Data Science Core

项目摘要 理解大脑如何产生行为需要两种非常敏锐的透镜：一种聚焦于 神经活动，另一个是动物本身，因为它与世界互动。我们可以使用的镜片 对大脑的观察和行为特征的描述都在稳步提高，这既是一个布恩，也是一个诅咒： 这是一个布恩，因为很可能关键的见解将产生于神经和行为数据， 其他方面的分辨率，但一个诅咒，因为组织和建模这样密集和多样化的数据是一个 重大挑战。 该项目在此赠款联合收割机结合先进的技术，机器视觉，机器学习和神经 记录以解决中脑和纹状体回路中的神经活动如何协调啮齿动物的行为 并控制它的进化。该项目的实验部分将由位于 在波士顿和湾区都有在这里，我们提出了一个数据科学核心（DSC），将使这些 不同的研究小组存储，检索和分析他们的数据使用模块化程序，可以热- 换成了简单的实验和迭代。在这种结构作用下，DSC将坚持一系列核心 开放科学的原则，包括尽可能使用开放源代码和数据标准， 创建允许轻松共享数据的框架，并仔细管理元数据，以允许汇集 从多个实验室的信息，以实现大规模的统计测试和验证。DSC还将 负责将生成的数据（包括原始数据、元数据和分析的数据流）分发到 更广泛的社区，包括其他U19联盟。因此，DSC将位于这一中心， 作为一个关键的枢纽，数据和洞察力通过它在研究人员和实验室之间自由传递。

Project abstract Understanding how the brain generates behavior requires two types of very sharp lenses: one focused on neural activity, and the other on the animal itself as it interacts with the world. The lenses available to us for peering at the brain and for characterizing behavior have steadily improved, which is both a boon and a curse: a boon because it is likely that key insights will arise from neural and behavioral data that approximate each other in terms of resolution, but a curse because organizing and modeling such dense and diverse data is a significant challenge. The Projects in this grant combine advanced techniques in machine vision, machine learning and neural recordings to address how neural activity in midbrain and striatal circuits orchestrate the behavior of rodents and control its evolution. The experimental aspects of this project are to be carried out by researchers located both in the Boston and the Bay area. Here we propose a Data Science Core (DSC) that will enable these diverse research groups to store, retrieve, and analyze their data using modular programs that can be hot- swapped for easy experimentation and iteration. In this structural role the DSC will adhere to a series of core principles for open science, including the use of open source code and data standards whenever possible, creating frameworks that allow for easy data sharing, and the careful curation of metadata to allow pooling of information from multiple labs to enable large-scale statistical testing and validation. The DSC will also be responsible for the distribution of generated data (including raw data, metadata, and analyzed datastreams) to the broader community, including to other U19 consortia. The DSC will therefore sit at the center of this proposal, acting as a crucial hub through which data and insight pass freely between investigators and labs.