MCA Pilot PUI: From glomeruli to pollination: vertical integration of neural encoding through ecologically-relevant behavior

MCA Pilot PUI：从肾小球到授粉：通过生态相关行为进行神经编码的垂直整合

• 批准号: 2322310
• 负责人: Jordanna Sprayberry
• 金额: $ 29.21万
• 依托单位: Muhlenberg College
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-04-15 至 2027-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2322310&HistoricalAwards=false
• 关键词: MCA; Pilot; PUI; glomeruli; pollination

Ecological degradation driven by human behavior and the resultant disruptions to sensory processing is a major focus of conservation neuroscience. The impacts of odor pollution have come under increasing scrutiny in recent decades. Agrochemical scent pollution has been found to disrupt bumblebee behavior, a particularly alarming finding in light of their critical role as pollinators in agricultural and natural ecosystems. These findings imply that neural processing of floral odors is impacted by odor pollution. One barrier for understanding these impacts of agrochemicals on bumblebee foraging behavior is that there are no concrete computational structures for representing and exploring odor perception, as current methods are statistical in nature. This means pollution cannot be easily measured, or quantified; which makes it challenging to develop agricultural recommendations. This project is building upon earlier work that established a quantification mechanism for complex odors (i.e. odors made up of many molecules) to establish an algorithm for representing bumblebee odor perception. The established “Compounds with Borders” (CWB) method allows the difference between any two odors to be represented as an angular distance, and has been used to establish a ‘safe zone’ of odor pollution for complex odors: polluted-odors within a 20-30 degree range are generalized. Next steps include expanding CWB into a more comprehensive geometry that can accurately account for simpler odors as well. This work will be performed at a ‘primarily undergraduate institution’, incorporating valuable research experiences for the next generation of STEM professionals.Given the neurophysiological organization of odor processing, the relative importance of molecular-identity versus -feature of odorants is linked to stimulus complexity, with encoding of simpler odors correlating with identity and more complex odors correlating with features. “Compounds with Borders” is particularly effective for complex blends because it quantifies the amount of sensory energy that is distributed across molecular features in an odor using a Euclidean approach where ‘dimensions’ in odor space represent those features. The next hurdle is to expand the geometry of this odor-space to incorporate molecular identity. This is not logistically tractable without data that delineate what level of odor complexity shifts the primary-processing output from ‘identity’ to ‘feature’ correlation. This project aims to develop a more comprehensive geometry using associative odor learning paradigms combined with recording neural activity at both the input (antennae) and output (antennal lobe tracts) from primary olfactory processing. Gas Chromatography-Electroantennographic recordings will establish a species specific odor-salience across molecular identities and features. Spike-resolved multi-unit recordings from the antennal lobe tracts will assay odor information as it moves forward to integration and action centers. Comparing the point at which odor responses shift from correlating with molecular identity to molecular feature at a neurophysiological and behavioral level will inform an expanded geometry that utilizes stimulus complexity to shape dimensional weighting. Thus, this work aims to establish a novel paradigm for vertical integration of neural encoding through behavior in olfaction.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

由人类行为驱动的生态退化以及由此导致的对感觉处理的破坏是保护神经科学的主要焦点。 近几十年来，气味污染的影响受到越来越多的关注。农业化学品气味污染已被发现会扰乱大黄蜂的行为，鉴于它们在农业和自然生态系统中作为授粉者的关键作用，这是一个特别令人担忧的发现。这些发现意味着植物气味的神经处理受到气味污染的影响。了解这些影响的农用化学品对大黄蜂觅食行为的一个障碍是，没有具体的计算结构来表示和探索气味感知，因为目前的方法本质上是统计的。这意味着污染无法轻易测量或量化;这使得制定农业建议具有挑战性。该项目是建立在早期工作的基础上，建立了一个复杂气味（即由许多分子组成的气味）的量化机制，以建立一个代表大黄蜂气味感知的算法。已建立的“具有边界的化合物”（CWB）方法允许将任何两种气味之间的差异表示为角距离，并且已用于建立复杂气味的气味污染的“安全区”：在20-30度范围内的污染气味被概括。接下来的步骤包括将CWB扩展为更全面的几何形状，可以准确地解释更简单的气味。 这项工作将在一个“主要是本科院校”进行，为下一代的STEM专业人士结合宝贵的研究经验。鉴于气味处理的神经生理学组织，气味的分子身份与特征的相对重要性与刺激的复杂性有关，编码与身份相关的简单气味和更复杂的气味与特征相关。“具有边界的化合物”对于复杂的共混物特别有效，因为它使用欧几里德方法量化了气味中分布在分子特征上的感觉能量的量，其中气味空间中的“维度”表示这些特征。下一个障碍是扩展这种气味空间的几何结构，以纳入分子身份。如果没有数据说明气味复杂性的水平如何将初级处理输出从“身份”转移到“特征”相关性，这在逻辑上是不容易处理的。 该项目旨在开发一个更全面的几何使用联想气味学习范式结合记录神经活动的输入（触角）和输出（触角叶束）从初级嗅觉处理。气相色谱-触角电位记录将建立一个物种特异性的气味显着性的分子身份和功能。从触角叶束的尖峰分辨多单元记录将分析气味信息，因为它向前移动到整合和行动中心。 比较气味反应从与分子身份相关转变为神经生理和行为水平的分子特征的点将告知利用刺激复杂性来形成维度权重的扩展几何结构。因此，这项工作的目的是建立一个新的范式，通过嗅觉行为的神经编码的垂直整合。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。