Spatially Distinct Beta-Band Activities Reflect Implicit Sensorimotor Adaptation and Explicit Re-aiming Strategy
Bibliographic record
Abstract
Previous research suggests that so-called implicit and explicit processes of motor adaptation are implemented by distinct neural structures. Here we tested whether implicit sensorimotor adaptation and strategic re-aiming used to reduce movement error are reflected by spatially distinct EEG oscillatory components. We analyzed beta-band oscillations (∼13–30 Hz), which have long been linked to sensorimotor functions, at the time when these adaptive processes intervene for movement planning. We hypothesized that beta-band activity within sensorimotor regions relates to implicit adaptive processes, whereas beta-band activity within medial motor areas reflects deliberate re-aiming. In female and male human volunteers, we recorded EEG in a motor adaptation task in which a visual rotation was introduced in short series of trials separated by unperturbed trials. Participants were instructed in advance about the nature of the visual perturbation and trained to counter it by strategically re-aiming at a neighboring target. Consistent with our hypothesis, we found that preparatory beta-band activities within the two regions exhibited different patterns of modulation. Beta power in lateral central regions was attenuated when a change in the visual condition rendered internal-model predictions uncertain. In contrast, beta power in medial frontal regions was selectively decreased when participants strategically re-aimed their reaches. We propose that the reduction in lateral central beta power reflects an increased weighting of peripheral sensory information implicitly triggered when an adaptive change in the sensorimotor mapping is required, whereas the reduction in medial frontal beta-band activity relates to the inhibition of automatic motor responses in favor of cognitively controlled movements. SIGNIFICANCE STATEMENT Behavioral and modeling studies have proposed that so-called implicit and explicit components of motor adaptation recruit different neural circuits. Here, we investigated whether these different processes are reflected by spatially distinct beta-band activities. Analyzing EEG signals at the time they influence movement planning, during the foreperiod, we found that beta power within lateral central regions was decreased when a change in visual conditions required implicit sensorimotor remapping, which may reflect enhanced sensory processing when internal-model predictions are rendered uncertain. In contrast, beta-band power within medial frontal areas was selectively attenuated when participants deliberately re-aimed their movements to improve task performance, which may be associated with the inhibition of automatic motor responses in favor of cognitively controlled movements.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".