Recollection memory deficits in patients with major depressive disorder predicted by past depressions but not current mood state or treatment status
Bibliographic record
Abstract
BACKGROUND: Neuropsychological studies have suggested that memory systems reliant on medial temporal lobe structures are impaired in patients with depression. There is less data regarding whether this impairment is specific to recollection memory systems, and whether clinical features predict impairment. This study sought to address these issues. METHOD: A computerized process-dissociation memory task was utilized to dissociate recollection and habit memory in 40 patients with past or current major depression and 40 age, sex and IQ matched non-psychiatric control subjects. The Cognitive Failures Questionnaire was used to assess patients' perceptions of day-to-day memory failures. RESULTS: Patients had impaired recollection memory (t = 4.7, P < 0.001), but no impairment in habit memory when compared to controls. Recollection memory performance was not predicted by indices of current mood state, but was predicted by self-assessments of impairment (beta = -0.33; P = 0.008) and past number of depressions (beta = -0.41; P = 0.001). There was no evidence that standard therapy with antidepressant medication either improved or worsened memory performance. CONCLUSIONS: The results confirm that patients with multiple past depressions have reduced function on recollection memory tasks, but not on habit memory performance. The memory deficits were independent of current mood state but related to past course of illness and significant enough that patients detected impairment in day-to-day memory function.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".