Long-Term Effects of Concussions on Psychomotor Speed and Cognitive Control Processes During Motor Sequence Learning
Bibliographic record
Abstract
Abstract. In asymptomatic multiple-concussion athletes, studies evidenced long-term impairments in psychomotor speed, motor sequence learning, and cognitive control processes, as indexed by the Error Negativity (Ne), also commonly referred to as the Error-related Negativity (ERN). In healthy controls, motor sequence learning during a Serial Reaction Time (SRT) task is associated with an increase in Ne/ERN amplitude. The objective of this paper is to investigate whether concussion effects on cognitive control are associated with sequence learning changes in asymptomatic multi-concussion athletes. Thirty-seven athletes (18 nonconcussed; 19 concussed) completed a SRT task during which continuous electroencephalographic (EEG) activity was recorded. Ne/ERN amplitude modulation from early to late learning blocks of the task was measured. Median reaction times (RTs) were computed to assess psychomotor speed and motor sequence learning. Psychomotor speed was significantly reduced in concussed athletes. Accentuated Ne/ERN amplitude from early to late learning blocks significantly correlated with motor sequence learning in nonconcussed athletes. In contrast, Ne/ERN amplitude was found to decrease significantly with task progression in concussed athletes who nonetheless achieved normal motor sequence learning. Multiple concussions detrimentally affect psychomotor speed. Unlike nonconcussed athletes, motor sequence learning in multi-concussion athletes was not associated with Ne/ERN amplitude modulation, indicating that cognitive control processes do not centrally contribute to learning of a motor sequence after repeated concussions.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".