F95. DISRUPTION IN HIPPOCAMPAL-PREFRONTAL WHITE MATTER PATHWAYS AND MEMORY PERFORMANCE ACROSS STAGES OF SCHIZOPHRENIA-SPECTRUM DISORDER
Bibliographic record
Abstract
Memory impairment is a consistent finding in the schizophrenia literature, and it is possible that deficits are the result of disrupted connectivity between key memory-related brain regions – namely, the hippocampus and the prefrontal cortex. However, while previous studies have identified relationships between memory performance and hippocampal and cortical grey matter volumes, few studies have investigated relationships between memory performance and measures of white matter (WM) connectivity and integrity. The current study therefore examined whether deficits in episodic and working memory in early and established psychosis were related to (1) disrupted hippocampal-prefrontal WM connectivity, and (2) reduced integrity in key memory-related WM tracts. Measurements of episodic memory (CANTAB Paired Associates Learning) and working memory (CANTAB Spatial Working Memory) were obtained for 51 individuals with a chronic schizophrenia-spectrum disorder, 28 individuals with first-episode psychosis (FEP), 52 older healthy controls, and 27 younger healthy controls. Probabilistic tractography was used to map trajectories of hippocampal-prefrontal WM tracts in each individual, with prefrontal targets including the orbitofrontal, dorsolateral prefrontal, medial prefrontal, and anterior cingulate cortices. Inter-individual variation in the connectivity strength (i.e. streamline counts) was then examined in relation to memory performance. Additionally, two measures of WM integrity (i.e. tract-averaged fractional anisotropy [FA] and mean diffusivity [MD]) across four key memory-related WM tracts (dorsal and ventral cingulum, fornix, uncinate fasciculus) were also examined in relation to memory performance. Both chronic and FEP patients had impaired episodic memory, however, only chronic patients had impaired working memory. In terms of hippocampal-prefrontal streamline counts, these were reduced in chronic patients compared to healthy controls, but not in FEP patients. FEP patients also did not differ from chronic. No relationships were observed between memory performance and hippocampal-prefrontal WM streamline counts. Both chronic and first-episode patients had reduced WM integrity compared to their respective healthy control groups, with the greatest reductions observed in the chronic patients, and these reductions were further related to memory performance. Specifically, in first-episode patients, poorer working memory performance was associated with reduced fractional anisotropy in the dorsal cingulum bilaterally. In chronic patients, poorer episodic memory and spatial working memory were associated with increased mean diffusivity in the left fornix. While reduced hippocampal-prefrontal connectivity (as measured by number of connections) was observed in individuals with chronic schizophrenia, such deficits were not associated with memory performance. Both FEP and chronic patients had reduced WM integrity (indexed by FA and MD) relative to healthy controls, and memory impairment was associated with reduced WM integrity in key memory-related tracts in both patient groups. These findings suggest that WM integrity in specific WM tracts, including the fornix and the cingulum bundle, might be more critical for memory performance in individuals with psychotic disorders than the number of connections between the hippocampus and the prefrontal cortex.
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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 | 0.000 | 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) | 0.003 | 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".