ArticleHuman brain mapping2024
Functional Brain Network of Trait Impulsivity: Whole-Brain Functional Connectivity Predicts Self-Reported Impulsivity.
Article in Human brain mapping, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed.
- Neural representations of dynamical state and trait impulsivity in individuals at risk for internet gaming disorder.Molecular psychiatry · 2026Article
- Neuroanatomy reflects individual variability in impulsivity in youth.Molecular psychiatry · 2026Article
- A view-engage-predict framework for enhancing brain-behavior mapping with naturalistic movie-watching fMRI.Communications biology · 2026Article
- Brain-Behavior Relationships: Neural Mechanisms of Impulsivity and Compulsivity in Neuropsychiatric Disorders.Cognitive and behavioral neurology : official journal of the Society for Behavioral and Cognitive Neurology · 2025Review
- Impact of impulsivity on the relationship of the brain structures with school performance.NPJ science of learning · 2025Article
- Resting-State Sensory-Motor Connectivity between Hand and Mouth as a Neural Marker of Socioeconomic Disadvantage, Psychosocial Stress, Cognitive Difficulties, Impulsivity, Depression, and Substance Use in Children.Journal of cellular neuroscience · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
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.
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