A model for focal seizure onset, propagation, evolution, and progression

GABA-Induced Seizure-Like Events Caused by Multi-ionic Interactive Dynamics

Experimental evidence showed that an increase in intracellular chloride concentration [Formula: see text] caused by gamma-aminobutyric acid (GABA) input can promote epileptic firing activity, but the actual mechanisms remain elusive. Here in this theoretical work, we show that influx of chloride and concomitant bicarbonate ion [Formula: see text] efflux upon GABA receptor activation can induce epileptic firing activity by transition of GABA from inhibition to excitation. We analyzed the intrinsic property of neuron firing states as a function of [Formula: see text] We found that as [Formula: see text] increases, the system exhibits a saddle-node bifurcation, above which the neuron exhibits a spectrum of intensive firing, periodic bursting interrupted by depolarization block (DB) state, and eventually a stable DB through a Hopf bifurcation. We demonstrate that only GABA stimuli together with [Formula: see text] efflux can switch GABA's effect to excitation which leads to a series of seizure-like events (SLEs). Exposure to a low [Formula: see text] can drive neurons with high concentrations of [Formula: see text] downward to lower levels of [Formula: see text], during which it could also trigger SLEs depending on the exchange rate with the bath. Our analysis and simulation results show how the competition between GABA stimuli-induced accumulation of [Formula: see text] and [Formula: see text] application-induced decrease of [Formula: see text] regulates the neuron firing activity, which helps to understand the fundamental ionic dynamics of SLE.

Mechanism of Duration Perception in Artificial Brains Suggests New Model of Attentional Entrainment

While cognitive theory has advanced several candidate frameworks to explain attentional entrainment, the neural basis for the temporal allocation of attention is unknown. Here we present a new model of attentional entrainment guided by empirical evidence obtained using a cohort of 50 artificial brains. These brains were evolved in silico to perform a duration judgment task similar to one where human subjects perform duration judgments in auditory oddball paradigms. We found that the artificial brains display psychometric characteristics remarkably similar to those of human listeners and exhibit similar patterns of distortions of perception when presented with out-of-rhythm oddballs. A detailed analysis of mechanisms behind the duration distortion suggests that attention peaks at the end of the tone, which is inconsistent with previous attentional entrainment models. Instead, the new model of entrainment emphasizes increased attention to those aspects of the stimulus that the brain expects to be highly informative.

Focal seizures induce spatiotemporally organized spiking activity in the human cortex

Epileptic seizures are debilitating because of the clinical symptoms they produce. These symptoms, in turn, may stem directly from disruptions in neural coding. Recent evidence has suggested that the specific temporal order, or sequence, of spiking across a population of cortical neurons may encode information. Here, we investigate how seizures disrupt neuronal spiking sequences in the human brain by recording multi-unit activity from the cerebral cortex in five male participants undergoing monitoring for seizures. We find that pathological discharges during seizures are associated with bursts of spiking activity across a population of cortical neurons. These bursts are organized into highly consistent and stereotyped temporal sequences. As the seizure evolves, spiking sequences diverge from the sequences observed at baseline and become more spatially organized. The direction of this spatial organization matches the direction of the ictal discharges, which spread over the cortex as traveling waves. Our data therefore suggest that seizures can entrain cortical spiking sequences by changing the spatial organization of neuronal firing, providing a possible mechanism by which seizures create symptoms.

Involvement of the contralateral hippocampus in ictal-like but not interictal epileptic activities in the kainate mouse model of temporal lobe epilepsy

OBJECTIVE

Animal and human studies have shown that the seizure-generating region is vastly dependent on distant neuronal hubs that can decrease duration and propagation of ongoing seizures. However, we still lack a comprehensive understanding of the impact of distant brain areas on specific interictal and ictal epileptic activities (e.g., isolated spikes, spike trains, seizures). Such knowledge is critically needed, because all kinds of epileptic activities are not equivalent in terms of clinical expression and impact on the progression of the disease.

METHODS

We used surface high-density electroencephalography and multisite intracortical recordings, combined with pharmacological silencing of specific brain regions in the well-known kainate mouse model of temporal lobe epilepsy. We tested the impact of selective regional silencing on the generation of epileptic activities within a continuum ranging from very transient to more sustained and long-lasting discharges reminiscent of seizures.

RESULTS

Silencing the contralateral hippocampus completely suppresses sustained ictal activities in the focus, as efficiently as silencing the focus itself, but whereas focus silencing abolishes all focus activities, contralateral silencing fails to control transient spikes. In parallel, we observed that sustained focus epileptiform discharges in the focus are preceded by contralateral firing and more strongly phase-locked to bihippocampal delta/theta oscillations than transient spiking activities, reinforcing the presumed dominant role of the contralateral hippocampus in promoting long-lasting, but not transient, epileptic activities.

SIGNIFICANCE

Altogether, our work provides suggestive evidence that the contralateral hippocampus is necessary for the interictal to ictal state transition and proposes that crosstalk between contralateral neuronal activity and ipsilateral delta/theta oscillation could be a candidate mechanism underlying the progression from short- to long-lasting epileptic activities.

A personalized earbud for non-invasive long-term EEG monitoring

Objective. The primary objective of this study was to evaluate the reliability, comfort, and performance of a custom-fit, non-invasive long-term electrophysiologic headphone, known as Aware Hearable, for the ambulatory recording of brain activities. These recordings play a crucial role in diagnosing neurological disorders such as epilepsy and in studying neural dynamics during daily activities.Approach.The study uses commercial manufacturing processes common to the hearing aid industry, such as 3D scanning, computer-aided design modeling, and 3D printing. These processes enable the creation of the Aware Hearable with a personalized, custom-fit, thereby ensuring complete and consistent contact with the inner surfaces of the ear for high-quality data recordings. Additionally, the study employs a machine learning data analysis approach to validate the recordings produced by Aware Hearable, by comparing them to the gold standard intracranial electroencephalography recordings in epilepsy patients.Main results.The results indicate the potential of Aware Hearable to expedite the diagnosis of epilepsy by enabling extended periods of ambulatory recording.Significance.This offers significant reductions in burden to patients and their families. Furthermore, the device's utility may extend to a broader spectrum, making it suitable for other applications involving neurophysiological recordings in real-world settings.

