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The cerebral cortex, the brain's outermost layer, is pivotal in processing complex cognitive tasks, emotions, and various sensory inputs and executing voluntary motor activities. This intricate structure is divided into three primary functional areas: the motor areas, sensory areas, and association areas.
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Related Experiment Video

Updated: Feb 10, 2026

Stimulating the Lip Motor Cortex with Transcranial Magnetic Stimulation
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Neural modes in motor cortex cycle over fast timescales.

Stephen E Clarke, Elizabeth Jun, Paul Nuyujukian

    Biorxiv : the Preprint Server for Biology
    |February 9, 2026
    PubMed
    Summary

    Neural population activity exhibits fast switches and slow drift, impacting motor learning and recovery. Understanding these dynamics is key to brain function and repair.

    Area of Science:

    • Systems Neuroscience
    • Computational Neuroscience
    • Motor Control

    Background:

    • Low-dimensional latent states are embedded in neural population activity.
    • Individual neuron activity changes over time, but population-level dynamics on short timescales are less understood.
    • Adaptation during learning or after injury requires rapid network changes.

    Purpose of the Study:

    • Investigate changes in coordinated neuron population activity on short timescales.
    • Determine if fast and slow drift timescales share common physiological mechanisms.
    • Explore the relationship between neural drift and behavioral performance.

    Main Methods:

    • Tracked individual neuron contributions to population state dimensions in motor cortex during reaching tasks.

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  • Analyzed changes in encoding patterns over short blocks of repeated trials.
  • Applied causal perturbation (electrical current) to motor cortex to induce drift.
  • Main Results:

    • Distinct encoding patterns were fewer than typical motor cortex dimensionality.
    • Population state space and dynamics were conserved, but encoding patterns showed fast switches and slow modifications.
    • Electrical perturbation induced drift on both fast and slow timescales.
    • Increased slow drift correlated with decreased behavioral performance, while fast switches did not.

    Conclusions:

    • Revealed an additional timescale of drift in correlated population activity.
    • Suggests distinct mechanisms for fast and slow drift.
    • Highlights the importance of slow drift for maintaining behavioral performance.
    • Provides insights into neural mechanisms for structure maintenance, relearning, and recovery.