CAREER: Neural Dynamics, Olfactory Coding and Behavior

职业：神经动力学、嗅觉编码和行为

• 批准号: 1453022
• 负责人: Baranidharan Raman
• 金额: $ 60万
• 依托单位: Washington University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1453022&HistoricalAwards=false
• 关键词: CAREER; Neural; Dynamics; Olfactory; Coding

This project focuses on how neural activity in relatively simple invertebrates encodes information about an odorant?s identity and intensity, in a manner that is robust to variations in the intensities and background contexts in which sensory stimuli can be encountered. Electrophysiological, computational and behavioral approaches are combined in this effort to determine the basic principles of olfactory information processing. The identified biological olfaction principles will also lead to development of novel signal-processing algorithms for artificial olfaction, i.e. for electronic noses used in many non-invasive chemical-sensing applications.The technical goals of the project are to determine how response dynamics at the single neuron and population levels maintain/alter olfactory invariance and examine correlations between physiology and odor-driven behavior. An integrative approach will take advantage of the rich repertoire of genetic tools available in the fruit fly (Drosophila melanogaster) to study single neuron dynamics, and combine it with multi-unit electrophysiological approaches that are well established in locusts (Schistocerca americana) to examine neural circuit dynamics. The biological data will be used to develop experimentally constrained models of olfactory signal processing to gain mechanistic insights and facilitate development of bio-inspired algorithms for an electronic nose. This research will reveal how dynamic patterns of neural activity allow the olfactory system to represent odorants in a background- and concentration-invariant manner. Examination of the interactions between an external stimulus and intrinsic neural dynamics is also expected to inform a better general understanding of dynamical neuronal networks. Data and analytical approaches obtained from the proposed work will be used to develop new neural engineering modules for undergraduate and graduate courses and thereby enhance the existing biomedical engineering curriculum. Furthermore, a K-12 teachers professional development workshop: ?Where biology meets engineering? will be created to provide middle- and high-school teachers with content and tools to offer their students a meaningful exposure to the interdisciplinary nature of science education.

该项目重点研究相对简单的无脊椎动物中的神经活动如何以一种对可能遇到的感觉刺激的强度和背景环境的变化具有鲁棒性的方式编码有关气味剂的特性和强度的信息。这项工作结合了电生理学、计算和行为方法，以确定嗅觉信息处理的基本原理。所确定的生物嗅觉原理还将导致人工嗅觉的新型信号处理算法的开发，即用于许多非侵入性化学传感应用中的电子鼻。该项目的技术目标是确定单个嗅觉的响应动态如何神经元和群体水平维持/改变嗅觉不变性并检查生理学和气味驱动行为之间的相关性。综合方法将利用果蝇（Drosophila melanogaster）中丰富的遗传工具来研究单个神经元动力学，并将其与蝗虫（Schistocerca americana）中成熟的多单元电生理学方法相结合，以检查神经元电路动力学。生物数据将用于开发嗅觉信号处理的实验约束模型，以获得机械见解并促进电子鼻仿生算法的开发。 这项研究将揭示神经活动的动态模式如何使嗅觉系统以背景和浓度不变的方式表示气味。对外部刺激和内在神经动力学之间相互作用的检查也有望有助于更好地理解动态神经元网络。从拟议工作中获得的数据和分析方法将用于为本科生和研究生课程开发新的神经工程模块，从而增强现有的生物医学工程课程。此外，K-12 教师专业发展研讨会：“生物学与工程学的结合？”将创建为初中和高中教师提供内容和工具，让学生能够有意义地接触科学教育的跨学科性质。

项目成果

Invariant odor recognition with ON–OFF neural ensembles

通过 ON-OFF 神经元进行不变的气味识别

• DOI: 10.1073/pnas.2023340118
• 发表时间: 2022-01
• 期刊: Proceedings of the National Academy of Sciences
• 作者: Nizampatnam, Srinath;Zhang, Lijun;Chandak, Rishabh;Li, James;Raman, Baranidharan
• 通讯作者: Raman, Baranidharan

Neural manifolds for odor-driven innate and acquired appetitive preferences

气味驱动的先天和后天食欲偏好的神经流形

• DOI: 10.1038/s41467-023-40443-2
• 发表时间: 2023-08-05
• 期刊: Nature Communications
• 影响因子: 16.6
• 作者: Chandak, Rishabh;Raman, Baranidharan
• 通讯作者: Raman, Baranidharan

Dynamic contrast enhancement and flexible odor codes

动态对比度增强和灵活的气味代码

• DOI: 10.1038/s41467-018-05533-6
• 发表时间: 2018-08-03
• 期刊: Nature Communications
• 影响因子: 16.6
• 作者: Nizampatnam S;Saha D;Chandak R;Raman B
• 通讯作者: Raman B