Mindscape Collective is now The Consciousness Library. Same library, new name. You may need to sign in again. About the change
Skip to content

The neural signature of inner peace: morphometric differences between high and low accepters

Alessandro Grecucci, Parisa Ahmadi Ghomroudi, Bianca Monachesi, Irene Messina

arXiv Preprint Archive October 20, 2023 via arXiv

Summary

AI-generated from the abstract

People who frequently use acceptance as an emotion regulation strategy show distinct brain structure and personality traits compared to those who rarely use it. Using a machine learning approach, the authors identified two brain networks that differ between high and low accepters: one network (overlapping with the Default Mode Network) showed decreased gray and white matter concentration, while another (related to the Central Executive Network) showed increased concentration. High accepters also scored higher on openness to experience. The findings suggest that dispositional acceptance is associated with measurable neural and psychological differences.

Study at a glance

Characteristics Observational cohort Peer reviewed
Sample size 128
Population High accepters (N=50) and low accepters (N=78) selected from a larger sample
Keywords Q-bio.nc
Key finding Two covarying gray matter and white matter networks separate high from low accepters, and high accepters display higher openness to experience.

Abstract

Acceptance is an adaptive emotion regulation strategy characterized by an open and non-judgmental attitude toward mental and sensory experiences. While a few studies have investigated the neural correlates of acceptance in task-based fMRI studies, a gap remains in the scientific literature in dispositional use of acceptance, and how this is sedimented at a structural level. Therefore, the aim of the present study is to investigate the neural and psychological differences between infrequent acceptance users (i.e., low accepters) and frequent users (i.e., high accepters). Another question is whether high and low accepters differ in personality traits and emotional intelligence. To this aim, we applied, for the first time, a data fusion unsupervised machine learning approach (mCCA-jICA) to the gray matter (GM) and white matter (WM) of high accepters (N = 50), and low accepters (N = 78) to possibly find joint GM-WM differences in both modalities. Our results show that two covarying GM-WM networks separate high from low accepters. The first network showed decreased GM-WM concentration in a fronto-temporal-parietal circuit largely overlapping with the Default Mode Network, while the second network showed increased GM-WM concentration in portions of the orbito-frontal, temporal, and parietal areas, related to a Central Executive Network. At the psychological level, the high accepters display higher openness to experience compared to low accepters. Overall, our findings suggest that high accepters compared to low accepters differ in neural and psychological mechanisms. These findings confirm and extend previous studies on the relevance of acceptance as a strategy associated with well-being.

Comments

No comments yet.

Log in to comment