A review of epileptic markers: from ion channels, astrocytes, synaptic imbalance to whole brain network dynamics

• Published in: Exploration of neuroscience Vol. 3; no. 5; pp. 478 - 492
• Main Authors: Swati Banerjee, Viktor Jirsa
• Format: Journal Article
• Language: English
• Published: Open Exploration Publishing Inc 29.09.2024
• Subjects: astrocytes; epilepsy; ion channel imbalance; neural mass model; whole brain network
• ISSN: 2834-5347
• DOI: 10.37349/en.2024.00060

Epilepsy, a neurological disorder characterized by recurrent seizures, presents a complex interplay of cellular and molecular mechanisms. The symptoms manifest themselves at various scales, from ion channels to brain regions to behavior in humans. Various screening, treatment, and preventive measures use this knowledge to tackle the disorder effectively. This article aims to summarize the current state of the art in epileptic markers from ion channels, astrocytes, and synaptic imbalance to whole brain Network Dynamics. Recent research has shed light on the critical involvement of astrocytes, the multifunctional glial cells, in the pathogenesis and modulation of epileptic seizures in humans. Astrocytes, once considered as mere supportive cells, are now recognized as active participants in the regulation of neuronal excitability, synaptic transmission, and brain homeostasis. Ion channel imbalance is one of the widely studied areas in the context of epilepsy and is partially addressed in the abstract. Recent advances in computational neuroscience have led to the development of whole brain network models, providing valuable tools for studying the complex dynamics of epileptic seizures. These models integrate diverse biological factors, including neuronal connectivity, synaptic dynamics, and cellular properties, to simulate the spatiotemporal patterns of epileptic activity across brain regions. Through computational simulations and analysis, whole brain network models offer insights into seizure initiation, propagation, and termination mechanisms, shedding light on the dynamic interactions between epileptic foci and distributed brain networks. Moreover, these models facilitate the exploration of network-based biomarkers for seizure prediction and intervention optimization. Challenges and limitations, such as model complexity and validation against experimental data, are also discussed. Despite these challenges, whole brain network models represent a promising approach for advancing our understanding of epilepsy and identifying novel therapeutic strategies. Future research efforts should focus on refining model fidelity, incorporating multimodal data, and translating computational findings into clinically relevant applications, ultimately improving the management and treatment of epilepsy patients.