Neurophysiological dysconnectivity across multiple resting state brain networks and cognitive impairment in children with Prader-Willi Syndrome
Bibliographic record
Abstract
Abstract Prader-Willi Syndrome (PWS) is a rare genetic condition with multifaceted physical, behavioural and cognitive difficulties that is characterized by hyperphagia and low executive functioning. Food-seeking behaviours may be moderated by hormonal, cognitive, and psychological factors, and are thought to be mediated in part by functional brain abnormalities. Here, we used an experimental protocol integrating eyes opens resting state magnetoencephalography (MEG) - a high-resolution neurophysiological imaging technique - and neuropsychological profiling to understand the relationship between executive functioning, and intrinsic brain activity & functional connectivity in a prospective, cross-sectional cohort with PWS, and a sex-, age- and BMI-matched control group. We observed lower executive functioning in PWS as well as functional dysconnectivity across multiple channels of brain synchrony - in other words, across multiple frequency bands that mediate communication within and between brain networks - in the visual, attentional, and the default mode networks. Moreover, we found ‘brain-wide’ changes in the topological structure of brain networks in those with PWS, with increased ‘hubness’ of functional networks, but decreased centrality. However, none of these measures survived multiple comparison correction after correlating with neuropsychological outcomes, although there were moderate effect sizes (degree of association). This is the first study to combine neuropsychology and neurophysiological imaging to show that functional synchrony in multiple brain networks is dysregulated in PWS.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".