Functional brain rewiring and altered cortical stability in ulcerative colitis
Bibliographic record
Abstract
Despite recent advances, there is still a major need to better understand the interactions between brain function and chronic gut inflammation and its clinical implications. Alterations in executive function have previously been identified in several chronic inflammatory conditions, including inflammatory bowel diseases. Inflammation-associated brain alterations can be captured by connectome analysis. Here, we used the resting-state fMRI data from 222 participants comprising three groups (ulcerative colitis (UC), irritable bowel syndrome (IBS), and healthy controls (HC), N = 74 each) to investigate the alterations in functional brain wiring and cortical stability in UC compared to the two control groups and identify possible correlations of these alterations with clinical parameters. Globally, UC participants showed increased functional connectivity and decreased modularity compared to IBS and HC groups. Regionally, UC showed decreased eigenvector centrality in the executive control network (UC < IBS < HC) and increased eigenvector centrality in the visual network (UC > IBS > HC). UC also showed increased connectivity in dorsal attention, somatomotor network, and visual networks, and these enhanced subnetwork connectivities were able to distinguish UC participants from HCs and IBS with high accuracy. Dynamic functional connectome analysis revealed that UC showed enhanced cortical stability in the medial prefrontal cortex (mPFC), which correlated with severe depression and anxiety-related measures. None of the observed brain changes were correlated with disease duration. Together, these findings are consistent with compromised functioning of networks involved in executive function and sensory integration in UC.
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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 | 0.000 |
| 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) | 0.001 | 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".