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Independent rate and temporal coding in hippocampal pyramidal cells

Author

Listed:
  • John Huxter

    (University College London
    University of Bristol)

  • Neil Burgess

    (University College London
    Institute of Cognitive Neuroscience, University College London)

  • John O'Keefe

    (University College London
    Institute of Cognitive Neuroscience, University College London)

Abstract

In the brain, hippocampal pyramidal cells use temporal1 as well as rate2 coding to signal spatial aspects of the animal's environment or behaviour. The temporal code takes the form of a phase relationship to the concurrent cycle of the hippocampal electroencephalogram theta rhythm1. These two codes could each represent a different variable3,4. However, this requires the rate and phase to vary independently, in contrast to recent suggestions5,6 that they are tightly coupled, both reflecting the amplitude of the cell's input. Here we show that the time of firing and firing rate are dissociable, and can represent two independent variables: respectively the animal's location within the place field, and its speed of movement through the field. Independent encoding of location together with actions and stimuli occurring there may help to explain the dual roles of the hippocampus in spatial and episodic memory7,8, or may indicate a more general role of the hippocampus in relational/declarative memory9,10.

Suggested Citation

  • John Huxter & Neil Burgess & John O'Keefe, 2003. "Independent rate and temporal coding in hippocampal pyramidal cells," Nature, Nature, vol. 425(6960), pages 828-832, October.
    • Handle: RePEc:nat:nature:v:425:y:2003:i:6960:d:10.1038_nature02058
    DOI: 10.1038/nature02058
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    Cited by:

    1. Upadhyay, Ranjit Kumar & Mondal, Argha, 2017. "Synchronization of bursting neurons with a slowly varying d. c. current," Chaos, Solitons & Fractals, Elsevier, vol. 99(C), pages 195-208.
    2. Eric Reifenstein & Martin Stemmler & Andreas V M Herz & Richard Kempter & Susanne Schreiber, 2014. "Movement Dependence and Layer Specificity of Entorhinal Phase Precession in Two-Dimensional Environments," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-11, June.
    3. Gross, Eitan, 2015. "Classification error analysis in stereo vision," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 430(C), pages 1-10.
    4. Sara Mahallati & James C Bezdek & Milos R Popovic & Taufik A Valiante, 2019. "Cluster tendency assessment in neuronal spike data," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-29, November.

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