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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, usingin vivowhole-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 STATEMENTEpileptic 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.

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.

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

Our understanding of the genetic aetiology of paediatric epilepsies has grown substantially over the last decade. However, in order to translate improved diagnostics to personalised treatments, there is an urgent need to link molecular pathophysiology in epilepsy to whole-brain dynamics in seizures. Zebrafish have emerged as a promising new animal model for epileptic seizure disorders, with particular relevance for genetic and developmental epilepsies. As a novel model organism for epilepsy research they combine key advantages: the small size of larval zebrafish allows high throughput in vivo experiments; the availability of advanced genetic tools allows targeted modification to model specific human genetic disorders (including genetic epilepsies) in a vertebrate system; and optical access to the entire central nervous system has provided the basis for advanced microscopy technologies to image structure and function in the intact larval zebrafish brain. There is a growing body of literature describing and characterising features of epileptic seizures and epilepsy in larval zebrafish. Recently genetically encoded calcium indicators have been used to investigate the neurobiological basis of these seizures with light microscopy. This approach offers a unique window into the multiscale dynamics of epileptic seizures, capturing both whole-brain dynamics and single-cell behaviour concurrently. At the same time, linking observations made using calcium imaging in the larval zebrafish brain back to an understanding of epileptic seizures largely derived from cortical electrophysiological recordings in human patients and mammalian animal models is non-trivial. In this review we briefly illustrate the state of the art of epilepsy research in zebrafish with particular focus on calcium imaging of epileptic seizures in the larval zebrafish. We illustrate the utility of a dynamic systems perspective on the epileptic brain for providing a principled approach to linking observations across species and identifying those features of brain dynamics that are most relevant to epilepsy. In the following section we survey the literature for imaging features associated with epilepsy and epileptic seizures and link these to observations made from humans and other more traditional animal models. We conclude by identifying the key challenges still facing epilepsy research in the larval zebrafish and indicate strategies for future research to address these and integrate more directly with the themes and questions that emerge from investigating epilepsy in other model systems and human patients.

SummaryExcitation-inhibition (EI) balance may be required for the organisation of brain dynamics to a phase transition, criticality, which confers computational benefits. Brain pathology associated with EI imbalance may therefore occur due to a deviation from criticality. However, evidence linking critical dynamics with EI imbalance-induced pathology is lacking. Here, we studied the effect of EI imbalance-induced epileptic seizures on brain dynamics, using in vivo whole-brain 2-photon imaging of GCaMP6s larval zebrafish at single-neuron resolution. We demonstrate the importance of EI balance for criticality, with EI imbalance causing a loss of whole-brain critical statistics. Using network models we show that a reorganisation of network topology drives this loss of criticality. Seizure dynamics match theoretical predictions for networks driven away from a phase transition into disorder, with the emergence of chaos and a loss of network-mediated separation, dynamic range and metastability. These results demonstrate that EI imbalance drives a pathological deviation from criticality.

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.

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., Sukhvir Wright et al. present a NMDAR antibody-induced model of encephalitis in rats and use in vitro, in vivo, and in silico electrophysiology to examine alterations in neural circuit behavior. Their results suggest that reduction of NMDARs leads to increased excitability and seizure activity, and highlights the potential use of receptor-specific treatments in antibody-mediated seizures and epilepsy.

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.

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.

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., Gain of function mutations in SCN1A cause severe developmental and epileptic encephalopathy. Gorman et al. identify a novel variant, T782I, in a patient with a fatal encephalopathy associated with developmental regression and a hyperkinetic movement disorder. T782I causes a large persistent sodium current predicted to cause neuronal hyperexcitability., Graphical Abstract Graphical AbstractNote:Created with BioRender.com

Glia-Neuron Interactions Underlie State Transitions to Generalized Seizures Diaz Verdugo C, Myren-Svelstad S, Aydin E, et al. Nat Commun. 2019;10:3830. doi:10.1038/s41467-019-11739-z. Brain activity and connectivity alter drastically during epileptic seizures. The brain networks shift from a balanced resting state to a hyperactive and hypersynchronous state. It is, however, less clear which mechanisms underlie the state transitions. By studying neural and glial activity in zebrafish models of epileptic seizures, we observe striking differences between these networks. During the preictal period, neurons display a small increase in synchronous activity only locally, while the gap-junction-coupled glial network was highly active and strongly synchronized across large distances. The transition from a preictal state to a generalized seizure leads to an abrupt increase in neural activity and connectivity, which is accompanied by a strong alteration in glia-neuron interactions and a massive increase in extracellular glutamate. Optogenetic activation of glia excites nearby neurons through the action of glutamate and gap junctions, emphasizing a potential role for glia–glia and glia–neuron connections in the generation of epileptic seizures.

