Neuroanatomical correlates of behavioral rating versus performance measures of working memory in typically developing children and adolescents.
Bibliographic record
Abstract
OBJECTIVE: The frequent lack of correspondence between performance and observational measures of executive functioning, including working memory, has raised questions about the validity of the observational measures. This study was conducted to investigate sources of this discrepancy through correlation of volumetric and cortical thickness (CT) neuroimaging values with performance and questionnaire measures of working memory (WM). METHODS: Using longitudinal data from the NIH MRI Study of Normal Brain Development (Volumes, N= 347, 54.3% female; CT, N= 350, 54.6% female; age range: 6 to 16.9 years), scores on the Behavioral Rating Inventory of Executive Function (BRIEF) WM, Emotional Control (EC) and Inhibition (INH) scales; Wechsler Scale of Intelligence for Children-III Digit Span; and Cambridge Neuropsychological Test Battery Spatial Working Memory (CANTAB SWM) were correlated with each other and with morphometric measurements using mixed effects linear regression models. RESULTS: BRIEF WM was correlated with CANTAB SWM (p < .001). With whole brain correction, BRIEF WM and EC were both correlated with CT of the posterior parahippocampal gyrus (PHG), EC on the right side only. Performance measures of WM were unrelated to lobar volumes or CT, but were associated with volumes of hippocampus and amygdala. CONCLUSIONS: The known role of PHG in contextual learning suggests that the BRIEF WM assesses contextualized learning/memory, potentially explaining its loose correspondence to the decontextualized performance measures. Observational measures can be useful and valid functional metrics, complementing performance measures. Labels used to characterize scales should be interpreted with caution, however.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".