Postacquisition suppression of large‐vessel BOLD signals in high‐resolution fMRI
Why this work is in the frame
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Bibliographic record
Abstract
Large-vessel BOLD contamination is a serious impediment to localization of neural activity in high-resolution fMRI studies. A new method is presented which estimates and removes the fraction of BOLD signal that arises from oriented vessels, such as cerebral and pial veins in a voxel, by measuring their influence on the phase angle of the complex valued fMRI time series. A maximum likelihood estimator based on a linear least-squares fit of the BOLD signal phase to the BOLD signal magnitude in a voxel is shown to efficiently suppress the BOLD effect from these larger veins, whose activation is not well colocalized with the neural response. In high-resolution in vivo fMRI data at 4 T, it is estimated that the method is sensitive to the phase changes in the cerebral, larger intracortical, and pial veins. The technique requires no special pulse sequence modifications or acquisition strategies, and is computationally fast and intrinsically robust.
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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 | 0.001 |
| 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 it