Linking brain and behavior in ADHD traits: A partial least squares analysis reveals somatosensory-motor
1Faculty of Psychology, Southwest University, Chongqing, 400715, China; Key Laboratory of Cognition and Personality, Ministry of Education, China.
Abstract:
Partial Least Squares (PLS) is a multivariate data-driven approach advantageous in handing high-dimensional data and mitigating multicollinearity, which allow us to include a wide range of variables from multiple models and generate robust results. This study introduces partial least squares (PLS) as a novel application within ADHD research to address its complex symptomatology and delve deeper into the neural basis of ADHD. To achieve this, 231 participants (75 with ADHD traits) were recruited to undergo resting-state functional magnetic resonance imaging (rs-fMRI) acquisition as well as scales (e.g., ASRS, WURS, BIS) and tasks (e.g., ANT, N-back, SST) related to ADHD. Using behavioral PLS, we examined the associations between 24 variables related to ADHD symptoms, executive function, and resting-state functional connectivity (RSFC) in this sample. Results showed that a significant latent component explained 27% of the RSFC-behavior covariance, characterized by reduced connectivity within the somatomotor network (SMN) and increased connectivity between the SMN and subcortical regions. Further analysis revealed that the SMN dysconnectivity, recognized by PLS, mediated the effect of cool executive function on inattention. These findings suggest that the SMN might represent a neural correlate of ADHD traits and offer new insights and targets for future neuroregulatory interventions.
