I am a computational & theoretical neuroscientist with a focus on cortical computation and large scale neural data analyses. My work lies at the intersection of neuroscience, computation and physics. In my research, I combine computational/theoretical studies with multiscale high-throughput experimental data to formalize a global theory of multiscale state-dependent cortical computation. My objective is to understand the computational foundations of neural information processing in the cortex and use these insights in designing novel neuro-inspired computation, neuroprosthetics and pattern recognition algorithms.
My research track encompasses interconnected frontiers: i) investigating the nature of state-dependent collective information processing ranging from macroscopic/mesoscopic scale dynamics (Spatiotemporal characteristics of large scale oscillations), ii) understanding ensemble pattern formation at mesoscopic/microcircuitry scale (Spatiotemporal orchestration of local field potential and spiking ensembles patterns) iii) to bridge across these computational scales, I study the physical nature of the measured signals at multiple scale (MEG, EEG, Electrocorticogram, Local field potential, Spiking) and their underlying biophysical constitutes (Biophysical links across these scales of observation).
Neuroimaging, Neurophysiology & Bioelectromagnetism.
Fundamentals of Neural Computation: Network dynamics & Neural rhythmicity.
Intelligence: Artificial Intelligence & Neuro-Inspired Intelligent systems.
Neuroengineering/Translational: Neuroprosthetics, Anticipatory neuro-devices & Neurodiagnostic tools.