Literature DB >> 3843299

A computational model of hippocampal place fields.

D Zipser.   

Abstract

There are neurons in the hippocampus that become active only when an animal is near a particular location in a specific environment. The activity of some of these units is known to be governed by the configuration of a small set of discrete landmarks. In order to respond in this fashion, these neurons must, in effect, be able to recognize particular locations. A model of this recognition process is described which is able to make quantitative predictions about how the response of these place-field units varies as properties of the environmental landmarks are manipulated. Computer simulations of the model show that it is consistent with the available quantitative data. These simulations also predict large, characteristic changes in place-field location and size with manipulations of the environmental landmarks. Comparison of this kind of prediction with actual experiments will serve as a test of the validity of the model.

Mesh:

Year:  1985        PMID: 3843299     DOI: 10.1037//0735-7044.99.5.1006

Source DB:  PubMed          Journal:  Behav Neurosci        ISSN: 0735-7044            Impact factor:   1.912


  14 in total

1.  The involvement of recurrent connections in area CA3 in establishing the properties of place fields: a model.

Authors:  S Káli; P Dayan
Journal:  J Neurosci       Date:  2000-10-01       Impact factor: 6.167

2.  The temporal context model in spatial navigation and relational learning: toward a common explanation of medial temporal lobe function across domains.

Authors:  Marc W Howard; Mrigankka S Fotedar; Aditya V Datey; Michael E Hasselmo
Journal:  Psychol Rev       Date:  2005-01       Impact factor: 8.934

3.  New and distinct hippocampal place codes are generated in a new environment during septal inactivation.

Authors:  Mark P Brandon; Julie Koenig; Jill K Leutgeb; Stefan Leutgeb
Journal:  Neuron       Date:  2014-05-21       Impact factor: 17.173

Review 4.  Framing spatial cognition: neural representations of proximal and distal frames of reference and their roles in navigation.

Authors:  James J Knierim; Derek A Hamilton
Journal:  Physiol Rev       Date:  2011-10       Impact factor: 37.312

5.  Path integration and cognitive mapping in a continuous attractor neural network model.

Authors:  A Samsonovich; B L McNaughton
Journal:  J Neurosci       Date:  1997-08-01       Impact factor: 6.167

6.  Megamap: flexible representation of a large space embedded with nonspatial information by a hippocampal attractor network.

Authors:  Kathryn R Hedrick; Kechen Zhang
Journal:  J Neurophysiol       Date:  2016-05-18       Impact factor: 2.714

Review 7.  Neuronal vector coding in spatial cognition.

Authors:  Andrej Bicanski; Neil Burgess
Journal:  Nat Rev Neurosci       Date:  2020-08-06       Impact factor: 34.870

8.  Quantitative estimate of the information relayed by the Schaffer collaterals.

Authors:  A Treves
Journal:  J Comput Neurosci       Date:  1995-09       Impact factor: 1.621

9.  Conjoint control of hippocampal place cell firing by two visual stimuli. I. The effects of moving the stimuli on firing field positions.

Authors:  A A Fenton; G Csizmadia; R U Muller
Journal:  J Gen Physiol       Date:  2000-08       Impact factor: 4.086

10.  Spatial firing properties of hippocampal CA1 populations in an environment containing two visually identical regions.

Authors:  W E Skaggs; B L McNaughton
Journal:  J Neurosci       Date:  1998-10-15       Impact factor: 6.167

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