High frequency oscillations (HFO) in scalp EEG are a new and promising epilepsy biomarker. HFO analysis is typically restricted to random and relatively brief sleep segments. However, considerable fluctuations of HFO rates have been observed over the recording nights, particularly in relation to sleep stages and cycles. Here, we identify the timing within the sleep period and the minimal data interval length that allow for sensitive and reproducible detection of scalp HFO. We selected 16 seizure-free whole-night scalp EEG recordings of children and adolescents with focal lesional epilepsy (median age 7.6 y, range 2.2-17.4 y). We used an automated and clinically validated HFO detector to determine HFO rates (80-250 Hz) in bipolar channels. To identify significant variability over different NREM sleep stages and over time spent in sleep, we modelled HFO rate as a Poisson process. We analysed the test-retest reliability to evaluate the reproducibility of HFO detection across recording intervals. Scalp HFO rates were higher in N3 than in N2 sleep and highest in the first sleep cycle, decreasing with time spent in sleep. In N3 sleep, the median reliability of HFO detection increased from 67% to 79% to 100% for 5-, 10-, and 15-min data intervals, improving significantly (p=0.004) from 5 to 10 min but not from 10 to 15 min. In this analysis of whole-night scalp EEG, we identified the first N3 sleep stage as the most sensitive time window for HFO rate detection. N3 data intervals of 10 min duration are required and sufficient for reliable measurements of HFO rates. Our study provides a robust and reliable framework for implementing scalp HFO as an EEG biomarker in pediatric epilepsy.

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., Cserpan et al. report the impact of age on high-frequency oscillations recorded in the scalp EEG of children with epilepsy. Children, Graphical Abstract Graphical Abstract

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., Driscoll, Rosch et al. design transparent graphene-based surface probes to achieve simultaneous electrophysiological recording and calcium imaging of epileptic seizures in mice. This method could be used to investigate circuit dynamics during seizure onset and evolution with high temporal and spatial resolution.

Zusammenfassung Hintergrund Die Epilepsiechirurgie hat sich als wirksame Behandlungsmethode für pharmakoresistente, strukturelle Epilepsien erwiesen. Läsionen im posterioren Kortex stellen dabei – gerade bei Kindern – eine besondere Herausforderung dar. Fragestellung Wirksamkeit der epilepsiechirurgischen Eingriffe bei Kindern und Jugendlichen mit posterioren strukturellen Läsionen. Material und Methoden Literaturüberblick und Zusammenfassung der hauptsächlichen Befunde publizierter Studien zu pädiatrischen Kohorten nach epilepsiechirurgischer Behandlung posteriorer Epilepsien. Ergebnisse Epilepsien aufgrund posteriorer Läsionen sind bei Kindern häufiger als bei Erwachsenen und sind oft weniger klar lokalisiert und weniger deutlich von eloquentem Kortex abgrenzbar. Dennoch haben sich die postoperativen Verläufe in den letzten Jahrzehnten auf Grund von Fortschritten in der Abklärung deutlich verbessert. Schlussfolgerung Auch bei posterioren epileptogenen Läsionen ist die Epilepsiechirurgie oft eine wirksame Behandlungsmethode. Dabei bestehen die besten Aussichten auf Anfallsfreiheit nach frühzeitigen, ausreichend ausgedehnten Eingriffen. Das heißt, diese Kinder und Jugendlichen müssen für ein optimales Outcome umfangreich und v. a. frühzeitig abgeklärt werden.

Seizures are a prominent feature in N-Methyl-D-Aspartate receptor antibody (NMDAR-Ab) 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 novel treatment compound, we developed an NMDAR-Ab 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 an NMDAR-specific neurosteroid, pregnenolone sulfate, 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.

