Cognitive and Neural State Dynamics of Story Comprehension
Bibliographic record
Abstract
Abstract Understanding a story involves a constant interplay of the accumulation of narratives and its integration into a coherent structure. This study characterizes cognitive state dynamics during story comprehension and the corresponding network-level reconfiguration of the whole brain. We presented movie clips of temporally scrambled sequences, eliciting fluctuations in subjective feelings of understanding. An understanding occurred when processing events with high causal relations to previous events. Functional neuroimaging results showed that, during moments of understanding, the brain entered into a functionally integrated state with increased activation in the default mode network (DMN). Large-scale neural state transitions were synchronized across individuals who comprehended the same stories, with increasing occurrences of the DMN-dominant state. The time-resolved functional connectivities predicted changing cognitive states, and the predictive model was generalizable when tested on new stories. Taken together, these results suggest that the brain adaptively reconfigures its interactive states as we construct narratives to causally coherent structures.
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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 | 0.004 |
| 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".