Modelling cortical network dynamics.

We have investigated the theoretical constraints of the interactions between coupled cortical columns. Each cortical column consists of a set of neural populations where each population is modelled as a neural mass. The existence of semi-stable states within a cortical column is dependent on the type of interaction between the neuronal populations, i.e., the form of the synaptic kernels. Current-to-current coupling has been shown, in contrast to potential-to-current coupling, to create semi-stable states within a cortical column. The interaction between semi-stable states of the cortical columns is studied where we derive the dynamics for the collected activity. For small excitations the dynamics follow the Kuramoto model; however, in contrast to previous work we derive coupled equations between phase and amplitude dynamics with the possibility of defining connectivity as a stationary and dynamic variable. The turbulent flow of phase dynamics which occurs in networks of Kuramoto oscillators would indicate turbulent changes in dynamic connectivity for coupled cortical columns which is something that has been recorded in epileptic seizures. We used the results we derived to estimate a seizure propagation model which allowed for inversions using the Laplace assumption (Dynamic Causal Modelling). The seizure propagation model was trialed on simulated data, and future work will investigate the estimation of the connectivity matrix from empirical data. This model can be used to predict changes in seizure evolution after virtual changes in the connectivity network, something that could be of clinical use when applied to epilepsy surgical cases.

The mismatch negativity as an index of cognitive abilities in adults with Down syndrome.

Down syndrome (DS) is associated with an ultra-high risk of developing Alzheimer's disease (AD). Understanding variability in pre-AD cognitive abilities may help understand cognitive decline in this population. The mismatch negativity (MMN) is an event-related potential component reflecting the detection of deviant stimuli that is thought to represent underlying memory processes, with reduced MMN amplitudes being associated with cognitive decline. To further understand the MMN in adults with DS without AD, we explored the relationships between MMN, age, and cognitive abilities (memory, language, and attention) in 27 individuals (aged 17-51) using a passive auditory oddball task. Statistically significant MMN was present only in 18 individuals up to 41 years of age and the latency were longer than canonical parameters reported in the literature. Reduced MMN amplitude was associated with lower memory scores, while longer MMN latencies were associated with poorer memory, verbal abilities, and attention. Therefore, the MMN may represent a valuable index of cognitive abilities in DS. In combination with previous findings, we hypothesize that while MMN response and amplitude may be associated with AD-related memory loss, MMN latency may be associated with speech signal processing. Future studies may explore the potential impact of AD on MMN in people with DS.

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.

Global dynamics of neural mass models.

Neural mass models are used to simulate cortical dynamics and to explain the electrical and magnetic fields measured using electro- and magnetoencephalography. Simulations evince a complex phase-space structure for these kinds of models; including stationary points and limit cycles and the possibility for bifurcations and transitions among different modes of activity. This complexity allows neural mass models to describe the itinerant features of brain dynamics. However, expressive, nonlinear neural mass models are often difficult to fit to empirical data without additional simplifying assumptions: e.g., that the system can be modelled as linear perturbations around a fixed point. In this study we offer a mathematical analysis of neural mass models, specifically the canonical microcircuit model, providing analytical solutions describing slow changes in the type of cortical activity, i.e. dynamical itinerancy. We derive a perturbation analysis up to second order of the phase flow, together with adiabatic approximations. This allows us to describe amplitude modulations in a relatively simple mathematical format providing analytic proof-of-principle for the existence of semi-stable states of cortical dynamics at the scale of a cortical column. This work allows for model inversion of neural mass models, not only around fixed points, but over regions of phase space that encompass transitions among semi or multi-stable states of oscillatory activity. Crucially, these theoretical results speak to model inversion in the context of multiple semi-stable brain states, such as the transition between interictal, pre-ictal and ictal activity in epilepsy.

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 GABAA 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.

Drug-resistant focal epilepsy in children is associated with increased modal controllability of the whole brain and epileptogenic regions.

