Williams syndrome: a relationship between genetics, brain morphology and behaviour
Bibliographic record
Abstract
BACKGROUND: Genetically Williams syndrome (WS) promises to provide essential insight into the pathophysiology of cortical development because its ∼28 deleted genes are crucial for cortical neuronal migration and maturation. Phenotypically, WS is one of the most puzzling childhood neurodevelopmental disorders affecting most intellectual deficiencies (i.e. low-moderate intelligence quotient, visuospatial deficits) yet relatively preserving what is uniquely human (i.e. language and social-emotional cognition). Therefore, WS provides a privileged setting for investigating the relationship between genes, brain and the consequent complex human behaviour. METHODS: We used in vivo anatomical magnetic resonance imaging analysing cortical surface-based morphometry, (i.e. surface area, cortical volume, cortical thickness, gyrification index) and cortical complexity, which is of particular relevance to the WS genotype-phenotype relationship in 22 children (2.27-14.6 years) to compare whole hemisphere and lobar surface-based morphometry between WS (n = 10) and gender/age matched normal controls healthy controls (n = 12). RESULTS: Compared to healthy controls, WS children had a (1) relatively preserved Cth; (2) significantly reduced SA and CV; (3) significantly increased GI mostly in the parietal lobe; and (4) decreased CC specifically in the frontal and parietal lobes. CONCLUSION: Our findings are then discussed with reference to the Rakic radial-unit hypothesis of cortical development, arguing that WS gene deletions may spare Cth yet affecting the number of founder cells/columns/radial units, hence decreasing the SA and CV. In essence, cortical brain structure in WS may be shaped by gene-dosage abnormalities.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".