Intrinsic functional connectivity of periaqueductal gray subregions in humans
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Bibliographic record
Abstract
The periaqueductal gray matter (PAG) is a key brain region of the descending pain modulation pathway. It is also involved in cardiovascular functions, anxiety, and fear; however, little is known about PAG subdivisions in humans. The aims of this study were to use resting-state fMRI-based functional connectivity (FC) to parcellate the human PAG and to determine FC of its subregions. To do this, we acquired resting-state fMRI scans from 79 healthy subjects and (1) used a data-driven method to parcellate the PAG, (2) used predefined seeds in PAG subregions to evaluate PAG FC to the whole brain, and (3) examined sex differences in PAG FC. We found that clustering of the left and right PAG yielded similar patterns of caudal, middle, and rostral subdivisions in the coronal plane, and dorsal and ventral subdivisions in the sagittal plane. FC analysis of predefined subregions revealed that the ventolateral(VL)-PAG was supfunctionally connected to brain regions associated with descending pain modulation (anterior cingulate cortex (ACC), upper pons/medulla), whereas the lateral (L) and dorsolateral (DL) subregions were connected with brain regions implicated in executive functions (prefrontal cortex, striatum, hippocampus). We also found sex differences in FC including areas implicated in pain, salience, and analgesia including the ACC and the insula in women, and the MCC, parahippocampal gyrus, and the temporal pole in men. The organization of the human PAG thus provides a framework to understand the circuitry underlying the broad range of responses to pain and its modulation in men and women.
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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 | 0.000 |
| 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) | 0.000 | 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