Sensitivity to White Matter fMRI Activation Increases with Field Strength
Bibliographic record
Abstract
Functional magnetic resonance imaging (fMRI) activation in white matter is controversial. Given that many of the studies that report fMRI activation in white matter used high field MRI systems, we investigated the field strength dependence of sensitivity to white matter fMRI activation. In addition, we evaluated the temporal signal to noise ratio (tSNR) of the different tissue types as a function of field strength. Data were acquired during a motor task (finger tapping) at 1.5 T and 4 T. Group and individual level activation results were considered in both the sensorimotor cortex and the posterior limb of the internal capsule. We found that sensitivity increases associated with field strength were greater for white matter than gray matter. The analysis of tSNR suggested that white matter might be less susceptible to increases in physiological noise related to increased field strength. We therefore conclude that high field MRI may be particularly advantageous for fMRI studies aimed at investigating activation in both gray and white matter.
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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 | 0.002 | 0.007 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".