Literature DB >> 30536788

Brain connection pattern under interoceptive attention state predict interoceptive intensity and subjective anxiety feeling.

Xinran Wu1,2, Liang Shi1,2, Dongtao Wei1,2, Jiang Qiu1,2.   

Abstract

Interoception involves the processing of a variety of different types of information ascending from the body. Accumulating evidence has indicated that interoception plays a fundamental role in cognitive and emotional processes, such as anxiety, but how different functional connectivity patterns contribute to emotions and visceral feelings during an interoceptive attention state is still unclear. In the present study, an interoceptive attention task was performed during functional magnetic resonance imaging of healthy subjects, and the participants' subjective ratings of the intensity of interoception and feelings of anxiety were recorded. Several network nodes were selected, based on previous studies, to construct task-dependent functional connectivity patterns, which were processed by support vector regression to predict the corresponding feeling scores. The results showed that for interoception, the cingulo-opercular task control network provided the greatest contribution, whereas the most important feature for anxiety was the connections between the sensorimotor area (SSM) and the salience network (SN). There existed four overlapping connections between the two predictions: two negative connections between the default mode network (DMN) and the SSM, one negative connection between the DMN and the SN, and one positive connection between the ventral attention network and the SN; this overlap might suggest common bodily attention processing that is involved in both interoception and anxiety. This study remediates the lack of network-level biomarkers of interoception and provides a reference at the level of the brain for further understanding anxiety from an interoceptive perspective.
© 2018 Wiley Periodicals, Inc.

Entities:  

Keywords:  SVR; anxiety; biomarker; interoception; prediction; task-dependent network

Mesh:

Year:  2018        PMID: 30536788      PMCID: PMC6865411          DOI: 10.1002/hbm.24488

Source DB:  PubMed          Journal:  Hum Brain Mapp        ISSN: 1065-9471            Impact factor:   5.038


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  2 in total

1.  Brain connection pattern under interoceptive attention state predict interoceptive intensity and subjective anxiety feeling.

Authors:  Xinran Wu; Liang Shi; Dongtao Wei; Jiang Qiu
Journal:  Hum Brain Mapp       Date:  2018-12-07       Impact factor: 5.038

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