Florey Department of Neuroscience and Mental Health - Theses
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ItemComputational modelling of pathologic mechanisms in genetic epilepsies: ion channels, single neurons and neural networks( 2021)Epilepsy is a common and chronic neurological condition characterised by the emergence of excessive or hypersynchronous electrical activity within the brain. A significant proportion of epilepsy is caused by gene mutations, many of which disrupt the function of subcellular protein structures known as ion channels that regulate the excitability of nerve cells (neurons). Despite the prevalence of epilepsy and its societal and economic impact, the mechanisms relating ion channel dysfunction to abnormal electrical activity within neuronal networks remain unclear. This is a matter of importance as approximately one-third of patients with epilepsy suffer intractable seizures despite treatment with modern anti-seizure pharmacotherapy. A more comprehensive understanding of epilepsy pathophysiology that that links ion channel pathology to network dysfunction may reveal new avenues for treatment. In this thesis, the biophysical consequences of two ion channel mutations associated with genetic forms of human epilepsy are explored using computational modelling and experimental electrophysiology. The first is a mutation of the NaV1.1 channel: a voltage-gated sodium channel that serves as an important regulator of neuronal excitability. In this work, we find that a NaV1.1 mutation associated with a severe form of epilepsy leads to impaired cortical inhibition through depolarisation block of inhibitory interneurons. Our results also suggest that NaV1.1 plays a central physiological role for sustaining high firing rates within cortical inhibitory interneurons. The second is a mutation of the GABAA (gamma-aminobutyric acid) receptor: a ligand-gated ion channel that mediates a powerful inhibitory influence within the brain known as tonic inhibition. Using computational modelling we predict that tonic inhibition can selectively modulate the excitability of subtypes of cortical interneurons according to their intrinsic electrophysiological properties. Our models suggest that differential modulation of neuronal excitability occurs via a novel electrophysiological mechanism that is mediated through the dendritic tree. These predictions are supported by in-vitro experiments, and further analysis suggests that modulation of neuronal excitability is dependent upon the expression of certain subtypes of voltage-gated potassium channels, such as the KV3.1 channel. A theme arising from this work is the relevance of distinct subtypes of inhibitory interneurons for regulating excitability in the brain. Therefore, this idea is explored in further detail using a cortical network model that incorporates different interneuron subtypes. Our model suggests that interneurons with properties typical of Parvalbumin-positive subtypes – a prevalent interneuron class within the cortex – are crucial for regulating the extent of internally-driven excitatory activity within a neuronal network. Reductions of excitability in Parvalbumin-positive interneurons promote a network state characterised by strong coupling between excitatory neurons. Known as an inhibition-stabilised network, this network regime is associated with certain cortical computational abilities and the potential to generate epileptic seizures.