Superior non-specific motor learning in the blind
Bibliographic record
Abstract
It is well established that blindness induces changes in cerebral function and structure, namely affecting the somatomotor regions. However, the behavioural significance of these changes on the motor system, and on motor learning in particular, remains elusive. In this study, we used a modified version of the serial reaction time task (SRTT) with auditory cues to assess sequence specific and non-specific motor learning in blind adults and sighted controls, and compare them with sighted controls performing the classic visual SRTT. Our results show that the auditory SRTT faithfully replicates the typical learning pattern obtained with the visual SRTT. On the auditory SRTT, blind individuals consistently showed faster reaction times than sighted controls, being at par with sighted individuals performing the visual SRTT. On the other hand, blind participants displayed a particular pattern of motor learning in comparison to both sighted groups; while controls improved prominently on sequence specific learning, blind individuals displayed comparable performance on both specific and non-specific learning, markedly outperforming the control groups on non-specific learning. These results show that blindness, in addition to causing long-term changes in cortical organisation, can also influence dynamic neuroplastic mechanisms in systems beyond those typically associated with compensatory sensory processing.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".