Neurally Encoding Time for Olfactory Navigation.
Neurally Encoding Time for Olfactory Navigation.
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DOI：
10.1371/journal.pcbi.1004682
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发表时间：
2016-01
影响因子：
4.3
通讯作者：
Principe JC
中科院分区：
文献类型：
--
作者：
Park IJ;Hein AM;Bobkov YV;Reidenbach MA;Ache BW;Principe JC
准确地编码时间是神经系统在调节行为方面面临的基本挑战之一。我们最近报道，一些动物的嗅觉器官中有一个特殊的节律性活跃神经元群体，有可能在外围编码关于气味接触的时间信息。如果这些神经元确实编码了气味到达的时间，应该可以证明这种能力具有一定的功能意义。在这里，我们展示了这种感官输入如何深刻地影响动物在现实动荡的环境中定位气味线索来源的能力--这是依赖嗅觉线索导航的物种面临的常见任务。使用实验室中产生的湍流羽流的详细数据，我们重建了真实气味场的时空行为。我们使用递归理论来表明，关于气味羽流相对于来源的位置的信息嵌入在气味脉冲之间的定时中。然后，使用一个参数化的计算模型，我们展示了动物如何使用节律活跃的神经元群体来实时捕获和编码这些时间信息，并使用它来有效地导航到气味来源。我们的结果表明，准确编码有关感觉线索的时间信息的能力可能是有效的嗅觉导航的关键。更广泛地说，我们的结果提出了一种从感觉环境中提取和编码时间信息的机制，这可能对神经信息处理具有广泛的实用价值。许多动物使用气味线索在动荡的环境中导航，这种行为被称为嗅觉搜索。我们提出了一种嗅觉搜索的神经机制，该机制的基础是有证据表明，嗅觉感受器神经元(ON)的一个功能子集，称为爆裂球或Borns，可以编码连续与气味相遇的时间间隔。我们证明，这些时间间隔是重现时间的估计器，重现时间是湍流的一个信息丰富的统计量。使用由实际湍流羽流数据参数化的计算模型，我们演示了搜索者仅使用新生儿的输入就可以有效地定位气味来源。这些发现提供了科学证据，表明嗅觉系统捕捉到的最重要的导航信息可能以时间测量的形式出现。
Accurately encoding time is one of the fundamental challenges faced by the nervous system in mediating behavior. We recently reported that some animals have a specialized population of rhythmically active neurons in their olfactory organs with the potential to peripherally encode temporal information about odor encounters. If these neurons do indeed encode the timing of odor arrivals, it should be possible to demonstrate that this capacity has some functional significance. Here we show how this sensory input can profoundly influence an animal’s ability to locate the source of odor cues in realistic turbulent environments—a common task faced by species that rely on olfactory cues for navigation. Using detailed data from a turbulent plume created in the laboratory, we reconstruct the spatiotemporal behavior of a real odor field. We use recurrence theory to show that information about position relative to the source of the odor plume is embedded in the timing between odor pulses. Then, using a parameterized computational model, we show how an animal can use populations of rhythmically active neurons to capture and encode this temporal information in real time, and use it to efficiently navigate to an odor source. Our results demonstrate that the capacity to accurately encode temporal information about sensory cues may be crucial for efficient olfactory navigation. More generally, our results suggest a mechanism for extracting and encoding temporal information from the sensory environment that could have broad utility for neural information processing. Many animals navigate turbulent environments using odor cues, a behavior known as olfactory search. We propose a neural mechanism for olfactory search based on evidence that a functional subset of olfactory receptor neurons (ORNs) called bursting ORNs or bORNs can encode the time intervals between successive encounters with odor. We show that these time intervals are estimators of the recurrence time, an information-rich statistic of the turbulent flow. Using a computational model parameterized with data from an actual turbulent plume, we demonstrate that a searcher can locate an odor source efficiently using only input from bORNs. These findings provide scientific evidence that the most important navigational information captured by the olfactory system may come in the form of measurements of time.