Memory Performance and Normalized Regional Brain Volumes in Patients with Pediatric-Onset Multiple Sclerosis
Bibliographic record
Abstract
Studies in adults with multiple sclerosis (MS) have associated regional brain abnormalities with memory impairment. While memory problems in children with MS are often reported, little is known about the neural correlates that may contribute to these difficulties. We measured verbal and nonverbal memory using the Test of Memory and Learning (TOMAL-2) in 32 children and adolescents with MS and 26 age- and sex-matched healthy controls. Memory performance was correlated with volumetric measures of the whole brain, hippocampus, amygdala, and thalamus. Brain volumes were normalized for age and sex using magnetic resonance imaging (MRI) data from the National Institutes of Health MRI Study of Normal Brain development. With the exception of story recall, performance on memory tests was similar to that of the control group. Relative to controls, patient with MS showed reduced volume in the whole brain (p < .001), amygdala (p < .005), and thalamus (p < .001), but not the hippocampus. In the patient group, word-list learning correlated with whole brain volume (r = .53) and hippocampal volume (r = .43), whereas visual recognition memory correlated with thalamic volume (r = .48). Findings are consistent with the well-established role of the hippocampus in learning and consolidation and also highlight the importance of diffuse brain pathology on memory function.
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) | 0.001 | 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".