Time Course of Changes in Brain Activity and Functional Connectivity Associated With Long-Term Adaptation to a Rotational Transformation
Bibliographic record
Abstract
The purpose of this study was to examine the time course of changes in cerebral activity and functional connectivity during long-term adaptation to a visuomotor transformation. Positron emission tomography was used to measure changes in brain activity as subjects tracked a target under the influence of a rotational transformation that distorted visual feedback. The experiment was 1 week long and consisted of two scanning sessions (obtained on days 2 and 7), aimed at examining early and late stages of learning. On average, visuomotor adaptation was achieved within 3 days. During early stages of adaptation, better performance was associated with greater activity in brain areas related to attention including bilateral dorso- and ventrolateral prefrontal cortices, frontal eye fields, and the human homologue of area MT. However, as adaptation proceeded, improvements in performance were associated with greater activity in motor regions such as the left (contralateral) sensorimotor cortex, bilateral anterior cerebellum, left cingulate motor area, right putamen, and a nonmotor region within the middle temporal gyrus. This learning-specific shift in brain activity was associated with a progressive change in the functional connectivity of these regions toward the end of the first session. Interestingly, only the functional connections between the anterior cerebellum, left middle temporal gyrus, and left sensorimotor cortex remained strong once visuomotor adaptation was achieved. Our findings suggest that visuomotor adaptation is not only reflected in persistent changes in activity in motor-related regions, but also in the strengthening and maintenance of specific functional connections.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.000 |
| 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".