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Juan A Gallego1,2,3, Matthew G Perich4, Raeed H Chowdhury5

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Neural latent dynamics remain stable over time, enabling consistent learned behaviors despite neuron turnover. This stability in the cortex is key for reliable motor control and execution of learned tasks.

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Area of Science:

  • Neuroscience
  • Systems Neuroscience
  • Motor Control

Background:

  • Learned behaviors are executed consistently over long periods.
  • The neural basis for this long-term stability in cortical processing remains unclear.
  • Understanding neural stability is crucial for explaining consistent behavioral execution.

Purpose of the Study:

  • To investigate the hypothesis that stable neural latent dynamics underlie consistent motor control.
  • To determine if the low-dimensional latent activity in the cortex is preserved over time.
  • To explore the relationship between neural dynamics stability and behavioral consistency.

Main Methods:

  • Recorded neural activity from populations of neurons in premotor, primary motor, and somatosensory cortices in monkeys.
  • Monitored neural activity during a reaching task for up to two years.
  • Analyzed the stability of low-dimensional latent dynamics within neural population activity.

Main Results:

  • Neural latent dynamics were found to be stable over the two-year recording period.
  • Despite significant turnover in individual neurons, the overall population dynamics remained consistent.
  • Stable latent dynamics enabled reliable decoding of behavioral features over time.
  • Decoders based on raw neural activity degraded significantly over the same period.

Conclusions:

  • Stable low-dimensional latent cortical dynamics are fundamental for consistent execution of learned behaviors.
  • The preservation of latent dynamics, rather than individual neurons, supports long-term behavioral stability.
  • This finding offers a new perspective on how the cortex achieves stable motor control.