Extracellular glutamate and GABA transients at the transition from interictal spiking to seizures

Focal epilepsy is associated with intermittent brief population discharges (interictal spikes), which resemble sentinel spikes that often occur at the onset of seizures. Why interictal spikes self-terminate whilst seizures persist and propagate is incompletely understood. We used fluorescent glutamate and GABA sensors in an awake rodent model of neocortical seizures to resolve the spatiotemporal evolution of both neurotransmitters in the extracellular space. Interictal spikes were accompanied by brief glutamate transients which were maximal at the initiation site and rapidly propagated centrifugally. GABA transients lasted longer than glutamate transients and were maximal ∼1.5 mm from the focus where they propagated centripetally. Prior to seizure initiation GABA transients were attenuated, whilst glutamate transients increased, consistent with a progressive failure of local inhibitory restraint. As seizures increased in frequency, there was a gradual increase in the spatial extent of spike-associated glutamate transients associated with interictal spikes. Neurotransmitter imaging thus reveals a progressive collapse of an annulus of feed-forward GABA release, allowing seizures to escape from local inhibitory restraint.

Cell-type specific and multiscale dynamics of human focal seizures in limbic structures

The relationship between clinically accessible epileptic biomarkers and neuronal activity underlying the transition to seizure is complex, potentially leading to imprecise delineation of epileptogenic brain areas. In particular, the pattern of interneuronal firing at seizure onset remains under debate, with some studies demonstrating increased firing and others suggesting reductions. Previous study of neocortical sites suggests that seizure recruitment occurs upon failure of inhibition, with intact feedforward inhibition in non-recruited territories. We investigated whether the same principle applies in limbic structures. We analysed simultaneous electrocorticography (ECoG) and neuronal recordings of 34 seizures in a cohort of 19 patients (10 male, 9 female) undergoing surgical evaluation for pharmacoresistant focal epilepsy. A clustering approach with five quantitative metrics computed from ECoG and multiunit data was used to distinguish three types of site-specific activity patterns during seizures, which at times co-existed within seizures. Overall, 156 single units were isolated, subclassified by cell-type and tracked through the seizure using our previously published methods to account for impacts of increased noise and single-unit waveshape changes caused by seizures. One cluster was closely associated with clinically defined seizure onset or spread. Entrainment of high-gamma activity to low-frequency ictal rhythms was the only metric that reliably identified this cluster at the level of individual seizures (P < 0.001). A second cluster demonstrated multi-unit characteristics resembling those in the first cluster, without concomitant high-gamma entrainment, suggesting feedforward effects from the seizure. The last cluster captured regions apparently unaffected by the ongoing seizure. Across all territories, the majority of both excitatory and inhibitory neurons reduced (69.2%) or ceased firing (21.8%). Transient increases in interneuronal firing rates were rare (13.5%) but showed evidence of intact feedforward inhibition, with maximal firing rate increases and waveshape deformations in territories not fully recruited but showing feedforward activity from the seizure, and a shift to burst-firing in seizure-recruited territories (P = 0.014). This study provides evidence for entrained high-gamma activity as an accurate biomarker of ictal recruitment in limbic structures. However, reduced neuronal firing suggested preserved inhibition in mesial temporal structures despite simultaneous indicators of seizure recruitment, in contrast to the inhibitory collapse scenario documented in neocortex. Further study is needed to determine if this activity is ubiquitous to hippocampal seizures or indicates a 'seizure-responsive' state in which the hippocampus is not the primary driver. If the latter, distinguishing such cases may help to refine the surgical treatment of mesial temporal lobe epilepsy.

Mechanisms of Neurostimulation for Epilepsy

This review discusses the use of neurostimulation therapies for epilepsy treatment, including vagal nerve stimulation, responsive neurostimulation, and deep brain stimulation. Different therapeutic strategies and their underlying mechanisms are explored, with a focus on optimizing parameters for seizure reduction. The review also highlights the paradigm shift toward a more diverse and multimodal approach to deep brain neuromodulation.

Spatial organisation of the mesoscale connectome: A feature influencing synchrony and metastability of network dynamics

Significant research has investigated synchronisation in brain networks, but the bulk of this work has explored the contribution of brain networks at the macroscale. Here we explore the effects of changing network topology on functional dynamics in spatially constrained random networks representing mesoscale neocortex. We use the Kuramoto model to simulate network dynamics and explore synchronisation and critical dynamics of the system as a function of topology in randomly generated networks with a distance-related wiring probability and no preferential attachment term. We show networks which predominantly make short-distance connections smooth out the critical coupling point and show much greater metastability, resulting in a wider range of coupling strengths demonstrating critical dynamics and metastability. We show the emergence of cluster synchronisation in these geometrically-constrained networks with functional organisation occurring along structural connections that minimise the participation coefficient of the cluster. We show that these cohorts of internally synchronised nodes also behave en masse as weakly coupled nodes and show intra-cluster desynchronisation and resynchronisation events related to inter-cluster interaction. While cluster synchronisation appears crucial to healthy brain function, it may also be pathological if it leads to unbreakable local synchronisation which may happen at extreme topologies, with implications for epilepsy research, wider brain function and other domains such as social networks.

Does seizure propagate within or across intrinsic brain networks? An intracranial EEG study

BACKGROUND

Understanding the spatiotemporal propagation profiles of seizures is crucial for the preoperative assessment of epilepsy patients. The present study aimed to investigate whether seizures exhibit propagation patterns that align with intrinsic networks (INs).

METHODS

A quantitative analysis was conducted to examine ictal fast activity (IFA). The Epileptogenicity Index (EI) was employed to assess the epileptogenicity, spectral features, and temporal characteristics of IFA. Intra-network and inter-network comparisons were made regarding the IFA-related metrics. Additionally, the metrics were correlated with Euclidean distance. Network connection maps were generated to visualize seizures originating from different INs, allowing for comparisons between distinct groups.

