Modularization and integration of the International Brain Laboratory spike-sorting pipeline into SpikeInterface

将国际脑实验室尖峰分选流程模块化并集成到 SpikeInterface 中

基本信息

批准号：
10609320
负责人：
ANNE KATHRYN CHURCHLAND
金额：
$ 21.3万
依托单位：
COLUMBIA UNIV NEW YORK MORNINGSIDE
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-08-15 至 2026-07-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10609320
关键词：
Behavior Brain Code Collaborations Communities Computer software Data Data Analyses Data Files Data Science Data Science Core Data Set Decision Making Development Devices Disease Documentation Ecosystem Electrophysiology (science)Ensure Environment Evaluation Goals Impairment Individual Industry Standard Infrastructure Ingestion Inherited International Intuition Laboratories Methods Modeling Neurons Neurosciences Output Resources Running Schizophrenia Signal Transduction Software Engineering Software Framework Sorting - Cell Movement Speed Standardization Structure Testing Work Writing addiction analysis pipeline autism spectrum disorder base cohesion computational pipelines data acquisition data analysis pipeline density expectation extracellular improved improved outcome integrated circuit interest mouse model multi-electrode arrays neural circuit neuromechanism neurophysiology novel open source outreach parallel computer parent grant parent project performance tests relating to nervous system repository scale up software infrastructure tool

项目摘要

PROJECT SUMMARY The parent grant titled “State-dependent Decision-making in Brainwide Neural Circuits” has the goal of understanding how internal states influence decisions and identifying the underlying neural mechanisms. The project builds upon the International Brain Laboratory (IBL) effort, which brings together a large consortium of laboratories to standardize and parallelize neural data acquisition and analysis. The parent project includes an extensive data acquisition work package leveraging Neuropixels 2.0 probes, which are state-of-the-art high- density neural devices that can record from up to 384 channels simultaneously. The large amount of raw electrophysiology data (~100 TB) requires the development of cutting-edge analysis tools for neural data science. Specifically, “spike sorting” is the crucial processing step that enables the extraction of single-neuron activity from the recorded signals; the sorted single-neuron signals are then used for downstream analysis and modeling. In this direction, the Data Science Core of the parent project has been developing computational pipelines and novel processing steps to automate and improve the outcome of spike sorting for the IBL data. However, these novel tools are tightly bound to the IBL analysis pipeline and would benefit from a generalization and standardization effort to be more useful to the general neurophysiology community. The main goal of this supplement project is therefore to integrate such state-of-the-art tools into the well- established SpikeInterface software framework1 in order to maximize outreach and accessibility to the broad electrophysiology community. In doing so, we aim to modularize the developed pipeline into discrete, decoupled, and interchangeable processing sorting components and to improve their software implementation in terms of speed, efficiency, and scalability, as well as documentation and testing. Finally, we will build a software infrastructure to enable users to construct and run full spike sorting pipelines into containerized and cloud-ready solutions.

项目概要题为“全脑神经回路中的状态相关决策”的家长资助的目标是了解内部状态如何影响决策并识别潜在的神经机制。该项目以国际脑实验室（IBL）的努力为基础，该实验室汇集了一个大型联盟实验室标准化和并行化神经数据采集和分析父项目包括一个。广泛的数据采集工作包利用 Neuropixels 2.0 探头，这是最先进的高密度神经设备可同时记录多达 384 个通道的大量原始数据。电生理学数据（~100 TB）需要开发尖端的神经数据分析工具具体来说，“尖峰排序”是提取单个神经元的关键处理步骤。记录的信号的活动；然后将排序的单神经元信号用于下游分析和在这个方向上，父项目的数据科学核心一直在开发计算。管道和新颖的处理步骤可实现 IBL 数据尖峰排序的自动化和改进结果。然而，这些新颖的工具与 IBL 分析流程紧密结合，并将受益于泛化标准化工作对一般神经生理学界更有用。因此，这个补充项目的主要目标是将这些最先进的工具集成到良好的环境中。建立了 SpikeInterface 软件框架1，以最大限度地扩大广泛的影响力和可访问性在此过程中，我们的目标是将开发的管道模块化为离散、解耦、和可互换的处理分选组件，并在以下方面改进其软件实施最后，我们将构建一个软件。基础设施，使用户能够构建和运行完整的尖峰分类管道到容器化和云就绪解决方案。