Neurovascular coupling over cortical brain areas and resting state network connectivity with and without rigidified carotid artery
Bibliographic record
Abstract
Significance: Neurovascular coupling (NVC) is key to research as hemodynamics can reflect neuronal activation and is often used in studies regarding the resting state network (RSN). However, several circumstances, including diseases that reduce blood vessel elasticity, can diminish NVC. In these cases, hemodynamic proxies might not accurately reflect the neuronal RSN. Aim: We aim to investigate in resting state if (1) NVC differs over brain regions, (2) NVC remains intact with a mild rigidification of the carotid artery, (3) hemodynamic-based RSN reflects neuronal-based RSN, and (4) RSN differs with a mildly rigidified artery. Approach: ). With simultaneous GCaMP and intrinsic optical imaging, we compared neuronal activation to hemodynamic changes over the entire cortex. Results: NVC parameters did not differ between the CaCl and Sham groups. Likewise, GCaMP and hemodynamic RSN showed similar connections in both groups. However, the parameters of NVC differed over brain regions. Retrosplenial regions had a slower response and a higher HbR peak than sensory and visual regions, and the motor cortex showed less HbO influx than sensory and visual regions. Conclusions: NVC in a resting state differs over brain regions but is not altered by mild rigidification of the carotid artery.
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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 | 0.001 |
| 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".