EPA-0448 – Failure of de-activation in the default mode network: a trait marker for schizophrenia?
Bibliographic record
Abstract
Background Functional imaging abnormality has been proposed as a trait marker or endophenotype for schizophrenia. Although studies examining dorsolateral prefrontal cortex activation in relatives of schizophrenic patients have not had consistent findings, failure of de-activation in the medial frontal cortex may be a promising alternative candidate. Method Twenty-nine patients with schizophrenia, 29 of their siblings and 58 healthy controls underwent fMRI during performance of the n-back working memory task. An ANOVA was fitted to individual whole-brain maps from each set of patient-relative-matched pair of controls. Clusters of significant difference among the groups were used as regions-of-interest to compare mean activations/de-activations between them. Results Four clusters of significant difference were found. The schizophrenic patients, but not the relatives, showed reduced activation compared to the controls in the left lateral frontal cortex, the left basal ganglia and the cerebellum. In contrast, both the patients and the relatives showed significantly reduced de-activation compared to the healthy controls in the medial frontal cortex, with evidence of an intermediate pattern in the relatives. Failure of de-activation was not associated with schizotypy scores or presence of psychotic experiences in the relatives. Conclusions Both schizophrenic patients and their relatives show altered task-related de-activation in the medial frontal cortex. This in turn suggests that default mode dysfunction may function as a trait marker or endophenotype for schizophrenia. Table. 1 . Demographic characteristics of the patinents (n = 29), healthy relatives (n = 29) and controls (n = 58) Schizophrenic patients (n = 29) Healthy relatives (n = 29) Controls (n = 58) p value Sex (male/female) 7/22 12/17 19/39 p = 0.38 Age (SD) (Range) 35.79 (9.55) (19-57) 37-31 (9.03) (19-52) 36.86 (9.91) (19-60) p = 0.82 Pre-morbid IQ (TAP) (SD) (Range) 94.92 (9.56) (77-110) 101.96 (7.80) (83-112) 100.05 (8.09) (81-114) p = 0.03 Current IQ score (WAIS-III score) 92.08 (14.17) (63-121) 108.76 (11.29) (81-122) 104.27 (12.47) (72-128) SCZ (SD) (Range) SCZ GAF score (SD) (Range) 52.41 (12.07) (35-75) - - PANSS score (SD) (Range) 66.55 (14.79) (35-96) - - Positives symptoms 15.44 (4.53) (8-26) Negative symptoms 20.88 (7.33) (7-30) General symptoms 30.92 (8.08) (17-50) Download : Download full-size image Fig. 1 . Brain regions showing a significant effect in the 2-back versus baseline contrast in controls (a), healthy first-degree relatives (b) and in schizophrenic patients (c) Yellow indicates a positive association (activation) with the task. Blue indicates areas where the task led to a decrease in the blood oxygenation level-dependent (BOLD) response (deactivation). Numbers refer to Montreal Neurological Institute (MNI) z coordinates of the slice shown. The right side of each image represents the right side of the brain. Results are thresholdedd at z = 3.5 and corrected for multiple comparisons across space using Gaussian random field methods. Download : Download full-size image Fig. 2 . Clusters of difference between schizophrenic patients (SCZ, n = 29), their first-degree healthy relatives (REL, n = 29) and healthy controls (CTRL, n = 58) (a) Left caudate gryus, globus pallidus and putamen activation, (b) bilateral cerebellar activation, (c) left dorsolateral activation and (d) anterior cingulate deactivation. The right side of each image represents the right side of the brain. Whole brain results are corrected for multiple comparisons across space using Gaussian random field methods. Analyses within ROIs were FDR-corrected for multiple comparisons.
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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 | 0.000 |
| 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) | 0.004 | 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".