Lewis Suzanne M, Xu Lai, Rigolli Nicola, Tariq Mohammad F, Suarez Lucas M, Stern Merav, Seminara Agnese, Gire David H
Department of Psychology, University of Washington, Seattle, WA, United States.
Dipartimento di Fisica, Istituto Nazionale Fisica Nucleare (INFN) Genova, Universitá di Genova, Genova, Italy.
Front Cell Neurosci. 2021 Apr 30;15:633757. doi: 10.3389/fncel.2021.633757. eCollection 2021.
Although mice locate resources using turbulent airborne odor plumes, the stochasticity and intermittency of fluctuating plumes create challenges for interpreting odor cues in natural environments. Population activity within the olfactory bulb (OB) is thought to process this complex spatial and temporal information, but how plume dynamics impact odor representation in this early stage of the mouse olfactory system is unknown. Limitations in odor detection technology have made it difficult to measure plume fluctuations while simultaneously recording from the mouse's brain. Thus, previous studies have measured OB activity following controlled odor pulses of varying profiles or frequencies, but this approach only captures a subset of features found within olfactory plumes. Adequately sampling this feature space is difficult given a lack of knowledge regarding which features the brain extracts during exposure to natural olfactory scenes. Here we measured OB responses to naturally fluctuating odor plumes using a miniature, adapted odor sensor combined with wide-field GCaMP6f signaling from the dendrites of mitral and tufted (MT) cells imaged in olfactory glomeruli of head-fixed mice. We precisely tracked plume dynamics and imaged glomerular responses to this fluctuating input, while varying flow conditions across a range of ethologically-relevant values. We found that a consistent portion of MT activity in glomeruli follows odor concentration dynamics, and the strongest responding glomeruli are the best at following fluctuations within odor plumes. Further, the reliability and average response magnitude of glomerular populations of MT cells are affected by the flow condition in which the animal samples the plume, with the fidelity of plume following by MT cells increasing in conditions of higher flow velocity where odor dynamics result in intermittent whiffs of stronger concentration. Thus, the flow environment in which an animal encounters an odor has a large-scale impact on the temporal representation of an odor plume in the OB. Additionally, across flow conditions odor dynamics are a major driver of activity in many glomerular networks. Taken together, these data demonstrate that plume dynamics structure olfactory representations in the first stage of odor processing in the mouse olfactory system.
尽管小鼠利用空气中动荡的气味羽流来定位资源，但波动羽流的随机性和间歇性给在自然环境中解读气味线索带来了挑战。嗅球（OB）内的群体活动被认为是在处理这种复杂的空间和时间信息，但在小鼠嗅觉系统的这个早期阶段，羽流动力学如何影响气味表征尚不清楚。气味检测技术的局限性使得在同时记录小鼠大脑活动时难以测量羽流波动。因此，先前的研究测量了在不同形状或频率的受控气味脉冲之后的OB活动，但这种方法只捕捉到了嗅觉羽流中发现的一部分特征。鉴于缺乏关于大脑在接触自然嗅觉场景时提取哪些特征的知识，充分采样这个特征空间很困难。在这里，我们使用一个微型的、经过改装的气味传感器，结合来自头部固定小鼠嗅小球中成像的二尖瓣和簇状（MT）细胞树突的宽视野GCaMP6f信号，测量了OB对自然波动气味羽流的反应。我们精确跟踪羽流动力学，并对这种波动输入的小球反应进行成像，同时在一系列与行为学相关的值范围内改变流动条件。我们发现，小球中MT活动的一个一致部分跟随气味浓度动态变化，并且反应最强的小球最能跟随气味羽流中的波动。此外，MT细胞小球群体的可靠性和平均反应幅度受到动物采样羽流时的流动条件的影响，在较高流速的条件下，气味动态导致更强浓度的间歇性气味，MT细胞对羽流的跟随保真度增加。因此，动物遇到气味时的流动环境对OB中气味羽流的时间表征有大规模影响。此外，在不同的流动条件下，气味动态是许多小球网络活动的主要驱动因素。综上所述，这些数据表明羽流动力学在小鼠嗅觉系统气味处理的第一阶段构建了嗅觉表征。
