The role of inhibition in oscillatory wave dynamics in the cortex

A deep generative adversarial network capturing complex spiral waves in disinhibited circuits of the cerebral cortex

BACKGROUND

In the cerebral cortex, disinhibited activity is characterized by propagating waves that spread across neural tissue. In this pathological state, a widely reported form of activity are spiral waves that travel in a circular pattern around a fixed spatial locus termed the center of mass. Spiral waves exhibit stereotypical activity and involve broad patterns of co-fluctuations, suggesting that they may be of lower complexity than healthy activity.

RESULTS

To evaluate this hypothesis, we performed dense multi-electrode recordings of cortical networks where disinhibition was induced by perfusing a pro-epileptiform solution containing 4-Aminopyridine as well as increased potassium and decreased magnesium. Spiral waves were identified based on a spatially delimited center of mass and a broad distribution of instantaneous phases across electrodes. Individual waves were decomposed into "snapshots" that captured instantaneous neural activation across the entire network. The complexity of these snapshots was examined using a measure termed the participation ratio. Contrary to our expectations, an eigenspectrum analysis of these snapshots revealed a broad distribution of eigenvalues and an increase in complexity compared to baseline networks. A deep generative adversarial network was trained to generate novel exemplars of snapshots that closely captured cortical spiral waves. These synthetic waves replicated key features of experimental data including a tight center of mass, a broad eigenvalue distribution, spatially-dependent correlations, and a high complexity. By adjusting the input to the model, new samples were generated that deviated in systematic ways from the experimental data, thus allowing the exploration of a broad range of states from healthy to pathologically disinhibited neural networks.

CONCLUSIONS

Together, results show that the complexity of population activity serves as a marker along a continuum from healthy to disinhibited brain states. The proposed generative adversarial network opens avenues for replicating the dynamics of cortical seizures and accelerating the design of optimal neurostimulation aimed at suppressing pathological brain activity.

Reconfiguration of αmplitude driven dominant coupling modes (DoCM) mediated by α-band in adolescents with schizophrenia spectrum disorders

Electroencephalography (EEG) based biomarkers have been shown to correlate with the presence of psychotic disorders. Increased delta and decreased alpha power in psychosis indicate an abnormal arousal state. We investigated brain activity across the basic EEG frequencies and also dynamic functional connectivity of both intra and cross-frequency coupling that could reveal a neurophysiological biomarker linked to an aberrant modulating role of alpha frequency in adolescents with schizophrenia spectrum disorders (SSDs). A dynamic functional connectivity graph (DFCG) has been estimated using the imaginary part of phase lag value (iPLV) and correlation of the envelope (corrEnv). We analyzed DFCG profiles of electroencephalographic resting state (eyes closed) recordings of healthy controls (HC) (n = 39) and SSDs subjects (n = 45) in basic frequency bands {δ,θ,α₁,α₂,β₁,β₂,γ}. In our analysis, we incorporated both intra and cross-frequency coupling modes. Adopting our recent Dominant Coupling Mode (DοCM) model leads to the construction of an integrated DFCG (iDFCG) that encapsulates the functional strength and the DοCM of every pair of brain areas. We revealed significantly higher ratios of delta/alpha₁,₂ power spectrum in SSDs subjects versus HC. The probability distribution (PD) of amplitude driven DoCM mediated by alpha frequency differentiated SSDs from HC with absolute accuracy (100%). The network Flexibility Index (FI) was significantly lower for subjects with SSDs compared to the HC group. Our analysis supports the central role of alpha frequency alterations in the neurophysiological mechanisms of SSDs. Currents findings open up new diagnostic pathways to clinical detection of SSDs and support the design of rational neurofeedback training.

Propagating wave activity in a tangential cortical slice

Propagating neural waves in the cerebral cortex influence the integration of incoming sensory information with ongoing cortical activity. However, the neural circuit elements that support these cortical waves remain to be fully defined. Here, a novel tangential slice preparation was developed that exhibited propagating wave activity across the dorsal cortical sheet, as assessed using autofluorescence imaging following focal electrical stimulation. Analysis of functional connectivity in the slice preparation with laser-scanning photostimulation via glutamate uncaging revealed a lack of short-latency, presumed monosynaptic, long-range connections (>300 μm) in the slice preparation. These results establish a novel slice preparation for assessing cortical dynamics and support the proposition that interactions among local cortical elements are sufficient to enable widespread propagating wave activity.

