Department of Physics, Harvard University, Cambridge, MA 02138, USA; Center for Brain Science, Harvard University, Cambridge, MA 02138, USA.
Center for Brain Science, Harvard University, Cambridge, MA 02138, USA; Program in Neuroscience, Harvard University, Cambridge, MA 02138, USA.
Neuron. 2019 Mar 6;101(5):950-962.e7. doi: 10.1016/j.neuron.2018.12.030. Epub 2019 Jan 22.
Odor perception allows animals to distinguish odors, recognize the same odor across concentrations, and determine concentration changes. How the activity patterns of primary olfactory receptor neurons (ORNs), at the individual and population levels, facilitate distinguishing these functions remains poorly understood. Here, we interrogate the complete ORN population of the Drosophila larva across a broadly sampled panel of odorants at varying concentrations. We find that the activity of each ORN scales with the concentration of any odorant via a fixed dose-response function with a variable sensitivity. Sensitivities across odorants and ORNs follow a power-law distribution. Much of receptor sensitivity to odorants is accounted for by a single geometrical property of molecular structure. Similarity in the shape of temporal response filters across odorants and ORNs extend these relationships to fluctuating environments. These results uncover shared individual- and population-level patterns that together lend structure to support odor perceptions.
气味感知使动物能够区分气味、识别不同浓度下的相同气味,并确定浓度变化。但是,在个体和群体水平上,主要嗅觉受体神经元 (ORN) 的活动模式如何促进这些功能的区分,目前仍知之甚少。在这里,我们在广泛的气味样本中检测了果蝇幼虫的整个 ORN 群体。我们发现,每个 ORN 的活动都与任何气味剂的浓度呈比例关系,通过一个具有可变灵敏度的固定剂量反应函数。不同气味剂和 ORN 的灵敏度遵循幂律分布。嗅觉受体对气味剂的敏感性很大程度上归因于分子结构的单一几何特性。在不同气味剂和 ORN 之间,时间响应滤波器的形状相似性将这些关系扩展到了波动的环境中。这些结果揭示了共同的个体和群体水平模式,这些模式共同为气味感知提供了结构支持。