Network control theory provides a framework by which neurophysiological dynamics of the brain can be modelled as a function of the structural connectome constructed from diffusion MRI. Average controllability describes the ability of a region to drive the brain to easy-to-reach neurophysiological states whilst modal controllability describes the ability of a region to drive the brain to difficult-to-reach states. In this study, we identify increases in mean average and modal controllability in children with drug-resistant epilepsy compared to healthy controls. Using simulations, we purport that these changes may be a result of increased thalamocortical connectivity. At the node level, we demonstrate decreased modal controllability in the thalamus and posterior cingulate regions. In those undergoing resective surgery, we also demonstrate increased modal controllability of the resected parcels, a finding specific to patients who were rendered seizure free following surgery. Changes in controllability are a manifestation of brain network dysfunction in epilepsy and may be a useful construct to understand the pathophysiology of this archetypical network disease. Understanding the mechanisms underlying these controllability changes may also facilitate the design of network-focussed interventions that seek to normalise network structure and function.

Variation of scalp EEG high frequency oscillation rate with sleep stage and time spent in sleep in patients with pediatric epilepsy.

OBJECTIVE: High frequency oscillations (HFO) in scalp EEG are a new and promising epilepsy biomarker. However, considerable fluctuations of HFO rates have been observed through sleep stages and cycles. Here, we aimed to identify the optimal timing within sleep and the minimal data length for sensitive and reproducible HFO detection. METHODS: We selected 16 whole-night scalp EEG recordings of paediatric patients with a focal structural epilepsy. We used an automated clinically validated HFO detector to determine HFO rates (80-250 Hz). We evaluated the reproducibility of HFO detection across intervals. RESULTS: HFO rates were higher in N3 than in N2 and REM (rapid eye movement) sleep and highest in the first sleep cycle, decreasing with time in sleep. In N3 sleep, the median reliability of HFO detection increased from 67% (interquartile range: iqr 57) to 78% (iqr 59) to 100% (iqr 70%) for 5-, 10-, and 15-min data intervals, improving significantly (p = 0.004, z = 2.9) from 5 to 10 min but not from 10 to 15 min. CONCLUSIONS: We identified the first N3 sleep stage as the most sensitive time window for HFO rate detection. At least 10 min N3 data intervals are required and sufficient for reliable measurements of HFO rates. SIGNIFICANCE: Our study provides a robust and reliable framework for scalp HFO detection that may facilitate their implementation as an EEG biomarker in paediatric epilepsy.

The L1624Q Variant in SCN1A Causes Familial Epilepsy Through a Mixed Gain and Loss of Channel Function.

Variants of the SCN1A gene encoding the neuronal voltage-gated sodium channel NaV1.1 cause over 85% of all cases of Dravet syndrome, a severe and often pharmacoresistent epileptic encephalopathy with mostly infantile onset. But with the increased availability of genetic testing for patients with epilepsy, variants in SCN1A have now also been described in a range of other epilepsy phenotypes. The vast majority of these epilepsy-associated variants are de novo, and most are either nonsense variants that truncate the channel or missense variants that are presumed to cause loss of channel function. However, biophysical analysis has revealed a significant subset of missense mutations that result in increased excitability, further complicating approaches to precision pharmacotherapy for patients with SCN1A variants and epilepsy. We describe clinical and biophysical data of a familial SCN1A variant encoding the NaV1.1 L1624Q mutant. This substitution is located on the extracellular linker between S3 and S4 of Domain IV of NaV1.1 and is a rare case of a familial SCN1A variant causing an autosomal dominant frontal lobe epilepsy. We expressed wild-type (WT) and L1642Q channels in CHO cells. Using patch-clamp to characterize channel properties at several temperatures, we show that the L1624Q variant increases persistent current, accelerates fast inactivation onset and decreases current density. While SCN1A-associated epilepsy is typically considered a loss-of-function disease, our results put L1624Q into a growing set of mixed gain and loss-of-function variants in SCN1A responsible for epilepsy.

