Resting-state EEG oscillations are reduced in asymptomatic <i>C9orf72</i> repeat expansion carriers
Bibliographic record
Abstract
Abstract Objective We investigated the signature of the C9orf72 repeat expansion on resting-state cortical activity in asymptomatic individuals and explored its relationship with structural, gene expression, and cognitive measures. Methods High-density resting-state EEG was compared between 90 asymptomatic family members of patients with familial amyotrophic lateral sclerosis (ALS), dichotomised into carriers of the pathological C9orf72 repeat expansion (N = 37) and non-carrier controls (N = 53). Periodic (oscillatory) and aperiodic (1/f) components of the power spectrum were analysed at the sensor- and source-level. Regional EEG power changes were correlated with C9orf72 expression from the Allen Human Brain Atlas, cortical MRI thickness and performance on the Complementary Cognitive ALS Screen (C-CAS). Results Asymptomatic carriers exhibited significantly lower periodic power in the α and β frequency bands (10-30 Hz) across posterior cortical regions, including the parietal, occipital, and temporal lobes. The magnitude of this power reduction was associated with increased C9orf72 expression and reduced cortical thickness in the same regions. In carriers, reduced β-band power was associated with poorer performance on Visuoconstructive Immediate and Body Representation tasks. The aperiodic component of the EEG power did not differ between groups. Interpretation In asymptomatic C9orf72 repeat expansion carriers, resting-state EEG reveals differences in oscillatory power in the posterior brain regions. The correlational findings suggest that C9orf72 repeat expansion may be involved in functional and structural changes in the posterior cerebral cortex, which may contribute to deficits in tasks requiring visuospatial processing.
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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 | 0.000 | 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) | 0.002 | 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".