MULTIUNIT, MULTIELECTRODE SPIKE-SORTING SOFTWARE

多单元、多电极尖峰排序软件

• 批准号: 6292731
• 负责人: CHARLOTTE Mason GRUNER
• 金额: $ 9.66万
• 依托单位: PRONGHORN SCIENTIFIC, LLC
• 依托单位国家: 美国
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-04-14 至 2003-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6292731
• 关键词: action potentials; computer data analysis; computer program /software; computer system design /evaluation; electrodes; electrophysiology; mathematics; neurons; neurophysiology; time resolved data

DESCRIPTION (adapted from applicant's abstract): The use of multiple electrodes to record the activity of a neural populations is a technique that has shown promise in obtaining spike data from neural populations. This population data is clearly needed to further the study of how neurons code, process, learn, and retain information. Better understanding of neural population coding would have wide clinical benefits, for example, in the design of microelectronic devices such as cochlear and retinal implants. Currently, most researchers who collect multielectrode data are forced to also develop their own software to sort the recorded action potentials from each of the neurons recorded, determining the relative time-of-occurrence of each action potential, a process known as "spike-sorting." The long-term objective of this research program is to develop a MATLAB software toolbox for automated multichannel spike-sorting incorporating state-of-the-art algorithms using advanced signal processing techniques. The objective of the Phase I project is to develop prototype software using the MATLAB environment that expands existing work and incorporates new methods for spike sorting. This will be the first commercially available package that will allow the effective solution to a major problem facing neuroscientists: the discrimination and identification of spike superpositions. PROPOSED COMMERCIAL APPLICATION: There are many potential users of multichannel spike-sorting software who are already obtaining multichannel data. The number of researchers doing multi-channel studies has increased dramatically and will continue to increase as computer become faster and better multielectrodes are producted.

描述（改编自申请人摘要）：使用多个电极 记录神经群的活动是一种技术， 从神经群体中获得尖峰数据的前景。这些人口数据 显然需要进一步研究神经元如何编码，处理，学习， 保留信息。更好地了解神经群体编码将有助于 广泛的临床益处，例如，在微电子设备的设计中 例如耳蜗和视网膜植入物。目前，大多数研究人员收集 多电极数据也被迫开发自己的软件来分类 记录来自每个记录的神经元的动作电位， 每个动作电位发生的相对时间，这一过程称为 “尖峰排序。“这项研究计划的长期目标是开发 用于自动多通道尖峰分选的MATLAB软件工具箱 采用先进的信号处理技术， 技术.第一阶段项目的目标是开发原型 使用MATLAB环境的软件，扩展了现有的工作， 结合了新的尖峰分选方法。这将是第一个商业化的 有效解决重大问题的一揽子计划 神经科学家面临的问题：锋电位的识别与鉴别 叠加 拟定商业应用： 有许多多通道尖峰信号分类软件的潜在用户， 获得多通道数据。 进行多渠道研究的研究人员数量 急剧增加，并将继续增加，随着计算机变得更快， 生产出更好的多电极。