Meta-Connectomic Analysis Reveals Commonly Disrupted Functional Architectures in Network Modules and Connectors across Brain Disorders
Why this work is in the frame
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Bibliographic record
Abstract
Neuropsychiatric disorders are increasingly conceptualized as disconnection syndromes that are associated with abnormal network integrity in the brain. However, whether different neuropsychiatric disorders show commonly dysfunctional connectivity architectures in large-scale brain networks remains largely unknown. Here, we performed a meta-connectomic study to identify disorder-related functional modules and brain regions by combining meta-analyses of 182 published resting-state functional MRI studies in 11 neuropsychiatric disorders and graph-theoretical analyses of 3 independent resting-state functional MRI datasets with healthy and diseased populations (Alzheimer's disease and major depressive disorder [MDD]). Three major functional modules, the default mode, frontoparietal, and sensorimotor networks were commonly abnormal across disorders. Moreover, most of the disorders preferred to target the network connector nodes that were primarily involved in intermodule communications and multiple cognitive components. Apart from these common dysfunctions, different brain disorders were associated with specific alterations in network modules and connector regions. Finally, these meta-connectomic findings were confirmed by two empirical example cases of Alzheimer's disease and MDD. Collectively, our findings shed light on the shared biological mechanisms of network dysfunctions of diverse disorders and have implications for clinical diagnosis and treatment from a network perspective.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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