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 社会互动是一个进化保守的工具包，对各种各样的生存和发展至关重要。 物种。社交障碍是许多神经精神疾病的主要症状之一， 包括自闭症谱系障碍和精神分裂症。因此，阐明潜在的神经 社会行为的电路和计算对于理解许多社会行为的原因和机制至关重要。 具有强烈的翻译影响的神经系统疾病。社会互动在本质上是动态的，因为它经常 涉及所有参与个体的行动和反应的恒定反馈循环。但目前的 社会神经科学的方法往往忽视了这一特性，主要集中在潜在的神经 在一个人的过程中。为了充分了解社会大脑在健康和疾病中的功能， 对于研究所有社会参与者的综合系统以及由此产生的神经特性至关重要。 了这些涌现的特征之一是脑间同步。近年来， 来研究在社会交往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，脑间同步出现 在不同的社会背景下的社会参与者之间。事实上，也有研究表明，大脑间的同步是 由精神疾病引起的社会缺陷的个体改变。尽管有如此显著的发现， 技术上的限制限制了研究的范围，并留下了各种各样的问题： 从细胞级电路组件中出现，以及这些动力学如何与计算过程相关 支持健康或受损的社会交往将新的机器学习方法与 最先进的在自由相互作用的小鼠体内钙成像，拟议的实验将解决如何脑间 同步（脑间神经相关）出现在不同的遗传定义的神经元群体中， 内侧前额叶皮层（Aim 1）。这项工作也将表征脑间同步的潜在改变 及其在Shank 3突变小鼠中的行为意义-一种已建立的ASD小鼠模型（目的2）。的见解 从这项研究中得出的结论将扩大我们对如何在多个国家共享信息的理解。 相互作用的大脑可以塑造正在进行的社会互动，为大脑间的同步如何 作为ASD中受损的社会互动的假定生物标志物，并为新的 治疗精神疾病的方法。