In the brain, unlike conventional computers, cognitive processes like memory and perception are tightly interlinked with their physical substrate. Understanding the biophysical mechanisms and the morphological/ anatomical structure behind the repertoire of dynamical phenomena the nervous system generates is therefore an essential part for understanding brain function in general. We gain insight into the material basis of cognition by developing biophysically highly realistic computer models. These models are based upon electrophysiological measurements and morphological reconstructions obtained from isolated cortical neurons and synapses probed 'in a dish' (in brain slices, in vitro). At the same time, in collaboration with other groups we analyze spatio-temporal patterns within electrophysiological recordings from behaving animals (Prof. Seamans, UBC, Vancouver) and neuroimaging data from humans (Prof. Meyer-Lindenberg, CIMH Mannheim) using advanced data analysis techniques based on nonlinear dynamics and multivariate statistics, and relate these observations to the behavior of the simulated models. Hence, using physiologically detailed modeling approaches, we are trying to span the bridge from the biophysical properties of single neurons and synapses via the dynamics of neural networks as observed in vivo to behavioral and computational properties of the brain. More see here!
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