Imaging attractor dynamics in the neural compass

神经罗盘中吸引子动力学的成像

• 批准号: RGPIN-2017-04539
• 负责人: Brandon, Mark
• 金额: $ 2.4万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=646163
• 关键词: Imaging; attractor; dynamics; neural; compass

Individual neurons work on short timescales; from an action potential duration of 1 ms to synaptic currents that persist for just 10 ms or 100 ms of milliseconds. Yet, neurons embedded within a network are capable of maintaining persistent activity in the absence of external stimuli. One prominent computational theory uses 'attractor dynamics', whereby the connectivity of the network stabilizes activity without additional input to the network. In general, this is implemented in network that consists of recurrent excitatory connections between neurons that code for similar features along with feedforward inhibitory connectivity to silence the activity of neurons coding for non-similar features. This creates a competitive network that will sustain its current activity without any additional input, and will not change until a new input is strong enough to change the ‘attractor state'. Importantly, this framework can encode discrete and continuous ‘analog' variables. Here we propose to look for evidence of attractor dynamics in the head direction (HD) cell network.? ******The HD system has almost exclusively been modeled using a continuous ring attractor network. Briefly, activity representing the current HD is maintained by traditional attractor connectivity, while activity is gradually moved along this continuous ring attractor by vestibular inputs that relay head movements of the animal. We will use optical imaging in the anterior thalamic nucleus (ATN), which contains abundant HD cells, in an attempt to visualize this activity in freely behaving mice. We will use and further develop miniaturized microscopes that will allow us to record from hundreds of HD cells simultaneously. This approach is a major improvement over traditional electrode recordings, with which researchers have only recorded from up to 10 HD cells at a time. We will investigate whether attractor-like dynamics exist within the head direction network. We will develop the hardware and software for a closed-loop system to perform optogenetic perturbations based on slight head movements, perform optical imaging of HD cells in a variety of behaviors to look for ring attractors and coherent drift in the network, and finally will perform optogenetic silencing of the HD generation circuitry to determine to induce and analyze larger shifts in the HD network and compare this larger drift to behavior in a path integration task. These experiments will provide the first optical recordings of large populations of HD cells and will provide insight into the network dynamics of the HD network.

单个神经元在短时间尺度上工作；从持续1毫秒的动作电位到持续10毫秒或100毫秒的突触电流。然而，嵌入网络中的神经元能够在没有外部刺激的情况下保持持续的活动。一个著名的计算理论使用了“吸引子动力学”，即网络的连通性在没有额外输入网络的情况下稳定了活动。一般来说，这是在网络中实现的，该网络由编码相似特征的神经元之间的循环兴奋性连接以及前馈抑制性连接组成，以沉默编码非相似特征的神经元的活动。这创造了一个竞争网络，它将在没有任何额外输入的情况下维持其当前的活动，并且在新的输入足够强大以改变“吸引状态”之前不会改变。重要的是，这个框架可以编码离散和连续的“模拟”变量。在这里，我们建议在头部方向（HD）蜂窝网络中寻找吸引子动力学的证据。****** HD系统几乎完全是用连续环吸引子网络建模的。简而言之，代表当前HD的活动是由传统的吸引器连接维持的，而活动则是通过前庭输入（传递动物头部运动）沿着这个连续的环形吸引器逐渐移动的。我们将在含有大量HD细胞的丘脑前核（ATN）中使用光学成像，试图在自由行为的小鼠中可视化这种活动。我们将使用并进一步开发微型显微镜，使我们能够同时记录数百个HD细胞。这种方法是对传统电极记录的重大改进，研究人员一次只能记录多达10个HD细胞。我们将研究头部方向网络中是否存在类吸引子动力学。我们将开发闭环系统的硬件和软件，以执行基于轻微头部运动的光遗传扰动，对HD细胞的各种行为进行光学成像，以寻找网络中的环吸引子和相干漂移，最后将对HD生成电路进行光遗传沉默，以确定诱导和分析HD网络中的较大偏移，并将这种较大的漂移与路径集成任务中的行为进行比较。这些实验将首次提供大量高清细胞的光学记录，并将为高清网络的网络动力学提供见解。