A failure of conflict to modulate dual-stream processing may underlie the formation and maintenance of delusions
Bibliographic record
Abstract
BACKGROUND: Dual-stream information processing proposes that reasoning is composed of two interacting processes: a fast, intuitive system (Stream 1) and a slower, more logical process (Stream 2). In non-patient controls, divergence of these streams may result in the experience of conflict, modulating decision-making towards Stream 2, and initiating a more thorough examination of the available evidence. In delusional schizophrenia patients, a failure of conflict to modulate decision-making towards Stream 2 may reduce the influence of contradictory evidence, resulting in a failure to correct erroneous beliefs. METHOD: Delusional schizophrenia patients and non-patient controls completed a deductive reasoning task requiring logical validity judgments of two-part conditional statements. Half of the statements were characterized by a conflict between logical validity (Stream 2) and content believability (Stream 1). RESULTS: Patients were significantly worse than controls in determining the logical validity of both conflict and non-conflict conditional statements. This between groups difference was significantly greater for the conflict condition. CONCLUSIONS: The results are consistent with the hypothesis that delusional schizophrenia patients fail to use conflict to modulate towards Stream 2 when the two streams of reasoning arrive at incompatible judgments. This finding provides encouraging preliminary support for the Dual-Stream Modulation Failure model of delusion formation and maintenance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".