".. a model of prefrontal cortex function emphasizing the influence of goal-related activity on the choice of the next motor output. ... Different neocortical minicolumns represent distinct sensory input states and distinct motor output actions. The dynamics of each minicolumn include separate phases of encoding and retrieval. During encoding, strengthening of excitatory connections forms forward and reverse associations between each state, the following action, and a subsequent state, which may include reward. During retrieval, activity spreads from reward states throughout the network. The interaction of this spreading activity with a specific input state directs selection of the next appropriate action. Simulations demonstrate how these mechanisms can guide performance in a range of goal directed tasks, and provide a functional framework for some of the neuronal responses previously observed in the medial prefrontal cortex during performance of spatial memory tasks in rats."
Model Type: Connectionist Network
Region(s) or Organism(s): Prefrontal cortex (PFC)
Model Concept(s): Simplified Models; Reinforcement Learning
Simulation Environment: MATLAB (web link to model)
Implementer(s): Hasselmo, Michael E [hasselmo at bu.edu]
References:
Hasselmo ME. (2005). A model of prefrontal cortical mechanisms for goal-directed behavior. Journal of cognitive neuroscience. 17 [PubMed]