FG 868: TP A3 Dynamical complex network approaches of the analysis and modeling of large scale brain activities during cognitive processes

We propose to study neural network foundations of cognitive processes. This will be done by analyzing and modeling large-scale event-related brain responses (ERP) using the principles of nonlinear dynamical complex networks, and by fusioning of electrophysiological and structural neuroimaging data. In a close collaboration between the expertise from dynamical complex network analysis and modeling [Group of Nonlinear Dynamics Humboldt-Universität zu Berlin], biological psychology [Department of Psychology, Humboldt-Universität zu Berlin], and signal- and information processing in the neurosciences [Department of Computer Science, Humboldt-Universität zu Berlin], we will pursue the following goals:
(i) Obtain high-resolution ERP data from psychological experiments with well-defined cognitive processes that are relevant for reading and (as benchmark) face processing.
(ii) Extract functional and effective (causal) connectivity in sensor and source spaces to monitor the successive cognitive subprocesses of the brain activity during cognition. The analysis of these large-scale brain networks will be performed by advanced tools based on the concept of hierarchical complex networks to characterise the time evolving connectivity associated with different experimental conditions.
(iii) Develop biophysical complex dynamical network models that can account for ERP-like activity, representing the activation of brain regions involved in the processes under study. The coupling parameters of such a model will allow us to identify the causal connectivity in the processing stream
In order to improve the analysis and the modeling, we will: (a) obtain structural MRT of the participants to be used in accurate source localisation of the brain activity, and (b) estimate structural networks of the brains of the participants, using diffusion imaging such us DTI and/or HARDI or DSI and sufficient tractography methods to integrate the structural connectivity information into the network modeling.

Sommer, Werner Prof. Dr. rer. soc. habil. (Details) (Forschergruppen)

DFG: Forschergruppen

Projektstart: 01/2011
Projektende: 12/2014

Zuletzt aktualisiert 2020-11-03 um 23:13