Alterations of GABA B receptors in the APP/PS1 mouse model of Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by the progressive decline of memory and cognitive function. The disease is characterized by the presence of amyloid plaques, tau tangles, altered inflammatory signaling, and alterations in numerous neurotransmitter signaling systems, including γ-aminobutyric acid (GABA). Given the extensive role of GABA in regulating neuronal activity, a careful investigation of GABA-related changes is needed. Further, given persistent inflammation has been demonstrated to drive AD pathology, the presence of GABA B receptor expressed on glia that serve a role regulation of the immune response adds to potential implications of altered GABA in AD. There has not previously been a systematic evaluation of GABA-related changes in an amyloid model of AD that specifically focuses on examining changes in GABA B receptors. In the present study, we examined alterations in several GABA-specific targets in the APP/PS1 mouse model at different ages. In the 4-month-old cohort, no significant deficits in spatial learning and memory or alterations in any of the GABAergic targets were observed compared with wild-type controls. However, we identified significant alterations in several GABA-related targets in the 6-month-old cohort that exhibited spatial learning deficits that include changes in glutamic acid decarboxylase 65, GABA transporter type 3, and GABA B receptors protein and mRNA levels. This was the same cohort at which learning and memory deficits and significant amyloid pathology was observed. Overall, our study provides evidence of altered GABAergic signaling in an amyloid model of AD at a time point consistent with AD-related deficits.

The effect of inhibition on the existence of traveling wave solutions for a neural field model of human seizure termination

In this paper we study the influence of inhibition on an activity-based neural field model consisting of an excitatory population with a linear adaptation term that directly regulates the activity of the excitatory population. Such a model has been used to replicate traveling wave data as observed in high density local field potential recordings (González-Ramírez et al. PLoS Computational Biology, 11(2), e1004065, 2015). In this work, we show that by adding an inhibitory population to this model we can still replicate wave properties as observed in human clinical data preceding seizure termination, but the parameter range over which such waves exist becomes more restricted. This restriction depends on the strength of the inhibition and the timescale at which the inhibition acts. In particular, if inhibition acts on a slower timescale relative to excitation then it is possible to still replicate traveling wave patterns as observed in the clinical data even with a relatively strong effect of inhibition. However, if inhibition acts on the same timescale as the excitation, or faster, then traveling wave patterns with the desired characteristics cease to exist when the inhibition becomes sufficiently strong.

Vascular-metabolic and GABAergic Inhibitory Correlates of Neural Variability Modulation. A Combined fMRI and PET Study

Neural activity varies continually from moment to moment. Such temporal variability (TV) has been highlighted as a functionally specific brain property playing a fundamental role in cognition. We sought to investigate the mechanisms involved in TV changes between two basic behavioral states, namely having the eyes open (EO) or eyes closed (EC) in vivo in humans. To these ends we acquired BOLD fMRI, ASL, and [¹⁸F]-fluoro-deoxyglucose PET in a group of healthy participants (n = 15), along with BOLD fMRI and [¹⁸F]-flumazenil PET in a separate group (n = 19). Focusing on an EO- vs EC-sensitive region in the occipital cortex (identified in an independent sample), we show that TV is constrained in the EO condition compared to EC. This reduction is correlated with an increase in energy consumption and with regional GABA_A receptor density. This suggests that the modulation of TV by behavioral state involves an increase in overall neural activity that is related to an increased effect from GABAergic inhibition in addition to any excitatory changes. These findings contribute to our understanding of the mechanisms underlying activity variability in the human brain and its control.

Traveling waves and breathers in an excitatory-inhibitory neural field

We study existence and stability of traveling activity bump solutions in an excitatory-inhibitory (E-I) neural field with Heaviside firing rate functions by deriving existence conditions for traveling bumps and an Evans function to analyze their spectral stability. Subsequently, we show that these existence and stability results reduce, in the limit of wave speed c→0, to the equivalent conditions developed for the stationary bump case. Using the results for the stationary bump case, we show that drift bifurcations of stationary bumps serve as a mechanism for generating traveling bump solutions in the E-I neural field as parameters are varied. Furthermore, we explore the interrelations between stationary and traveling types of bumps and breathers (time-periodic oscillatory bumps) by bridging together analytical and simulation results for stationary and traveling bumps and their bifurcations in a region of parameter space. Interestingly, we find evidence for a codimension-2 drift-Hopf bifurcation occurring as two parameters, inhibitory time constant τ and I-to-I synaptic connection strength w[over ¯]_{ii}, are varied and show that the codimension-2 point serves as an organizing center for the dynamics of these four types of spatially localized solutions. Additionally, we describe a case involving subcritical bifurcations that lead to traveling waves and breathers as τ is varied.

Interplay between non-NMDA and NMDA receptor activation during oscillatory wave propagation: Analyses of caffeine-induced oscillations in the visual cortex of rats

