Postictal Brain Network Dynamics and Their Clinical Applications

Background/Objectives: The postictal state encompasses complex changes in brain-network organisation, involving multiple pathophysiological processes whose interactions remain incompletely understood. An integrative approach across recording modalities and spatial and temporal scales may help elucidate the relationships underlying these changes. This review provides a network-centred synthesis of postictal dynamics, examining the ictal–postictal transition, operational definitions of recovery, and the potential clinical relevance of postictal network changes. Methods: We reviewed electrophysiological, metabolic, neurovascular, imaging and modelling findings across experimental seizure models, seizures in human epilepsy and electroconvulsive therapy-induced seizures, with particular emphasis on the temporal evolution of postictal brain activity and quantitative approaches to defining recovery. Results: Across modalities, seizure offset does not consistently mark immediate restoration of the preictal state. Postictal activity evolves over seconds to hours through changes in suppression and slowing, signal complexity, functional connectivity, information flow, perfusion and metabolism. These patterns are influenced by seizure propagation, severity, localisation and clinical context. Quantitative approaches further indicate that electrophysiological recovery may outlast visually apparent abnormalities and may dissociate from behavioural recovery. Postictal dynamics may provide clinically exploitable information for epileptogenic-network localisation and surgical prognosis, objective assessment of recovery, investigation of autonomic dysfunction and sudden unexpected death in epilepsy, automated seizure-state classification and therapeutic targeting. Conclusions: The postictal period encompasses heterogeneous network dynamics organised across multiple spatial and temporal scales, which may interact with pathophysiological processes underlying recovery. Its systematic characterisation may improve understanding of seizure termination and recovery while expanding the clinical utility of peri-ictal signal analysis.