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Computational study on the neural mechanism of sequential pattern memory

M Morita1

  • 1Institute of Information Sciences and Electronics, University of Tsukuba, Ibaraki, Japan. mor@is.tsukuba.ac.jp

Brain Research. Cognitive Brain Research
|December 1, 1996
PubMed
Summary

This study presents a neural network model for stable long-term storage and noise-tolerant recall of temporal sequences, like motor skills and melodies. The findings suggest a general principle applicable to brain memory systems.

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Cognitive Science

Background:

  • The brain effectively stores diverse temporal sequences as long-term memories, including motor sequences, episodes, and melodies.
  • Understanding the general principles governing the storage and retrieval of these sequential memories is crucial for advancing neuroscience and artificial intelligence.

Purpose of the Study:

  • To clarify the general principle underlying the brain's storage of temporal sequences.
  • To propose and examine a computational theory and neural network model for sequential pattern memory.

Main Methods:

  • Examined sequential pattern memory mechanisms using computational theory and neural network modeling.
  • Developed a neural network model comprising pairs of excitatory and inhibitory cells with recurrent connections.

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  • Utilized a learning algorithm based on the covariance rule for storage, requiring multiple sequence inputs.

    • Main Results:

    • The proposed neural network model stably stores gradually varying spatio-temporal patterns.
    • The network architecture, featuring excitatory-inhibitory cell pairs, exhibits non-monotonic input-output characteristics essential for smooth sequential recall.
    • The storage mechanism is robust, requiring only a few repetitions of the sequence, and retrieval demonstrates high tolerance to noise.

    Conclusions:

    • A simple and effective principle for sequential pattern memory has been presented, applicable to neural network models.
    • The study suggests that similar principles may underlie memory systems in the brain.
    • Potential roles for the hippocampus and basal ganglia in memorizing sequences are proposed, warranting further investigation.