Functional Brain Network of Trait Impulsivity: Whole‐Brain Functional Connectivity Predicts Self‐Reported Impulsivity

Human Brain Mapping, vol. 45, pp. e70059

Abstract

Given impulsivity's multidimensional nature and its implications across various aspects of human behavior, a comprehensive understanding of functional brain circuits associated with this trait is warranted. In the current study, we utilized whole-brain resting-state functional connectivity data of healthy males (n = 156) to identify a network of connections predictive of an individual's impulsivity, as assessed by the Barratt Impulsiveness Scale (BIS)-11. Our participants were selected, in part, based on their self-reported BIS-11 impulsivity scores. Specifically, individuals who reported high or low trait impulsivity scores during screening were selected first, followed by those with intermediate impulsivity levels. This enabled us to include participants with rare, extreme scores and to cover the entire BIS-11 impulsivity spectrum. We employed repeated K-fold cross-validation for feature-selection and used stratified 10-fold cross-validation to train and test our models. Our findings revealed a widespread neural network associated with trait impulsivity and a notable correlation between predicted and observed scores. Feature importance and node degree were assessed to highlight specific nodes and edges within the impulsivity network, revealing previously overlooked key brain regions, such as the cerebellum, brainstem, and temporal lobe, while supporting previous findings on the basal ganglia-thalamo-prefrontal network and the prefrontal-motor strip network in relation to impulsiveness. This deepened understanding establishes a foundation for identifying alterations in functional brain networks associated with dysfunctional impulsivity.

Authors 6

1. Philippa Hüpen corresponding Aachen Department of Psychiatry, Psychotherapy and Psychosomatics Faculty of Medicine

   Jülich Aachen Research Alliance · RWTH Aachen University

   Affiliation as printed

   Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine RWTH Aachen Aachen Germany

   JARA ‐ Translational Brain Medicine Aachen Germany

2. Himanshu Kumar

   Indian Institute of Technology Madras

   Affiliation as printed

   Department of Applied Mechanics and Biomedical Engineering Indian Institute of Technology Madras Chennai India

3. Dario Müller Aachen Department of Psychiatry, Psychotherapy and Psychosomatics Faculty of Medicine

   Jülich Aachen Research Alliance · RWTH Aachen University

   Affiliation as printed

   Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine RWTH Aachen Aachen Germany

   JARA ‐ Translational Brain Medicine Aachen Germany

4. Ramakrishnan Swaminathan

   Indian Institute of Technology Madras

   Affiliation as printed

   Department of Applied Mechanics and Biomedical Engineering Indian Institute of Technology Madras Chennai India

5. Ute Habel Aachen Department of Psychiatry, Psychotherapy and Psychosomatics Faculty of Medicine

   Forschungszentrum Jülich · Jülich Aachen Research Alliance · RWTH Aachen University

   Affiliation as printed

   Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine RWTH Aachen Aachen Germany

   Institute of Neuroscience and Medicine: JARA‐Institute Brain Structure Function Relationship (INM 10) Research Center Jülich Jülich Germany

6. Carmen Weidler corresponding Aachen Department of Psychiatry, Psychotherapy and Psychosomatics Faculty of Medicine

   RWTH Aachen University

   Affiliation as printed

   Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine RWTH Aachen Aachen Germany