Data Science Core

项目摘要 要了解大脑是如何产生行为的，需要两种非常锐利的透镜：一种专注于 一种是神经活动，另一种是动物与世界互动时的自身。可供我们使用的镜片 凝视大脑和描述行为特征的能力稳步提高，这既是好事，也是坏事： 这是一个福音，因为关键的洞察力很可能来自接近每个数据的神经和行为数据 另一个方面是分辨率，但这是一种诅咒，因为组织和建模如此密集和多样化的数据是一种 这是一个巨大的挑战。 这笔赠款中的项目结合了机器视觉、机器学习和神经网络的先进技术。 记录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。该项目的实验方面将由以下研究人员进行 在波士顿和湾区都是如此。在此，我们建议使用数据科学核心(DSC)来实现以下功能 不同的研究小组使用模块化程序存储、检索和分析他们的数据，这些程序可以 换成了简单的实验和迭代。在这一结构角色中，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池化 来自多个实验室的信息，以实现大规模统计测试和验证。DSC也将是 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财团。因此，DSC将处于这一事件的中心 提案，作为数据和洞察力在调查人员和实验室之间自由传递的关键枢纽。

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.