BIOL NEURAL NETWORKS: MULTICHANNEL RECORD & ANALYSIS & DATA ACQUISITION

BIOL 神经网络：多通道记录

• 批准号: 6355366
• 负责人: DAVID JAMES ANDERSON
• 金额: $ 19.69万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-08-01 至 2001-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6355366
• 关键词: Mammalia; animal tissue; bioengineering /biomedical engineering; biomedical equipment development; biomedical resource; ear; hearing; nervous system; technology /technique

This project addresses biological neural networks (NNs) in the auditory system in the context of high-channel count electrodes. We propose to extend our past work on recording in the cochlear nuclei (CN) and inferior colliculus (IC) using thin-film electrode technology to address technical, biological, and theoretical questions about data collection and analysis and neural circuit identification. Both acute and chronic multiunit recording at CN, IC, and auditory cortex (AC) of guinea pig will be used to address these questions. The general aims of this project are to apply the enhanced data gathering made possible by the thin-film, multicontact electrode technologies which concern this Resource Center to advance network estimation for NNs in general, and to obtain a better understanding of neural processing in the networks of the auditory system. The areas of work include 1) the study of waveforms recorded with multicontact electrodes including field potentials and the detection of discharges and their parsing into valid spike trains; 2) the collection and analysis of multiple spike train data from CN, IC, and AC using sound stimuli and local chemical and electrical stimuli in acute and chronic guinea pig preparations; 3) the study of NN identification problems using simulations of classes of networks and experimental data from thin-film electrodes.

该项目涉及生物神经网络（NNS） 听觉系统在高通道计数电极的背景下。 我们 提议扩展我们过去在人工耳蜗中记录的工作 使用薄膜电极技术（CN）和下丘（IC）（IC） 解决有关数据的技术，生物学和理论问题 收集和分析以及神经回路识别。 两者都急性 以及CN，IC和听觉皮层（AC）的慢性多单元记录 豚鼠将用于解决这些问题。 总目标 这个项目是应用增强的数据收集 通过薄膜，多接触电极技术 这个资源中心可以推进NNS的网络估计， 并更好地了解神经处理 听觉系统的网络。 工作领域包括1） 使用多连接电极记录的波形的研究 野外电势和排放的检测及其解析 进入有效的尖峰火车； 2）多重收集和分析 使用声音刺激和本地的CN，IC和AC的尖峰训练数据 急性和慢性豚鼠的化学和电刺激 准备； 3）使用 来自网络类别的模拟和实验数据 薄膜电极。