Computational model of the entorhinal-hippocampal region derived from a single principle

Andras Lorincz, Gyorgy Buzsaki

Research output: Contribution to conferencePaper

1 Citation (Scopus)

Abstract

Several properties of highly elaborate structure of the entorhinal cortex-hippocampus (EC-HC) loop can be explained using the single principle that to recall past and to foresee future events a predictive structure is necessary. Prediction based on information emerging from a high dimensional sensory system becomes less demanding if the processed sensory information can be separated into components that evolve independently. Networks that develop independent components (IC) in an efficient manner can be built from two stages. The stages were identified with the CA3 AND CA1 layers of the HC. The forming of ICs requires nonlinear operation, whereas IC outputs arise under linear operation and thus two-phase operation follows.

Original languageEnglish
Pages58-63
Number of pages6
Publication statusPublished - Dec 1 1999
EventInternational Joint Conference on Neural Networks (IJCNN'99) - Washington, DC, USA
Duration: Jul 10 1999Jul 16 1999

Other

OtherInternational Joint Conference on Neural Networks (IJCNN'99)
CityWashington, DC, USA
Period7/10/997/16/99

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

Cite this

Lorincz, A., & Buzsaki, G. (1999). Computational model of the entorhinal-hippocampal region derived from a single principle. 58-63. Paper presented at International Joint Conference on Neural Networks (IJCNN'99), Washington, DC, USA, .