RESULTS

Data for 81 seizures in 43 subjects were captured using stereoelectroencephalography implantation. Three metrics were compared: EI, time involvement (TI), and energy ratio index (ERI). Intra-network channels exhibited higher EI, earlier involvement of IFA, and stronger high-frequency energy. These findings were further validated through subgroup analyses stratified by neuropathology, seizure type, and seizure origination lobe. Correlation analyses revealed a negative association between distance and both EI and ERI, while distance exhibited a positive correlation with TI. Seizures originating from different INs exhibited varying propagation characteristics.

CONCLUSIONS

The study findings highlight the dominant role of intra-network dynamics over inter-network during seizure propagation. These results contribute to our understanding of seizure dynamics and their relationship with INs.

Controlling neocortical epileptic seizures using forced temporal spike-time stimulation: an in silico computational study

Epileptic seizure is typically characterized by highly synchronized episodes of neural activity. Existing stimulation therapies focus purely on suppressing the pathologically synchronized neuronal firing patterns during the ictal (seizure) period. While these strategies are effective in suppressing seizures when they occur, they fail to prevent the re-emergence of seizures once the stimulation is turned off. Previously, we developed a novel neurostimulation motif, which we refer to as "Forced Temporal Spike-Time Stimulation" (FTSTS) that has shown remarkable promise in long-lasting desynchronization of excessively synchronized neuronal firing patterns by harnessing synaptic plasticity. In this paper, we build upon this prior work by optimizing the parameters of the FTSTS protocol in order to efficiently desynchronize the pathologically synchronous neuronal firing patterns that occur during epileptic seizures using a recently published computational model of neocortical-onset seizures. We show that the FTSTS protocol applied during the ictal period can modify the excitatory-to-inhibitory synaptic weight in order to effectively desynchronize the pathological neuronal firing patterns even after the ictal period. Our investigation opens the door to a possible new neurostimulation therapy for epilepsy.

Seizure onset patterns predict outcome after stereo-electroencephalography-guided laser amygdalohippocampotomy

OBJECTIVE

Stereotactic laser amygdalohippocampotomy (SLAH) is an appealing option for patients with temporal lobe epilepsy, who often require intracranial monitoring to confirm mesial temporal seizure onset. However, given limited spatial sampling, it is possible that stereotactic electroencephalography (stereo-EEG) may miss seizure onset elsewhere. We hypothesized that stereo-EEG seizure onset patterns (SOPs) may differentiate between primary onset and secondary spread and predict postoperative seizure control. In this study, we characterized the 2-year outcomes of patients who underwent single-fiber SLAH after stereo-EEG and evaluated whether stereo-EEG SOPs predict postoperative seizure freedom.

METHODS

This retrospective five-center study included patients with or without mesial temporal sclerosis (MTS) who underwent stereo-EEG followed by single-fiber SLAH between August 2014 and January 2022. Patients with causative hippocampal lesions apart from MTS or for whom the SLAH was considered palliative were excluded. An SOP catalogue was developed based on literature review. The dominant pattern for each patient was used for survival analysis. The primary outcome was 2-year Engel I classification or recurrent seizures before then, stratified by SOP category.

RESULTS

Fifty-eight patients were included, with a mean follow-up duration of 39 ± 12 months after SLAH. Overall 1-, 2-, and 3-year Engel I seizure freedom probability was 54%, 36%, and 33%, respectively. Patients with SOPs, including low-voltage fast activity or low-frequency repetitive spiking, had a 46% 2-year seizure freedom probability, compared to 0% for patients with alpha or theta frequency repetitive spiking or theta or delta frequency rhythmic slowing (log-rank test, p = .00015).

SIGNIFICANCE

Patients who underwent SLAH after stereo-EEG had a low probability of seizure freedom at 2 years, but SOPs successfully predicted seizure recurrence in a subset of patients. This study provides proof of concept that SOPs distinguish between hippocampal seizure onset and spread and supports using SOPs to improve selection of SLAH candidates.

Microscale Neuronal Activity Collectively Drives Chaotic and Inflexible Dynamics at the Macroscale in Seizures

Neuronal activity propagates through the network during seizures, engaging brain dynamics at multiple scales. Such propagating events can be described through the avalanches framework, which can relate spatiotemporal activity at the microscale with global network properties. Interestingly, propagating avalanches in healthy networks are indicative of critical dynamics, where the network is organized to a phase transition, which optimizes certain computational properties. Some have hypothesized that the pathologic brain dynamics of epileptic seizures are an emergent property of microscale neuronal networks collectively driving the brain away from criticality. Demonstrating this would provide a unifying mechanism linking microscale spatiotemporal activity with emergent brain dysfunction during seizures. Here, we investigated the effect of drug-induced seizures on critical avalanche dynamics, using in vivo whole-brain two-photon imaging of GCaMP6s larval zebrafish (males and females) at single neuron resolution. We demonstrate that single neuron activity across the whole brain exhibits a loss of critical statistics during seizures, suggesting that microscale activity collectively drives macroscale dynamics away from criticality. We also construct spiking network models at the scale of the larval zebrafish brain, to demonstrate that only densely connected networks can drive brain-wide seizure dynamics away from criticality. Importantly, such dense networks also disrupt the optimal computational capacities of critical networks, leading to chaotic dynamics, impaired network response properties and sticky states, thus helping to explain functional impairments during seizures. This study bridges the gap between microscale neuronal activity and emergent macroscale dynamics and cognitive dysfunction during seizures.SIGNIFICANCE STATEMENT Epileptic seizures are debilitating and impair normal brain function. It is unclear how the coordinated behavior of neurons collectively impairs brain function during seizures. To investigate this we perform fluorescence microscopy in larval zebrafish, which allows for the recording of whole-brain activity at single-neuron resolution. Using techniques from physics, we show that neuronal activity during seizures drives the brain away from criticality, a regime that enables both high and low activity states, into an inflexible regime that drives high activity states. Importantly, this change is caused by more connections in the network, which we show disrupts the ability of the brain to respond appropriately to its environment. Therefore, we identify key neuronal network mechanisms driving seizures and concurrent cognitive dysfunction.

