Neural Basis of Inter-brain Synchrony during Social Interaction in Health and Disease

健康和疾病社会互动过程中脑间同步的神经基础

• 批准号: 10751334
• 负责人: Nguyen Thanh Phi
• 金额: $ 4.13万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-30 至 2026-09-29
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10751334
• 关键词: Address; Adopted; Animals; Behavior; Behavioral; Biological Markers; Brain; Calcium; Cells; Cognitive; Complex; Dedications; Development; Disease; Ethology; Exhibits; Feedback; Future; Glutamates; Health; Human; Image; Impairment; Individual; Interneurons; Investigation; Machine Learning; Medial; Mental disorders; Methods; Mus; Mutant Strains Mice; Nature; Neurodevelopmental Disorder; Neurons; Participant; Population; Prefrontal Cortex; Process; Property; Reaction; Research; Schizophrenia; Shapes; Social Behavior; Social Environment; Social Facilitation; Social Interaction; Societies; Symptoms; Systems Integration; Techniques; Thalamencephalon; Work; autism spectrum disorder; cell type; cognitive process; dyadic interaction; experimental study; high dimensionality; hippocampal pyramidal neuron; in vivo calcium imaging; insight; mouse model; mutant; nervous system disorder; neural; neural circuit; neural correlate; neural patterning; neuroimaging; neuropsychiatric disorder; novel; novel strategies; repetitive behavior; response; sensory input; social; social deficits; social implication; social neuroscience

Abstract Social interaction is an evolutionarily conserved toolkit, critical to the survival and development of a wide variety of species. Impaired social interaction is one of the key symptoms across many neuropsychiatric disorders, including autism spectrum disorder (ASD) and schizophrenia. Therefore, elucidating the underlying neural circuits and computations of social behaviors is essential to understand the causes and mechanisms of many neurological disorders with a strong translational implication. Social interaction is dynamical in nature as it often involves a constant feedback loop of actions and reactions of all participating individuals. However, current approaches in social neuroscience often overlook this property and mostly focus on the underlying neural processes within a single individual. To fully understand how the social brain functions in health and disease, it is critical to examine the integrated system of all social participants and the neural properties that emerge from it. One of such emergent features is inter-brain synchrony. In recent years, substantial effort has been dedicated to investigating how neural dynamics across individuals are coordinated during social interaction. Using non- invasive recording techniques, many human studies have demonstrated that inter-brain synchrony emerges across social participants in various social contexts. In fact, it has also been shown that inter-brain synchrony is altered in individuals with social deficits caused by psychiatric illnesses. Despite such remarkable findings, technical constraints limit the extent of investigation and leave open various questions: how inter-brain synchrony emerges from cellular-level circuit components, and how these dynamics are related to computational processes that support healthy or impaired social interaction? Integrating a novel machine-learning approach with state-of- the-art in vivo calcium imaging in freely interacting mice, the proposed experiments will address how inter-brain synchrony (inter-brain neural correlation) arises in different genetically-defined neuronal populations in the medial prefrontal cortex (Aim 1). This work will also characterize the potential alteration of inter-brain synchrony and its behavioral implications in Shank3 mutant mice – an established ASD mouse model (Aim 2). The insights derived from this research will expand our understanding of how the information shared across multiple interacting brains can shape on-going social interaction, shedding new light onto how inter-brain synchrony can serve as a putative biomarker for impaired social interaction in ASD and laying the groundwork for new approaches to treat psychiatric illnesses.

摘要 社会互动是进化上保守的工具包，对各种各样的生物的生存和发展至关重要 物种的。社交障碍是许多神经精神障碍的主要症状之一， 包括自闭症谱系障碍(ASD)和精神分裂症。因此，阐明潜在的神经 社会行为的回路和计算对于理解许多 具有强烈翻译含义的神经性障碍。社交互动本质上是动态的，因为它经常 包括所有参与的个人的行动和反应的持续反馈循环。但是，当前 社会神经科学的方法往往忽略了这一特性，而主要集中在潜在的神经 在一个人的内部进行处理。为了充分了解社交大脑如何在健康和疾病中发挥作用，它 对于检查所有社会参与者的集成系统以及从 它。这种新出现的特征之一是大脑之间的同步性。近年来，我们付出了巨大的努力。 研究在社会互动中个体之间的神经动力学是如何协调的。使用非- 侵入性记录技术，许多人类研究表明，大脑之间的同步性出现 在不同社会背景下的社会参与者之间。事实上，也有研究表明，大脑之间的同步性 因精神疾病而导致社交缺陷的个体发生改变。尽管有如此惊人的发现， 技术限制限制了调查的范围，并留下了各种悬而未决的问题：大脑之间如何同步 来自细胞级别的电路组件，以及这些动态如何与计算过程相关 支持健康的或受损的社交互动？将一种新的机器学习方法与状态相结合 在自由相互作用的小鼠中进行体内钙成像，拟议的实验将解决大脑之间的 同步性(脑神经间相关性)出现在不同的遗传定义的神经元群体中 内侧前额叶皮质(目标1)。这项工作还将表征大脑间同步性的潜在变化 及其对Shank3突变小鼠的行为影响--已建立的ASD小鼠模型(目标2)。洞察力 这项研究将扩大我们对信息如何在多个 相互作用的大脑可以塑造正在进行的社交活动，这为大脑之间的同步提供了新的线索 作为ASD社交功能受损的假定生物标志物，并为新的 治疗精神疾病的方法。