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.

In this opinion paper, we describe a combined view of functional and effective brain connectivity along with the free-energy principle for investigating persistent disruptions in brain networks of patients with focal epilepsy. These changes are likely reflected in effective connectivity along the cortical hierarchy and construct the basis of increased local functional connectivity in focal epilepsy. We propose a testable framework based on dynamic causal modelling and functional connectivity analysis with the capacity of explaining commonly observed connectivity changes during interictal periods. We then hypothesise their possible relation with disrupted free-energy minimisation in the Bayesian brain. This may offer a new approach for neuroimaging to specifically develop and address hypotheses regarding the network pathomechanisms underlying epileptic phenotypes., Highlights • A combined view of functional brain connectivity and dynamic causal modeling of persistent networks changes in focal epilepsy. • Increased functional connectivity in focal epilepsy is likely reflected in effective connectivity of cortical hierarchy. • A testable framework based on dynamic causal modeling and functional connectivity analysis during interictal periods.

The presence of interictal epileptiform discharges on electroencephalography (EEG) may indicate increased epileptic seizure risk and on invasive EEG are the signature of the irritative zone. In highly epileptogenic lesions – such as cortical tubers in tuberous sclerosis – these discharges can be recorded with intracranial stereotactic EEG as part of the evaluation for epilepsy surgery. Yet the network mechanisms that underwrite the generation and spread of these discharges remain poorly understood, limiting their current diagnostic use.Here, we investigate the dynamics of interictal epileptiform discharges using a combination of quantitative analysis of invasive EEG recordings and mesoscale neural mass modelling of cortical dynamics. We first characterise spatially organised local dynamics of discharges recorded from 36 separate tubers in 8 patients with tuberous sclerosis. We characterise these dynamics with a set of competing explanatory network models using dynamic causal modelling. Bayesian model comparison of plausible network architectures suggests that the recurrent coupling between neuronal populations within – and adjacent to – the tuber core explains the travelling wave dynamics observed in these patient recordings.Our results – based on interictal activity – unify competing theories about the pathological organisation of epileptic foci and surrounding cortex in patients with tuberous sclerosis. Coupled oscillator dynamics have previously been used to describe ictal activity, where fast travelling ictal discharges are commonly observed within the recruited seizure network. The interictal data analysed here add the insight that this functional architecture is already established in the interictal state. This links observations of interictal EEG abnormalities directly to pathological network coupling in epilepsy, with possible implications for epilepsy surgery approaches in tuberous sclerosis.Significance StatementInterictal epileptiform discharges (IEDs) are clinically important markers of an epileptic brain. Here we link local IED spread to network coupling through a combination of clinical recordings in paediatric patients with tuberous sclerosis complex, quantitative EEG analysis of interictal discharges spread, and Bayesian inference on coupled neural mass model parameters. We show that the kinds of interictal discharges seen in our patients require recurrent local network coupling extending beyond the putative seizure focus and that in fact only those recurrent coupled networks can support seizure-like and interictal dynamics when run in simulation. Our findings provide a novel integrated perspective on emergent epileptic dynamics in human patients.

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.

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.

We evaluated a new epilepsy genetic diagnostic and counseling service covering a UK population of 3.5 million. We calculated diagnostic yield, estimated clinical impact, and surveyed referring clinicians and families. We costed alternative investigational pathways for neonatal onset epilepsy. Patients with epilepsy of unknown aetiology onset 2 years, with turnaround time of 21 days. Pathogenic variants were seen in SCN8A, SCN2A, SCN1A, KCNQ2, HNRNPU, GRIN2A, SYNGAP1, STXBP1, STX1B, CDKL5, CHRNA4, PCDH19 and PIGT. Clinician prediction was poor. Clinicians and families rated the service highly. In neonates, the cost of investigations could be reduced from £9362 to £2838 by performing gene panel earlier and the median diagnostic delay of 3.43 years reduced to 21 days. Panel testing for epilepsy has a high yield among children with onset, Genetic screening: actionable information for epilepsy patients and clinicians Screening for epilepsy-related gene variants can lead to effective, personalized treatment plans while reducing costs. UK and Danish scientists, led by Deb Pal, King’s College London, evaluated a new service within the UK that searches for genetic variants in patients that cause epilepsy. The authors assessed the impact of next-generation gene panel tests, as well as the necessary resources to make such a service effective. Genetic testing was most effective in patients with seizure onset under 2 years old (21% diagnosed) and yield even higher in neonatal-onset epilepsy (63% diagnosed). For many patients with pathogenic variants, the diagnoses allowed for recommendations on treatment or enrolment in clinical trials. The researchers found that diagnostic delay and financial burden in neonatal epilepsy could be drastically reduced with gene panel testing. The scheme was highly rated by users and patients alike.

