Neural synchrony in patients with a first episode of schizophrenia: tracking relations with grey matter and symptom profile
Bibliographic record
Abstract
BACKGROUND: Although schizophrenia has been characterized by disruptions to neural synchrony, it remains unknown whether these disturbances are related to symptoms and loss of grey matter. We examined relations between 40 Hz Gamma band synchrony and grey matter in patients with schizophrenia at first episode and after 2.5 years. METHODS: From an initial recruitment of 35 medicated patients with a first episode of schizophrenia, 25 patients completed clinical and oddball task-elicited Gamma synchrony within 3 months of health service contact and again after 2.5 years, 23 completed magnetic resonance imaging (MRI) at these time points, and 13 completed all sessions. We compared patients with 35 matched healthy controls. We identified early (0-150 ms) and late (250-500 ms) peaks in Gamma synchrony locked to oddball targets, and we analyzed MRI data using voxel-based morphometry. We evaluated group and test-retest differences using repeated-measures analyses of variance. RESULTS: Compared with controls, at first contact, patients with a first episode of schizophrenia showed a disruption to the laterality of early Gamma synchrony and global reduction in late Gamma synchrony, with a corresponding loss of fronto-temporal-parietal grey matter. Gamma synchrony was increased at follow-up among patients with a first episode of schizophrenia. It related negatively to further loss of grey matter, but positively to improvement in reality distortion symptoms. These relations could not be explained by medication dose. LIMITATIONS: Our study did not include unmedicated patients or normative follow-up testing. CONCLUSION: Gamma synchrony may track the progression of schizophrenia from first episode. An increase in Gamma synchrony over time might reflect an attempt to adapt to a progressive loss of cortical grey matter and associated changes in cognitive and emotional function.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".