) or the VIP inhibitory populations. Our model uncovers that a change in amplitude, but not duration of the high activity states can account for the lowered pyramidal (PYR) population firing rates recorded in α5 SNP mice. We demonstrate how nicotine-induced desensitization and upregulation of the β2 nAChRs located on SOM interneurons, as opposed to the activation of α5 nAChRs located on VIP interneurons, is sufficient to explain the nicotine-induced activity normalization in α5 SNP mice. The model further implies that subsequent nicotine withdrawal may exacerbate the hypofrontality over and beyond one caused by the SNP mutation.

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Prefrontal cortex shows ultra-slow alterations between low and high activity states at rest. This activity is characteristically decreased in schizophrenia patients.

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Model identifies local circuit origin of hypofrontality associated with schizophrenia and a5 nicotinic receptor malfunction.

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Decrease in PFC VIP-interneuron excitability drives decrease in high-activity-state stability and overall hypofrontality.

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Model shows desensitization/upregulation of SOM-expressed β2-NAChRs drive nicotine-induced renormalization of PFC activity.

Towards simulations of long-term behavior of neural networks: Modeling synaptic plasticity of connections within and between human brain regions

Simulations of neural networks can be used to study the direct effect of internal or external changes on brain dynamics. However, some changes are not immediate but occur on the timescale of weeks, months, or years. Examples include effects of strokes, surgical tissue removal, or traumatic brain injury but also gradual changes during brain development. Simulating network activity over a long time, even for a small number of nodes, is a computational challenge. Here, we model a coupled network of human brain regions with a modified Wilson-Cowan model representing dynamics for each region and with synaptic plasticity adjusting connection weights within and between regions. Using strategies ranging from different models for plasticity, vectorization and a different differential equation solver setup, we achieved one second runtime for one second biological time.

Divisive gain modulation enables flexible and rapid entrainment in a neocortical microcircuit model

Neocortical circuits exhibit a rich dynamic repertoire, and their ability to achieve entrainment (adjustment of their frequency to match the input frequency) is thought to support many cognitive functions and indicate functional flexibility. Although previous studies have explored the influence of various circuit properties on this phenomenon, the role of divisive gain modulation (or divisive inhibition) is unknown. This gain control mechanism is thought to be delivered mainly by the soma-targeting interneurons in neocortical microcircuits. In this study, we use a neural mass model of the neocortical microcircuit (extended Wilson-Cowan model) featuring both soma-targeting and dendrite-targeting interneuronal subpopulations to investigate the role of divisive gain modulation in entrainment. Our results demonstrate that the presence of divisive inhibition in the microcircuit, as delivered by the soma-targeting interneurons, enables its entrainment to a wider range of input frequencies. Divisive inhibition also promotes a faster entrainment, with the microcircuit needing less time to converge to the fully entrained state. We suggest that divisive inhibition, working alongside subtractive inhibition, allows for more adaptive oscillatory responses in neocortical circuits and, thus, supports healthy brain functioning.NEW & NOTEWORTHY We introduce a computational neocortical microcircuit model that features two inhibitory neural populations, with one providing subtractive and the other divisive inhibition to the excitatory population. We demonstrate that divisive inhibition widens the range of input frequencies to which the microcircuit can become entrained and diminishes the time needed to reach full entrainment. We suggest that divisive inhibition enables more adaptive oscillatory activity, with important implications for both normal and pathological brain function.

Computational modelling of the long-term effects of brain stimulation on the local and global structural connectivity of epileptic patients

Computational studies of the influence of different network parameters on the dynamic and topological network effects of brain stimulation can enhance our understanding of different outcomes between individuals. In this study, a brain stimulation session along with the subsequent post-stimulation brain activity is simulated for a period of one day using a network of modified Wilson-Cowan oscillators coupled according to diffusion imaging based structural connectivity. We use this computational model to examine how differences in the inter-region connectivity and the excitability of stimulated regions at the time of stimulation can affect post-stimulation behaviours. Our findings indicate that the initial inter-region connectivity can heavily affect the changes that stimulation induces in the connectivity of the network. Moreover, differences in the excitability of the stimulated regions seem to lead to different post-stimulation connectivity changes across the model network, including on the internal connectivity of non-stimulated regions.

