Tuckman Harrison, Kim Jungmin, Rangan Aaditya, Lei Hong, Patel Mainak
Department of Mathematics, William & Mary Williamsburg, VA 23187, USA.
Department of Pharmacology, University of Colorado Denver, Aurora, CO 80045, USA.
J Theor Biol. 2021 Jan 21;509:110510. doi: 10.1016/j.jtbi.2020.110510. Epub 2020 Oct 3.
Odors emanating from a biologically relevant source are rapidly embedded within a windy, turbuluent medium that folds and spins filaments into fragmented strands of varying sizes. Environmental odor plumes therefore exhibit complex spatiotemporal dynamics, and rarely yield an easily discernible concentration gradient marking an unambiguous trail to an odor source. Thus, sensory integration of chemical input, encoding odor identity or concentration, and mechanosensory input, encoding wind speed, is a critical task that animals face in resolving the complex dynamics of odor plumes and tracking an odor source. In insects, who employ olfactory navigation as their primary means of foraging for food and finding mates, the antennal lobe (AL) is the first brain structure that processes sensory odor information. Although the importance of chemosensory and mechanosensory integration is widely recognized, the AL itself has traditionally been viewed purely from the perspective of odor encoding, with little attention given to its role as a bimodal integrator. In this work, we seek to explore the AL as a model for studying sensory integration - it boasts well-understood architecture, well-studied olfactory responses, and easily measurable cells. Using a moth model, we present experimental data that clearly demonstrates that AL neurons respond, in dynamically distinct ways, to both chemosensory and mechanosensory input; mechanosensory responses are transient and temporally precise, while olfactory responses are long-lasting but lack temporal precision. We further develop a computational model of the AL, show that our model captures odor response dynamics reported in the literature, and examine the dynamics of our model with the inclusion of mechanosensory input; we then use our model to pinpoint dynamical mechanisms underlying the bimodal AL responses revealed in our experimental work. Finally, we propose a novel hypothesis about the role of mechanosensory input in sculpting AL dynamics and the implications for biological odor tracking.
来自生物相关源的气味会迅速嵌入到有风的湍流介质中，这种介质会将细丝折叠并旋转成大小各异的碎片状股线。因此，环境气味羽流呈现出复杂的时空动态，很少产生易于辨别的浓度梯度来明确标记通往气味源的路径。所以，对化学输入（编码气味特征或浓度）和机械感觉输入（编码风速）进行感觉整合，是动物在解决气味羽流的复杂动态并追踪气味源时面临的一项关键任务。在昆虫中，嗅觉导航是它们觅食和寻找配偶的主要方式，触角叶（AL）是处理气味感觉信息的首个脑结构。尽管化学感觉和机械感觉整合的重要性已得到广泛认可，但传统上触角叶本身仅从气味编码的角度来看待，很少关注其作为双模式整合器的作用。在这项工作中，我们试图将触角叶作为研究感觉整合的模型——它具有易于理解的结构、经过充分研究的嗅觉反应以及易于测量的细胞。我们以蛾类为模型，呈现的实验数据清楚地表明，触角叶神经元对化学感觉和机械感觉输入会以动态不同的方式做出反应；机械感觉反应是短暂且时间精确的，而嗅觉反应是持久的但缺乏时间精确性。我们进一步开发了触角叶的计算模型，表明我们的模型捕捉到了文献中报道的气味反应动态，并在包含机械感觉输入的情况下检查了模型的动态；然后我们使用模型来确定实验工作中揭示的双模式触角叶反应背后的动态机制。最后，我们提出了一个关于机械感觉输入在塑造触角叶动态中的作用以及对生物气味追踪影响的新假设。
