SimBa: a fuzzy similarity-based modelling framework for large-scale cerebral networks

Authors:
Julien Erny;Josette Pastor;Henri Prade
Affiliations:
Inserm, Toulouse, France and Université Toulouse III Paul Sabatier, Toulouse, France and CNRS, IRIT, Toulouse, France;Inserm, Toulouse, France and Université Toulouse III Paul Sabatier, Toulouse, France;CNRS, IRIT, Toulouse, France
Venue:
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Year:
2007

Citing 5
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A Similarity and Fuzzy Logic-Based Approach to Cerebral Categorisation

Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Cerebral modeling and dynamic Bayesian networks

Artificial Intelligence in Medicine

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Abstract

Motivated by a better understanding of cerebral information processing, a lot of work has been done recently in bringing together connectionist numerical models and symbolic cognitive frameworks, allowing for a better modelling of some cerebral mechanisms. However, a gap still exists between models that describe functionally small neural populations and cognitive architectures that are used to predict cerebral activity. The model presented here tries to fill partly this gap. It uses existing knowledge of the brain structure to describe neuroimaging data in terms of interacting functional units. Its merits rely on an explicit handling of neural populations proximity in the brain, relating it to similarity between the pieces of information processed.