Basic neural processing mechanisms of live human face viewing

实时人脸观看的基本神经处理机制

• 批准号: 10610114
• 负责人: megan Kelley
• 金额: $ 3.27万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10610114
• 关键词: Academia; Address; Appearance; Arousal; Attention; Behavior; Binding; Brain; Characteristics; Clinical; Code; Complex; Computer Models; Coupled; Coupling; Data; Data Analyses; Data Set; Development; Disease; Dyslexia; Electroencephalography; Experimental Designs; Eye; Eye Movements; Face; Face Processing; Factor Analysis; Follow-Up Studies; Frequencies; Functional disorder; Funding; Goals; Health; Human; Impairment; Learning; Literature; Mental disorders; Mission; Motion; Neurocognition; Neurocognitive; Participant; Patients; Perception; Phase; Population; Positioning Attribute; Postdoctoral Fellow; Pupil; Research; Research Personnel; Research Project Grants; Robot; Role; Schizophrenia; Seeds; Social Functioning; Social Interaction; Special Population; Stimulus; System; Techniques; Testing; Time; Time Management; Training; Transcend; United States National Institutes of Health; Visual; advanced analytics; career; complex data; data acquisition; data management; design; experience; experimental study; functional near infrared spectroscopy; gaze; humanoid robot; multimodal data; multimodality; neuromechanism; patient population; post-doctoral training; relating to nervous system; showing emotion; simulation; skills; social; social cognition; source localization; statistics; visual tracking

Project Summary Significance. The human brain has a dedicated neural system for processing other humans. However relatively little is known about the basic mechanisms of this processing. Prior research has found that live human face viewing results in more activity in the right temporoparietal junction (TPJ) than does viewing a face simulation like a robot face. This suggests that live faces have characteristics that transcend appearance, motion, co- presence, and embodiment which give them access to sociocognitive systems that face simulations cannot access. Research question. What are the neural mechanisms of this access and how do they relate to stimulus acquisition? Further, how might these mechanisms contribute to dysfunction in psychiatric illnesses like schizophrenia? Addressing these gaps in the literature requires skills in: (1) multimodal data acquisition; (2) advanced analytics; and (3) experimental design for clinical populations. To pursue these questions long-term by becoming an independent researcher, I propose a two-phase training plan. In Aim 1, I will supplement existing skills for multimodal experimental design, acquisition, and preprocessing with intermediate multimodal analytics, advanced programming, dataset management, and professionalization. Approach. I will do this with a study on neurotypical neural processing during live human face viewing with robot face viewing as control and will acquire simultaneous functional Near Infra-Red Spectroscopy (fNIRS), electroencephalography (EEG), eye-tracking, and pupillometry. I will then apply eye-behavior-guided time frequency decomposition of EGG data, cross- frequency phase-amplitude coupling, and fNIRS-constrained EEG source localization. Hypotheses. Visual sensing is an active component of the neural processing of live faces. If true, then we hypothesize that eye movements and pupil size during live face viewing will be greater due to increased attention and arousal and greater acquisition of meaningful information from a live face. These differences are hypothesized to correspond to increased power in gamma (30-100hz)—reflecting configural processing—and theta (4-8hz)—reflecting perceptual binding. These frequencies are hypothesized to be coupled to each other—reflecting information transfer from local to global processing—and to localize to regions identified with fNIRS contrasts of live face and robot face viewing. This will identify the temporal and spatial features of the social processing network. Preliminary Results. Participants show greater pupil size and differences in dwell time during live face viewing. Right-TPJ-localized theta band power is greater during live face than robot face viewing. Aim 2, I will complete post-doctoral training on experimental design for those with schizophrenia and on advanced computational analytics like factor analysis and predictive coding. I will do this through research on live face viewing paradigms, such as emotional expression or direct gaze perception, during multimodal data acquisition with a population of patients and non-patients. This training will give me the skills necessary for long term research independence to explore the role of social neurocognitive function and dysfunction in health and psychiatric illness.

项目摘要 意义。人脑具有用于处理其他人类的专用神经系统。但是相对 关于此处理的基本机制知之甚少。先前的研究发现，活人的脸 查看右颞叶交界处（TPJ）的活动比查看面部模拟更多的活动 像机器人的脸。这表明，活面部的面孔具有超越外观，运动，共同的特征 在场和实施方案，使他们可以访问面对模拟的社会认知系统 使用权。研究问题。这种通道的神经机制是什么，它们与刺激有何关系 获得？此外，这些机制如何导致精神病疾病功能障碍 精神分裂症？在文献中解决这些差距需要以下技能：（1）多模式数据获取； （2） 高级分析； （3）临床人群的实验设计。长期提出这些问题 通过成为一名独立的研究人员，我提出了一个两阶段的培训计划。在AIM 1中，我将补充现有 多模式实验设计，获取和使用中级多模式分析的预处理的技能， 高级编程，数据集管理和专业化。方法。我将通过研究 在现场人脸观看现场表面上的神经型神经化学，并将其视为控制 同时在红外光谱（FNIRS），脑电图（EEG），眼睛跟踪的同时功能 和化学计量法。然后，我将应用鸡蛋数据的眼睛行为引导的时间频率分解，交叉 频率相位振幅耦合和FNIRS约束的EEG源定位。假设。视觉的 感应是活面部神经加工的活跃组成部分。如果是真的，那么我们假设那只眼睛 由于注意力和唤醒和 从现场表面更多地获取有意义的信息。这些差异被认为是对应的 为了增加伽玛（30-100Hz）的功率 - 反射可配置的处理 - 和theta（4-8Hz） - 反射 感知结合。这些频率被认为是相互耦合的 - 反射信息 从本地处理到全球处理，并本地化到与现场面孔对比的区域 和机器人的脸观看。这将确定社会处理网络的临时和空间特征。 初步结果。参与者表现出更大的学生大小和现场直觉观看期间住宿时间的差异。 在现场表面上，右TPJ-Locatization Theta频带功率比机器人脸观看更大。目标2，我将完成 精神分裂症患者和高级计算的实验设计培训后培训 分析等因素分析和预测性编码。我将通过有关现场观看范式的研究来做到这一点， 例如情感表达或直接凝视感知，在多模式数据获取期间 患者和非患者。这项培训将为我提供长期研究独立所需的技能 探索社会神经认知功能和功能障碍在健康和精神病中的作用。