Aberrant functional network recruitment of posterior parietal cortex in turner syndrome
Bibliographic record
Abstract
Turner syndrome is a genetic disorder caused by the complete or partial absence of an X chromosome in affected women. Individuals with TS show characteristic difficulties with executive functions, visual-spatial and mathematical cognition, with relatively intact verbal skills, and congruent abnormalities in structural development of the posterior parietal cortex (PPC). The functionally heterogeneous PPC has recently been investigated using connectivity-based clustering methods, which sub-divide a given region into clusters of voxels showing similar structural or functional connectivity to other brain regions. In the present study, we extended this method to compare connectivity-based clustering between groups and investigate whether functional networks differentially recruit the PPC in TS. To this end, we parcellated the PPC into sub-regions based on temporal correlations with other regions of the brain. fMRI data were collected from 15 girls with TS and 14 typically developing (TD) girls, aged 7-14, while they performed a visual-spatial task. Temporal correlations between voxels in the PPC and a set of seed regions were calculated, and the PPC divided into clusters of voxels showing similar connectivity. It was found that in general the PPC parcellates similarly in TS and TD girls, but that regions in bilateral inferior parietal lobules, and posterior right superior parietal lobule, were reliably recruited by different networks in TS relative to TD participants. These regions showed weaker correlation in TS with a set of regions involved in visual processing. These results suggest that abnormal development of visuospatial functional networks in TS may relate to the well documented cognitive difficulties in this disorder.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".