# Characterizing and modulating motor cortical dynamics underlying rapid sequence learning in primates

> **NIH NIH F31** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2023 · $39,574

## Abstract

PROJECT SUMMARY
A fundamentally important question is how the nervous system converges on optimal solutions during the
process of motor learning. A growing body of evidence in humans has remarkably demonstrated the presence
of micro-offline gains (MOGs), or significant “offline” performance gains after a brief rest period (~10 second),
during motor sequence learning, which diminish as a fast and reliable performance is consolidated.
Magnetoencephalography (MEG) recordings have linked this rapid form of consolidation to 13-30 Hz oscillations
in field potentials (β, beta) and replay of broad-band field potential patterns across the motor cortex, particularly
the primary motor cortex (M1) – an area essential to the execution and learning of motor skills. However, it
remains unclear how high-resolution spiking signals in M1 are reflected in reactivations of spatially broad MEG
signals and how offline β may support consolidation. Moreover, it is unclear if such micro-offline processing is
causal to rapid behavioral modifications.
Here, we use a novel sequential reach task for non-human primates (NHPs) that reliably elicits MOGs, combined
with LFP and neuronal spiking recordings in motor cortex, to probe how the primate motor cortex enables rapid
sequence learning. Our preliminary data shows that task-active neuronal ensembles in M1 are reactivated during
short breaks, particularly in early learning when MOGs are highest. In contrast, offline β is highest during later
breaks and is inversely correlated with MOGs. Together, these results motivate our overall hypothesis that
micro-offline reactivation of task-active spiking patterns promotes rapid learning, and as behavior is
optimized, offline β increases to promote stability of learned neural activity patterns.
To test this hypothesis, we use an interdisciplinary approach of high-speed reach and gaze tracking, precise
neural recordings, computational modeling, and causal manipulations. In Aim 1, we will assess whether
reactivations of task-active ensembles during brief rest periods correlate with rapid behavioral modifications. In
Aim 2, we will quantify the relationship between offline β-coherent spiking patterns and changes in online spiking
dynamics. Finally, in Aim 3, we will use 20 Hz alternating current stimulation (ACS) to causally determine the
role of offline β in regulating rapid consolidation and behavioral stability. Together, these experiments will further
our understanding of how the primate cortex enables adaptive behavioral modifications on short timescales and
lay a strong foundation for stimulation-based interventions for pathological conditions of behavioral and cognitive
rigidity, such as Parkinson’s disease, obsessive-compulsive disorder, and depression.

## Key facts

- **NIH application ID:** 10677450
- **Project number:** 1F31NS132428-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Sandon Montgomery Griffin
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $39,574
- **Award type:** 1
- **Project period:** 2023-05-01 → 2024-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10677450

## Citation

> US National Institutes of Health, RePORTER application 10677450, Characterizing and modulating motor cortical dynamics underlying rapid sequence learning in primates (1F31NS132428-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10677450. Licensed CC0.

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