Fatigue in perinatal stroke is associated with resting-state functional connectivity
Bibliographic record
Abstract
Abstract Fatigue is prevalent in youth with perinatal stroke, but the causes are unclear. Predictive coding models of adult post-stroke fatigue suggest that fatigue may arise from dysfunction in predictive processing networks. To date, the association between fatigue and neural network connectivity in youth with perinatal stroke has not been examined. The present study examined the association between fatigue and the functional connectivity of predictive processing neural networks, measured using resting-state functional magnetic resonance imaging, in individuals with perinatal stroke. Participants who reported experiencing fatigue had weaker functional connectivity between the non-lesioned middle frontal and supramarginal gyri and between the non-lesioned intracalcarine cortex and the lesioned paracingulate cortex. In contrast, participants reporting fatigue had stronger functional connectivity between the lesioned inferior temporal gyrus and non-lesioned insula. These results suggest that fatigue in youth with hemiparetic cerebral palsy caused by perinatal stroke is associated with the functional connectivity of hubs previously associated with predictive processing and fatigue. These results suggest potential cortical and behavioral targets for the treatment of fatigue in individuals with perinatal stroke.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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) | 0.003 | 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".