交互感受
心理学
神经影像学
脑岛
岛叶皮质
神经科学
扣带回前部
认知心理学
意识的神经相关物
大脑活动与冥想
功能磁共振成像
神经功能成像
前额叶皮质
默认模式网络
认知
脑电图
感知
作者
Norman A. S. Farb,Zoey Zuo,Cynthia Price
出处
期刊:ENeuro
[Society for Neuroscience]
日期:2023-06-01
卷期号:10 (6): ENEURO.0088-23.2023
被引量:6
标识
DOI:10.1523/eneuro.0088-23.2023
摘要
Interoception, the representation of the body's internal state, serves as a foundation for emotion, motivation, and wellbeing. Yet despite its centrality in human experience, the neural mechanisms of interoceptive attention are poorly understood. The Interoceptive/Exteroceptive Attention Task (IEAT) is a novel neuroimaging paradigm that compares behavioral tracking of the respiratory cycle (Active Interoception) to tracking of a visual stimulus (Active Exteroception). Twenty-two healthy participants completed the IEAT during two separate scanning sessions (N = 44) as part of a randomized control trial of mindful awareness in body-oriented therapy (MABT). Compared with Active Exteroception, Active Interoception deactivated somatomotor and prefrontal regions. Greater self-reported interoceptive sensibility (MAIA scale) predicted sparing from deactivation within the anterior cingulate cortex (ACC) and left-lateralized language regions. The right insula, typically described as a primary interoceptive cortex, was only specifically implicated by its deactivation during an exogenously paced respiration condition (Active Matching) relative to self-paced Active Interoception. Psychophysiological interaction (PPI) analysis characterized Active Interoception as promoting greater ACC connectivity with lateral prefrontal and parietal regions commonly referred to as the dorsal attention network (DAN). In contrast to evidence relating accurate detection of liminal interoceptive signals such as the heartbeat to anterior insula activity, interoceptive attention toward salient signals such as the respiratory cycle may involve reduced cortical activity but greater ACC-DAN connectivity, with greater sensibility linked to reduced deactivation within the ACC and language-processing regions.
科研通智能强力驱动
Strongly Powered by AbleSci AI