Persistent sodium currents in SCN1A developmental and degenerative epileptic dyskinetic encephalopathy.

Pathogenic variants in the voltage-gated sodium channel gene (SCN1A) are amongst the most common genetic causes of childhood epilepsies. There is considerable heterogeneity in both the types of causative variants and associated phenotypes; a recent expansion of the phenotypic spectrum of SCN1A associated epilepsies now includes an early onset severe developmental and epileptic encephalopathy with regression and a hyperkinetic movement disorder. Herein, we report a female with a developmental and degenerative epileptic-dyskinetic encephalopathy, distinct and more severe than classic Dravet syndrome. Clinical diagnostics indicated a paternally inherited c.5053G>T; p. A1685S variant of uncertain significance in SCN1A. Whole-exome sequencing detected a second de novo mosaic (18%) c.2345G>A; p. T782I likely pathogenic variant in SCN1A (maternal allele). Biophysical characterization of both mutant channels in a heterologous expression system identified gain-of-function effects in both, with a milder shift in fast inactivation of the p. A1685S channels; and a more severe persistent sodium current in the p. T782I. Using computational models, we show that large persistent sodium currents induce hyper-excitability in individual cortical neurons, thus relating the severe phenotype to the empirically quantified sodium channel dysfunction. These findings further broaden the phenotypic spectrum of SCN1A associated epilepsies and highlight the importance of testing for mosaicism in epileptic encephalopathies. Detailed biophysical evaluation and computational modelling further highlight the role of gain-of-function variants in the pathophysiology of the most severe phenotypes associated with SCN1A.

Multimodal electrophysiological analyses reveal that reduced synaptic excitatory neurotransmission underlies seizures in a model of NMDAR antibody-mediated encephalitis.

Seizures are a prominent feature in N-Methyl-D-Aspartate receptor antibody (NMDAR antibody) encephalitis, a distinct neuro-immunological disorder in which specific human autoantibodies bind and crosslink the surface of NMDAR proteins thereby causing internalization and a state of NMDAR hypofunction. To further understand ictogenesis in this disorder, and to test a potential treatment compound, we developed an NMDAR antibody mediated rat seizure model that displays spontaneous epileptiform activity in vivo and in vitro. Using a combination of electrophysiological and dynamic causal modelling techniques we show that, contrary to expectation, reduction of synaptic excitatory, but not inhibitory, neurotransmission underlies the ictal events through alterations in the dynamical behaviour of microcircuits in brain tissue. Moreover, in vitro application of a neurosteroid, pregnenolone sulphate, that upregulates NMDARs, reduced established ictal activity. This proof-of-concept study highlights the complexity of circuit disturbances that may lead to seizures and the potential use of receptor-specific treatments in antibody-mediated seizures and epilepsy.

ZMYND11 variants are a novel cause of centrotemporal and generalised epilepsies with neurodevelopmental disorder.

ZMYND11 is the critical gene in chromosome 10p15.3 microdeletion syndrome, a syndromic cause of intellectual disability. The phenotype of ZMYND11 variants has recently been extended to autism and seizures. We expand on the epilepsy phenotype of 20 individuals with pathogenic variants in ZMYND11. We obtained clinical descriptions of 16 new and nine published individuals, plus detailed case history of two children. New individuals were identified through GeneMatcher, ClinVar and the European Network for Therapies in Rare Epilepsy (NETRE). Genetic evaluation was performed using gene panels or exome sequencing; variants were classified using American College of Medical Genetics (ACMG) criteria. Individuals with ZMYND11 associated epilepsy fell into three groups: (i) atypical benign partial epilepsy or idiopathic focal epilepsy (n = 8); (ii) generalised epilepsies/infantile epileptic encephalopathy (n = 4); (iii) unclassified (n = 8). Seizure prognosis ranged from spontaneous remission to drug resistant. Neurodevelopmental deficits were invariable. Dysmorphic features were variable. Variants were distributed across the gene and mostly de novo with no precise genotype-phenotype correlation. ZMYND11 is one of a small group of chromatin reader genes associated in the pathogenesis of epilepsy, and specifically ABPE. More detailed epilepsy descriptions of larger cohorts and functional studies might reveal genotype-phenotype correlation. The epileptogenic mechanism may be linked to interaction with histone H3.3.

