Mapping the Brain Network of Conduct Disorder: Heterogeneous fMRI findings converge on a Common Brain Circuit
Bibliographic record
Abstract
Conduct disorder (CD) is among the most prevalent and burdensome disorders in early adolescence. Over the past decade, there has been growing interest in identifying reliable and localized neurobiological markers of conduct disorder (CD). However, recent meta-analyses have highlighted the weak reliability of these so-called markers, thereby limiting the ability to draw firm conclusions. Using normative network mapping (598 healthy subjects), we rather sought to investigate whether the heterogeneous findings across studies may map unto a common brain network. A meta-analysis of 38 fMRI studies involving adolescents with a CD (932 cases, 975 controls) was first conducted and showed only a very weak spatial convergence in brain activity alterations in the anterior temporal lobe (5 out of 38 studies). In turn, network mapping revealed that findings across studies show a consistent connectivity pattern across the whole brain, with regional overlap reaching up to 94.7% (36 out of 38 studies). This network was primarily driven by functional connectivity of brainstem nuclei, subcortical structures (i.e., thalamus, ventral striatum), cingulate cortex (i.e., anterior to posterior midcingulate), superior temporal sulcus, and visual cortices. We further describe the neurochemicals and genetic markers of this CD-Network with emphasis on midbrain serotoninergic, dopaminergic and cholinergic projections. Our findings suggest that our understanding of the neurobiological markers of CD could be enhanced by viewing the brain as a complex interconnected system rather than reducing its complexity to a limited number of brain structures. More importantly, this CD-Network may serve as evidence that the various theories of CD can be reconciled rather than seen as conflicting.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".