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Related Experiment Videos

Place from time: Reconstructing position from a distributed representation of temporal context.

Marc W Howard1, Vaidehi S Natu

  • 1Department of Psychology, Syracuse University, 430 Huntington Hall, Syracuse, NY 13244-2340, USA. marc@memory.syr.edu

Neural Networks : the Official Journal of the International Neural Network Society
|October 4, 2005
PubMed
Summary

The temporal context model (TCM) explains memory recall and spatial navigation. A new study shows that temporal context can generate accurate spatial representations, even with limited cells, reconciling entorhinal cortex and hippocampal function.

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Area of Science:

  • Neuroscience
  • Cognitive Psychology
  • Computational Neuroscience

Background:

  • The temporal context model (TCM) explains recency and associative effects in episodic recall.
  • Episodic recall and spatial coding rely on the medial temporal lobe.
  • TCM's leaky integrator can model ventromedial entorhinal cortex cell activity during navigation.

Purpose of the Study:

  • To investigate if temporal context representations can support accurate spatial coding.
  • To reconcile the noisy spatial representations in the entorhinal cortex with the precise place code in the hippocampus.

Main Methods:

  • Simulated a leaky integrator model of temporal context with velocity input.
  • Extracted spatial representations from simulated temporal context cell populations.

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  • Analyzed the number of cells required for accurate spatial representation.

    • Main Results:

    • Temporal context representations can generate noisy place cells, consistent with entorhinal cortex recordings.
    • As few as eight temporal context cells can yield a reasonably accurate spatial representation.
    • The spatial precision of hippocampal place cells is not inconsistent with entorhinal temporal-spatial context input.

    Conclusions:

    • Temporal context provides a viable mechanism for spatial representation in the brain.
    • The findings suggest a unified account of medial temporal lobe function across memory and navigation.
    • This work bridges computational models of memory with neural recordings of spatial navigation.