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Conference paper, 2002

Regulating Cortical Neurodynamics for Past, Present and Future

Liljenström, Hans


Behaving systems, biological as well as artificial, need to respond quickly and accurately to changes in the environment. The response is dependent on stored memories, and novel situations should be learnt for the guidance of future behavior. A highly nonlinear system dynamics is required in order to cope with a complex and changing environment, and this dynamics should be regulated to match the demands of the current situation, and to predict future behavior. In many cases the dynamics should be regulated to minimize processing time. We use computer simulations of cortical structures in order to investigate how the neurodynamics of these systems can be regulated for optimal performance in an unknown and changing environment. In particular, we study how cortical oscillations can serve to amplify weak signals and sustain an input pattern for more accurate information processing, and how chaotic-like behavior could increase the sensitivity in initial, exploratory states. We mimic regulating mechanisms based on neuromodulators, intrinsic noise levels, and various synchronizing effects. We find optimal noise levels where system performance is maximized, and neuromodulatory strategies for an efficient pattern recognition, where the anticipatory state of the system plays an important role


Neural networks; olfaction; associative memory; neuromodulation; evolution

Published in

AIP Conference Proceedings
2002, volume: 627
ISBN: 0-7354-0081-4
Publisher: American Institute of Physics


CASYS 2001 - Fifth International Conference of Compting Anticipatory Systems

Authors' information

Swedish University of Agricultural Sciences, Department of Energy and Technology

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