Neural mass modeling of slow-fast dynamics of seizure initiation and abortion

• Published in: PLoS computational biology Vol. 16; no. 11; p. e1008430
• Main Authors: Köksal Ersöz, Elif, Modolo, Julien, Bartolomei, Fabrice, Wendling, Fabrice
• Format: Journal Article
• Language: English
• Published: United States PLOS 01.11.2020; Public Library of Science; Public Library of Science (PLoS)
• Subjects: Action Potentials - physiology; Bioengineering; Biology and Life Sciences; Brain - physiopathology; Computational Biology; Computer and Information Sciences; Computer Science; Electric Stimulation Therapy - methods; Electroencephalography; Electrophysiological Phenomena; Engineering Sciences; Epilepsy - physiopathology; Epilepsy - therapy; Humans; Life Sciences; Medicine and Health Sciences; Modeling and Simulation; Models, Neurological; Neurons - physiology; Neurons and Cognition; Physical Sciences; Research and Analysis Methods; Seizures - physiopathology; Seizures - therapy; Signal and Image processing
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1008430

Epilepsy is a dynamic and complex neurological disease affecting about 1% of the worldwide population, among which 30% of the patients are drug-resistant. Epilepsy is characterized by recurrent episodes of paroxysmal neural discharges (the so-called seizures), which manifest themselves through a large-amplitude rhythmic activity observed in depth-EEG recordings, in particular in local field potentials (LFPs). The signature characterizing the transition to seizures involves complex oscillatory patterns, which could serve as a marker to prevent seizure initiation by triggering appropriate therapeutic neurostimulation methods. To investigate such protocols, neurophysiological lumped-parameter models at the mesoscopic scale, namely neural mass models, are powerful tools that not only mimic the LFP signals but also give insights on the neural mechanisms related to different stages of seizures. Here, we analyze the multiple time-scale dynamics of a neural mass model and explain the underlying structure of the complex oscillations observed before seizure initiation. We investigate population-specific effects of the stimulation and the dependence of stimulation parameters on synaptic timescales. In particular, we show that intermediate stimulation frequencies (>20 Hz) can abort seizures if the timescale difference is pronounced. Those results have the potential in the design of therapeutic brain stimulation protocols based on the neurophysiological properties of tissue.