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Spatial Learning and Action Planning in a Prefrontal Cortical Network Model
 

Summary: Spatial Learning and Action Planning in a Prefrontal
Cortical Network Model
Louis-Emmanuel Martinet, Denis Sheynikhovich, Karim Benchenane, Angelo Arleo*
Laboratory of Neurobiology of Adaptive Processes, UMR 7102, CNRS - UPMC Univ P6, Paris, France
Abstract
The interplay between hippocampus and prefrontal cortex (PFC) is fundamental to spatial cognition. Complementing
hippocampal place coding, prefrontal representations provide more abstract and hierarchically organized memories
suitable for decision making. We model a prefrontal network mediating distributed information processing for spatial
learning and action planning. Specific connectivity and synaptic adaptation principles shape the recurrent dynamics of the
network arranged in cortical minicolumns. We show how the PFC columnar organization is suitable for learning sparse
topological-metrical representations from redundant hippocampal inputs. The recurrent nature of the network supports
multilevel spatial processing, allowing structural features of the environment to be encoded. An activation diffusion
mechanism spreads the neural activity through the column population leading to trajectory planning. The model provides a
functional framework for interpreting the activity of PFC neurons recorded during navigation tasks. We illustrate the link
from single unit activity to behavioral responses. The results suggest plausible neural mechanisms subserving the cognitive
``insight'' capability originally attributed to rodents by Tolman & Honzik. Our time course analysis of neural responses shows
how the interaction between hippocampus and PFC can yield the encoding of manifold information pertinent to spatial
planning, including prospective coding and distance-to-goal correlates.
Citation: Martinet L-E, Sheynikhovich D, Benchenane K, Arleo A (2011) Spatial Learning and Action Planning in a Prefrontal Cortical Network Model. PLoS Comput
Biol 7(5): e1002045. doi:10.1371/journal.pcbi.1002045

  

Source: Arleo, Angelo - Laboratory of Neurobiology of Adaptive Processes, Université Pierre-et-Marie-Curie, Paris 6

 

Collections: Biology and Medicine