Altered beta-band functional connectivity may be related to ‘performance slowing’ in good outcome aneurysmal subarachnoid patients
Bibliographic record
Abstract
Recent evidence suggests that good neurological outcome in subarachnoid hemorrhage (SAH) does not equate to good neuropsychological and cognitive outcome. These individuals continue to face cognitive difficulties in tasks involving mental flexibility, short-term memory and attention, resulting in decreased independence in daily living and reduced ability to return to work. In the current study, we examined the functional connectivity profiles using magnetoencephalography (MEG) in SAH patients, versus controls, during a visual short-term memory, 1-back, task. Our results found that a global measure of MEG-based phase synchrony in the beta band (15-30 Hz), derived from a time window during correct recognition, significantly differentiated the controls from the patients. During correct recognition, the connectivity patterns in the controls were characterized by inter-hemispheric parieto-frontal connections, involving the posterior parietal cortex, while patients appeared to recruit an entirely different network of regions, involving the anterior frontal and temporal regions. Reduced beta-band synchrony during recognition was associated with overall poorer performance, demonstrated as lower accuracy and slower reaction times in patients, but not in controls. This differentiation between groups suggests an important and distinct role of beta-band phase synchronization, perhaps for memory retrieval, associated with good performance. Performance slowing, short-term memory and attention deficits in these patients may be attributed to the impaired beta-band connectivity among prefrontal regions and the posterior parietal cortex.
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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 | 0.001 | 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".