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The trait and state negative affect can be separately predicted by stable and variable resting-state functional connectivity

Published online by Cambridge University Press:  13 July 2020

Yu Li ,
Kaixiang Zhuang ,
Zili Yi ,
Dongtao Wei ,
Jiangzhou Sun  and
Jiang Qiu Open the ORCID record for Jiang Qiu [Opens in a new window]
Yu Li
Affiliation:
Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China Department of Psychology, Southwest University, Chongqing, China
Kaixiang Zhuang
Affiliation:
Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China Department of Psychology, Southwest University, Chongqing, China
Zili Yi
Affiliation:
Beibei Mental Health Center, Chongqing400715, China
Dongtao Wei
Affiliation:
Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China Department of Psychology, Southwest University, Chongqing, China
Jiangzhou Sun
Affiliation:
Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China Department of Psychology, Southwest University, Chongqing, China
Jiang Qiu*
Affiliation:
Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China Department of Psychology, Southwest University, Chongqing, China Southwest University Branch, Collaborative Innovation Center of Assessment Toward Basic Education Quality at Beijing Normal University
*
Author for correspondence: Jiang Qiu, E-mail: qiuj318@swu.edu.cn
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Abstract

Background

Many emotional experiences such as anxiety and depression are influenced by negative affect (NA). NA has both trait and state features, which play different roles in physiological and mental health. Attending to NA common to various emotional experiences and their trait-state features might help deepen the understanding of the shared foundation of related emotional disorders.

Methods

The principal component of five measures was calculated to indicate individuals' NA level. Applying the connectivity-based correlation analysis, we first identified resting-state functional connectives (FCs) relating to NA in sample 1 (n = 367), which were validated through an independent sample (n = 232; sample 2). Next, based on the variability of FCs across large timescale, we further divided the NA-related FCs into high- and low-variability groups. Finally, FCs in different variability groups were separately applied to predict individuals' neuroticism level (which is assumed to be the core trait-related factor underlying NA), and the change of NA level (which represents the state-related fluctuation of NA).

Results

The low-variability FCs were primarily within the default mode network (DMN) and between the DMN and dorsal attention network/sensory system and significantly predicted trait rather than state NA. The high-variability FCs were primarily between the DMN and ventral attention network, the fronto-parietal network and DMN/sensory system, and significantly predicted the change of NA level.

Conclusions

The trait and state NA can be separately predicted by stable and variable spontaneous FCs with different attentional processes and emotion regulatory mechanisms, which could deepen our understanding of NA.

Keywords

Negative affectresting-state functional connectivitystate-traitvariability
Type
Original Article
Information
Psychological Medicine , Volume 52 , Issue 5 , April 2022 , pp. 813 - 823
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Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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Footnotes

*

These authors contributed equally to this work.

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