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.

Epilepsy is defined as the brain’s susceptibility to recurrent, hypersynchronous discharges that disrupt normal neuronal function. Over the last decades, progress has been made in using dynamical systems theory and computational analyses to characterise the nature of seizure-like activity. Using simplified models of population dynamics, macroscale features of epileptic seizures can be described as expressions of model interactions. There is a trade-off between complexity of these models and their explanatory power: Models that represent biophysical components of the brain often contain many degrees of freedom and nonlinearities, which can make them challenging to interpret and often means that different model parameterisations can produce similar results. Simple models, on the other hand, do not usually have a direct correlate in brain anatomy or physiology, but rather capture more abstract quantities in the brain. However, the effects of individual parameters are easier to interpret. Here we suggest a design principle to generate the complex rhythmic evolution of tonic-clonic epileptic seizures in a neural population approach. Starting from a simple neuronal oscillator with a single nonlinearity , we show in a step-by-step analysis how complex neuronal dynamics derived from patient observations can be reconstructed.

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. Objectifs Des systemes de soins de sante efficaces necessitent de la recherche de haute qualite pour guider les interventions fondees sur des preuves et la planification strategique. Dans les pays a revenus faibles et intermediaires, en particulier ceux qui sortent d'un conflit violent, la capacite de la recherche est souvent en retard par rapport a d'autres aspects de developpement des systemes de sante. Ici, nous visons a analyser bibliometriquement les resultats de la recherche liee a la sante au Somaliland, une nation autoproclamee autonome post-conflit sur la corne de l'Afrique, comme un moyen d’evaluer la capacite de la recherche. Methodes Nous avons examine des articles de recherche lies a la sante menee au Somaliland entre 1991 et 2013, qui comprenaient une description du concept experimental comme en temoigne la section des methodes et des resultats, et qui ont ete publies soit dans un journal scientifique fiable ou dans le cadre d'un programme scientifique avec une analyse formelle. Nous n'avons pas inclus la recherche sur les politiques ou sciences sociales qui n'ont pas recrute ou interagi avec des sujets du Somaliland. En utilisant les bases de donnees en ligne, toutes les etudes repondant aux criteres minimaux d’eligibilite ont ete examinees en ce qui concerne la paternite d'auteur basee au Somaliland, le sujet de la recherche et les mesures specifiques de qualite. Resultats Au total 37 (42%) etudes ont ete incluses dans cette revue dont seulement 19 (51%) incluaient des co-auteurs bases au Somaliland. Sur les 21 etudes rapportant une approbation ethique, 16 (64%) ont recu l'approbation du ministere de la Sante de la Somalie ou du Somaliland, tandis que cinq ont recu l'approbation d'une universite ou d'une commission nationale. Plus de deux tiers des recherches publiees etaient limitees a quelques domaines de recherche, la plupart (19, 51%) suivant des concepts de base d’etude transversale. Le nombre d'articles publies par an est passe de 0 a 1 dans les annees 1991-2007 a un maximum de 8 en 2013. Conclusions L'activite de recherche dans le Somaliland est extremement limitee. Les investigateurs des pays a revenus eleves ont largement oriente la recherche au Somaliland; seule la moitie des etudes incluses impliquent des co-auteurs d'institutions du Somaliland. Un leadership et une gouvernance de la recherche en sante est necessaire au Somaliland pour definir les priorites nationales, promouvoir l'activite educative et guider la conduite responsable de la recherche. Les methodes utilisees ici pour evaluer la capacite de la recherche peuvent etre generalisables a d'autres pays a revenus faibles et intermediaires et a des regions en post-conflit afin de mesurer l'impact des efforts de renforcement des capacites de la recherche. Objetivos Los sistemas de atencion sanitaria efectivos requieren