Generation and propagation of oscillatory activities in cortical networks are important features of the brain. However, many issues related to oscillatory phenomena are unclear. We previously reported neocortical oscillation following caffeine treatment of rat brain slices. Input to the primary visual cortex (Oc1) generates N-methyl-d-aspartate (NMDA) receptor-dependent oscillations, and we proposed that the oscillatory signals originate in the secondary visual cortex (Oc2). Because non-NMDA and NMDA receptors cooperate in synaptic transmission, non-NMDA receptors may also play an important role in oscillatory activities. Here we investigated how non-NMDA receptor activities contribute to NMDA receptor-dependent oscillations by using optical recording methods. After induction of stable oscillations with caffeine application, blockade of NMDA receptors abolished the late stable oscillatory phase, but elicited 'hidden' non-NMDA receptor-dependent oscillation during the early depolarizing phase. An interesting finding is that the origin of the non-NMDA receptor-dependent oscillation moved from the Oc1, during the early phase, toward the origin of the NMDA receptor-dependent oscillation that is fixed in the Oc2. In addition, the frequency of the non-NMDA receptor-dependent oscillation was higher than that of the NMDA receptor-dependent oscillation. Thus, in one course of spatiotemporal oscillatory activities, the relative balance in receptor activities between non-NMDA and NMDA receptors gradually changes, and this may be due to the different kinetics of the two receptor types. These results suggest that interplay between the two receptor types in the areas of Oc1 and Oc2 may play an important role in oscillatory signal communication.

Role of GABA(B) receptors in learning and memory and neurological disorders

Although it is evident from the literature that altered GABAB receptor function does affect behavior, these results often do not correspond well. These differences could be due to the task protocol, animal strain, ligand concentration, or timing of administration utilized. Because several clinical populations exhibit learning and memory deficits in addition to altered markers of GABA and the GABAB receptor, it is important to determine whether altered GABAB receptor function is capable of contributing to the deficits. The aim of this review is to examine the effect of altered GABAB receptor function on synaptic plasticity as demonstrated by in vitro data, as well as the effects on performance in learning and memory tasks. Finally, data regarding altered GABA and GABAB receptor markers within clinical populations will be reviewed. Together, the data agree that proper functioning of GABAB receptors is crucial for numerous learning and memory tasks and that targeting this system via pharmaceuticals may benefit several clinical populations.

Resting State EEG Hemispheric Power Asymmetry in Children with Dyslexia

Dyslexia is a neurodevelopmental disorder estimated to affect between 4 and 7% of the population. It is often referred to as a learning disability and is characterized by deficits in the linguistic system. To better understand the neural underpinnings of dyslexia, we examined the electroencephalography (EEG) power spectra between pre-adolescents with dyslexia and neurotypical control children during eyes closed state. We reported the differences in spontaneous oscillatory activity of each major EEG band (delta, theta, alpha, and beta) adopting a global as well as in a region-by-region and hemispheric approach to elucidate whether there are changes in asymmetry in children with dyslexia compared to controls. We also examined the relationship between EEG power spectra and clinical variables. The findings of our study confirm the presence of an atypical linguistic network, evident in children with dyslexia. This abnormal network hallmarked by a dominance of theta activity suggests that these abnormalities are present prior to these children learning to read, thus implicating delayed maturation and abnormal hypoarousal mechanisms.

Altered resting-state EEG source functional connectivity in schizophrenia: the effect of illness duration

Despite the increasing body of evidence supporting the hypothesis of schizophrenia as a disconnection syndrome, studies of resting-state EEG Source Functional Connectivity (EEG-SFC) in people affected by schizophrenia are sparse. The aim of the present study was to investigate resting-state EEG-SFC in 77 stable, medicated patients with schizophrenia (SCZ) compared to 78 healthy volunteers (HV). In order to study the effect of illness duration, SCZ were divided in those with a short duration of disease (SDD; n = 25) and those with a long duration of disease (LDD; n = 52). Resting-state EEG recordings in eyes closed condition were analyzed and lagged phase synchronization (LPS) indices were calculated for each ROI pair in the source-space EEG data. In delta and theta bands, SCZ had greater EEG-SFC than HV; a higher theta band connectivity in frontal regions was observed in LDD compared with SDD. In the alpha band, SCZ showed lower frontal EEG-SFC compared with HV whereas no differences were found between LDD and SDD. In the beta1 band, SCZ had greater EEG-SFC compared with HVs and in the beta2 band, LDD presented lower frontal and parieto-temporal EEG-SFC compared with HV. In the gamma band, SDD had greater connectivity values compared with LDD and HV. This study suggests that resting state brain network connectivity is abnormally organized in schizophrenia, with different patterns for the different EEG frequency components and that EEG can be a powerful tool to further elucidate the complexity of such disordered connectivity.

The dynamics of neurological disease: integrating computational, experimental and clinical neuroscience

There is a vast (and rapidly growing) amount of experimental and clinical data of the nervous system at very diverse spatial scales of activity (e.g. from sub-cellular through to whole organ), with many neurological disorders characterized by oscillations in neural activity across these disparate scales. Computer modelling and the development of associated mathematical theories provide us with a unique opportunity to integrate information from across these diverse scales of activity; leading to explanations of the potential mechanisms underlying the time-evolving dynamics and, more importantly, allowing the development of new hypotheses regarding neural function that may be tested experimentally and ultimately translated into the clinic. The purpose of this special issue is to present an overview of current integrative research in the areas of epilepsy, Parkinson's disease and schizophrenia, where multidisciplinary relationships involving theory, experimental and clinical research are becoming increasingly established.