White matter maturation in visual and motor areas predicts the latency of visual activation in children
Bibliographic record
Abstract
In humans, white matter maturation is important for the improvement of cognitive function and performance with age. Across studies the variables of white matter maturity and age are highly correlated; however, the unique contributions of white matter to information processing speed remain relatively unknown. We investigated the relations between the speed of the visually-evoked P100m response and the biophysical properties of white matter in 11 healthy children performing a simple, visually-cued finger movement. We found that: (1) the latency of the early, visually-evoked response was related to the integrity of white matter in both visual and motor association areas and (2) white matter maturation in these areas accounted for the variations in visual processing speed, independent of age. Our study is a novel investigation of spatial-temporal dynamics in the developing brain and provides evidence that white matter maturation accounts for age-related decreases in the speed of visual response. Developmental models of cortical specialization should incorporate the unique role of white matter maturation in mediating changes in performance during tasks involving visual processing.
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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 | 0.000 |
| 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) | 0.000 | 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".