de una investigacion de calidad que guie las intervenciones basadas en la evidencia y la planeacion estrategica. En paises con ingresos bajos y medios, especialmente en aquellos que estan saliendo de un conflicto violento, la capacidad de investigacion a menudo se queda atras con respecto al desarrollo de otros aspectos del sistema sanitario. Aqui buscamos realizar una revision bibliometrica de los resultados de investigaciones relacionados con la salud en Somalilandia, una nacion en el Cuerno de Africa que se ha autodeclarado autonoma despues de un conflicto, para evaluar su capacidad de investigacion. Metodos Hemos revisado los articulos de investigaciones relacionadas con la salud llevadas a cabo en Somaliland entre 1991 y 2013 que incluian la descripcion del diseno experimental evidenciados en las secciones de metodos y resultados, y habian sido publicados en una revista con revision por pares o como parte de un programa academico sujeto a una revision formal. No incluimos investigaciones en ciencias politicas o sociales que no incluyesen a o interactuase con sujetos de Somalilandia. Utilizando bases de datos online, todos los estudios que alcanzaban los criterios de elegibilidad minimos fuero revisados teniendo en cuenta la coautoria de investigadores basados en Somalilandia, el topico de la investigacion y medidas especificas de calidad. Resultados En la revision se incluyeron 37 (42%) estudios. De estos, solo 19 (51%) incluian un coautor basado en Somaliland. De los 21 estudios que reportaban tener aprobacion etica, 16 (64%) recibieron aprobacion del Ministerio de Salud de Somalia o de Somalilandia, mientras que cinco recibieron aprobacion de una comision universitaria o nacional. Mas de dos tercios de la investigacion publicada se limitaba a unas pocas areas de investigacion, con la mayoria (19, 51%) siguiendo disenos de estudio croseccionales basicos. El numero de articulos publicados por ano aumento de 0-1 en los anos 1991 – 2007, a un maximo de 8 en el 2013. Conclusiones La actividad de investigacion en Somalilandia es extremadamente limitada. Los investigadores de paises con ingresos altos han sido quienes, en su mayoria, han dirigido estudios en Somalilandia; solo la mitad de los estudios incluidos tenian coautores de instituciones en Somalilandia. Se necesita liderazgo y gobernanza en la investigacion sanitaria de Somalilandis para definir las prioridades nacionales, promover las actividades academicas y guiar un desempeno responsable de la investigacion. Los metodos aqui utilizados para evaluar la capacidad de investigacion podrian generalizarse a otros paises con ingresos medios y lugares postconflicto, para medir el impacto de la investigacion en el fomento y la creacion de capacidades.

SummaryPathophysiological 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. Empirically measured 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 synaptic connection strength and their temporal dynamics are both required to explain observed seizure patterns. These findings challenge a simple excitation-inhibition account of seizures, and highlight changes in synaptic transmission dynamics as a possible seizure generation pathomechanism.AbbreviationsLFPlocal field potentialPTZpentylenetetrazoleDCMdynamic causal modellingCSDcross spectral densitiesPEBParametric Empirical Bayes

Significance Recently, autoantibodies against NMDA receptors (NMDARs) were identified as a major cause of autoimmune encephalitis. They cause abnormalities in brain function often associated with significant changes in patients’ brain dynamics. Here we use computational modeling to identify how NMDAR dysfunction causes abnormalities in brain dynamics using patient EEGs and local field potential recordings in a mouse model of NMDAR-Ab encephalitis. NMDAR autoantibodies cause a specific shift in excitatory coupling within cortical circuits that places the circuits closer to pathological transitions between dynamic brain states. Because of the proximity to these phase transitions, otherwise benign fluctuations in neuronal coupling cause abnormal EEG responses in the presence of the antibodies. Our modeling results thus explain fluctuating abnormalities in brain dynamics observed in patients., 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.

