Dorsal Striatal Functional Connectivity and Repetitive Behavior Dimensions in Children and Youths With Neurodevelopmental Disorders
Bibliographic record
Abstract
BACKGROUND: Impairing repetitive behaviors are one of the core diagnostic symptoms in autism spectrum disorder and obsessive-compulsive disorder, but they also manifest in attention-deficit/hyperactivity disorder. Although the dorsal striatal circuit has been implicated in repetitive behaviors, extensive heterogeneity in and cross-diagnostic manifestations of these behaviors have suggested phenotypic and likely neurobiological heterogeneity across neurodevelopmental disorders (NDDs). METHODS: Intrinsic dorsal striatal functional connectivity was examined in 3 NDDs (autism spectrum disorder, obsessive-compulsive disorder, and attention-deficit/hyperactivity disorder) and typically developing control participants in a large single-cohort sample (N = 412). To learn how diagnostic labels and overlapping behaviors manifest in dorsal striatal functional connectivity measured with functional magnetic resonance imaging, the main and interaction effects of diagnosis and behavior were examined in 8 models (2 seed functional connectivity [caudate and putamen] × 4 sub-behavioral domains [sameness/ritualistic, self-injury, stereotypy, and compulsions]). RESULTS: The obsessive-compulsive disorder group demonstrated distinctive patterns in visual and visuomotor coordination regions compared with the other diagnostic groups. Lower-order repetitive behaviors (self-injury and stereotypy) manifesting across all participants were implicated in regions involved in motor and cognitive control, although the findings did not survive effects of multiple comparisons, suggesting heterogeneity in these behavioral domains. An interaction between self-injurious behavior and an attention-deficit/hyperactivity disorder diagnosis were observed on caudate-cerebellum functional connectivity. CONCLUSIONS: These findings confirmed high heterogeneity and overlapping behavioral manifestations in NDDs and their complex underlying neural mechanisms. A call for diagnosis-free symptom measures that can capture not only observable symptoms and severity across NDDs but also the underlying functions and motivations of such behaviors across diagnoses is needed.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".