A Theory of How Columns in the Neocortex Enable Learning the Structure of the World.

ABSTRACT: Neocortical regions are organized into columns and layers. Connections between layers run mostly perpendicular to the surface suggesting a columnar functional organization. Some layers have long-range excitatory lateral connections suggesting interactions between columns. Similar patterns of connectivity exist in all regions but their exact role remain a mystery. In this paper, we propose a network model composed of columns and layers that performs robust object learning and recognition. Each column integrates its changing input over time to learn complete predictive models of observed objects. Excitatory lateral connections across columns allow the network to more rapidly infer objects based on the partial knowledge of adjacent columns. Because columns integrate input over time and space,

SUBMITTER: Hawkins J 

PROVIDER: S-EPMC5661005 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature