EEG Microstates in Social and Affective Neuroscience.

IF 2.3 3区 医学 Q3 CLINICAL NEUROLOGY Brain Topography Pub Date : 2024-07-01 Epub Date: 2023-07-31 DOI:10.1007/s10548-023-00987-4
Bastian Schiller, Matthias F J Sperl, Tobias Kleinert, Kyle Nash, Lorena R R Gianotti
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Abstract

Social interactions require both the rapid processing of multifaceted socio-affective signals (e.g., eye gaze, facial expressions, gestures) and their integration with evaluations, social knowledge, and expectations. Researchers interested in understanding complex social cognition and behavior face a "black box" problem: What are the underlying mental processes rapidly occurring between perception and action and why are there such vast individual differences? In this review, we promote electroencephalography (EEG) microstates as a powerful tool for both examining socio-affective states (e.g., processing whether someone is in need in a given situation) and identifying the sources of heterogeneity in socio-affective traits (e.g., general willingness to help others). EEG microstates are identified by analyzing scalp field maps (i.e., the distribution of the electrical field on the scalp) over time. This data-driven, reference-independent approach allows for identifying, timing, sequencing, and quantifying the activation of large-scale brain networks relevant to our socio-affective mind. In light of these benefits, EEG microstates should become an indispensable part of the methodological toolkit of laboratories working in the field of social and affective neuroscience.

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社会和情感神经科学中的脑电图微状态。
社会交往需要快速处理多方面的社会情感信号(如眼神、面部表情和手势),并将其与评价、社会知识和期望结合起来。有兴趣了解复杂社会认知和行为的研究人员面临着一个 "黑箱 "问题:在感知和行动之间迅速发生的潜在心理过程是什么,为什么会存在如此巨大的个体差异?在这篇综述中,我们将脑电图(EEG)微观状态作为一种强大的工具,用于研究社会情感状态(例如,在特定情况下处理某人是否需要帮助)和确定社会情感特征(例如,帮助他人的一般意愿)的异质性来源。脑电图微状态是通过分析随时间变化的头皮场图(即头皮上的电场分布)来确定的。这种数据驱动、不依赖参照物的方法可以识别、计时、排序和量化与我们的社会情感心理相关的大规模大脑网络的激活。鉴于这些优势,脑电图微状态应成为社会和情感神经科学领域实验室方法工具包中不可或缺的一部分。
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来源期刊
Brain Topography
Brain Topography 医学-临床神经学
CiteScore
4.70
自引率
7.40%
发文量
41
审稿时长
3 months
期刊介绍: Brain Topography publishes clinical and basic research on cognitive neuroscience and functional neurophysiology using the full range of imaging techniques including EEG, MEG, fMRI, TMS, diffusion imaging, spectroscopy, intracranial recordings, lesion studies, and related methods. Submissions combining multiple techniques are particularly encouraged, as well as reports of new and innovative methodologies.
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