The concept of the Epileptogenic Network defines a new dimension for the analysis of ictal phenomenology and classification of seizures and epilepsy. It provides more depth in understanding the aetiopathogenesis and pathophysiology of seizures, while bears crucial implications for pharmacological, stimulation and surgical treatment approaches.
Given the same neuronal machinery implicated during ictal and interictal states, seizures seem to be dynamic phenomena (oscillopathies) that emerge from the very same mechanisms that generate cortical oscillatory activities. The conventional classification scheme of seizures and epilepsy as 'focal' or 'generalised' is more of an operational than a pragmatic dichotomy.
A wide range of aetiologies gives rise to a relatively small array of seizure types, while different patients who may have seizure onset from different brain regions can produce seizures that appear quite similar. Many different microscale mechanisms of seizure generation seem to converge through large-scale brain networks into common pathways of seizure propagation and phenotypic expression.
For the first time we present a systems neuroscience approach, integrating bottom-up and top-down translational methods into a unifying mechanism of epileptogenesis. This critically depends on the intrinsic neuronal excitability and network architectonics, the interaction of excitatory and inhibitory components, the structural and functional brain connectivity and transition from local-to-global cortical states.
We explore the pathomechanism of seizures by means of mathematical neuronal models and simulations of complex artificial neuronal networks. We use neuronal spiking models and local field potentials to model and simulate the effect of channelopathies, abnormal receptors and neurotransmitters, intrinsic synaptic and extrasynaptic membrane properties, aberrant ionic conductances, excitatory, inhibitory or modulatory neurotransmitter release and receptor function.
Epileptogenic depolarising and afterhyperpolarizing currents can emerge from a combination of abnormal ionic conductances, neurotransmitter release and receptor function. The critical small-to-large scale synchronisation of stochastic and driven resonant oscillations, and massive depolarisation of excitatory and inhibitory neurons, result in a sustained paroxysmal depolarisation shift of principal/pyramidal neurons. This is what we detect as baseline shifts and pathological high-frequency oscillations in intracranial EEG or a range of ictal phenomena on scalp EEG.
Apart from advancing Artificial Intelligence and understanding epileptogenesis, for the first time we can predict and simulate the effects of a channel mutation or a specific drug from the individual neuron across the neuronal network scale. This paves the way for precision medicine in neurodiagnostics and pharmacogenetics, in designing effective antiseizure and/or epileptogenesis-modifying medicines, and optimising the pharmacological, neurostimulation and neurosurgical treatment strategies for epilepsy.
