Purposive behavior and cognitive mapping: a neural network model.

Published

Journal Article

This study presents a real-time, biologically plausible neural network approach to purposive behavior and cognitive mapping. The system is composed of (a) an action system, consisting of a goal-seeking neural mechanism controlled by a motivational system; and (b) a cognitive system, involving a neural cognitive map. The goal-seeking mechanism displays exploratory behavior until either (a) the goal is found or (b) an adequate prediction of the goal is generated. The cognitive map built by the network is a topological map, i.e., it represents only the adjacency, but not distances or directions, between places. The network has recurrent and non-recurrent properties that allow the reading of the cognitive map without modifying it. Two types of predictions are introduced: fast-time and real-time predictions. Fast-time predictions are produced in advance of what occurs in real time, when the information stored in the cognitive map is used to predict the remote future. Real-time predictions are generated simultaneously with the occurrence of environmental events, when the information stored in the cognitive map is being updated. Computer simulations show that the network successfully describes latent learning and detour behavior in rats. In addition, simulations demonstrate that the network can be applied to problem-solving paradigms such as the Tower of Hanoi puzzle.

Full Text

Cited Authors

  • Schmajuk, NA; Thieme, AD

Published Date

  • January 1, 1992

Published In

Volume / Issue

  • 67 / 2

Start / End Page

  • 165 - 174

PubMed ID

  • 1627685

Pubmed Central ID

  • 1627685

Electronic International Standard Serial Number (EISSN)

  • 1432-0770

International Standard Serial Number (ISSN)

  • 0340-1200

Digital Object Identifier (DOI)

  • 10.1007/bf00201023

Language

  • eng