Verbal Episodic Memory Impairment in Schizophrenia: A Comparison with Frontal Lobe Lesion Patients
Bibliographic record
Abstract
Schizophrenia (SCZ)-related verbal memory impairment is hypothesized to be mediated, in part, by frontal lobe (FTL) dysfunction. However, little research has contrasted the performance of SCZ patients with that of patients exhibiting circumscribed frontal lesions. The current study compared verbal episodic memory in patients with SCZ and focal FTL lesions (left frontal, LF; right frontal, RF; and bi-frontal, BF) on a four-trial list learning task consisting of three lists of varying semantic organizational structure. Each dependent variable was examined at two levels: scores collapsed across all four trials and learning scores (i.e., trial 4-trial 1). Performance deficits were observed in each patient group across most dependent measures at both levels. Regarding patient group differences, SCZ patients outperformed LF/BF patients (i.e., either learning scores or scores collapsed across trial) on free recall, primacy, primary memory, secondary memory, and subjective organization, whereas they only outperformed RF patients on the semantically blocked list on recency and primary memory. Collectively, these results indicate that the pattern of memory performance is largely similar between patients with SCZ and those with RF lesions. These data support tentative arguments that verbal episodic memory deficits in SCZ may be mediated by frontal dysfunction in the right hemisphere.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".