Mehdi Bayati, M.Sc.

Institut für Neuroinformatik
Ruhr-Universität Bochum
Universitätsstraße 150
Building NB, Room NB 3/70
D-44801 Bochum
Computational Neuroscience



As a Ph.D. student, I based my work on the CRISP theory, that is about the hippocampal function in episodic memory. We believe that episodic memory is represented and stored as a sequence of activity patterns in the hippocampus. I investigate the recurrent network structures that can generate robust spatiotemporal sequences and embed them into a hippocampal loop as a CA3 model. My work illustrates how essential it is to consider the whole hippocampal loop while investigating individual functional roles of the subregions.



I completed my M.Sc. degree in Physics at the IASBS (Institute for Advanced Studies in Basic Sciences). My thesis research was mainly focused on the effect of STDP learning rule on the structure and dynamics of the spiking recurrent neural networks.

Bayati, M., Valizadeh, A., Abbassian, A., & Cheng, S.. (2015). Self-organization of synchronous activity propagation in neuronal networks driven by local excitation. Frontiers in Computational Neuroscience, 9, 69.
Bayati, M., & Valizadeh, A. (2012). Effect of synaptic plasticity on the structure and dynamics of disordered networks of coupled neurons. Phys. Rev. E, 86(1), 011925.