Information processing in large-scale cerebral networks: the causal connectivity approach |
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Authors: | Josette Pastor Marc Lafon Louise Travé-Massuyès Jean-François Démonet Bernard Doyon Pierre Celsis |
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Institution: | (1) INSERM U455, Services de Neurologie, CHU Purpan, F-31059 Toulouse Cedex 3, France, FR;(2) LAAS/CNRS, 7 Avenue du Colonel Roche, F-31077 Toulouse Cedex 4, France, FR |
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Abstract: | Today, cognitive functions are considered to be the offspring of the activity of large-scale networks of functionally interconnected
cerebral regions. The interpretation of cerebral activation data provided by functional imaging has therefore recently moved
to the search for the effective connectivity of activated regions, which aims at understanding the role of anatomical links
in the activation propagation. Our assumption is that only causal connectivity can offer a real understanding of the links
between brain and mind. Causal connectivity is based on the anatomical connection pattern, the information processing within
cerebral regions and the causal influences that connected regions exert on each other. In our approach, the information processing
within a region is implemented by a causal network of functional primitives, which are the interpretation of integrated biological
properties. Our choice of a qualitative representation of information reflects the fact that cerebral activation data are
only the approximate view, provided by imaging techniques, of the real cerebral activity. This explicit modeling approach
allows the formulation and the simulation of functional and physiological assumptions about activation data. Two alternative
models explaining results of the striate cortex activation described by Fox and Raichle (Fox PT, Raichle ME (1984) J. Neurophysiol
51:1109–1120; Fox PT, Raichle ME (1985) Ann Neurol 17:303–305) are provided as an example of our approach.
Received: 22 December 1998 / Accepted in revised form: 23 June 1999 |
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