Dendritic Computation and Representation of Head Direction in Retrosplenial Cortex

压后皮质头部方向的树突计算和表示

• 批准号: 10198060
• 负责人: Mark Thomas Harnett
• 金额: $ 41.28万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-15 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10198060
• 关键词: Adaptive Behaviors; Alzheimer' s Disease; Anatomy; Animals; Anterior; Apical; Area; Attention deficit hyperactivity disorder; Axon; Behavior; Biological; Biological Models; Brain; Brain Diseases; Brain region; Cells; Code; Complex; Dendrites; Detection; Disease; Distal; Distant; Environment; Exhibits; Future; Head; Image; Individual; Investigation; Learning; Measures; Methods; Modeling; Motion; Mus; Neurons; Pattern; Play; Population; Positioning Attribute; Process; Rattus; Recurrence; Resolution; Role; Rotation; Schizophrenia; Signal Transduction; Source; Stream; Sum; Synapses; Technology; Testing; Thalamic structure; Visual; Visuospatial; Work; artificial neural network; cell cortex; experimental study; flexibility; in vivo; insight; neural circuit; neuronal cell body; novel; novel strategies; postsynaptic; receptive field; sensory cortex; tool; two-photon; visual information; visual motor

The mammalian cortex plays a critical role in integrating multiple streams of information to guide adaptive behavior. For example, head direction (HD) information is combined with visual and spatial input in the mouse retrosplenial cortex (RSC). Accurate integration of these signals is a necessary component of navigation: recognizing a distant landmark while facing north vs. facing south has very different interpretations for one's position and future actions. However, the mechanisms by which any cortical association area integrates different inputs at the level of individual neurons during behavior is unknown. RSC is therefore a compelling model system in which to test general associative computations during a complex behavior: the combination of visual and HD information during navigation. Anatomical evidence suggests that HD inputs computed in the anterior thalamus make their synapses at distal apical dendrites in RSC, while visual and motor synapses are located closer to the somas of RSC principal neurons. This arrangement suggests that nonlinear dendritic integration may be used by RSC to combine HD with other inputs. Active dendritic integration is theorized to allow single neurons to respond flexibly to different combinations of input, where the state of one input nonlinearly influences the impact of another input. Our overarching hypothesis is that such mechanisms could work in concert with neural circuit computations to implement context-dependent cortical computations. Congruent with this idea, RSC neurons in navigating rats exhibit complex conjunctive receptive fields, a feature that is lacking from commonly studied primary sensory cortices. RSC is therefore an ideal area to evaluate the role of dendrites in associative computations during navigation. However, current methods are not well-suited to this level of investigation: they either allow mice to behave freely or they achieve sub-cellular resolution. This has led to a critical gap in our understanding of navigation, and by extension, associative cortex function. We have recently developed technology that bridges this gap: an animal-actuated rotating headpost that allows mice to engage in 2-D navigation by freely turning their head during conventional 2-photon imaging. We will use this new approach to test the hypothesis that neurons in RSC use sub-cellular processing to flexibly combine HD and visual information during navigation behavior. These experiments will provide new insights into cellular- and circuit-level mechanisms of navigation, and of associative cortical function in general. Results from this project will be valuable for understanding brain disease states as well as for building biologically-inspired artificial neural networks.

哺乳动物皮层在整合多种信息流以指导适应性方面发挥着关键作用 行为。例如，头部方向（HD）信息与鼠标中的视觉和空间输入相结合 压后皮质（RSC）。这些信号的准确集成是导航的必要组成部分： 面向北和面向南时认出远处的地标对一个人的解释有很大不同 的立场和未来的行动。然而，任何皮质关联区域整合不同的机制 行为过程中单个神经元水平的输入是未知的。因此，RSC 是一个引人注目的模型系统 在复杂行为期间测试一般关联计算：视觉和高清的结合 导航期间的信息。 解剖学证据表明，在前丘脑中计算的 HD 输入使它们的突触位于 RSC 中的远端顶端树突，而视觉和运动突触则更靠近 RSC 主体的体细胞 神经元。这种安排表明 RSC 可以使用非线性树突积分来组合 HD 与其他输入。理论上，主动树突整合允许单个神经元灵活地响应不同的 输入的组合，其中一个输入的状态非线性地影响另一输入的影响。我们的 总体假设是，这种机制可以与神经电路计算协同工作，以 实现上下文相关的皮层计算。与这个想法一致的是，导航大鼠中的 RSC 神经元 表现出复杂的联合感受野，这是通常研究的初级感觉所缺乏的特征 皮质。因此，RSC 是评估树突在关联计算中的作用的理想区域。 导航。然而，当前的方法不太适合这种水平的研究：它们要么允许小鼠 行为自由或者它们实现亚细胞分辨率。这导致我们对以下问题的理解存在严重差距： 导航，以及扩展的联想皮层功能。我们最近开发了一种技术，可以连接 这个间隙：动物驱动的旋转头柱，允许小鼠通过自由转动进行二维导航 在传统的 2 光子成像过程中他们的头部。我们将使用这种新方法来检验以下假设： RSC 中的神经元在导航过程中使用亚细胞处理灵活地结合高清和视觉信息 行为。这些实验将为细胞和电路级导航机制提供新的见解， 以及一般关联皮质功能。该项目的结果对于理解大脑很有价值 疾病状态以及构建受生物学启发的人工神经网络。