Visualization of Altered Neurovascular Coupling in Chronic Stroke Patients using Multimodal Functional MRI
Bibliographic record
Abstract
Evaluation of cortical reorganization in chronic stroke patients requires methods to accurately localize regions of neuronal activity. Blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) is frequently employed; however, BOLD contrast depends on specific coupling relationships between the cerebral metabolic rate of oxygen (CMRO(2)), cerebral blood flow (CBF), and volume (CBV), which may not exist following stroke. The aim of this study was to understand whether CBF-weighted (CBFw) and CBV-weighted (CBVw) fMRI could be used in sequence with BOLD to characterize neurovascular coupling mechanisms poststroke. Chronic stroke patients (n=11) with motor impairment and age-matched controls (n=11) performed four sets of unilateral motor tasks (60 seconds/30 seconds off/on) during CBFw, CBVw, and BOLD fMRI acquisition. While control participants elicited mean BOLD, CBFw, and CBVw responses in motor cortex (P<0.01), patients showed only mean changes in CBF (P<0.01) and CBV (P<0.01), but absent mean BOLD responses (P=0.20). BOLD intersubject variability was consistent with differing coupling indices between CBF, CBV, and CMRO(2). Thus, CBFw and/or CBVw fMRI may provide crucial information not apparent from BOLD in these patients. A table is provided outlining distinct vascular and metabolic uncoupling possibilities that elicit different BOLD responses, and the strengths and limitations of the multimodal protocol are summarized.
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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 | 0.000 |
| 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) | 0.001 | 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 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".