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Spatiotemporal dynamics of the human emotion network

Spatiotemporal dynamics of the human emotion network
人类情感网络的时空动态
批准号:
10650379
负责人:
Edward Chang
金额:
$66.99万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-09-10 至 2026-06-30

项目摘要

项目成果

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中文摘要
翻译
摘要 情感症状是神经精神障碍的共同特征,其反映了分布在神经系统中的功能障碍。 支持情绪的大脑网络。一个单一情感网络的异常功能是如何构成一个广泛的 一系列的情感症状,如抑郁和焦虑,还没有得到很好的理解。由前壁固定 扣带皮层和腹侧前额叶,情绪网络对大量的情感刺激做出反应。一个更 对情绪网络如何产生情绪以及非典型情绪网络如何产生情绪的复杂理解, 功能与情感障碍有关-将是推进当前神经解剖模型的关键, 神经精神障碍颅内脑电图(iEEG)提供了神经元的直接估计, 群体,可用于以毫秒级绘制情感网络的时空动态 分辨率虽然功能性神经影像学研究发现神经分化的证据很少 在情绪中,这些研究缺乏时空和光谱分辨率来确定情绪是否 都有独特的神经信号拟议项目的总体目标是阐明如何 情绪网络动态与伴随的行为、自主和经验变化有关 情绪,并探讨情绪网络功能障碍与情感症状的关系。从解剖学上讲- 情绪网络功能障碍的特定生物标志物可用于指导新治疗的开发, 监测症状和治疗反应,并改进情感症状的动物模型。我们将研究 100例接受癫痫发作定位手术的难治性癫痫患者。植入iEEG电极的受试者 情绪网络中的神经元将在多天的住院期间接受连续的神经和视频记录。 受试者在整个住院期间自发表现出的自然主义情感行为, 对标准化情感刺激的反应,以及电刺激后的情绪反应。 情感网络枢纽将被量化。我们将研究情绪网络中心的活动是如何变化的 以及情感网络特性如何使一些人更容易受到情感的影响。 比其他症状。我们将实现三个关键目标。在目标1中,我们将确定情绪网络活动如何 与自然主义情感行为有关。在目标2中,我们将揭示离散神经元的独特神经特征。 情绪及其与基于任务的情绪反应测量的关系。在目标3中,我们将探讨 情绪网络中枢的电刺激改变网络活动并改变情绪、情绪和焦虑。 通过利用多学科的方法,拟议的项目有可能提出关于 情绪的神经起源,并推进情绪和情感的神经生物学基础的当前模型 症状
英文摘要
ABSTRACT Affective symptoms are a common feature of neuropsychiatric disorders that reflect dysfunction in a distributed brain network that supports emotion. How aberrant functioning in a single emotion network underlies a wide range of affective symptoms, such as depression and anxiety, is not well understood. Anchored by the anterior cingulate cortex and ventral anterior insula, the emotion network responds to numerous affective stimuli. A more sophisticated understanding of how the emotion network produces emotions—and how atypical emotion network functioning relates to affective symptoms—will be critical for advancing current neuroanatomical models of neuropsychiatric disorders. Intracranial electroencephalography (iEEG) provides direct estimates of neuronal populations and can be used to map the spatiotemporal dynamics of the emotion network at a millisecond-level resolution. Although functional neuroimaging studies have uncovered little evidence for neural differentiation among emotions, these studies lack the spatiotemporal and spectral resolution to determine whether emotions are characterized by unique neural signatures. The overall goals of the proposed project are to elucidate how emotion network dynamics relate to the behavioral, autonomic, and experiential changes that accompany emotions and to investigate how emotion network dysfunction relates to affective symptoms. Anatomically- specific biomarkers of emotion network dysfunction could be used to guide development of novel treatments, monitor symptoms and treatment response, and improve animal models of affective symptoms. We will study 100 patients with intractable epilepsy undergoing surgery for seizure localization. Subjects with iEEG electrodes within the emotion network will undergo continuous neural and video recordings during a multi-day hospital stay. Naturalistic affective behaviors that subjects display spontaneously throughout their hospitalization, emotional reactivity in response to standardized affective stimuli, and emotional reactions following electrical stimulation of emotion network hubs will be quantified. We will examine how activity within emotion network hubs changes during emotions and how emotion network properties make some individuals more vulnerable to affective symptoms than others. We will address three key aims. In Aim 1, we will determine how emotion network activity relates to naturalistic affective behaviors. In Aim 2, we will uncover the unique neural signatures of discrete emotions and their relations to task-based measures of emotional reactivity. In Aim 3, we will probe whether electrical stimulation of emotion network hubs changes network activity and alters emotions, mood, and anxiety. By utilizing a multidisciplinary approach, the proposed project has the potential to ask novel questions about the neural origins of emotions and to advance current models of the neurobiological basis of emotions and affective symptoms.
期刊论文(1)
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会议论文
DOI: 10.1038/s41562-022-01310-0
发表时间: 2022-06
期刊: NATURE HUMAN BEHAVIOUR
影响因子: 29.9
作者: [Bijanzadeh, Maryam, Khambhati, Ankit N., Desai, Maansi, Wallace, Deanna L., Shafi, Alia, Dawes, Heather E., Sturm, Virginia E., Chang, Edward F.]
通讯作者: Chang, Edward F.
Spatiotemporal dynamics of the human emotion network
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