BRAIN EAGER: Massive-scale multi-area single neuron recordings to reveal circuits underlying short-term memory

该奖项由生物科学理事会（BIO）的两个项目联合颁发：生物研究仪器开发项目（IDBR）和新兴前沿项目（EF）。短期记忆是认知功能的重要组成部分，几乎渗透到我们精神生活的各个方面。先前的研究表明，短期记忆涉及多个认知成分和不同的大脑区域。然而，目前还没有从机制上理解什么时候涉及哪些区域，在这些区域内招募了哪些神经元子集，或者它们如何相互作用以代表与行为相关的信息。本研究旨在阐明视觉、联想和运动皮层在小鼠视觉线索短时记忆任务中的作用。这将通过使用行为小鼠的双光子钙成像来实现，以同时测量这些多个大脑区域中数千个神经元的活动。随后，大脑区域和计算识别的神经元组装的光遗传学操作将用于确定它们在行为中的因果作用。这些技术和结果将对理解行为和认知背后的神经回路产生广泛的影响。新的方法将被引入到一个可量化的行为的单神经元活动的双尺度映射。新的方法来确定电路连接，和新的组合计算和光遗传学技术来操纵关键电路组件，将被介绍。这些大型数据集将被广泛和免费提供，使其他研究小组能够利用这些数据进行新的分析，该提案的目标是开发新的工具，并提供有关神经元活动模式和电路的前所未有的信息，以了解多个皮层区域在小鼠短期记忆中的作用。经典的电生理记录仅限于相对少量的未知身份的神经元。此外，虽然微刺激或药理学操作可用于激活或抑制局部区域内的所有神经元，但不可能选择性地激活或抑制已知在行为中起作用的特定神经元亚群。该提案通过开发新的工具来研究小鼠执行视觉提示记忆引导的辨别任务来解决这些问题。首先，将开发在小鼠皮层中跨越几毫米的多个皮层区域的大规模成像（同时多达一万个神经元）的方法。第二，将对小鼠进行具有适当行为丰富性的视觉提示短期记忆任务的训练，包括单独的感觉、记忆和反应时期，使得可以对分布式皮质区域（例如视觉、顶叶和额叶运动皮质）中的活动进行成像，并且可以确定每个时期中各个区域的作用。第三，将对特定脑区进行靶向失活，以确定它们在行为中的作用。最后，将刺激特定区域中通过计算识别的神经元子集，以确定它们是否足以改变行为。总之，这些将是该领域中第一个将行为、超大规模多区域记录以及区域和识别神经元组装的因果操纵联系起来的研究。通过引入与以前对记忆和记忆引导功能的分析截然不同的方法的工具，预计该项目将对该领域产生重大影响。

This award is jointly made by two programs: Instrument Development for Biological Research program (IDBR), and Emerging Frontiers (EF), in the Directorate of Biological Sciences (BIO).Short-term memory is a crucial component of cognitive function and pervades nearly all aspects of our mental lives. Previous research has shown that short-term memory involves multiple cognitive components and diverse brain regions. However, it is not mechanistically understood what regions are involved when, what neuronal subsets are recruited within these regions, or how they interact to represent information relevant to behavior. This proposal aims to elucidate the role of visual, association, and motor cortex in mice performing a visually-cued short-term memory task. This will be accomplished using massive-scale two-photon calcium imaging in behaving mice to measure activity of thousands of neurons simultaneously across these multiple brain regions. Subsequently, optogenetic manipulation of brain regions and of computationally identified neuronal assemblies will be used to determine their causal role in behavior. These technologies and results will have wide impact on understanding neural circuits underlying behavior and cognition. New approaches will be introduced for massive-scale mapping of single neuron activity in relation to a quantifiable behavior. New ways to determine circuit connectivity, and novel combination computational and optogenetic technologies to manipulate critical circuit components, will be introduced. These large data sets will be made widely and freely available, enabling other research groups to avail of these data for novel analyses.The goal of this proposal is to develop novel tools and provide unprecedented information on neuronal activity patterns and circuits in order to understand the role of multiple cortical areas during short-term memory in mice. Classical electrophysiological recordings are limited to relatively small numbers of neurons with unknown identity. In addition, while microstimulation or pharmacological manipulations can be used to activate or inhibit all the neurons within a local area, it is not possible to selectively excite or inhibit specific neuronal subpopulations that are known to play a role in the behavior. The proposal addresses these issues by developing novel tools to study mice performing a visually-cued memory-guided discrimination task. First, methods for massive scale imaging (up to ten thousand neurons simultaneously) of multiple cortical regions spanning several millimeters in the mouse cortex will be developed. Second, mice will be trained on a visually cued short-term memory task with suitable behavioral richness, including separate sensory, memory and response epochs, so that activity in distributed cortical regions (such as visual, parietal, and frontal motor cortices) can be imaged and the role of individual areas in each epoch can be ascertained. Third, targeted inactivation of specific brain areas will be performed to determine their role in the behavior. Finally, computationally identified neuronal subsets in specific areas will be stimulated in order to determine if they are sufficient for altering behavior. Together, these will be the first studies in the field to link behavior, extremely large-scale multiple-area recordings, and causal manipulations of areas and identified neuronal assemblies. By introducing tools for a radically different approach from previous analyses of memory and memory-guided functions, it is expected that the project will have a significant impact on the field.