Dendritic Computation and Representation of Head Direction in Retrosplenial Cortex

哺乳动物大脑皮层在整合多个信息流以引导适应性方面起着关键作用。 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）。这些信号的精确积分是导航的必要组成部分： 面对北方和面对南方时识别远处的地标对一个人的认知有非常不同的解释。 立场和未来行动。然而，任何皮层联合区整合不同的机制， 在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 在复杂的行为过程中测试一般的关联计算：视觉和HD的结合 导航时的信息。 解剖学证据表明，在前丘脑中计算的HD输入使它们的突触在 在RSC的远端顶端树突，而视觉和运动突触位于更接近RSC主体的胞体 神经元这种排列表明，RSC可以利用非线性树枝状整合来联合收割机HD 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信号。 输入的组合，其中一个输入的状态非线性地影响另一个输入的影响。我们 最重要的假设是，这种机制可以与神经回路计算协同工作， 实现上下文相关的皮层计算。与这一观点相一致，导航大鼠的RSC神经元 表现出复杂的联合感受野，这是一个通常研究的初级感觉缺乏的特征。 皮质因此，RSC是一个理想的领域，以评估在关联计算过程中树突的作用。 导航然而，目前的方法并不适合这种水平的研究：它们要么允许小鼠 或者它们实现亚细胞分辨率。这导致了我们在理解 导航，以及由此延伸的关联皮层功能。我们最近开发了一种技术， 这个缺口：一个动物驱动的旋转头柱，允许老鼠通过自由转动进行二维导航 他们的头部在传统的双光子成像。我们将使用这种新方法来检验假设， 在导航过程中，RSC中的神经元使用亚细胞处理来灵活地将联合收割机HD和视觉信息结合 行为这些实验将为细胞和电路水平的导航机制提供新的见解， 以及大脑皮层的联想功能。该项目的结果将对了解大脑有价值 疾病状态以及用于构建生物启发的人工神经网络。

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.