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White matter-based brain network topological properties associated with individual impulsivity
Wi Hoon Jung1, Euitae Kim2,3
1Department of Psychology, Gachon University, 1342 Seongnam-daero, Sujeong-gu, Seongnam-si, Gyeonggi-do, 13120, South Korea. jwhnavy@gmail.com.
Scientific Reports
|December 13, 2023
Summary
Individuals with steeper delay discounting (DD), indicating greater impatience, show altered brain network structures in the medial superior prefrontal cortex. Impulsivity measures reveal distinct neural correlates for delay discounting versus motor impulsiveness.
Area of Science:
- Neuroscience
- Cognitive Neuroscience
- Behavioral Economics
Background:
- Delay discounting (DD) is a key indicator of impulsivity, linked to health issues and control disorders.
- Neural correlates of DD are known, but structural brain network associations with individual differences remain understudied.
- It's unclear if self-reported impulsivity (BIS-11) shares neural mechanisms with DD.
Purpose of the Study:
- To investigate associations between delay discounting and structural brain network topology.
- To explore if BIS-11 impulsivity subscales share neural mechanisms with DD.
- To identify potential neural markers for impulsive behaviors.
Main Methods:
- Combined graph theoretical analysis with diffusion tensor imaging.
- Examined structural connectivity network topologies.
- Correlated network properties with delay discounting and BIS-11 scores.
Main Results:
- Steeper delay discounting correlated with decreased small-worldness and increased medial superior prefrontal cortex degree centrality.
- DD was associated with BIS-11 motor impulsiveness, but with distinct neural correlates.
- High motor impulsiveness linked to decreased local efficiency and precentral gyrus degree centrality.
Conclusions:
- Individual differences in delay discounting are associated with specific structural brain network alterations.
- Motor impulsiveness has distinct neural underpinnings compared to delay discounting.
- Findings offer insights into brain characteristics of impulsivity and potential predictive neural markers.
