Bayesian Modeling of Cerebral Information Processing

International audience; Modeling explicitly the links between cognitive functions and networks of cerebral areas is necessitated both by the understanding of the clinical outcomes of brain lesions and by the interpretation of activation data provided by functional neuroimaging techniques. At this global level of representation, the human brain can be best modeled by a probabilistic functional causal network. Our modeling approach is based on the anatomical connection pattern, the information processing within cerebral areas and the causal influences that connected regions exert on each other. The information processing within a region is implemented by a causal network of functional primitives that are the interpretation of integrated biological properties. This explicit modeling approach allows the formulation and the simulation of functional and physiological assumptions.