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Related Experiment Video

Updated: Aug 18, 2025

Brain Imaging Investigation of the Neural Correlates of Emotion Regulation

Brain Imaging Investigation of the Neural Correlates of Emotion Regulation

Published on: August 26, 2011

Decoding individual differences in expressing and suppressing anger from structural brain networks: A supervised

Alessandro Grecucci¹, Sara Sorella², Jennifer Consolini²

¹Clinical and Affective Neuroscience Lab, Cli.A.N. Lab, Department of Psychology and Cognitive Sciences - DiPSCo, University of Trento, Rovereto, Italy; Center for Medical Sciences, CISMed, University of Trento, Trento, Italy.

Behavioural Brain Research

|December 5, 2022

Summary

This summary is machine-generated.

Brain structure differences predict how individuals express or suppress anger. Grey matter patterns in specific brain networks correlate with anger expression and suppression abilities, aiding in understanding anger regulation.

Keywords:

Anger Anger expression Anger suppression Brain networks Kernel Ridge Regression Machine Learning

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Area of Science:

Neuroscience
Psychology
Brain Imaging

Background:

Anger comprises distinct components: state anger, trait anger, anger expression (anger-out), anger suppression (anger-in), and anger control.
Individual differences in anger expression and suppression are crucial for daily anger management and life outcomes.

Purpose of the Study:

To investigate if specific brain grey matter patterns can predict individual differences in anger expression and suppression.
To identify neural networks associated with distinct anger regulation strategies.

Main Methods:

Utilized Kernel Ridge Regression, a supervised machine learning technique.
Analyzed grey matter concentration in 212 healthy subjects.
Predicted individual scores for anger expression and suppression.

Main Results:

Grey matter patterns linked to the Default-Mode Network and Salience Network predicted anger suppression.
A distinct neural circuit, involving subcortical and fronto-temporal regions, predicted anger expression.
Demonstrated that specific brain networks' grey matter features correlate with distinct anger components.

Conclusions:

Individual differences in anger suppression and expression are associated with specific grey matter patterns in distinct brain networks.
Findings contribute to understanding the neural underpinnings of anger regulation and individual differences.
Highlights the potential of neuroimaging and machine learning in dissecting complex emotional processes.