Functional architecture of cerebral cortex during naturalistic movie watching
Bibliographic record
Abstract
Characterizing the functional organization of cerebral cortex is a fundamental step in understanding how different kinds of information are processed in the brain. However, it is still unclear how these areas are organized during naturalistic visual and auditory stimulation. Here, we used high-resolution functional MRI data from 176 human subjects to map the macro-architecture of the entire cerebral cortex based on responses to a 60-min audiovisual movie stimulus. A data-driven clustering approach revealed a map of 24 functional areas/networks, each explicitly linked to a specific aspect of sensory or cognitive processing. Novel features of this map included an extended scene-selective network in the lateral prefrontal cortex, separate clusters responsive to human-object and human-human interaction, and a push-pull interaction between three executive control (domain-general) networks and domain-specific regions of the visual, auditory, and language cortex. Our cortical parcellation provides a comprehensive and unified map of functionally defined areas in the human cerebral cortex.
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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 | 0.000 | 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) | 0.001 | 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 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".