Persistent psychogenic déjà vu: a case report
Bibliographic record
Abstract
INTRODUCTION: Déjà vu is typically a transient mental state in which a novel experience feels highly familiar. Although extensively studied in relation to temporal lobe epilepsy as part of simple partial seizures, déjà vu has been less studied in other clinical populations. A recent review of temporal lobe epilepsy suggested a possible link between clinical levels of anxiety and debilitating déjà vu, indicating further research is required. Here, for the first time in the literature, we present a case study of a young man with anxiety and depersonalisation who reported experiencing persistent and debilitating déjà vu. This report therefore adds to the limited literature on the relationship between anxiety and déjà vu. CASE PRESENTATION: A 23-year-old White British man presented with a form of persistent déjà vu in 2010, approximately 3 years since symptom onset. He reported a history of anxiety and experiencing feelings of depersonalisation. Neurological assessment (electroencephalogram and magnetic resonance imaging) did not indicate any abnormalities. We assessed his recognition memory with a task used in patients with dementia who report similar experiences but lack awareness of their falseness. CONCLUSIONS: Our case's memory performance was more conservative than controls but did not indicate a memory deficit. Unlike other patients with chronic déjà vu (for example, in dementia), he is fully aware of the false nature of his déjà vu and this presumably leads to his intact recognition memory performance. We suggest that his persistent déjà vu is psychogenic and conclude that déjà vu should be further studied in psychiatric disorders.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".