Functional connectivity abnormalities of the long-axis hippocampal subregions in schizophrenia during episodic memory
Why this work is in the frame
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Bibliographic record
Abstract
Past evidence suggests that hippocampal subregions, namely the anterior and posterior parts, may be engaged in distinct networks underlying the memory functions which may be altered in patients with schizophrenia. However, of the very few studies that have investigated the hippocampal longitudinal axis subdivisions functional connectivity in patients with schizophrenia, the majority was based on resting-state data, and yet, none aimed to examine these during an episodic memory task. A total of 41 patients with schizophrenia and 45 healthy controls were recruited for a magnetic resonance imaging protocol in which they performed an explicit memory task. Seed-based functional connectivity analysis was employed to assess connectivity abnormalities between hippocampal subregions and voxel-wise connectivity targets in patients with schizophrenia. We observed a significantly reduced connectivity between the posterior hippocampus and regions from the default mode network, but increased connectivity with the primary visual cortex, in patients with schizophrenia compared to healthy subjects. Increased connectivity between the anterior hippocampus and anterior temporal regions also characterized patients with schizophrenia. In the current study, we provided evidence and support for studying hippocampal subdivisions along the longitudinal axis in schizophrenia. Our results suggest that the abnormalities in hippocampal subregions functional connectivity reflect deficits in episodic memory that may be implicated in the pathophysiology of schizophrenia.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it