Tenth Annual Computational Neuroscience Meeting
San Francisco and Pacific Grove, California, June 30 - July 5, 2001
Complex nonlinear neural dynamics
Studying nonlinear, dynamical aspects of information processing and memory in biological and computational neural systems has attracted a lot of attention in recent years. This session aims at giving a forum to reserchers interested in this field introducing their results and discussing new developments in this area. The major questions addressed at this session will be:
- What evidence do we have that indicates that neurons, neural circuits or brain components have functionally meaningful complex nonlinear dynamic or chaotic activity ? How should we interpret these experimental results ?
- What is the role of noise in the operation of biological systems? How does noise contribute to the stability of complex nonlinear systems in biology and in computational models?
- What are the most promising approaches to the analysis of complex nonlinear dynamics in neural network models ? What spatio-temporal features indicate complex behavior? What new insights are provided by the analysis of lattices of coupled nonlinear maps ? Is symbolic dynamics the right conceptual framework to describe the dynamical macro-behavior of neural systems ?
- How does the chaotic dynamics analysed in the context of some neural network models correspond to the complex spatio-temporal dynamical effects observed in biological brains ? What are the established links between the two kinds of complex neural dynamics and what are the gaps that are waiting to be bridged ? Is it essential to have complex nonlinear dynamics in the neural system to perform computation or would it be more advantageous to do it without any chaos ? Is it possible that chaos is just a side effect from the point of view of neural computation ?
Organized by P. Andras, A. Assadi, R. Kozma, T. Wennekers and D. L. Demaris.
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