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 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 脾后皮质(RSC)。这些信号的精确集成是导航的必要组件： 识别遥远的地标时，面朝北和面朝南，对一个人的理解截然不同 立场和未来行动。然而，任何皮质关联区整合的机制不同 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 其中测试复杂行为期间的一般关联计算：视觉和高清的组合 导航期间的信息。 解剖学证据表明，在丘脑前部计算的HD输入使它们的突触在 RSC的远端顶端树突，而视觉突触和运动性突触位于RSC主干的胞体附近 神经元。这一安排表明，RSC可以使用非线性树枝状整合来结合HD 使用其他输入。主动树突整合的理论是允许单个神经元灵活地对不同的 一种输入组合，其中一种输入的状态非线性地影响另一种输入的影响。我们的 最重要的假设是，这种机制可以与神经电路计算协同工作，以 实施上下文相关的皮质计算。与这一观点相一致的是，导航大鼠的RSC神经元 表现出复杂的连接感受场，这是通常研究的初级感觉所缺乏的特征 皮质。因此，RSC是评估树枝状结构在关联计算中的作用的理想区域 导航。然而，目前的方法并不完全适合这种水平的调查：它们要么允许小鼠 要么自由行动，要么实现亚细胞分辨率。这导致了我们对 导航，以此类推，联想皮质的功能。我们最近开发了一种技术，可以在 这个缺口：一种动物驱动的旋转头柱，允许老鼠通过自由旋转进行二维导航 他们的头部在常规的双光子成像过程中。我们将使用这种新方法来检验假设 RSC中的神经元在导航过程中使用亚细胞处理灵活地结合HD和视觉信息 行为。这些实验将为细胞和电路级别的导航机制提供新的见解， 和大体上的联合皮质功能。这个项目的结果将对理解大脑有价值。 疾病状态以及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.