Interhemispheric cooperation in global–local visual processing in pediatric multiple sclerosis
Bibliographic record
Abstract
Impairments in visuospatial abilities are commonly reported in children and adolescents with multiple sclerosis (MS). Corpus callosum (CC) pathology occurs in patients with MS and may contribute to impairment in visuospatial perception, particularly when interhemispheric information transfer is required. This study used a global-local hierarchical letter paradigm to examine the relationship between interhemispheric information transfer and white matter integrity in the CC assessed using diffusion tensor imaging. Thirteen cognitively preserved pediatric-onset MS patients and 15 age-matched healthy controls were asked to determine whether a target letter E appeared at the attended level of the stimulus. As expected, both groups processed global and local information more slowly under divided than selective attention conditions. The MS group performed similarly to the control group with respect to reaction time and accuracy on selective and divided attention conditions, with one exception. Specifically, the presence of a global target when attending to a local target caused greater response conflict in the MS group than in controls (p = .01). Pooling both the patient and control data, greater response conflict was associated with reduced white matter integrity as indicated by lower fractional anisotropy in the anterior body of the CC (r = -.33, p < .05). Results suggest that reduced white matter integrity in anterior regions of the CC may lead to less efficient inhibition of task-irrelevant global information in the hierarchal processing of visual information.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".