Disrupted self-perspective impact on episodic memory in individuals with self-disorders: A virtual investigation in the Latin Quarter of Paris
Bibliographic record
Abstract
ABSTRACT Virtual reality (VR) provides a powerful framework for investigating how environmental factors interact with self-referential processes during episodic memory (EM) formation. This study examined whether adopting a self-perspective or another person’s perspective while navigating a realistic simulation of the Latin Quarter of Paris differentially influenced EM in individuals at ultra-high risk (UHR) for psychosis (n=22), patients with schizophrenia (SCZ; n=20), and healthy controls (CTL; n=28). Participants encoded specific events from either their own first-person perspective or an avatar’s third-person perspective. After the navigation, they completed a free recall task assessing factual content, spatiotemporal context, and phenomenological details. Results showed that CTL exhibited a self-reference effect, recalling more details and demonstrating enhanced memory binding when encoding events from a self-perspective, compared to an other-perspective. In contrast, UHR and SCZ groups displayed pervasive EM deficits regardless of perspective and lacked this self-referential advantage. Deficits in self-perspective encoding correlated with neurological soft signs, while EM performance was associated with episodic mental time travel, executive functions, sense of presence and environmental familiarity, suggesting integrative processes between the environment, Self, and memory encoding. These findings support the theory of a disruption of minimal selfhood or ipseity in the SCZ spectrum, suggesting that core alterations in first-person anchoring compromise the encoding of experiences into coherent, spatially contextualised episodic memories. Furthermore, the results highlight the importance of naturalistic settings for uncovering how self-referential and environmental factors jointly shape memory in psychosis. VR-based approaches may facilitate early identification of at-risk individuals and inform targeted interventions to promote engagement with the environment, enhancing EM and self-related processes in clinical populations.
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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 | 0.001 | 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".