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.
The CRISP theory suggests that episodic memories are best represented by neuronal sequences and specific mechanisms by which sequences are stored and retrieved from the hippocampal circuit. Using neural network models, we investigate under which conditions the hippocampal circuit can perform the hypothesized functions reliably and robustly.
The Institut für Neuroinformatik (INI) is a central research unit of the Ruhr-Universität Bochum. We aim to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory systems and while acting in those environments through effector systems. Inspired by our insights into such natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental approaches from psychology and neurophysiology as well as theoretical approaches from physics, mathematics, electrical engineering and applied computer science, in particular machine learning, artificial intelligence, and computer vision.
Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, Germany
Tel: (+49) 234 32-28967
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