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.

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.

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.

NMDA-receptor antibodies alter cortical microcircuit dynamics.

NMDA-receptor antibodies (NMDAR-Abs) cause an autoimmune encephalitis with a diverse range of EEG abnormalities. NMDAR-Abs are believed to disrupt receptor function, but how blocking this excitatory synaptic receptor can lead to paroxysmal EEG abnormalities-or even seizures-is poorly understood. Here we show that NMDAR-Abs change intrinsic cortical connections and neuronal population dynamics to alter the spectral composition of spontaneous EEG activity and predispose brain dynamics to paroxysmal abnormalities. Based on local field potential recordings in a mouse model, we first validate a dynamic causal model of NMDAR-Ab effects on cortical microcircuitry. Using this model, we then identify the key synaptic parameters that best explain EEG paroxysms in pediatric patients with NMDAR-Ab encephalitis. Finally, we use the mouse model to show that NMDAR-Ab-related changes render microcircuitry critically susceptible to overt EEG paroxysms when these key parameters are changed, even though the same parameter fluctuations are tolerated in the in silico model of the control condition. These findings offer mechanistic insights into circuit-level dysfunction induced by NMDAR-Ab.

Dynamic Causal Modeling of the Relationship between Cognition and Theta-alpha Oscillations in Adults with Down Syndrome.

Individuals with Down syndrome (DS) show high inter-subject variability in cognitive ability and have an ultra-high risk of developing dementia (90% lifetime prevalence). Elucidating factors underlying variability in cognitive function can inform us about intellectual disability (ID) and may improve our understanding of factors associated with later cognitive decline. Increased neuronal inhibition has been posited to contribute to ID in DS. Combining electroencephalography (EEG) with dynamic causal modeling (DCM) provides a non-invasive method for investigating excitatory/inhibitory mechanisms. Resting-state EEG recordings were obtained from 36 adults with DS with no evidence of cognitive decline. Theta-alpha activity (4-13 Hz) was characterized in relation to general cognitive ability (raw Kaufmann's Brief Intelligence Test second Edition (KBIT-2) score). Higher KBIT-2 was associated with higher frontal alpha peak amplitude and higher theta-alpha band power across distributed regions. Modeling this association with DCM revealed intrinsic self-inhibition was the key network parameter underlying observed differences in 4-13 Hz power in relation to KBIT-2 and age. In particular, intrinsic self-inhibition in right V1 was negatively correlated with KBIT-2. Results suggest intrinsic self-inhibition within the alpha network is associated with individual differences in cognitive ability in adults with DS, and may provide a potential therapeutic target for cognitive enhancement.

Calcium imaging and dynamic causal modelling reveal brain-wide changes in effective connectivity and synaptic dynamics during epileptic seizures.

Pathophysiological explanations of epilepsy typically focus on either the micro/mesoscale (e.g. excitation-inhibition imbalance), or on the macroscale (e.g. network architecture). Linking abnormalities across spatial scales remains difficult, partly because of technical limitations in measuring neuronal signatures concurrently at the scales involved. Here we use light sheet imaging of the larval zebrafish brain during acute epileptic seizure induced with pentylenetetrazole. Spectral changes of spontaneous neuronal activity during the seizure are then modelled using neural mass models, allowing Bayesian inference on changes in effective network connectivity and their underlying synaptic dynamics. This dynamic causal modelling of seizures in the zebrafish brain reveals concurrent changes in synaptic coupling at macro- and mesoscale. Fluctuations of both synaptic connection strength and their temporal dynamics are required to explain observed seizure patterns. These findings highlight distinct changes in local (intrinsic) and long-range (extrinsic) synaptic transmission dynamics as a possible seizure pathomechanism and illustrate how our Bayesian model inversion approach can be used to link existing neural mass models of seizure activity and novel experimental methods.

Dynamic causal modelling of seizure activity in a rat model.

This paper presents a physiological account of seizure activity and its evolution over time using a rat model of induced epilepsy. We analyse spectral activity recorded in the hippocampi of three rats who received kainic acid injections in the right hippocampus. We use dynamic causal modelling of seizure activity and Bayesian model reduction to identify the key synaptic and connectivity parameters that underlie seizure onset. Using recent advances in hierarchical modelling (parametric empirical Bayes), we characterise seizure onset in terms of slow fluctuations in synaptic excitability of specific neuronal populations. Our results suggest differences in the pathophysiology - of seizure activity in the lesioned versus the non-lesioned hippocampus - with pronounced changes in excitation-inhibition balance and temporal summation on the lesioned side. In particular, our analyses suggest that marked reductions in the synaptic time constant of the deep pyramidal cells and the self-inhibition of inhibitory interneurons (in the lesioned hippocampus) are sufficient to explain changes in spectral activity. Although these synaptic changes are consistent over rats, the resulting electrophysiological phenotype can be quite diverse.

Use of a bibliometric literature review to assess medical research capacity in post-conflict and developing countries: Somaliland 1991-2013.

OBJECTIVES: Effective healthcare systems require high-quality research to guide evidence-based interventions and strategic planning. In low- and middle-income countries, especially those emerging from violent conflict, research capacity often lags behind other aspects of health system development. Here, we sought to bibliometrically review health-related research output in Somaliland, a post-conflict self-declared, autonomous nation on the Horn of Africa, as a means of assessing research capacity. METHODS: We reviewed articles on health-related research conducted in Somaliland between 1991 and 2013 that included a description of the experimental design, and articles were published in either a peer-reviewed journal or as part of a scholarly programme receiving formal review. We did not include policy or social science research that did not enrol or interact with subjects from Somaliland. Using online databases, all studies meeting minimum eligibility criteria were reviewed in regard to Somaliland-based co-authorship, topic of research and specific measures of quality. RESULTS: A total of 37 studies were included in this review. Of these, only 19 (51%) included co-authorship by Somaliland-based researchers. Of the 21 studies reporting ethical approval, 16 (64%) received approval from the Somalia or Somaliland Ministry of Health, while five received approval from a university or national commission. More than two-thirds of published research was limited to a few areas of investigation with most (19, 51%) following basic cross-sectional study designs. The number of articles published per year increased from 0 to 1 in the years 1991-2007 to a maximum of 8 in 2013. CONCLUSIONS: Research activity in Somaliland is extremely limited. Investigators from high-income countries have largely directed the research agenda in Somaliland; only half of the included studies list co-authors from institutions in Somaliland. Leadership and governance of health research in Somaliland is required to define national priorities, promote scholarly activity and guide the responsible conduct of research. The methods used here to assess research capacity may be generalisable to other low- and middle-income countries and post-conflict settings to measure the impact of research capacity-building efforts.

Guillain-Barré syndrome associated with CASPR2 antibodies: two paediatric cases.

The pathogenesis of Guillain-Barré syndrome (GBS) is considered to be, at least in part, mediated by autoantibodies directed against neuronal antigens. Antibodies to contactin-associated protein-like 2 (CASPR2), part of the voltage-gated potassium channel complex (VGKC-complex), are associated with neurological disease predominantly affecting the peripheral nervous system but are not known to be associated with GBS. We report two cases of ganglioside antibody-negative paediatric GBS associated with CASPR2 antibodies. Both patients made a complete clinical recovery. The tissue distribution and function of CASPR2 make it a biologically plausible autoimmune target in GBS and its clinical relevance in GBS should be determined in further studies.

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.

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.

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.

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.

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 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.

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.