ESR14 : Neural, Metabolic and biochemical mechanisms of epileptic seizure genesis and propagation
AMU has proposed a comprehensive mathematical framework that includes cellular and synaptic network variables to explain seizuredynamics. The model predicts that a state variable evolving slowly in time is required to explain seizure onset, time course and offset. Preliminary data show that molecular events such as those related to metabolism and energy supply, which evolve slowly in time, are integral components of this state variable. Alterations in molecular processes may also underlie cognitive deficits. We will combine molecular sensors and high-density electrophysiological recordings to obtain a complete electro-molecular picture of the events that may explain altered neuronal coding/retrieval, using computational frameworks such as reinforcement learning (in collaboration with UCL, DEEPMIND), and data analytical techniques for detecting molecular/neural patterns and sequences (in collaboration with RU), in particular for seizure prediction.
Supervisor Christophe Bernard with Viktor Jars
In collaboration with UCL, RU, ATLAS.
Mitsuyoshi Nakatani was recruited as M-GATE fellow for this project.