Learning intentional behavior in the K-model of the amygdala and entorhinal cortex with the cortico-hyppocampal formation
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.
amygdala entorhinal cortex kiv model phase transition spatial eeg