Sotos syndrome: a pitfall in the presurgical workup of temporal lobe epilepsy.

Tumour-associated epilepsy accounts for a quarter of paediatric patients undergoing epilepsy surgery with the vast majority achieving long-term seizure and drug freedom. We report the case of an eight-year-old patient who presented with developmental delay and overgrowth, followed by temporal lobe seizures that were attributed to a mesio-temporal brain tumour, and who was eventually treated with epilepsy surgery. Histopathology revealed a diffuse astrocytoma but its gross total resection surprisingly failed to control the temporal lobe seizures. Genetic testing identified a de novo pathogenic variant in the NSD1 gene, thus establishing the diagnosis of Sotos syndrome. Sotos syndrome is a rare overgrowth syndrome with an increased incidence of malignancy, including the very rare occurrence of brain tumours. Seizures are frequent in patients with Sotos syndrome, often occurring with temporal lobe semiology and ictal EEG patterns in the absence of a brain lesion, and usually responding to anti-seizure medication. Our case highlights Sotos syndrome as a rare but important pitfall in the presurgical workup of temporal lobe epilepsy that should be considered particularly in MRI-negative cases but also in the presence of a focal lesion that does not fully explain the clinical picture. Most importantly, our observations underline the value of thorough presurgical diagnostics including genetic testing, even in apparently straightforward cases of lesional epilepsy, to rule out an underlying genetic aetiology that may not be treated by surgery. Finally, our findings emphasize the need to re-evaluate our less successful epilepsy surgery cases and offer informed counselling and prognostication.

Scalp high-frequency oscillation rates are higher in younger children.

High-frequency oscillations in scalp EEG are promising non-invasive biomarkers of epileptogenicity. However, it is unclear how high-frequency oscillations are impacted by age in the paediatric population. We prospectively recorded whole-night scalp EEG in 30 children and adolescents with focal or generalized epilepsy. We used an automated and clinically validated high-frequency oscillation detector to determine ripple rates (80-250 Hz) in bipolar channels. Children < 7 years had higher high-frequency oscillation rates (P = 0.021) when compared with older children. The median test-retest reliability of high-frequency oscillation rates reached 100% (iqr 50) for a data interval duration of 10 min. Scalp high-frequency oscillation frequency decreased with age (r = -0.558, P = 0.002), whereas scalp high-frequency oscillation duration and amplitude were unaffected. The signal-to-noise ratio improved with age (r = 0.37, P = 0.048), and the background ripple band activity decreased with age (r = -0.463, P = 0.011). We characterize the relationship of scalp high-frequency oscillation features and age in paediatric patients. EEG intervals of ≥ 10 min duration are required for reliable measurements of high-frequency oscillation rates. This study is a further step towards establishing scalp high-frequency oscillations as a valid epileptogenicity biomarker in this vulnerable age group.

Multimodal in vivo recording using transparent graphene microelectrodes illuminates spatiotemporal seizure dynamics at the microscale.

Neurological disorders such as epilepsy arise from disrupted brain networks. Our capacity to treat these disorders is limited by our inability to map these networks at sufficient temporal and spatial scales to target interventions. Current best techniques either sample broad areas at low temporal resolution (e.g. calcium imaging) or record from discrete regions at high temporal resolution (e.g. electrophysiology). This limitation hampers our ability to understand and intervene in aberrations of network dynamics. Here we present a technique to map the onset and spatiotemporal spread of acute epileptic seizures in vivo by simultaneously recording high bandwidth microelectrocorticography and calcium fluorescence using transparent graphene microelectrode arrays. We integrate dynamic data features from both modalities using non-negative matrix factorization to identify sequential spatiotemporal patterns of seizure onset and evolution, revealing how the temporal progression of ictal electrophysiology is linked to the spatial evolution of the recruited seizure core. This integrated analysis of multimodal data reveals otherwise hidden state transitions in the spatial and temporal progression of acute seizures. The techniques demonstrated here may enable future targeted therapeutic interventions and novel spatially embedded models of local circuit dynamics during seizure onset and evolution.