Interictal discharges in the human brain are travelling waves arising from an epileptogenic source

While seizure activity may be electrographically widespread, increasing evidence has suggested that ictal discharges may in fact represent travelling waves propagated from a focal seizure source. Interictal epileptiform discharges (IEDs) are an electrographic manifestation of excessive hypersynchronization of cortical activity that occur between seizures and are considered a marker of potentially epileptogenic tissue. The precise relationship between brain regions demonstrating IEDs and those involved in seizure onset, however, remains poorly understood. Here, we hypothesize that IEDs likewise reflect the receipt of travelling waves propagated from the same regions which give rise to seizures. Forty patients from our institution who underwent invasive monitoring for epilepsy, proceeded to surgery and had at least one year of follow-up were included in our study. Interictal epileptiform discharges were detected using custom software, validated by a clinical epileptologist. We show that IEDs reach electrodes in sequences with a consistent temporal ordering, and this ordering matches the timing of receipt of ictal discharges, suggesting that both types of discharges spread as travelling waves. We use a novel approach for localization of ictal discharges, in which time differences of discharge receipt at nearby electrodes are used to compute source location; similar algorithms have been used in acoustics and geophysics. We find that interictal discharges co-localize with ictal discharges. Moreover, interictal discharges tend to localize to the resection territory in patients with good surgical outcome and outside of the resection territory in patients with poor outcome. The seizure source may originate at, and also travel to, spatially distinct IED foci. Our data provide evidence that interictal discharges may represent travelling waves of pathological activity that are similar to their ictal counterparts, and that both ictal and interictal discharges emerge from common epileptogenic brain regions. Our findings have important clinical implications, as they suggest that seizure source localizations may be derived from interictal discharges, which are much more frequent than seizures.

From phenomenological to biophysical models of seizures

Epilepsy is a complex disease that requires various approaches for its study. In this short review, we discuss the contribution of theoretical and computational models. The review presents theoretical frameworks that underlie the understanding of certain seizure properties and their classification based on their dynamical properties at the onset and offset of seizures. Dynamical system tools are valuable resources in the study of seizures. By analyzing the complex, dynamic behavior of seizures, these tools can provide insights into seizure mechanisms and offer a framework for their classification. Additionally, computational models have high potential for clinical applications, as they can be used to develop more accurate diagnostic and personalized medicine tools. We discuss various modeling approaches that span different scales and levels, while also questioning the neurocentric view, and emphasize the importance of considering glial cells. Finally, we explore the epistemic value provided by this type of approach.

Diverse nature of interictal oscillations: EEG-based biomarkers in epilepsy

Interictal electroencephalogram (EEG) patterns, including high-frequency oscillations (HFOs), interictal spikes (ISs), and slow wave activities (SWAs), are defined as specific oscillations between seizure events. These interictal oscillations reflect specific dynamic changes in network excitability and play various roles in epilepsy. In this review, we briefly describe the electrographic characteristics of HFOs, ISs, and SWAs in the interictal state, and discuss the underlying cellular and network mechanisms. We also summarize representative evidence from experimental and clinical epilepsy to address their critical roles in ictogenesis and epileptogenesis, indicating their potential as electrophysiological biomarkers of epilepsy. Importantly, we put forwards some perspectives for further research in the field.

Autonomic dysfunction in epilepsy mouse models with implications for SUDEP research

Epilepsy has a high prevalence and can severely impair quality of life and increase the risk of premature death. Sudden unexpected death in epilepsy (SUDEP) is the leading cause of death in drug-resistant epilepsy and most often results from respiratory and cardiac impairments due to brainstem dysfunction. Epileptic activity can spread widely, influencing neuronal activity in regions outside the epileptic network. The brainstem controls cardiorespiratory activity and arousal and reciprocally connects to cortical, diencephalic, and spinal cord areas. Epileptic activity can propagate trans-synaptically or via spreading depression (SD) to alter brainstem functions and cause cardiorespiratory dysfunction. The mechanisms by which seizures propagate to or otherwise impair brainstem function and trigger the cascading effects that cause SUDEP are poorly understood. We review insights from mouse models combined with new techniques to understand the pathophysiology of epilepsy and SUDEP. These techniques include in vivo, ex vivo, invasive and non-invasive methods in anesthetized and awake mice. Optogenetics combined with electrophysiological and optical manipulation and recording methods offer unique opportunities to study neuronal mechanisms under normal conditions, during and after non-fatal seizures, and in SUDEP. These combined approaches can advance our understanding of brainstem pathophysiology associated with seizures and SUDEP and may suggest strategies to prevent SUDEP.

Network analysis of preictal iEEG reveals changes in network structure preceding seizure onset

Seizures likely result from aberrant network activity and synchronization. Changes in brain network connectivity may underlie seizure onset. We used a novel method of rapid network model estimation from intracranial electroencephalography (iEEG) data to characterize pre-ictal changes in network structure prior to seizure onset. We analyzed iEEG data from 20 patients from the iEEG.org database. Using 10 s epochs sliding by 1 s intervals, a multiple input, single output (MISO) state space model was estimated for each output channel and time point with all other channels as inputs, generating sequential directed network graphs of channel connectivity. These networks were assessed using degree and betweenness centrality. Both degree and betweenness increased at seizure onset zone (SOZ) channels 37.0 ± 2.8 s before seizure onset. Degree rose in all channels 8.2 ± 2.2 s prior to seizure onset, with increasing connections between the SOZ and surrounding channels. Interictal networks showed low and stable connectivity. A novel MISO model-based network estimation method identified changes in brain network structure just prior to seizure onset. Increased connectivity was initially isolated within the SOZ and spread to non-SOZ channels before electrographic seizure onset. Such models could help confirm localization of SOZ regions.

