Hippocampus volume and episodic memory in schizophrenia
Bibliographic record
Abstract
Previous studies of schizophrenia have suggested a linkage between neuropsychological (NP) deficits and hippocampus abnormality. The relationship between hippocampus volume and NP functioning was investigated in 24 patients with chronic schizophrenia and 24 matched healthy controls. Overall intracranial, white and gray matter, and anterior (AH) and posterior (PH) hippocampus volumes were assessed from magnetic resonance images (MRI). NP domains of IQ, attention, and executive function were also evaluated with respect to volumetric measures. It was hypothesized that AH and PH volumes and episodic memory scores would be positively associated in controls and that the schizophrenia group would depart from this normative pattern. NP functioning was impaired overall and AH volume was smaller in the schizophrenia group. In the controls, the hippocampus-memory relationships involved AH and PH, and correlations were significant for verbal memory measures. In the schizophrenia group, positive correlations were constrained to PH. Negative correlations emerged between AH and verbal and visual memory measures. For both groups, cortical volume negatively correlated with age, but a negative correlation between age and hippocampus volume was found only in the schizophrenia group. In this sample of adults with schizophrenia, atypical relationships between regional hippocampus volumes and episodic memory ability were found, as was an atypical negative association between hippocampus volume and age.
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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 | 0.000 | 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".