Feature overlap in transdiagnostic connectome-based models of sustained attention and autism symptoms

Sustained attention is an important neurobiological process. Difficulties with attention play a key role in neurodevelopmental disorders, such as attention-deficit/hyperactivity disorder (ADHD) and autism. Here, we identified functional connections consistently associated with sustained attention across datasets, participant populations, and fMRI scan types. We interrogated five transdiagnostic, previously published connectome-based models predicting attention and autistic phenotypes. All models were related to sustained attention, including in samples comprising participants with autism. As expected, we observed that models predicting attention phenotypes shared more similar features with each other than models predicting autism symptoms. Interestingly, we observed no statistically significant model similarities when considering factors such as age, functional run type, or diagnosis. This suggests that functional connectivity patterns predicting individual differences in behavior tend to be phenotype-specific, regardless of age or clinical diagnosis. Our results underscore the importance of searching for consistent markers of transdiagnostic sustained attention phenotypes in neurodevelopmental conditions.