Downregulatory effect of miR-342-3p on epileptogenesis in the PTZ-kindling model

BACKGROUND

Epileptogenesis is a process that results in neurons firing abnormally, causing seizures. Increasing evidence has shown that miRNAs expressed in the epileptic hippocampus are involved in epileptogenesis. We demonstrated the expression changes of miRNAs that may be effective in epileptogenesis in silico analysis in the kindling model created with Pentylenetetrazole (PTZ). Thus, we aimed to identify the target genes responsible for epileptogenesis.

METHODS AND RESULTS

Fifteen male Wistar-albino rats (200-230 g) were randomly divided into two groups control (n = 6) and PTZ (n = 9). The control group received 0.5 ml saline, and the PTZ group (35 mg/kg i.p.) intraperitoneally (i.p.) (11 times, every other day) to induce tonic-clonic seizures. Seizures were observed and scored 30 min after PTZ injection. After the last dose of PTZ (75 mg/kg) administration, the hippocampus tissues of the rats were removed by anesthesia. Analysis of miRNAs was performed with the Affymetrix gene chip miRNA sequence (728 miRNA) and confirmed by the Real-Time Polymerase Chain Reaction (Real-Time PCR) method (29 miRNAs). We evaluated the expression change of the target gene of miRNA, whose expression change was detected using in silico analysis, by q-RT PCR. Eight miRNAs with changes in expression were detected. Of these miRNAs, miR-342-p was downregulated in the PTZ group and was statistically significant (p < 0.005). Ultimately, we determined that the target gene of miR-342-p is a metabotropic glutamate receptor 2 (GRM2) and that GRM2 expression is upregulated.

CONCLUSIONS

Downregulation of miR-342-3p in the PTZ kindling model may result in the upregulation of GRM2.

Ultrafast simulation of large-scale neocortical microcircuitry with biophysically realistic neurons

Understanding the activity of the mammalian brain requires an integrative knowledge of circuits at distinct scales, ranging from ion channel gating to circuit connectomics. Computational models are regularly employed to understand how multiple parameters contribute synergistically to circuit behavior. However, traditional models of anatomically and biophysically realistic neurons are computationally demanding, especially when scaled to model local circuits. To overcome this limitation, we trained several artificial neural network (ANN) architectures to model the activity of realistic multicompartmental cortical neurons. We identified an ANN architecture that accurately predicted subthreshold activity and action potential firing. The ANN could correctly generalize to previously unobserved synaptic input, including in models containing nonlinear dendritic properties. When scaled, processing times were orders of magnitude faster compared with traditional approaches, allowing for rapid parameter-space mapping in a circuit model of Rett syndrome. Thus, we present a novel ANN approach allowing for rapid, detailed network experiments using inexpensive and commonly available computational resources.

Multiple Sources of Fast Traveling Waves during Human Seizures: Resolving a Controversy

During human seizures, organized waves of voltage activity rapidly sweep across the cortex. Two contradictory theories describe the source of these fast traveling waves: either a slowly advancing narrow region of multiunit activity (an ictal wavefront) or a fixed cortical location. Limited observations and different analyses prevent resolution of these incompatible theories. Here we address this disagreement by combining the methods and microelectrode array recordings (N = 11 patients, 2 females, N = 31 seizures) from previous human studies to analyze the traveling wave source. We find, inconsistent with both existing theories, a transient relationship between the ictal wavefront and traveling waves, and multiple stable directions of traveling waves in many seizures. Using a computational model that combines elements of both existing theories, we show that interactions between an ictal wavefront and fixed source reproduce the traveling wave dynamics observed in vivo We conclude that combining both existing theories can generate the diversity of ictal traveling waves.SIGNIFICANCE STATEMENT The source of voltage discharges that propagate across cortex during human seizures remains unknown. Two candidate theories exist, each proposing a different discharge source. Support for each theory consists of observations from a small number of human subject recordings, analyzed with separately developed methods. How the different, limited data and different analysis methods impact the evidence for each theory is unclear. To resolve these differences, we combine the unique, human microelectrode array recordings collected separately for each theory and analyze these combined data with a unified approach. We show that neither existing theory adequately describes the data. We then propose a new theory that unifies existing proposals and successfully reproduces the voltage discharge dynamics observed in vivo.

Cell to network computational model of the epileptic human hippocampus suggests specific roles of network and channel dysfunctions in the ictal and interictal oscillations

The mechanisms underlying the generation of hippocampal epileptic seizures and interictal events and their interactions with the sleep-wake cycle are not yet fully understood. Indeed, medial temporal lobe epilepsy is associated with hippocampal abnormalities both at the neuronal (channelopathies, impaired potassium and chloride dynamics) and network level (neuronal and axonal loss, mossy fiber sprouting), with more frequent seizures during wakefulness compared with slow-wave sleep. In this article, starting from our previous computational modeling work of the hippocampal formation based on realistic topology and synaptic connectivity, we study the role of micro- and mesoscale pathological conditions of the epileptic hippocampus in the generation and maintenance of seizure-like theta and interictal oscillations. We show, through the simulations of hippocampal activity during slow-wave sleep and wakefulness that: (i) both mossy fiber sprouting and sclerosis account for seizure-like theta activity, (ii) but they have antagonist effects (seizure-like activity occurrence increases with sprouting but decreases with sclerosis), (iii) though impaired potassium and chloride dynamics have little influence on the generation of seizure-like activity, they do play a role on the generation of interictal patterns, and (iv) seizure-like activity and fast ripples are more likely to occur during wakefulness and interictal spikes during sleep.

