QOS-41NEURAL NETWORK DISTURBANCES IN CHILDREN TREATED FOR BRAIN TUMOURS
Bibliographic record
Abstract
BACKGROUND: Children treated for brain tumours consistently suffer from altered brain structure and function leading to long-term cognitive impairments. These structural and functional changes suggest there may also be perturbations in the neural networks that underlie cognitive function in these children. In this study we investigated whether pediatric brain tumour survivors express atypical brain networks following treatment by examining their resting-state functional connectivity compared to healthy children. METHODS: Resting-state brain activity was obtained from 28 pediatric brain tumour survivors (11.62 yrs ± 3.00) and 28 healthy children (11.60 yrs ± 3.26) using magnetoencephalography. Time-series were reconstructed for all cortical, subcortical and cerebellar sources in the Automated Anatomical Labeling atlas and filtered into delta (2-3 Hz), theta (4-7 Hz), alpha (8-12 Hz), beta (13-29 Hz), low gamma (30-59 Hz) and high gamma (60-100 Hz) frequency bandwidths. Weighted phase lag index values were computed to index functional connectivity among brain regions relative to controls. RESULTS: Following brain tumour treatment, pediatric brain tumour survivors express hyperconnectivity in the delta band compared to healthy children (P < 0.05). This atypical network is composed primarily of long-range connections spanning many cortical, subcortical and cerebellar regions across the brain. CONCLUSION: Children treated for brain tumours experience neural network disturbances in the low frequency range. These findings suggest that atypical functional connectivity may underlie cognitive deficits observed in pediatric brain tumour survivors.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".