Computational Synaptic Modeling of Pitch and Duration Mismatch Negativity in First-Episode Psychosis Reveals Selective Dysfunction of the N-Methyl-D-Aspartate Receptor

Mismatch negativity (MMN) to pitch (pMMN) and to duration (dMMN) deviant stimuli is significantly more attenuated in long-term psychotic illness compared to first-episode psychosis (FEP). It was recently shown that source-modeling of magnetically recorded MMN increases the detection of left auditory cortex MMN deficits in FEP, and that computational circuit modeling of electrically recorded MMN also reveals left-hemisphere auditory cortex abnormalities. Computational modeling using dynamic causal modeling (DCM) can also be used to infer synaptic activity from EEG-based scalp recordings. We measured pMMN and dMMN with EEG from 26 FEP and 26 matched healthy controls (HCs) and used a DCM conductance-based neural mass model including α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid, N-methyl-D-Aspartate (NMDA), and Gamma-aminobutyric acid receptors to identify any changes in effective connectivity and receptor rate constants in FEP. We modeled MMN sources in bilateral A1, superior temporal gyrus, and inferior frontal gyrus (IFG). No model parameters distinguished groups for pMMN. For dMMN, reduced NMDA receptor activity in right IFG in FEP was detected. This finding is in line with literature of prefrontal NMDA receptor hypofunction in chronic schizophrenia and suggests impaired NMDA-induced synaptic plasticity may be present at psychosis onset where scalp dMMN is only moderately reduced. To the best of our knowledge, this is the first report of impaired NMDA receptor activity in FEP found through computational modeling of dMMN and shows the potential of DCM to non-invasively reveal synaptic-level abnormalities that underly subtle functional auditory processing deficits in early psychosis.

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 organised to a phase transition, which optimises certain computational properties. Some have hypothesised that the pathological 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 2-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 behaviour 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.

Imaging epilepsy in larval zebrafish

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.

Cerebellar Asymmetry and Cortical Connectivity in Monozygotic Twins with Discordant Handedness

Handedness differentiates patterns of neural asymmetry and interhemispheric connectivity in cortical systems that underpin manual and language functions. Contemporary models of cerebellar function incorporate complex motor behaviour and higher-order cognition, expanding upon earlier, traditional associations between the cerebellum and motor control. Structural MRI defined cerebellar volume asymmetries and correlations with corpus callosum (CC) size were compared in 19 pairs of adult female monozygotic twins strongly discordant for handedness (MZHd). Volume and asymmetry of cerebellar lobules were obtained using automated parcellation.CC area and regional widths were obtained from midsagittal planimetric measurements. Within the cerebellum and CC, neurofunctional distinctions were drawn between motor and higher-order cognitive systems. Relationships amongst regional cerebellar asymmetry and cortical connectivity (as indicated by CC widths) were investigated. Interactions between hemisphere and handedness in the anterior cerebellum were due to a larger right-greater-than-left hemispheric asymmetry in right-handed (RH) compared to left-handed (LH) twins. In LH twins only, anterior cerebellar lobule volumes (IV, V) for motor control were associated with CC size, particularly in callosal regions associated with motor cortex connectivity. Superior posterior cerebellar lobule volumes (VI, Crus I, Crus II, VIIb) showed no correlation with CC size in either handedness group. These novel results reflected distinct patterns of cerebellar-cortical relationships delineated by specific CC regions and an anterior-posterior cerebellar topographical mapping. Hence, anterior cerebellar asymmetry may contribute to the greater degree of bilateral cortical organisation of frontal motor function in LH individuals.

Temperature-dependent changes in neuronal dynamics in a patient with an SCN1A mutation and hyperthermia induced seizures

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 missense variant (c3818C > T; pAla1273Val) in the Na_V1.1 brain sodium channel. We compared the functional effects of the variant vs. wild type Na_V1.1 using patch clamp recordings from channels expressed in Chinese Hamster Ovary Cells at different temperatures (32, 37, and 40 °C). The variant channels produced a temperature-dependent destabilization of activation and fast inactivation. Implementing these empirical abnormalities in a computational model predicts 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 Na_V1.1 biophysical properties on neuronal dynamics. They illustrate the value of combining cellular measurements with computational models to integrate different observational scales (gene/channel to patient).