Sensory Coding and Pattern Recognition with Hybird Olfactory Biosensor

EIA-0220301伊利诺伊州-芝加哥大学约翰赫特林大学BITS：使用混合嗅觉进行感觉编码和模式识别自然嗅觉系统结合了高灵敏度与宽带检测、出色的分辨率和快速响应时间。这些特性是传感器阵列设计和下游神经处理的结果。除了与人工鼻的发展有关外，嗅觉系统所面临的模式识别问题在许多方面类似于数据挖掘中的问题，特别是与DNA微阵列有关的问题。为了进一步了解生物解决这一普遍问题的方法，同时记录多个嗅觉神经元将是有利的。该方案旨在开发一种新型的混合器件嗅觉生物传感器，然后使用该系统来研究信号编码和模式识别。这将提供有关自然系统的编码策略的信息，并为复杂信号中的模式识别的新方法提供测试案例。

EIA-0220301 John Hetling University of Illinois-Chicago BITS: Sensory Coding and Pattern Recognition with Hybrid OlfactoryThe natural olfactory system combines high sensitivity with broadband detection, excellent discrimination, and fast response times. These characteristics are a result of the sensor array design and the down-stream neural processing. In addition to being relevant to the development of an artificial nose, the pattern recognition problem faced by olfactory systems is analogous in many respects to problems in data mining, especially related to DNA micro arrays. To further our understanding of the biological solution to this general problem, it will be advantageous to record from multiple olfactory neurons simultaneously. This proposal seeks to develop a novel hybrid-device olfactory biosensor, and then to use this system to investigate signal coding and pattern recognition. This will provide information about the coding strategy of the natural system, and provide a test case for new approaches to pattern recognition in complex signals.