Attractor-map versus autoassociation based attractor dynamics in the hippocampal network.

ABSTRACT: The autoassociative memory model of hippocampal field CA3 postulates that Hebbian associations among external input features produce attractor states embedded in a recurrent synaptic matrix. In contrast, the attractor-map model postulates that a two-dimensional continuum of attractor states is preconfigured in the network during development and that transitions among these states are governed primarily by self-motion information ("path-integration"), giving rise to the strong spatial characteristic of hippocampal activity. In this model, learned associations between "coordinates" on the attractor map and external cues can result in abrupt jumps between states, in the case of mismatches between the current input and previous associations between internal coordinates and external landmarks.

SUBMITTER: Colgin LL 

PROVIDER: S-EPMC2904215 | biostudies-literature | 2010 Jul

REPOSITORIES: biostudies-literature