Focal seizures are organized by feedback between neural activity and ion concentration changes

Human and animal EEG data demonstrate that focal seizures start with low-voltage fast activity, evolve into rhythmic burst discharges and are followed by a period of suppressed background activity. This suggests that processes with dynamics in the range of tens of seconds govern focal seizure evolution. We investigate the processes associated with seizure dynamics by complementing the Hodgkin-Huxley mathematical model with the physical laws that dictate ion movement and maintain ionic gradients. Our biophysically realistic computational model closely replicates the electrographic pattern of a typical human focal seizure characterized by low voltage fast activity onset, tonic phase, clonic phase and postictal suppression. Our study demonstrates, for the first time in silico, the potential mechanism of seizure initiation by inhibitory interneurons via the initial build-up of extracellular K+ due to intense interneuronal spiking. The model also identifies ionic mechanisms that may underlie a key feature in seizure dynamics, i.e., progressive slowing down of ictal discharges towards the end of seizure. Our model prediction of specific scaling of inter-burst intervals is confirmed by seizure data recorded in the whole guinea pig brain in vitro and in humans, suggesting that the observed termination pattern may hold across different species. Our results emphasize ionic dynamics as elementary processes behind seizure generation and indicate targets for new therapeutic strategies.

Why won't it stop? The dynamics of benzodiazepine resistance in status epilepticus

Status epilepticus is a life-threatening neurological emergency that affects both adults and children. Approximately 36% of episodes of status epilepticus do not respond to the current preferred first-line treatment, benzodiazepines. The proportion of episodes that are refractory to benzodiazepines is higher in low-income and middle-income countries (LMICs) than in high-income countries (HICs). Evidence suggests that longer episodes of status epilepticus alter brain physiology, thereby contributing to the emergence of benzodiazepine resistance. Such changes include alterations in GABA_A receptor function and in the transmembrane gradient for chloride, both of which erode the ability of benzodiazepines to enhance inhibitory synaptic signalling. Often, current management guidelines for status epilepticus do not account for these duration-related changes in pathophysiology, which might differentially impact individuals in LMICs, where the average time taken to reach medical attention is longer than in HICs. In this Perspective article, we aim to combine clinical insights and the latest evidence from basic science to inspire a new, context-specific approach to efficiently managing status epilepticus.

Multimodal, Multiscale Insights into Hippocampal Seizures Enabled by Transparent, Graphene-Based Microelectrode Arrays

Hippocampal seizures are a defining feature of mesial temporal lobe epilepsy (MTLE). Area CA1 of the hippocampus is commonly implicated in the generation of seizures, which may occur because of the activity of endogenous cell populations or of inputs from other regions within the hippocampal formation. Simultaneously observing activity at the cellular and network scales in vivo remains challenging. Here, we present a novel technology for simultaneous electrophysiology and multicellular calcium imaging of CA1 pyramidal cells (PCs) in mice enabled by a transparent graphene-based microelectrode array (Gr MEA). We examine PC firing at seizure onset, oscillatory coupling, and the dynamics of the seizure traveling wave as seizures evolve. Finally, we couple features derived from both modalities to predict the speed of the traveling wave using bootstrap aggregated regression trees. Analysis of the most important features in the regression trees suggests a transition among states in the evolution of hippocampal seizures.

Human interictal epileptiform discharges are bidirectional traveling waves echoing ictal discharges

Interictal epileptiform discharges (IEDs), also known as interictal spikes, are large intermittent electrophysiological events observed between seizures in patients with epilepsy. Although they occur far more often than seizures, IEDs are less studied, and their relationship to seizures remains unclear. To better understand this relationship, we examined multi-day recordings of microelectrode arrays implanted in human epilepsy patients, allowing us to precisely observe the spatiotemporal propagation of IEDs, spontaneous seizures, and how they relate. These recordings showed that the majority of IEDs are traveling waves, traversing the same path as ictal discharges during seizures, and with a fixed direction relative to seizure propagation. Moreover, the majority of IEDs, like ictal discharges, were bidirectional, with one predominant and a second, less frequent antipodal direction. These results reveal a fundamental spatiotemporal similarity between IEDs and ictal discharges. These results also imply that most IEDs arise in brain tissue outside the site of seizure onset and propagate toward it, indicating that the propagation of IEDs provides useful information for localizing the seizure focus.

Localisation in focal epilepsy: a practical guide

The semiology of epileptic seizures reflects activation, or dysfunction, of areas of brain (often termed the symptomatogenic zone) as a seizure begins and evolves. Specific semiologies in focal epilepsies provide an insight into the location of the seizure onset zone, which is particularly important for presurgical epilepsy assessment. The correct diagnosis of paroxysmal events also depends on the clinician being familiar with the spectrum of semiologies. Here, we summarise the current literature on localisation in focal epilepsies using illustrative cases and discussing possible pitfalls in localisation.

Brain injuries can set up an epileptogenic neuronal network

Development of epilepsy or epileptogenesis promotes recurrent seizures. As of today, there are no effective prophylactic therapies to prevent the onset of epilepsy. Contributing to this deficiency of preventive therapy is the lack of clarity in fundamental neurobiological mechanisms underlying epileptogenesis and lack of reliable biomarkers to identify patients at risk for developing epilepsy. This limits the development of prophylactic therapies in epilepsy. Here, neural network dysfunctions reflected by oscillopathies and microepileptiform activities, including neuronal hyperexcitability and hypersynchrony, drawn from both clinical and experimental epilepsy models, have been reviewed. This review suggests that epileptogenesis reflects a progressive and dynamic dysfunction of specific neuronal networks which recruit further interconnected groups of neurons, with this resultant pathological network mediating seizure occurrence, recurrence, and progression. In the future, combining spatial and temporal resolution of neuronal non-invasive recordings from patients at risk of developing epilepsy, together with analytics and computational tools, may contribute to determining whether the brain is undergoing epileptogenesis in asymptomatic patients following brain injury.

Modeling seizures: From single neurons to networks

Dynamical system tools offer a complementary approach to detailed biophysical seizure modeling, with a high potential for clinical applications. This review describes the theoretical framework that provides a basis for theorizing certain properties of seizures and for their classification according to their dynamical properties at onset and offset. We describe various modeling approaches spanning different scales, from single neurons to large-scale networks. This narrative review provides an accessible overview of this field, including non-exhaustive examples of key recent works.

