BDNF Val66Met polymorphism is associated with abnormal interhemispheric transfer of a newly acquired motor skill
Bibliographic record
Abstract
Recent data suggest that the Val66Met polymorphism of the brain-derived neurotrophic factor (BDNF) gene can alter cortical plasticity within the motor cortex of carriers, which exhibits abnormally low rates of cortical reorganization after repetitive motor tasks. To verify whether long-term retention of a motor skill is also modulated by the presence of the polymorphism, 20 participants (10 Val66Val, 10 Val66Met) were tested twice at a 1-wk interval. During each visit, excitability of the motor cortex was measured by transcranial magnetic stimulations (TMS) before and after performance of a procedural motor learning task (serial reaction time task) designed to study sequence-specific learning of the right hand and sequence-specific transfer from the right to the left hand. Behavioral results showed a motor learning effect that persisted for at least a week and task-related increases in corticospinal excitability identical for both sessions and without distinction for genetic group. Sequence-specific transfer of the motor skill from the right hand to the left hand was greater in session 2 than in session 1 only in the Val66Met genetic group. Further analysis revealed that the sequence-specific transfer occurred equally at both sessions in the Val66Val genotype group. In the Val66Met genotype group, sequence-specific transfer did not occur at session 1 but did at session 2. These data suggest a limited impact of Val66Met polymorphism on the learning and retention of a complex motor skill and its associated changes in corticospinal excitability over time, and a possible modulation of the interhemispheric transfer of procedural learning.
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) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".