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

人类是社会生物，拥有广泛的神经系统，致力于与他人互动所需的技能。这包括解码他人的行为来推断目标和意图，以及计划适合当前环境的自己的行为。支持这些技能的大脑区域在解剖学上分散在大脑的四个脑叶中，通过远程白质连接组织成一个交流网络。这个网络的一个关键枢纽是颞后上沟（pSTS）。这项工作将解决一个重要的突出问题：支持行动理解的远程连接是如何组织的，以及通过这些连接集成的信息的性质。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通路，特别关注通过pSTS的通路，并将使用计算统计分析来表征通过这些通路携带的神经信息。这个问题具有迫切的科学和临床意义：神经科学越来越认识到大脑区域并不是孤立地起作用，而是反映了来自许多皮层来源的神经信号的整合。本提案中的工作旨在通过在目标皮质网络中明确建模这些来源来推进脑科学。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新的诊断和干预这些疾病的临床工具至关重要。实施这项拨款的工作还将支持充分参与和促进代表性不足的第一代年轻科学家在神经科学研究方面的培训。如何在动作识别网络中传递和组织信息是一个重要的问题。关于颞后上沟及其在动作识别网络中的连接区域的功能专门化，存在许多相互竞争的科学模型。需要新的经验数据和分析技术来推进这些理论模型。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整合在神经信号中的来源，这些信号既反映了对社会线索的感觉驱动的知觉分析，也反映了自上而下的目标导向信号的调节影响。本研究将创新的实验设计与先进的多元统计分析相结合，从丰富的脑区域激活反应中提取结构，并分解感觉驱动信号和自上而下信号对神经调谐的贡献。同时，我们必须考虑自上而下的目标导向信号从何而来，以及它们传递的结构性途径。本提案中的工作是创新的，因为它将在结构和功能上描述网络架构，使用尽管具有明显互补性但很少实现的工具组合。

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.