Cerebral blood volume changes during human neuronal activation: a comparative study of VASO and VERVE
Bibliographic record
Abstract
In this research, two techniques which measure hemodynamic changes during neuronal activation in humans were studied.The Vascular Space Occupancy (VASO) technique indirectly measures changes in total cerebral blood volume (CBV) by measuring the decrease in grey matter signal during activation, in images in which the blood signal is nulled.The Venous Refocusing for Volume Estimation (VERVE) technique measures changes in venous blood volume by exploiting the dependence of partially-deoxygenated blood's T 2 on the refocusing interval 180 .Using a simultaneous visual and motor task, a (ΔCBV/CBV rest ) total of 25.0 ± 13.9 % and a (ΔCBV/CBV rest ) venous of 3.9 ± 1.6 % were measured using VASO and VERVE, respectively.Though the VASO technique has a high CNR and is simple to implement, its signal has contributions from many compartments other than grey matter.VERVE has fewer deleterious effects, but suffers from a higher power deposition.The activated regions in VERVE overlap better with BOLD activation than the VASO regions do, which, combined with VERVE's specificity to venous CBV changes, make it more appropriate in an investigation of the blood volume contribution to the BOLD signal.I would foremost like to thank my supervisor, Bruce Pike, for giving me the opportunity to
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".