N-methyl-D-aspartate receptors (NMDARs) are expressed widely throughout the human cortex. Yet disturbances in NMDAR transmission - as implicated in patients with schizophrenia or pharmacologically induced - can cause a regionally specific set of electrophysiological effects. Here, we present a double-blind placebo-controlled study of the effects of the NMDAR blocker ketamine in human volunteers. We employ a marker of auditory learning and putative synaptic plasticity - the mismatch negativity - in a roving auditory oddball paradigm. Using recent advances in Bayesian modelling of group effects in dynamic causal modelling, we fit biophysically plausible network models of the auditory processing hierarchy to whole-scalp evoked response potential recordings. This allowed us to identify the regionally specific effects of ketamine in a distributed network of interacting cortical sources. Under placebo, our analysis replicated previous findings regarding the effects of stimulus repetition and deviance on connectivity within the auditory hierarchy. Crucially, we show that the effect of ketamine is best explained as a selective change in intrinsic inhibition, with a pronounced ketamine-induced reduction of inhibitory interneuron connectivity in frontal sources. These results are consistent with findings from invasive recordings in animal models exposed to NMDAR blockers, and provide evidence that inhibitory-interneuron specific NMDAR dysfunction may be sufficient to explain electrophysiological abnormalities of sensory learning induced by ketamine in human subjects.

Electroencephalography (EEG) allows recording of cortical activity at high temporal resolution. EEG recordings can be summarised along different dimensions using network-level quantitative measures, e.g. channel-to-channel correlation, or band power distributions across channels. These reveal network patterns that unfold over a range of different time scales and can be tracked dynamically.Here we describe the dynamics of network-state transitions in EEG recordings of spontaneous brain activity in normally developing infants and infants with severe early infantile epileptic encephalopathies (n=8, age: 1-8 months). We describe differences in measures of EEG dynamics derived from band power, and correlation-based summaries of network-wide brain activity.We further show that EEGs from different patient groups and controls can be distinguished based on a small set of the novel quantitative measures introduced here, which describe dynamic network state switching. Quantitative measures related to the smoothness of switching from one correlation pattern to another show the largest differences between groups.These findings reveal that the early epileptic encephalopathies are associated with characteristic dynamic features at the network level. Quantitative network-based analyses like the one presented here may in future inform the clinical use of quantitative EEG for diagnosis.

Highlights • Active inference provides a principled account of epistemic behaviour. • Active inference rests upon hierarchical or deep generative models. • Deep generative models of state transitions embody nested temporal structure. • Reading can be simulated via active inference with deep models. • These simulations appear to have a high degree of biological plausibility., How do we navigate a deeply structured world? Why are you reading this sentence first – and did you actually look at the fifth word? This review offers some answers by appealing to active inference based on deep temporal models. It builds on previous formulations of active inference to simulate behavioural and electrophysiological responses under hierarchical generative models of state transitions. Inverting these models corresponds to sequential inference, such that the state at any hierarchical level entails a sequence of transitions in the level below. The deep temporal aspect of these models means that evidence is accumulated over nested time scales, enabling inferences about narratives (i.e., temporal scenes). We illustrate this behaviour with Bayesian belief updating – and neuronal process theories – to simulate the epistemic foraging seen in reading. These simulations reproduce perisaccadic delay period activity and local field potentials seen empirically. Finally, we exploit the deep structure of these models to simulate responses to local (e.g., font type) and global (e.g., semantic) violations; reproducing mismatch negativity and P300 responses respectively.

Using electroencephalography (EEG) dynamic brain function can be measured and its abnormalities identified and described. However, inferring pathological mechanisms from EEG recordings is an ill-posed, inverse problem. Here we illustrate the use of neural mass model based dynamic causal modelling to address this inverse problem. Using Bayesian model inversion and model comparison, DCM allows evaluation of different hypotheses regarding pathomechanisms leading to dynamic brain dysfunction in NMDA receptor encephalitis.

The pathogenesis of Guillain-Barre 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.

Summary Microcephaly is an important sign of neurological malformation and a predictor of future disability. The 2015–16 outbreak of Zika virus and congenital Zika infection brought the world's attention to links between Zika infection and microcephaly. However, Zika virus is only one of the infectious causes of microcephaly and, although the contexts in which they occur vary greatly, all are of concern. In this Review, we summarise important aspects of major congenital infections that can cause microcephaly, and describe the epidemiology, transmission, clinical features, pathogenesis, management, and long-term consequences of these infections. We include infections that cause substantial impairment: cytomegalovirus, herpes simplex virus, rubella virus, Toxoplasma gondii , and Zika virus. We highlight potential issues with classification of microcephaly and show how some infants affected by congenital infection might be missed or incorrectly diagnosed. Although Zika virus has brought the attention of the world to the problem of microcephaly, prevention of all infectious causes of microcephaly and appropriately managing its consequences remain important global public health priorities.

