A framework for analyzing converging feedforward and cortical-bulbar feedback dynamics in target detection from complex odor scenes

用于分析复杂气味场景目标检测中的收敛前馈和皮质球反馈动态的框架

• 批准号: 1656830
• 负责人: Dinu Albeanu
• 金额: $ 92.1万
• 依托单位: Cold Spring Harbor Laboratory
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2021-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1656830&HistoricalAwards=false
• 关键词: framework; analyzing; converging; feedforward; cortical

This project makes use of recent advances in optical imaging and optogenetic strategies to monitor the brain at work. Specifically, the project is focused on understanding the interplay between ascending and descending (feedback) activity patterns in the olfactory system of behaving mice. Here, the investigator does not simply focus on the olfactory sensory module that integrates and transmits information from the nose to the brain but determines how higher brain areas, namely, the olfactory cortex, interact in the recurrent processing loop. This strategy enables the investigator to evaluate how sensory inputs are shaped by internal brain states via feedback. Furthermore, the investigator works at the interface of two approaches by combining cutting-edge experimental approaches--optical imaging and optogenetic strategies-- with novel computational models that give rise to non-mutually exclusive testable predictions. The investigator determines whether these feedforward-feedback loops contribute to attention states, extraction of odor identity, or broadcasting of predictions and error signals related to the incoming odorants. Experimental techniques are complemented, through an international collaboration, with state-of-the-art data analysis that characterizes neuronal population dynamics along high-dimensional trajectories and measures occurrence of activity patterns, characteristic timescales, patterns interaction, and coordination as a function of behavior. Additionally, the project provides opportunities for students and postdoctoral trainees from the USA and Romania to expand their experimental and computational skills through their participation in the international collaboration.A central goal of systems neuroscience is to describe behaviors in terms of the neuronal circuits that control them. This constitutes a steep challenge in the mammalian brain, because behaviors are thought to rely on widely distributed feedforward, as well as top-down feedback neural representations, which are technically difficult to monitor at large scales and manipulate at cellular resolution. The project builds on recent experimental results from the lead investigator and novel algorithms for odor identification developed by the international collaborator. Specifically, the project probes the fine structure of olfactory perception and tests the central hypothesis that feedback serves one or more of the following three mechanisms: predictive coding, attractor generation, or attention to enhance the discriminability of behaviorally relevant stimuli. The dynamics of: a) cortical-bulbar feedback, and b) olfactory bulb output neurons on which feedback acts indirectly via interneurons are monitored and subsequently modulated with cellular resolution in mice engaged in olfactory discrimination forced-choice tasks and contextual reversal learning tasks. Reversible optogenetic local suppression of cortical feedback in the olfactory bulb is combined with simultaneous two-photon resonant scanning imaging (100 Hz) of hundreds of neurons. To address the proposed feedback roles, specific experimental design is combined with machine learning tools and dynamical systems analysis.

该项目利用光学成像和光遗传学策略的最新进展来监测工作中的大脑。具体来说，该项目的重点是了解行为小鼠嗅觉系统中上升和下降（反馈）活动模式之间的相互作用。在这里，研究人员不仅关注嗅觉感觉模块，它将信息从鼻子整合并传输到大脑，而且还确定了更高的大脑区域，即嗅觉皮层，在循环处理循环中如何相互作用。这种策略使研究人员能够评估感觉输入是如何通过反馈被内部大脑状态塑造的。此外，研究人员通过将尖端的实验方法-光学成像和光遗传学策略-与新的计算模型相结合，在两种方法的界面上工作，从而产生非互斥的可测试预测。研究人员确定这些前馈反馈回路是否有助于注意力状态，气味身份的提取，或与传入气味相关的预测和错误信号的广播。实验技术的补充，通过国际合作，与国家的最先进的数据分析，表征神经元群体动态沿着高维轨迹和措施的活动模式，特征时间尺度，模式的相互作用，并协调作为行为的函数。此外，该项目还为来自美国和罗马尼亚的学生和博士后学员提供了通过参与国际合作来扩展他们的实验和计算技能的机会。系统神经科学的一个中心目标是根据控制它们的神经元回路来描述行为。这对哺乳动物大脑构成了严峻的挑战，因为行为被认为依赖于广泛分布的前馈以及自上而下的反馈神经表征，这在技术上很难在大规模上进行监测并在细胞分辨率上进行操纵。该项目建立在首席研究员最近的实验结果和国际合作者开发的气味识别新算法的基础上。具体而言，该项目探讨嗅觉感知的精细结构，并测试反馈服务于以下三种机制中的一种或多种的中心假设：预测编码，吸引子生成或注意力，以增强行为相关刺激的可辨别性。以下方面的动态：a）皮质-延髓反馈，和B）嗅球输出神经元，反馈通过中间神经元间接作用于这些神经元，在参与嗅觉辨别强迫选择任务和背景逆转学习任务的小鼠中，监测并随后用细胞分辨率调制这些神经元。将嗅球中皮质反馈的可逆光遗传学局部抑制与数百个神经元的同时双光子共振扫描成像（100 Hz）相结合。为了解决所提出的反馈作用，具体的实验设计与机器学习工具和动力系统分析相结合。