Lesion network localization of functional and somatic symptoms
Bibliographic record
Abstract
Functional and somatic symptoms with no detectable structural abnormalities are a common cause of disability. These symptoms are widely believed to have neuropsychiatric origins, and thus may respond to network-targeted brain stimulation. To derive a network-based target, we studied functional and somatic disability after focal brain lesions. Using a normative human connectome database (n=1000), we mapped the circuitry functionally connected to lesions that selectively influence such symptoms in two datasets. First, in ischemic stroke (n=101), we mapped a network causally associated with self-reported functional disability, independent of individual measures of disability. In an independent sample with penetrating head trauma (n=181), lesions connected to our network were associated with greater somatic concern (p=0.001). Across both datasets, functional and somatic symptoms were most associated with lesions connected to the orbitofrontal cortex (pFWE<0.01) and dorsal anterior cingulate, which we propose as potential brain stimulation targets.
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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 | 0.002 |
| 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) | 0.003 | 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".