The Presynaptic Regulation of Dopamine and Norepinephrine Synthesis Has Dissociable Effects on Different Kinds of Cognitive Conflicts

Goal-directed behavior requires the ability to resolve subliminally or consciously induced response conflicts, both of which may benefit from catecholamine-induced increases in gain control. We investigated the effects of presynaptic differences in dopamine and norepinephrine synthesis with the help of the tyrosine hydroxylase (TH) rs10770141 and the dopamine-β-hydroxylase (DBH) rs1611115, rs6271, and rs1611122 polymorphisms. Conscious and subliminal response conflicts were induced with flanker and prime distractors in (n = 207) healthy young participants while neurophysiological data (EEG) was recorded. The results demonstrated that the increased presynaptic catecholamine synthesis associated with the TH rs10770141 TT genotype improves cognitive control in case of consciously perceived (flanker) conflicts, but not in case of subliminally processed (prime) conflicts. Only norepinephrine seemed to also modulate subliminal conflict processing, as evidenced by better performance of the DBH rs1611122 CC genotype in case of high subliminal conflict load. Better performance was linked to larger conflict-induced modulations in post-response alpha band power arising from parietal and inferior frontal regions, which likely helps to suppress the processing of distracting information. In summary, presynaptic catecholamine synthesis benefits consciously perceived conflicts by improving the suppression of distracting information following a conflict. Subliminal conflicts were modulated via the same mechanism, but only by norepinephrine.

Catecholaminergic Modulation of Conflict Control Depends on the Source of Conflicts

Background

To display goal-directed behavior, we must be able to resolve response conflicts that arise from processing various distractors. Such conflicts may be triggered by different kinds of distractor stimuli (e.g., priming and flanker stimuli), but it has remained largely unclear whether the functional and neurobiological underpinnings of both conflict types differ. We therefore investigated the functional relevance of the catecholamines dopamine and norepinephrine, which have been shown to increase the signal-to-noise ratio in neuronal processing and should therefore modulate response conflicts.

Methods

In a double-blind, randomized, placebo-controlled study design, we examined the effect of methylphenidate (0.5 mg/kg) on both flanker-induced and priming-induced response conflicts in a group of n=25 healthy young adults. We used EEG recordings to examine event-related potentials in combination with source localization analyses to identify the cognitive-neurophysiological subprocesses and functional neuroanatomical structures modulated by methylphenidate.

Results

Compared with placebo, methylphenidate decreased flanker conflicts. This was matched by increased congruency effects in the fronto-central N2/P3 event-related potential complex and associated with modulations in the right inferior frontal gyrus. In contrast to this, methylphenidate did not modulate the size of prime-evoked conflicts.

Conclusions

Our results suggest that catecholamine-driven increases in signal-to-noise ratio and neural gain control do not equally benefit differently evoked conflicts. This supports the hypothesis of an at least partly different neurobiological basis for flanker- and prime-evoked response conflicts. As the right inferior frontal gyrus plays an important role in inhibition, the catecholaminergic system may reduce flanker conflicts by supporting the inhibition of distracting information.

Stimulus-induced Epileptic Spike-Wave Discharges in Thalamocortical Model with Disinhibition

Epileptic absence seizure characterized by the typical 2–4 Hz spike-wave discharges (SWD) are known to arise due to the physiologically abnormal interactions within the thalamocortical network. By introducing a second inhibitory neuronal population in the cortical system, here we propose a modified thalamocortical field model to mathematically describe the occurrences and transitions of SWD under the mutual functions between cortex and thalamus, as well as the disinhibitory modulations of SWD mediated by the two different inhibitory interneuronal populations. We first show that stimulation can induce the recurrent seizures of SWD in the modified model. Also, we demonstrate the existence of various types of firing states including the SWD. Moreover, we can identify the bistable parametric regions where the SWD can be both induced and terminated by stimulation perturbations applied in the background resting state. Interestingly, in the absence of stimulation disinhibitory functions between the two different interneuronal populations can also both initiate and abate the SWD, which suggests that the mechanism of disinhibition is comparable to the effect of stimulation in initiating and terminating the epileptic SWD. Hopefully, the obtained results can provide theoretical evidences in exploring dynamical mechanism of epileptic seizures.