Stimulus-preceding negativity represents a conservative response tendency
Bibliographic record
Abstract
Humans tend to be conservative and typically will retain their initial decision even if an option to change is provided. We investigated whether the stimulus-preceding negativity (SPN), an event-related potential associated with the affective-motivational anticipation of feedback in gambling tasks, represents the strong response tendency to retain an initial decision. We compared SPNs in three different card-gambling tasks wherein the participants were given the opportunity to change their initial decision after they chose one of three cards. In two of these tasks, the winning probability was equiprobable (1/3 and 1/2, respectively) whether or not the participants changed their initial decision. However, in the Monty Hall dilemma task, changing the initial decision stochastically doubled the probability of winning (2/3) compared with retaining (1/3). In this counterintuitive probabilistic dilemma task, after the participant chose an option among three cards, a nonreward (losing) option is revealed. Then, the participants are offered a chance to change their mind and asked to make their final decision: to retain their initial choice or change to the alternate option. In all tasks, maintenance of previous behaviors was observed, although the rate of retaining earlier choices tended to be lower in the Monty Hall dilemma task than in the other two tasks. The SPNs were larger on retain trials than on change trials irrespective of task. These results suggest that underlying brain activities associated with the strong tendency to retain the initial decision can be observed by the SPN and thus it reflects expectancy of outcomes in terms of self-chosen behaviors.
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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 | 0.000 | 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".