A Non-spiking Neuron Model With Dynamic Leak to Avoid Instability in Recurrent Networks

Recurrent circuitry components are distributed widely within the brain, including both excitatory and inhibitory synaptic connections. Recurrent neuronal networks have potential stability problems, perhaps a predisposition to epilepsy. More generally, instability risks making internal representations of information unreliable. To assess the inherent stability properties of such recurrent networks, we tested a linear summation, non-spiking neuron model with and without a “dynamic leak”, corresponding to the low-pass filtering of synaptic input current by the RC circuit of the biological membrane. We first show that the output of this neuron model, in either of its two forms, follows its input at a higher fidelity than a wide range of spiking neuron models across a range of input frequencies. Then we constructed fully connected recurrent networks with equal numbers of excitatory and inhibitory neurons and randomly distributed weights across all synapses. When the networks were driven by pseudorandom sensory inputs with varying frequency, the recurrent network activity tended to induce high frequency self-amplifying components, sometimes evident as distinct transients, which were not present in the input data. The addition of a dynamic leak based on known membrane properties consistently removed such spurious high frequency noise across all networks. Furthermore, we found that the neuron model with dynamic leak imparts a network stability that seamlessly scales with the size of the network, conduction delays, the input density of the sensory signal and a wide range of synaptic weight distributions. Our findings suggest that neuronal dynamic leak serves the beneficial function of protecting recurrent neuronal circuitry from the self-induction of spurious high frequency signals, thereby permitting the brain to utilize this architectural circuitry component regardless of network size or recurrency.

Mean-Field Models for EEG/MEG: From Oscillations to Waves

Neural mass models have been used since the 1970s to model the coarse-grained activity of large populations of neurons. They have proven especially fruitful for understanding brain rhythms. However, although motivated by neurobiological considerations they are phenomenological in nature, and cannot hope to recreate some of the rich repertoire of responses seen in real neuronal tissue. Here we consider a simple spiking neuron network model that has recently been shown to admit an exact mean-field description for both synaptic and gap-junction interactions. The mean-field model takes a similar form to a standard neural mass model, with an additional dynamical equation to describe the evolution of within-population synchrony. As well as reviewing the origins of this next generation mass model we discuss its extension to describe an idealised spatially extended planar cortex. To emphasise the usefulness of this model for EEG/MEG modelling we show how it can be used to uncover the role of local gap-junction coupling in shaping large scale synaptic waves.

CODECHECK: an Open Science initiative for the independent execution of computations underlying research articles during peer review to improve reproducibility

The traditional scientific paper falls short of effectively communicating computational research.  To help improve this situation, we propose a system by which the computational workflows underlying research articles are checked. The CODECHECK system uses open infrastructure and tools and can be integrated into review and publication processes in multiple ways. We describe these integrations along multiple dimensions (importance, who, openness, when). In collaboration with academic publishers and conferences, we demonstrate CODECHECK with 25 reproductions of diverse scientific publications. These CODECHECKs show that asking for reproducible workflows during a collaborative review can effectively improve executability. While CODECHECK has clear limitations, it may represent a building block in Open Science and publishing ecosystems for improving the reproducibility, appreciation, and, potentially, the quality of non-textual research artefacts. The CODECHECK website can be accessed here: https://codecheck.org.uk/.

CODECHECK: an Open Science initiative for the independent execution of computations underlying research articles during peer review to improve reproducibility

The traditional scientific paper falls short of effectively communicating computational research.  To help improve this situation, we propose a system by which the computational workflows underlying research articles are checked. The CODECHECK system uses open infrastructure and tools and can be integrated into review and publication processes in multiple ways. We describe these integrations along multiple dimensions (importance, who, openness, when). In collaboration with academic publishers and conferences, we demonstrate CODECHECK with 25 reproductions of diverse scientific publications. These CODECHECKs show that asking for reproducible workflows during a collaborative review can effectively improve executability. While CODECHECK has clear limitations, it may represent a building block in Open Science and publishing ecosystems for improving the reproducibility, appreciation, and, potentially, the quality of non-textual research artefacts. The CODECHECK website can be accessed here: https://codecheck.org.uk/.

Travelling waves reveal a dynamic seizure source in human focal epilepsy

Treatment of patients with drug-resistant focal epilepsy relies upon accurate seizure localization. Ictal activity captured by intracranial EEG has traditionally been interpreted to suggest that the underlying cortex is actively involved in seizures. Here, we hypothesize that such activity instead reflects propagated activity from a relatively focal seizure source, even during later time points when ictal activity is more widespread. We used the time differences observed between ictal discharges in adjacent electrodes to estimate the location of the hypothesized focal source and demonstrated that the seizure source, localized in this manner, closely matches the clinically and neurophysiologically determined brain region giving rise to seizures. Moreover, we determined this focal source to be a dynamic entity that moves and evolves over the time course of a seizure. Our results offer an interpretation of ictal activity observed by intracranial EEG that challenges the traditional conceptualization of the seizure source.

Evidence for spreading seizure as a cause of theta-alpha activity electrographic pattern in stereo-EEG seizure recordings

Intracranial electroencephalography is a standard tool in clinical evaluation of patients with focal epilepsy. Various early electrographic seizure patterns differing in frequency, amplitude, and waveform of the oscillations are observed. The pattern most common in the areas of seizure propagation is the so-called theta-alpha activity (TAA), whose defining features are oscillations in the θ - α range and gradually increasing amplitude. A deeper understanding of the mechanism underlying the generation of the TAA pattern is however lacking. In this work we evaluate the hypothesis that the TAA patterns are caused by seizures spreading across the cortex. To do so, we perform simulations of seizure dynamics on detailed patient-derived cortical surfaces using the spreading seizure model as well as reference models with one or two homogeneous sources. We then detect the occurrences of the TAA patterns both in the simulated stereo-electroencephalographic signals and in the signals of recorded epileptic seizures from a cohort of fifty patients, and we compare the features of the groups of detected TAA patterns to assess the plausibility of the different models. Our results show that spreading seizure hypothesis is qualitatively consistent with the evidence available in the seizure recordings, and it can explain the features of the detected TAA groups best among the examined models.

