Learning intentional behavior in the K-model of the amygdala and entorhinal cortex with the cortico-hyppocampal formation

Authors:
Robert Kozma;Derek Wong;Murat Demirer;Walter J. Freeman
Affiliations:
Division of Computer Science, FedEx Institute of Technology, The University of Memphis, 373 Dunn Hall, Memphis, TN 38152, USA;Division of Computer Science, FedEx Institute of Technology, The University of Memphis, 373 Dunn Hall, Memphis, TN 38152, USA;Department of Biomedical Engineering, The University of Memphis, Memphis, TN 38152, USA;Division of Neurobiology, 101 Donner Hall, University of California at Berkeley, Berkeley, CA 94720, USA
Venue:
Neurocomputing
Year:
2005

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Abstract

The interaction between entorhinal cortex (EC), amygdala, and hippocampal and cortical areas in vertebrate brains is studied using the dynamical K model approach. Special emphasis is given to the role of EC in decision making under the influence of sensory, orientation, and motivational clues. We introduce a simplified KIV model with positive and negative reinforcement learning in the hippocampus and the cortex. The developed model is implemented in a 2D computational environment for multi-sensory control of the movement of a simulated animal. Our results support the interpretation of recent EEG measurements with instantaneous macroscopic phase transitions.