Collaborative Research: Structural and functional architecture shaping neural tuning within the human posterior superior temporal sulcus

人类是社会性生物，拥有广泛的神经系统，致力于掌握与他人互动所需的技能。这包括解码他人的行动以推断目标和意图，并计划适合当前环境的我们自己的行动。支持这些技能的大脑区域在解剖上分散在大脑的四个脑叶，组织成一个网络，通过远程白质连接进行交流。这个网络的一个关键枢纽是后上颞沟(PSTS)。工作是，这项提案将解决一个重要的悬而未决的问题：如何组织支持行动理解的远程联系，以及通过这些联系整合的信息的性质。这项工作将结合结构和功能脑成像来识别连接支持动作识别的系统的解剖路径，特别关注通过pSTS的路径，并将使用计算统计分析来表征通过这些路径携带的神经信息。这个问题具有迫切的科学和临床意义：神经科学越来越多地认识到，大脑区域的功能并不是孤立的，而是反映了来自许多皮质来源的神经信号的整合。这项提案中的工作试图通过在有针对性的皮质网络中明确地对这些来源进行建模来推进脑科学。动作识别网络对公众具有额外的重要性，因为一些神经发育障碍(如自闭症)与pSTS的非典型发育和该神经网络内沟通不良有关。因此，这项工作的结果可能对开发诊断和干预这些疾病的新临床工具至关重要。执行这笔赠款中的工作还将支持充分参与和促进未得到充分代表的第一代青年科学家在神经科学研究方面的培训。如何在行动识别网络内交流和组织信息是一个重要的问题。关于动作识别网络中后上颞沟和连接的大脑区域的功能专门化，存在许多相互竞争的科学模型。推进这些理论模型需要新的经验数据和分析技术。理解PSTS和更大的动作识别网络中的信息结构的关键是评估神经信号中整合的来源，神经信号既反映了对社会线索的感觉驱动的感知分析，也反映了自上而下的目标导向信号调节的影响。这项建议中的工作将把创新的实验设计与先进的多变量统计分析相结合，从丰富的大脑区域激活反应中提取结构，并将分解感觉驱动和自上而下的信号对神经调节的贡献。与此同时，人们必须考虑自上而下的目标导向信号的来源以及它们传递的结构路径。本提案中的工作具有创新性，因为它将使用很少实施的工具组合来描述网络架构的结构和功能，尽管这些工具具有明显的互补性。

Humans are social creatures with extensive neural systems dedicated to the skills required to navigate interactions with others. This includes decoding the actions of others to infer goals and intentions, and planning our own actions that are appropriate for the current context. Brain regions that support these skills are anatomically dispersed in the four lobes of the brain, organized as a network with communication via long-range white matter connections. One key hub of this network is the posterior superior temporal sulcus (pSTS). The work is this proposal will address an important outstanding question: how the long-range connections supporting action understanding are organized, and the nature of the information that is integrated through these connections. This work will combine structural and functional brain imaging to identify anatomical pathways connecting systems supporting action recognition, with particular attention to pathways through the pSTS, and will use computational statistical analyses to characterize the neural information that is carried through those pathways. This problem is of urgent scientific and clinical relevance: Neuroscience increasingly recognizes that brain regions do not function in isolation, but instead reflect the integration of neural signaling from many cortical sources. The work in this proposal seeks to advance brain science by explicitly modeling these sources in a targeted cortical network. The action recognition network holds additional importance to the public, as some neurodevelopmental disorders (such as autism) are linked to atypical development of the pSTS and poor communication within this neural network. Therefore the outcomes from this work may be critical for developing new clinical tools for diagnosis and interventions for these disorders. Implementing the work in this grant will also support the full engagement and promotion of under-represented and first-generation of young scientists training in neuroscientific research. The problem of how information is communicated and structured within the action recognition network is an important one. Many competing scientific models exist as to the functional specialization of the posterior superior temporal sulcus and connected brain regions within the action recognition network. New empirical data and analytical techniques are required to advance these theoretical models. A key to understanding information structure within the pSTS and the larger action recognition network is to evaluate the sources integrated within the neural signals, which reflect both sensory-driven perceptual analysis of social cues and the top-down goal-directed signals modulate influences. The work in this proposal will combine innovative experimental design with advanced multivariate statistical analyses to extract structure from the rich regional brain activation response, and will decompose the contribution of sensory-driven and top-down signals on neural tuning. At the same time, one must consider where top-down goal-directed signals originate and the structural pathways by which they are transmitted. The work in this proposal is innovative in that it will characterize the network architecture, both structurally and functionally, using a combination of tools rarely implemented despite their clear complementarity.