Dravet syndrome is the prototype of SCN1A-mutation associated epilepsies. It is characterised by prolonged seizures, typically provoked by fever. We describe the evaluation of an SCN1A mutation in a child with early-onset temperature-sensitive seizures.The patient carries a heterozygous miss-sense variant (c3818C>T; pAla1273Val) in the NaV1.1 brain sodium channel. We characterised the functional effects of the variant using patch clamp recordings on Chinese Hamster Ovary Cells at different temperatures (32, 37, and 40°C).The variant channels produced a temperature-dependent destabilization of channel activation and fast inactivation. Implementing these empirical abnormalities in a computational model produces a higher threshold for depolarization block in the variant, particularly at 40°C, suggesting a failure to autoregulate at high-input states.These results reveal direct effects of abnormalities in biophysical NaV1.1 channel properties on neuronal dynamics. They illustrate the value of combining cellular measurements with computational models to integrate different scales (gene/channel to patient) of observations.

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.

OBJECTIVE: To identify shared genes and pathways between common absence epilepsy (AE) subtypes (childhood absence epilepsy [CAE], juvenile absence epilepsy [JAE], and unclassified absence epilepsy [UAE]) that may indicate common mechanisms for absence seizure generation and potentially a diagnostic continuum.METHODS: We used high-density single-nucleotide polymorphism arrays to analyze genome-wide rare copy number variation (CNV) in a cohort of 144 children with AEs (95 CAE, 26 UAE, and 23 JAE).RESULTS: We identified CNVs that are known risk factors for AE in 4 patients, including 3x 15q11.2 deletion. We also expanded the phenotype at 4 regions more commonly identified in other neurodevelopmental disorders: 1p36.33 duplication, 1q21.1 deletion, 22q11.2 duplication, and Xp22.31 deletion and duplication. Fifteen patients (10.5%) were found to carry rare CNVs that disrupt genes associated with neuronal development and function (8 CAE, 2 JAE, and 5 UAE). Four categories of protein are each disrupted by several CNVs: (1) synaptic vesicle membrane or vesicle endocytosis, (2) synaptic cell adhesion, (3) synapse organization and motility via actin, and (4) gap junctions. CNVs within these categories are shared across the AE subtypes.CONCLUSIONS: Our results have reinforced the complex and heterogeneous nature of the AEs and their potential for shared genetic mechanisms and have highlighted several pathways that may be important in epileptogenesis of absence seizures.

Graphical abstract Highlights ► fTCD gives a reliable index of cerebral lateralisation for visuospatial attention. ► Task difficulty has no effect on the laterality index in the visuospatial paradigm. ► Visuospatial and language lateralisation are not correlated within subjects. ► The results challenge single-factor theories of hemispheric specialisation., Historically, most theoretical accounts of hemispheric specialisation have proposed a single underlying factor that leads to left hemisphere language and right hemisphere visuospatial processing in the majority of people. More recently empirical evidence has started to challenge this view, suggesting lateralisation of language and visuospatial attention are independent. However, so far studies did not control for a possible confound, task difficulty. For this study, 20 healthy right-handed volunteers underwent functional laterality assessment using functional transcranial Doppler ultrasound (fTCD). We assessed laterality using both a word generation task and a novel variation of the visuospatial landmark task that can be adjusted along two dimensions of difficulty (temporal and spatial). The visuospatial laterality measures were highly intercorrelated and unaffected by task difficulty. Furthermore, there was no correlation between visuospatial and verbal lateralisation within individuals – neither qualitatively (in direction of lateralisation), nor quantitatively (in laterality index size). These results substantiate a growing body of evidence suggesting multiple independent biases leading to the hemispheric lateralisation of different cognitive domains, thus further questioning previously accepted models of laterality development and evolution.