Research on Self-Organization

Our work in this area includes extending the Self-Organizing Map architecture (SOM; Kohonen, 1982; 1997; von der Malsburg, 1975) with lateral connections, hierarchies, sequential inputs, and growing network structures. This work has been done mainly with cognitive science and computational neuroscience applications in mind, as described in the visual cortex, concept and schema learning, episodic memory, and natural language processing pages. We have also applied such maps to character recognition, visualizing high-dimensional data, modeling multi-sensory integration, and speech recognition, as described below.

Our current research is supported in part by the NIMH Human Brain Project under grant 1R01-MH66991 (and previously by the National Science Foundation under grants IIS-9811478 and IRI-9309273). For more details, see publications in Self-Organization.

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Last update: 1.3 2002/04/27 06:10:04 risto