Neural Correlates of Mental State Decoding in Human Adults: An Event-related Potential Study
Bibliographic record
Abstract
Successful negotiation of human social interactions rests on having a theory of mind - an understanding of how others' behaviors can be understood in terms of internal mental states, such as beliefs, desires, intentions, and emotions. A core theory-of-mind skill is the ability to decode others' mental states on the basis of observable information, such as facial expressions. Although several recent studies have focused on the neural correlates of reasoning about mental states, no research has addressed the question of what neural systems underlie mental state decoding. We used dense-array event-related potentials (ERP) to show that decoding mental states from pictures of eyes is associated with an N270-400 component over inferior frontal and anterior temporal regions of the right hemisphere. Source estimation procedures suggest that orbitofrontal and medial temporal regions may underlie this ERP effect. These findings suggest that different components of everyday theory-of-mind skills may rely on dissociable neural mechanisms.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".