Callosal Contribution to Procedural Learning in Children
Bibliographic record
Abstract
A previous study in acallosal patients (De Guise, et al., 1999) has demonstrated the crucial role of the corpus callosum (CC) in a procedural learning task that requires the participation of both hemispheres. Because children often display limitations in interhemispheric communication linked to callosal immaturity, we expected that they would have difficulties learning a procedural skill that involved interhemispheric integration during its acquisition, but not when the skill was learned intrahemispherically. To test this hypothesis, 40 children, divided into 4 age groups (6 to 8 years, 9 to 11 years, 12 to 14 years, and 15 to 16 years), performed a modified version of the serial reaction time task developed by Nissen and Bullemer (1987). This task involves uni- or bimanual key-pressing responses to a fixed sequence of 10 visual stimuli that are repeated 80 times. All the children were able to learn the visuomotor skill in the unimanual condition and to transfer it interhemispherically. However, only the older children (12 years and over) learned the task in the bimanual (interhemispheric) condition. The results indicate that the maturation of the CC affects interhemispheric acquisition of a procedural skill in two different ways: While the immature CC appears to be sufficient to transfer a skill acquired by one hemisphere, a mature CC seems to be required to learn the skill bihemispherically. The latter skill was achieved around the age of 12, coinciding with the end of the maturation cycle of the CC. Although the young children were unable to learn the bimanual task implicitly, some of them showed explicit knowledge of the procedure, confirming once again the dissociation between explicit and implicit memory suggested by Squire (1992).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".