Neurochemical correlates of scene processing in the precuneus/posterior cingulate cortex: A multimodal fMRI and <sup>1</sup> H‐MRS study
Bibliographic record
Abstract
Abstract Precuneus/posterior cingulate cortex (PCu/PCC) are key components of a midline network, activated during rest but also in tasks that involve construction of scene or situation models. Despite growing interest in PCu/PCC functional alterations in disease and disease risk, the underlying neurochemical modulators of PCu/PCC's task‐evoked activity are largely unstudied. Here, a multimodal imaging approach was applied to investigate whether interindividual differences in PCu/PCC fMRI activity, elicited during perceptual discrimination of scene stimuli, were correlated with local brain metabolite levels, measured during resting‐state 1 H‐MRS. Forty healthy young adult participants completed an fMRI perceptual odd‐one‐out task for scenes, objects and faces. 1 H‐MRS metabolites N ‐acetyl‐aspartate (tNAA), glutamate (Glx) and γ‐amino‐butyric acid (GABA+) were quantified via PRESS and MEGA‐PRESS scans in a PCu/PCC voxel and an occipital (OCC) control voxel. Whole brain fMRI revealed a cluster in right dorsal PCu/PCC that showed a greater BOLD response to scenes versus faces and objects. When extracted from an independently defined PCu/PCC region of interest, scene activity (vs. faces and objects and also vs. baseline) was positively correlated with PCu/PCC, but not OCC, tNAA. A voxel‐wise regression analysis restricted to the PCu/PCC 1 H‐MRS voxel area identified a significant PCu/PCC cluster, confirming the positive correlation between scene‐related BOLD activity and PCu/PCC tNAA. There were no correlations between PCu/PCC activity and Glx or GABA+ levels. These results demonstrate, for the first time, that scene activity in PCu/PCC is linked to local tNAA levels, identifying a neurochemical influence on interindividual differences in the task‐driven activity of a key brain hub.
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How this classification was reachedexpand
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 | 0.001 | 0.003 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".