Imaging functional motor connectivity in hemiparetic children with perinatal stroke
Bibliographic record
Abstract
Perinatal stroke causes lifelong disability, particularly hemiparetic cerebral palsy. Arterial ischemic strokes (AIS) are large, cortical, and subcortical injuries acquired near birth due to acute occlusion of the middle cerebral artery. Periventricular venous infarctions (PVI) are smaller, subcortical strokes acquired prior to 34 weeks gestation involving injury to the periventricular white matter. Both stroke types can damage motor pathways, thus, we investigated resulting alterations in functional motor networks and probed function. We measured blood oxygen level dependent (BOLD) fluctuations at rest in 38 participants [10 arterial patients (age = 14.7 ± 4.1 years), 10 venous patients (age = 13.5 ± 3.7 years), and 18 typically developing controls (TDCs) (age = 15.3 ± 5.1 years)] and explored strength and laterality of functional connectivity in the motor network. Inclusion criteria included MRI-confirmed, unilateral perinatal stroke, symptomatic hemiparetic cerebral palsy, and 6-19 years old at time of imaging. Seed-based functional connectivity analyses measured temporal correlations in BOLD response over the whole brain using primary motor cortices as seeds. Laterality indices based on mean z-scores in lesioned and nonlesioned hemispheres explored laterality. In AIS patients, significant differences in both strength and laterality of motor network connections were observed compared with TDCs. In PVI patients, motor networks largely resembled those of healthy controls, albeit slightly weaker and asymmetric, despite subcortical damage and hemiparesis. Functional connectivity strengths were not related to motor outcome scores for either stroke group. This study serves as a foundation to better understand how resting-state fMRI can assess motor functional connectivity and potentially be applied to explore mechanisms of interventional therapies after 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 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 | 0.000 |
| 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) | 0.001 | 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".