Data-driven method to infer the seizure propagation patterns in an epileptic brain from intracranial electroencephalography

Surgical interventions in epileptic patients aimed at the removal of the epileptogenic zone have success rates at only 60-70%. This failure can be partly attributed to the insufficient spatial sampling by the implanted intracranial electrodes during the clinical evaluation, leading to an incomplete picture of spatio-temporal seizure organization in the regions that are not directly observed. Utilizing the partial observations of the seizure spreading through the brain network, complemented by the assumption that the epileptic seizures spread along the structural connections, we infer if and when are the unobserved regions recruited in the seizure. To this end we introduce a data-driven model of seizure recruitment and propagation across a weighted network, which we invert using the Bayesian inference framework. Using a leave-one-out cross-validation scheme on a cohort of 45 patients we demonstrate that the method can improve the predictions of the states of the unobserved regions compared to an empirical estimate that does not use the structural information, yet it is on the same level as the estimate that takes the structure into account. Furthermore, a comparison with the performed surgical resection and the surgery outcome indicates a link between the inferred excitable regions and the actual epileptogenic zone. The results emphasize the importance of the structural connectome in the large-scale spatio-temporal organization of epileptic seizures and introduce a novel way to integrate the patient-specific connectome and intracranial seizure recordings in a whole-brain computational model of seizure spread.

Isoflurane-Induced Burst Suppression Is a Thalamus-Modulated, Focal-Onset Rhythm With Persistent Local Asynchrony and Variable Propagation Patterns in Rats

Background: Inhalational anesthetic-induced burst suppression (BS) is classically considered a bilaterally synchronous rhythm. However, local asynchrony has been predicted in theoretical studies and reported in patients with pre-existing focal pathology. Method: We used high-speed widefield calcium imaging to study the spatiotemporal dynamics of isoflurane-induced BS in rats. Results: We found that isoflurane-induced BS is not a globally synchronous rhythm. In the neocortex, neural activity first emerged in a spatially shifting, variably localized focus. Subsequent propagation across the whole cortex was rapid, typically within <100 milliseconds, giving the superficial resemblance to global synchrony. Neural activity remained locally asynchronous during the bursts, forming complex recurrent propagating waves. Despite propagation variability, spatial sequences of burst propagation were largely preserved between the hemispheres, and neural activity was highly correlated between the homotopic areas. The critical role of the thalamus in cortical burst initiation was demonstrated by using unilateral thalamic tetrodotoxin injection. Conclusion: The classical impression that anesthetics-induced BS is a state of global brain synchrony is inaccurate. Bursts are a series of shifting local cortical events facilitated by thalamic projection that unfold as rapid, bilaterally asynchronous propagating waves.

Neuronal Firing and Waveform Alterations through Ictal Recruitment in Humans

Analyzing neuronal activity during human seizures is pivotal to understanding mechanisms of seizure onset and propagation. These analyses, however, invariably using extracellular recordings, are greatly hindered by various phenomena that are well established in animal studies: changes in local ionic concentration, changes in ionic conductance, and intense, hypersynchronous firing. The first two alter the action potential waveform, whereas the third increases the "noise"; all three factors confound attempts to detect and classify single neurons. To address these analytical difficulties, we developed a novel template-matching-based spike sorting method, which enabled identification of 1239 single neurons in 27 patients (13 female) with intractable focal epilepsy, that were tracked throughout multiple seizures. These new analyses showed continued neuronal firing with widespread intense activation and stereotyped action potential alterations in tissue that was invaded by the seizure: neurons displayed increased waveform duration (p < 0.001) and reduced amplitude (p < 0.001), consistent with prior animal studies. By contrast, neurons in "penumbral" regions (those receiving intense local synaptic drive from the seizure but without neuronal evidence of local seizure invasion) showed stable waveforms. All neurons returned to their preictal waveforms after seizure termination. We conclude that the distinction between "core" territories invaded by the seizure versus "penumbral" territories is evident at the level of single neurons. Furthermore, the increased waveform duration and decreased waveform amplitude are neuron-intrinsic hallmarks of seizure invasion that impede traditional spike sorting and could be used as defining characteristics of local recruitment.SIGNIFICANCE STATEMENT Animal studies consistently show marked changes in action potential waveform during epileptic discharges, but acquiring similar evidence in humans has proven difficult. Assessing neuronal involvement in ictal events is pivotal to understanding seizure dynamics and in defining clinical localization of epileptic pathology. Using a novel method to track neuronal firing, we analyzed microelectrode array recordings of spontaneously occurring human seizures, and here report two dichotomous activity patterns. In cortex that is recruited to the seizure, neuronal firing rates increase and waveforms become longer in duration and shorter in amplitude as the neurons are recruited to the seizure, while penumbral tissue shows stable action potentials, in keeping with the "dual territory" model of seizure dynamics.

Inhibitory stabilization and cortical computation

Neuronal networks with strong recurrent connectivity provide the brain with a powerful means to perform complex computational tasks. However, high-gain excitatory networks are susceptible to instability, which can lead to runaway activity, as manifested in pathological regimes such as epilepsy. Inhibitory stabilization offers a dynamic, fast and flexible compensatory mechanism to balance otherwise unstable networks, thus enabling the brain to operate in its most efficient regimes. Here we review recent experimental evidence for the presence of such inhibition-stabilized dynamics in the brain and discuss their consequences for cortical computation. We show how the study of inhibition-stabilized networks in the brain has been facilitated by recent advances in the technological toolbox and perturbative techniques, as well as a concomitant development of biologically realistic computational models. By outlining future avenues, we suggest that inhibitory stabilization can offer an exemplary case of how experimental neuroscience can progress in tandem with technology and theory to advance our understanding of the brain.

Connecting Pathological Cellular Mechanisms to Large-Scale Seizure Structures

Epilepsy is a neurological disorder characterized by recurrent seizures, where abnormal electrical activity begins in a local brain area and propagates before terminating. In a recent study, Liou and colleagues used multiscale computational modeling to gain mechanistic insights into clinical seizure dynamics based on cellular-level biophysical properties.