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Self-organising continuous attractor networks with multiple activity packets, and the representation of space.

Abstract:

'Continuous attractor' neural networks can maintain a localised packet of neuronal activity representing the current state of an agent in a continuous space without external sensory input. In applications such as the representation of head direction or location in the environment, only one packet of activity is needed. For some spatial computations a number of different locations, each with its own features, must be held in memory. We extend previous approaches to continuous attractor network...

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Publication status:
Published

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Institution:
University of Oxford
Division:
MSD
Department:
Experimental Psychology
Role:
Author
Journal:
Neural networks : the official journal of the International Neural Network Society
Volume:
17
Issue:
1
Pages:
5-27
Publication date:
2004-01-01
DOI:
EISSN:
1879-2782
ISSN:
0893-6080
Source identifiers:
15473
Language:
English
Keywords:
Pubs id:
pubs:15473
UUID:
uuid:370f41c3-ea2e-45ae-8afb-d83e8209b4e1
Local pid:
pubs:15473
Deposit date:
2012-12-19

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