BIOLOGICAL NEURAL NETWORKS: AUDITORY SYSTEM

生物神经网络：听觉系统

• 批准号: 6122982
• 负责人: DAVID JAMES ANDERSON
• 金额: $ 11.54万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-05-15 至 1999-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6122982
• 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.

该项目致力于生物神经网络（NN） 高通道数电极背景下的听觉系统。 我们 建议扩展我们过去在耳蜗核记录方面的工作 使用薄膜电极技术的 (CN) 和下丘 (IC) 解决有关数据的技术、生物学和理论问题 采集分析和神经回路识别。 两者都是急性的 以及 CN、IC 和听觉皮层 (AC) 的慢性多单元记录 豚鼠将被用来解决这些问题。 总体目标 该项目的目的是应用增强的数据收集功能 通过薄膜、多接触电极技术 该资源中心总体上推进神经网络的网络估计， 并更好地理解神经处理 听觉系统的网络。 工作领域包括 1) 研究用多接触电极记录的波形，包括 场电位和放电检测及其解析 进入有效的尖峰列车； 2）多方信息的收集与分析 使用声音刺激和本地信号从 CN、IC 和 AC 获取尖峰序列数据 急性和慢性豚鼠的化学和电刺激 准备工作； 3）利用神经网络识别问题的研究 网络类别的模拟和实验数据 薄膜电极。