Content-specific activity in frontoparietal and default-mode networks during prior-guided visual perception
Why this work is in the frame
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Bibliographic record
Abstract
How prior knowledge shapes perceptual processing across the human brain, particularly in the frontoparietal (FPN) and default-mode (DMN) networks, remains unknown. Using ultra-high-field (7T) functional magnetic resonance imaging (fMRI), we elucidated the effects that the acquisition of prior knowledge has on perceptual processing across the brain. We observed that prior knowledge significantly impacted neural representations in the FPN and DMN, rendering responses to individual visual images more distinct from each other, and more similar to the image-specific prior. In addition, neural representations were structured in a hierarchy that remained stable across perceptual conditions, with early visual areas and DMN anchored at the two extremes. Two large-scale cortical gradients occur along this hierarchy: first, dimensionality of the neural representational space increased along the hierarchy; second, prior's impact on neural representations was greater in higher-order areas. These results reveal extensive and graded influences of prior knowledge on perceptual processing across the brain.
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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