A Tale of two Networks-Glial Contributions to Generalized Seizures.

[Box: see text].

Seizure initiation in infantile spasms vs. focal seizures: proposed common cellular mechanisms.

Infantile spasms (IS) and seizures with focal onset have different clinical expressions, even when electroencephalography (EEG) associated with IS has some degree of focality. Oddly, identical pathology (with, however, age-dependent expression) can lead to IS in one patient vs. focal seizures in another or even in the same, albeit older, patient. We therefore investigated whether the cellular mechanisms underlying seizure initiation are similar in the two instances: spasms vs. focal. We noted that in-common EEG features can include (i) a background of waves at alpha to delta frequencies; (ii) a period of flattening, lasting about a second or more - the electrodecrement (ED); and (iii) often an interval of very fast oscillations (VFO; ~70 Hz or faster) preceding, or at the beginning of, the ED. With IS, VFO temporally coincides with the motor spasm. What is different between the two conditions is this: with IS, the ED reverts to recurring slow waves, as occurring before the ED, whereas with focal seizures the ED instead evolves into an electrographic seizure, containing high-amplitude synchronized bursts, having superimposed VFO. We used in vitro data to help understand these patterns, as such data suggest cellular mechanisms for delta waves, for VFO, for seizure-related burst complexes containing VFO, and, more recently, for the ED. We propose a unifying mechanistic hypothesis - emphasizing the importance of brain pH - to explain the commonalities and differences of EEG signals in IS versus focal seizures.

Epileptic Seizures: Glia-Neuron Interactions For Better or For Worse.

Investigations of the mechanisms generating epileptic seizures have primarily focused on neurons. However, more systemic research of brain circuits has highlighted an important role of non-neuronal cells such as glia in the genesis and spreading of generalized seizures in the brain.

Targeted knockout of GABA-A receptor gamma 2 subunit provokes transient light-induced reflex seizures in zebrafish larvae.

Epilepsy is a common primary neurological disorder characterized by the chronic tendency of a patient to experience epileptic seizures, which are abnormal body movements or cognitive states that result from excessive, hypersynchronous brain activity. Epilepsy has been found to have numerous etiologies and, although about two-thirds of epilepsies were classically considered idiopathic, the majority of those are now believed to be of genetic origin. Mutations in genes involved in gamma-aminobutyric acid (GABA)-mediated inhibitory neurotransmission have been associated with a broad range of epilepsy syndromes. Mutations in the GABA-A receptor gamma 2 subunit gene (GABRG2), for example, have been associated with absence epilepsy and febrile seizures in humans. Several rodent models of GABRG2 loss of function depict clinical features of the disease; however, alternative genetic models more amenable for the study of ictogenesis and for high-throughput screening purposes are still needed. In this context, we generated a gabrg2 knockout (KO) zebrafish model (which we called R23X) that displayed light/dark-induced reflex seizures. Through high-resolution in vivo calcium imaging of the brain, we showed that this phenotype is associated with widespread increases in neuronal activity that can be effectively alleviated by the anti-epileptic drug valproic acid. Moreover, these seizures only occur at the larval stages but disappear after 1 week of age. Interestingly, our whole-transcriptome analysis showed that gabrg2 KO does not alter the expression of genes in the larval brain. As a result, the gabrg2-/- zebrafish is a novel in vivo genetic model of early epilepsies that opens new doors to investigate ictogenesis and for further drug-screening assays.