Depersonalization and derealization as sequelae of a temporal lobe lesion: a case report
Bibliographic record
Abstract
BACKGROUND: Depersonalization and derealization can occur not just from psychiatric causes but also from various organic etiologies, such as seizures and intracerebral structural abnormalities. However, there have been no previous reported cases to the authors' knowledge detailing isolated depersonalization and derealization in the absence of clinical seizure activity or other psychiatric pathology, as sequelae of structural intracerebral lesions. CASE PRESENTATION: In this case report, we detail the unique presentation of a 68-year-old woman under the care of palliative medicine who experienced depersonalization and derealization secondary to a metastatic lesion in her temporal lobe, in the parahippocampal gyrus to medial occipitotemporal gyrus region. These symptoms were present in the absence of any clinical seizure activity or other psychiatric symptomatology and largely resolved with the use of steroidal therapy, before returning secondary to disease progression. CONCLUSIONS: We discuss the relationship among isolated depersonalization and derealization with pathology of the left posterior temporal lobe in the context of this interesting case. This case expands our knowledge of the neurobiology of these phenomena, given the specific localization of the intracerebral pathology and temporal specificity of symptoms relative to tumor growth and treatment course.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 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".