Improvements in brain mechanisms associated with the aberrant salience hypothesis of psychosis following Avatar therapy for refractory auditory verbal hallucinations
Bibliographic record
Abstract
Introduction Nearly 40% of individuals with schizophrenia are resistant to medication. Treatment-resistant schizophrenia leads to increased health-risk behaviors and reduced quality of life. Avatar therapy via virtual reality seems to be a very promising solution for individuals with treatment-resistant schizophrenia. This therapy targets refractory auditory verbal hallucinations, one of the core positive symptoms of schizophrenia. This symptom is thought to reflect a direct experience of the aberrant salience of internal representations according to the aberrant salience hypothesis of psychosis. Strong evidence suggests that the striatum plays an important role in the development of positive symptoms, as individuals with schizophrenia show an increased activation of this brain region at rest. One of the mechanisms underlying Avatar therapy may involve a reduction in aberrant salience. However, the neural processes involved in this therapeutic approach remain largely unexplored. Objectives This study aims to investigate the brain mechanisms underlying Avatar therapy in treatment-resistant schizophrenia by examining spontaneous brain activity at rest using functional magnetic resonance imaging (fMRI). Methods Fourteen participants with treatment-resistant schizophrenia participated in nine sessions of Avatar therapy. They underwent resting-state fMRI scans before and after the therapy. Voxel-wise analyses of fractional amplitude of low-frequency fluctuations (fALFF) were performed to examine differences between post- and pre-therapy in regional patterns of spontaneous brain activity. Results Importantly, after the therapy compared to before the therapy, we found that participants with treatment-resistant schizophrenia had reduced fALFF in the right putamen. We also observed increased fALFF in the bilateral occipital, right inferior temporal, right angular gyrus, left medial temporal and left supramarginal gyri after the therapy. Conclusions The putamen is a part of the striatum which is known to play a significant role in the emergence of psychosis. Mainly, our results suggest that Avatar therapy regulates putamen activity at rest, suggesting that the neural mechanisms underlying the therapy involve the alleviation of aberrant salience. Disclosure of Interest None Declared
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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 | 0.000 |
| 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) | 0.002 | 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".