Functional Neuroimaging Predictors of Self-Reported Psychotic Symptoms in Adolescents
Bibliographic record
Abstract
OBJECTIVE: This study investigated the neural correlates of psychotic-like experiences in youths during tasks involving inhibitory control, reward anticipation, and emotion processing. A secondary aim was to test whether these neurofunctional correlates of risk were predictive of psychotic symptoms 2 years later. METHOD: Functional imaging responses to three paradigms-the stop-signal, monetary incentive delay, and faces tasks-were collected in youths at age 14, as part of the IMAGEN study. At baseline, youths from London and Dublin sites were assessed on psychotic-like experiences, and those reporting significant experiences were compared with matched control subjects. Significant brain activity differences between the groups were used to predict, with cross-validation, the presence of psychotic symptoms in the context of mood fluctuation at age 16, assessed in the full sample. These prediction analyses were conducted with the London-Dublin subsample (N=246) and the full sample (N=1,196). RESULTS: Relative to control subjects, youths reporting psychotic-like experiences showed increased hippocampus/amygdala activity during processing of neutral faces and reduced dorsolateral prefrontal activity during failed inhibition. The most prominent regional difference for classifying 16-year-olds with mood fluctuation and psychotic symptoms relative to the control groups (those with mood fluctuations but no psychotic symptoms and those with no mood symptoms) was hyperactivation of the hippocampus/amygdala, when controlling for baseline psychotic-like experiences and cannabis use. CONCLUSIONS: The results stress the importance of the limbic network's increased response to neutral facial stimuli as a marker of the extended psychosis phenotype. These findings might help to guide early intervention strategies for at-risk youths.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".