Characterization of white matter integrity deficits in cocaine‐dependent individuals with substance‐induced psychosis compared with non‐psychotic cocaine users
Bibliographic record
Abstract
With sufficient drug exposure, some individuals develop transient psychotic symptoms referred to as 'substance-induced psychosis' (SIP), which closely resemble the symptoms observed in schizophrenia spectrum disorders. The comparability in psychotic presentation between SIP and the schizophrenias suggests that similar underlying neural deficits may contribute to the emergence of psychosis across these disorders. Only a small number of studies have investigated structural alterations in SIP, and all have been limited to volumetric imaging methods, with none controlling for the effects of chronic drug exposure. To investigate white matter abnormalities associated with SIP, diffusion tensor imaging was employed in a group of individuals with cocaine-associated psychosis (CAP; n = 24) and a cocaine-dependent non-psychotic (CDN) group (n = 43). Tract-based spatial statistics was used to investigate group differences in white matter diffusion parameters. The CAP group showed significantly lower fractional anisotropy values than the CDN group (p < 0.05) in voxels within white matter tracts of fronto-temporal, fronto-thalamic and interhemispheric pathways. The greatest differences in white matter integrity were present in the corpus callosum, corona radiata, bilateral superior longitudinal fasciculi and bilateral inferior longitudinal fasciculi. Additionally, the CAP group had voxels of significantly higher radial diffusivity in a subset of the previously mentioned pathways. These results are the first description of white matter integrity abnormalities in a SIP sample and indicate that differences in these pathways may be a shared factor in the expression of different forms of psychosis.
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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".