Computational and circuit mechanisms for information transmission in the brain

 描述(申请人提供)：大脑是一个巨大的相互连接的区域网络，每个区域都包含处理与感觉、运动和内部变量组合相关的信息的神经电路。适应行为需要这些区域进行交流：感觉和内部信息必须被评估并用于做出决定，然后这些信息必须转化为运动输出。尽管这个问题很重要，但我们对一个地区的尖峰活动如何影响下游地区的活动的原理知之甚少，特别是在决策等认知操作的背景下。在这里，我们建议通过关注腹侧纹状体(VS)是如何接收和处理来自两个重要的上游区域--眶前皮质(OFC)和海马体(HP)--的信息来解决这个问题。腹侧纹状体是行为动机控制的关键区域。我们组建了一支具有互补专业知识的独特科学家团队，研究惠普(Frank)、OFC和VS(Kepecs)，使用协同技术使用新型聚合物电极(Frank/Tolosa)和改进的光遗传学投影识别(Kepecs)进行大规模记录，并组建了一支在降维(Machens)、统计建模(Eden/Kramer)和标准模型(Ganguli)方面提供互补分析专业知识的统计和计算研究团队。我们的综合专业知识将使我们能够(1)测量大脑区域的大量神经元，(2)识别和(3)操作连接它们的神经元，以便(4)首次测试关于跨区域信息传输的不同模式和电路的一系列假设。除了揭示OFC、HP和VS在学习和决策过程中的沟通方式外，我们的方法还将为系统神经科学提供新的实验工具和计算方法，以及对跨区域信息传输的一般原理的新见解。

 DESCRIPTION (provided by applicant): The brain is a massively interconnected network of regions, each of which contains neural circuits that process information related to combinations of sensory, motor and internal variables. Adaptive behavior requires that these regions communicate: sensory and internal information must be evaluated and used to make a decision, which must then be transformed into a motor output. Despite the importance of this question, we know relatively little about the principles of how spiking activity in one region influences activiy in downstream areas, particularly in the context of cognitive operations like decision-making. Here we propose to address this question by focusing on how the ventral striatum (VS), a region critical for motivational control of behavior receives and processes information from two important upstream regions, the orbitofrontal cortex (OFC) and the hippocampus (HP). We have assembled a unique team of scientists with complementary expertise studying the HP (Frank), OFC and VS (Kepecs), using synergistic technologies for large-scale recordings using novel polymer electrodes (Frank/Tolosa) with improved optogenetic identification of projections (Kepecs), and a team of statistical and computational researchers providing complementary analytical expertise in dimensionality reduction (Machens), statistical modeling (Eden/Kramer) and normative models (Ganguli). Our combined expertise will allow us to (1) measure large populations of neurons across the brain regions, (2) identify and (3) manipulate the neurons connecting them in order to (4) test for the first time a range of hypotheses about different modes and circuits for information transmission across regions. Beyond revealing how the OFC, HP and VS communicate during learning and decision-making, our approach will provide new experimental tools and computational methods for systems neuroscience, as well as new insights into the general principles of information transmission across regions.