Microstructural thalamic changes in schizophrenia: a combined anatomic and diffusion weighted magnetic resonance imaging study
Bibliographic record
Abstract
OBJECTIVE: Several magnetic resonance imaging (MRI) and postmortem studies have supported the role of the thalamus in the pathophysiology of schizophrenia. Interestingly, a recent small diffusion weighted imaging (DWI) study showed abnormal thalamic microstructure in patients with schizophrenia. The objective of our study was to use structural MRI and DWI to explore for the first time both thalamic volumes and integrity in schizophrenia. METHODS: We measured thalamic volumes and apparent diffusion coefficient (ADC) measures bilaterally in 71 patients with schizophrenia, representative of those living in the geographically defined catchment area of South Verona (i.e., 100 000 inhabitants), and 75 individuals without schizophrenia. The presence of the adhesio interthalamica was also detected. RESULTS: We found no significant differences in thalamus size between patients with schizophrenia and participants in the control group, with only a trend for decreased left volumes. No abnormal frequency of the adhesio interthalamica was found. In contrast, significantly increased thalamic ADC values were shown in schizophrenia patients. Age significantly inversely correlated with thalamic volumes in both groups and correlated positively with posterior ADCs in patients with schizophrenia. No significant associations between clinical variables and either volumes or ADC values were reported. CONCLUSION: Widespread altered microstructure integrity and partially preserved thalamus size were found in schizophrenia patients. Therefore, subtle thalamic structural abnormalities are present in schizophrenia, even with maintained volumes. This may result from disruption at the cytoarchitecture level, ultimately supporting corticothalamic misconnection. Future imaging studies should further explore thalamic tissue coherence and its role for cognitive disturbances in patients at high risk for schizophrenia and in first-degree relatives.
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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 | 0.001 |
| 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".