Intersubject Spatial Pattern Correlations During Movie Viewing Are Stimulus-Driven and Nonuniform Across the Cortex
Bibliographic record
Abstract
A fundamental step to predicting brain activity in healthy and diseased populations is characterizing the common spatio-temporal response to a shared experience. Multivoxel pattern analysis allows us to investigate information encoding through these patterns; however, we have yet to explore local, stimulus-driven, patterns of cortical activity during naturalistic stimulation. We sought to examine these patterns with minimum interpolation-excluding functional alignment-to characterize the most basic degree of shared response between subjects. We used an unbiased analytic approach, combined with rich, naturalistic, and nonsemantic stimulation to estimate shared spatial patterns in functional magnetic resonance imaging responses across a large group. We found that meso-scale spatial patterns were shared nonuniformly across the visual cortex and represent information distinct from the shared temporal response. Shared spatial patterns were stimulus-driven, modulated by pattern size, and more sensitive to the contrast of 3D versus 2D stimulus differences than the temporal signals. Although the grand functional structure of the brain is understood to be common, these results suggest that even at a meso-scale, we share common spatial structures with anatomical alignment alone. The strength of this similarity varies across the cortex, suggesting some spatial structures are innately organized, whereas others are shaped by factors such as learning and plasticity.
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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 | 0.001 | 0.003 |
| 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 | 0.000 |
| 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".