期刊
NEUROIMAGE
卷 276, 期 -, 页码 -出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2023.120205
关键词
Self-prioritization effect; Resting state; fMRI; Functional connectivity; Machine learning
Recent research supports a fundamental self hypothesis, suggesting that the self is a baseline function of the brain that regulates cognitive processing and behavior. Understanding this hypothesis can help identify the emergence of self-biased behaviors and predict the influence of brain signals at rest on such behaviors.
Although the self has traditionally been viewed as a higher-order mental function by most theoretical frame-works, recent research advocates a fundamental self hypothesis , viewing the self as a baseline function of the brain embedded within its spontaneous activities, which dynamically regulates cognitive processing and subsequently guides behavior. Understanding this fundamental self hypothesis can reveal where self-biased behaviors emerge and to what extent brain signals at rest can predict such biased behaviors. To test this hypothesis, we inves-tigated the association between spontaneous neural connectivity and robust self-bias in a perceptual matching task using resting-state functional magnetic resonance imaging (fMRI) in 348 young participants. By decoding whole-brain connectivity patterns, the support vector regression model produced the best predictions of the mag-nitude of self-bias in behavior, which was evaluated via a nested cross-validation procedure. The out-of-sample generalizability was further authenticated using an external dataset of older adults. The functional connectiv-ity results demonstrated that self-biased behavior was associated with distinct connections between the default mode, cognitive control, and salience networks. Consensus network and computational lesion analyses further re-vealed contributing regions distributed across six networks, extending to additional nodes, such as the thalamus, whose role in self-related processing remained unclear. These results provide evidence that self-biased behavior derives from spontaneous neural connectivity, supporting the fundamental self hypothesis. Thus, we propose an integrated neural network model of this fundamental self that synthesizes previous theoretical models and por-trays the brain mechanisms by which the self emerges at rest internally and regulates responses to the external environment.
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