Behaviorally relevant cell ensembles in rat motor cortex are replayed during sleep and implicate hippocampal involvement in motor skill learning
Bibliographic record
Abstract
Abstract Motor memory is essential for our daily activities. It involves complex neural processes during learning and sleep. However, unlike explicit memory where its neural activation and role in memory consolidation are well-studied, the properties of cell ensembles for motor memory are less understood. In this study, we re-examined rats’ behavior and neural activity in the primary motor cortex (M1) and hippocampus while the animals were trained daily on a single-pellet reaching task. Recordings included both the training and 3 hr rest epochs before and after training. Behaviorally, the animals were classified into two learning types: rapid and gradual learners. Unsupervised cell ensemble detection on M1 neurons revealed that about 60% of the ensembles were modulated during reaching behavior. Those reach-related ensembles were further categorized into four types, and their replay was detected during both slow-wave sleep (SWS) and REM sleep. In SWS, replay preferentially occurred during spindles, especially slow-oscillation coupled spindles (SO-spindles). In addition, about 30% of the reach-related cell ensembles were modulated during the hippocampal sharp-wave ripples (SWRs). The direction of modulation and the temporal coupling between SWRs and SO-spindles depended on the training phase and the animals’ learning types. Our results demonstrate the replay of rats’ skilled-reaching memory during SWS and REM sleep and the possible involvement of the hippocampus through the modulation of M1 activations during SWRs. This study will advance our understanding of how neural activity patterns evolve during skilled-reaching learning and sleep, and help develop medical applications that leverage sleep’s memory functions. Significance Statement Most evidence for memory replay comes from hippocampal studies in which neural activity during rest is compared to a template constructed from activity recorded during a behavioral task. Here, we used an unsupervised ensemble detection on recordings from rat primary motor cortex (M1) that included both rest and a skilled reaching task. We discovered a variety of ensembles with different sizes and time scales. Many were related to reaching behavior and were replayed during sleep. Some M1 ensembles were also modulated by the hippocampal activity, suggesting their involvement in motor skill learning. This study will advance our understanding of motor memory and sleep and help develop medical applications that leverage sleep’s memory functions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".