Project 4: Neuronal Interactions

项目 4：神经元相互作用

• 批准号: 10247571
• 负责人: Hyunjune SEBASTIAN SEUNG
• 金额: $ 36.45万
• 依托单位: PRINCETON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-28 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10247571
• 关键词: Anatomy; Anterior; Area; Artificial Intelligence; Automation; Behavior; Biological Assay; Biophysics; Brain; Brain region; Calcium; Code; Cues; Data; Decision Making; Electron Microscopy; Elements; Exhibits; Funding; Goals; Grant; Image; Investigation; Laboratories; Mind; Modeling; Neocortex; Neurons; Optics; Physiological; Process; Property; Ramp; Research Personnel; Research Project Grants; Resolution; Role; Short-Term Memory; Synapses; Techniques; Technology; Testing; Time; Work; base; cognitive ability; cognitive process; computerized data processing; connectome; cost; design; experimental study; innovation; interest; millimeter; neural circuit; neural model; neuromechanism; optogenetics; reconstruction; relating to nervous system; response; virtual

Project Summary: Project 4, Anatomical and Physiological Assays of Neuronal Interactions Working memory, the ability to temporarily hold multiple pieces of information in mind for manipulation, is central to virtually all cognitive abilities. This multi-component research project aims to comprehensively dissect the neural circuit mechanisms of this ability across multiple brain areas. The overall goal is to construct a neural circuit model of working memory and decision­making across multiple brain regions, constrained by neural activity, inactivation results, and connectivity. The model is already constrained by preliminary data showing choice­-specific activity sequences in posterior cortical neurons in an evidence­-accumulation task. This modeling will generate predictions, which will be tested by several techniques. The first approach will compare neural coding properties with anatomical connectivity by combining calcium imaging with serial-­section electron microscopy. This aim will benefit from the Seung laboratory’s dramatic recent progress in automation by artificial intelligence, which will make it feasible to find connectomes of millimeter­scale cortical volumes. The second approach will compare neural coding with physiological connectivity by combining calcium imaging with optogenetic perturbation at cellular resolution. This aim will leverage the Tank laboratory’s recent work on all­optical assays of connectivity. The third approach will be to study the role of interactions between cortical areas by performing calcium imaging in one area during optogenetic inactivation of another area. Much of this project focuses on retrosplenial cortex, which is of special interest because choice­specific activity sequences are more linear in this part of cortex than in other cortical areas. Furthermore, temporally specific inactivation of retrosplenial cortex causes behavior that mimics the response to deletion of incoming evidence. The first two approaches will test the example prediction that the local circuitry underlying activity sequences will exhibit sequential connectivity, that is, that connections from earlier to later neurons will be stronger or more frequent than those from later to earlier neurons. The third approach will test a second example prediction, that inactivation of the anterior M2 region of cortex will lead to reduction in non­specific excitation in posterior cortices and alter sequence timing. Importantly, these example predictions are not intended to be comprehensive. Instead the generality of these techniques will enable researchers to test a wide variety of predictions that emerge from the neural circuit models that will be generated and refined based on data from these experiments and other components of the project.

项目摘要：项目4，神经元相互作用的解剖学和生理学测定 工作记忆是一种在头脑中暂时保存多条信息以进行操作的能力，几乎是所有认知能力的核心。这个多成分的研究项目旨在全面剖析这种能力在多个大脑区域的神经回路机制。总体目标是构建一个跨多个大脑区域的工作记忆和决策的神经回路模型，受神经活动，失活结果和连接的约束。该模型已经受到初步数据的限制，这些数据显示了在证据累积任务中后皮层神经元中的选择神经元特异性活动序列。这种建模将生成预测，这些预测将通过几种技术进行测试。第一种方法将通过结合钙成像和连续切片电子显微镜来比较神经编码特性和解剖连接。这一目标将受益于Seung实验室最近在人工智能自动化方面取得的巨大进展，这将使找到毫米级皮层体积的连接体成为可能。第二种方法将通过将钙成像与细胞分辨率下的光遗传学扰动相结合来比较神经编码与生理连接。这一目标将利用Tank实验室最近在所有连通性光学分析方面的工作。第三种方法将是通过在一个区域的光遗传学失活期间在另一个区域进行钙成像来研究皮质区域之间的相互作用的作用。这个项目的大部分集中在压后皮层，这是特别感兴趣的，因为选择神经元特异性活动序列在这部分皮层比在其他皮层区域更线性。此外，压后皮质的时间特异性失活导致模仿对删除传入证据的反应的行为。前两种方法将测试示例预测，即活动序列下的局部电路将表现出顺序连接，即从较早到较晚的神经元的连接将比从较晚到较早的神经元的连接更强或更频繁。第三种方法将测试第二个示例预测，即皮层的前M2区域的失活将导致后皮层中的非特异性兴奋减少并改变序列定时。重要的是，这些示例预测并不打算是全面的。相反，这些技术的通用性将使研究人员能够测试各种各样的预测，这些预测来自神经回路模型，这些模型将根据这些实验和项目其他组成部分的数据生成和改进。