A Fast, Accurate and Cloud-based Data Processing Pipeline for High-Density, High-Site-Count Electrophysiology

用于高密度、高位点计数电生理学的快速、准确且基于云的数据处理管道

• 批准号: 9905557
• 负责人: Bruce Kimmel
• 金额: $ 25.58万
• 依托单位: VIDRIO TECHNOLOGIES, LLC
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-07-06 至 2021-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9905557
• 关键词: Action Potentials; Adopted; Algorithmic Analysis; Algorithms; Animal Model; Animals; BRAIN initiative; Behavior; Behavior Control; Behavioral; Brain; Brain Diseases; Cells; Code; Communities; Complex; Complex Mixtures; Computer software; Custom; Data; Data Analyses; Data Compression; Data Set; Devices; Documentation; Electrodes; Electrophysiology (science); Environment; Exhibits; Feedback; Funding; Individual; Laboratory Research; Learning; Libraries; Measurement; Measures; Mediating; Medical Research; Methods; Morphologic artifacts; Motion; Motor; Neurobiology; Neurological Models; Neurons; Neurosciences; Noise; Online Systems; Output; Pathway interactions; Performance; Process; Prosthesis; Publishing; Reproducibility; Reproducibility of Results; Research; Research Personnel; Resources; Running; Sampling; Sensory; Signal Transduction; Site; Sorting - Cell Movement; Speed; Standardization; System; Technology; Testing; Time; Tissues; Tsunami; Validation; Vendor; Visualization; Visualization software; analysis pipeline; automated analysis; base; biomedical resource; cell type; cloud based; cloud platform; cognitive ability; computing resources; data acquisition; data analysis pipeline; data format; data hosting; data streams; data visualization; density; design; diverse data; empowered; experimental study; extracellular; file format; improved; information processing; innovation; large datasets; motor control; multi-electrode arrays; multiple datasets; nervous system disorder; open source; optogenetics; orientation selectivity; processing speed; relating to nervous system; relational database; sensor; shared database; software development; tool

The past decade has seen major advances in the tools available to neuroscientists, making it possible to ask increasingly specific questions regarding which neurons and circuits are correlated with, necessary for, and sufficient for, specific behavioral or computational functions. Advancements in our understanding of neural computation and how it leads to complex behavior critically depend on accurate measurements of coordinated neural activities in behaving animals. In the past several years there have been major coordinated efforts to advance neural probe technology by increasing site density, extending spatial coverage, providing high fidelity recording, and integrating with cell-type specific stimulation tools. Extracellular recordings exhibit action potentials (spikes) that require spike-sorting analysis to correctly detect and assign them to individual neurons. The demand for accurate and scalable spike sorting has increased due to the wide accessibility of extracellular recording technology and the increased requirements to record and separate activity from as many neurons as possible. Fundamental discoveries in neuroscience such as orientation-selective cells, place cells, and grid cells would not have been possible without reliable spike sorting of extracellular signals. These discoveries have illuminated the cellular basis of information processing and cognitive abilities. Recently, extracellular recording devices have also been applied to restoring motor function through prosthetics. However, as the number of electrodes needed for these treatments increases to allow for finer motor control so does the need for automated analysis. With more capacity for automated spike sorting the field’s progress in these domains would be accelerated. Existing spike analysis solutions suffer from a lack of scalability and are often designed to lock a user into a specific hardware platform. The community’s need for an integrated open-source analysis platform is rapidly growing with the increasing capacity of extracellular electrodes and the number of new and un-validated spike-sorting methods. JRCLUST, our free, open-source, standalone spike sorting software, offers a scalable, automated and well-validated spike sorting workflow that can tolerate experimental recording conditions with noise, probe drift, and motion artifacts from behaving animals. It can handle a wide range of datasets using a set of pre-optimized parameters making it practical for wide use in the community. Also, our processing speed and modular approach allows for rapid cycle innovation and practical pathways to interpret long recordings from hundreds of recording sites. Thanks to its real-time performance and accurate automated analysis requiring only a single workstation, JRCLUST has been rapidly adopted in 20+ labs worldwide since its inception less than a year ago. Successful completion of this project will enable Vidrio to support, expand and maintain JRCLUST thus empowering researchers to elucidate how functionally defined subpopulations of neurons mediate specific information-processing functions at key moments during behavior, in healthy animals and in animal models of neurological diseases.

在过去的十年里，神经科学家可以使用的工具取得了重大进展，使他们有可能提出问题