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基于数据驱动模型揭示的嗅球僧帽细胞在嗅入和吸入刺激时放电的差异。

Differences in olfactory bulb mitral cell spiking with ortho- and retronasal stimulation revealed by data-driven models.

机构信息

Department of Statistical Sciences and Operations Research, Virginia Commonwealth University, Richmond, Virginia, United States of America.

Department of Mathematics, Southern Methodist University, Dallas, Texas, United States of America.

出版信息

PLoS Comput Biol. 2021 Sep 20;17(9):e1009169. doi: 10.1371/journal.pcbi.1009169. eCollection 2021 Sep.

Abstract

The majority of olfaction studies focus on orthonasal stimulation where odors enter via the front nasal cavity, while retronasal olfaction, where odors enter the rear of the nasal cavity during feeding, is understudied. The coding of retronasal odors via coordinated spiking of neurons in the olfactory bulb (OB) is largely unknown despite evidence that higher level processing is different than orthonasal. To this end, we use multi-electrode array in vivo recordings of rat OB mitral cells (MC) in response to a food odor with both modes of stimulation, and find significant differences in evoked firing rates and spike count covariances (i.e., noise correlations). Differences in spiking activity often have implications for sensory coding, thus we develop a single-compartment biophysical OB model that is able to reproduce key properties of important OB cell types. Prior experiments in olfactory receptor neurons (ORN) showed retro stimulation yields slower and spatially smaller ORN inputs than with ortho, yet whether this is consequential for OB activity remains unknown. Indeed with these specifications for ORN inputs, our OB model captures the salient trends in our OB data. We also analyze how first and second order ORN input statistics dynamically transfer to MC spiking statistics with a phenomenological linear-nonlinear filter model, and find that retro inputs result in larger linear filters than ortho inputs. Finally, our models show that the temporal profile of ORN is crucial for capturing our data and is thus a distinguishing feature between ortho and retro stimulation, even at the OB. Using data-driven modeling, we detail how ORN inputs result in differences in OB dynamics and MC spiking statistics. These differences may ultimately shape how ortho and retro odors are coded.

摘要

大多数嗅觉研究都集中在前鼻腔的正鼻刺激上,而在进食过程中气味进入鼻腔后部的反鼻嗅觉则研究较少。尽管有证据表明,与正鼻刺激相比,高级处理过程不同,但嗅球(OB)中神经元协调放电对反鼻气味的编码在很大程度上仍是未知的。为此,我们使用多电极阵列在体记录大鼠 OB 僧帽细胞(MC)对食物气味的反应,同时采用两种刺激模式,并发现诱发放电率和尖峰计数协方差(即噪声相关性)有显著差异。尖峰活动的差异通常对感觉编码有影响,因此我们开发了一个单室生物物理 OB 模型,能够再现重要 OB 细胞类型的关键特性。先前在嗅觉受体神经元(ORN)中的实验表明,与正鼻刺激相比,反鼻刺激会产生较慢且空间较小的 ORN 输入,但这是否对 OB 活动有影响尚不清楚。事实上,对于这些 ORN 输入的规格,我们的 OB 模型能够捕捉到 OB 数据中的重要趋势。我们还分析了一阶和二阶 ORN 输入统计信息如何通过现象线性非线性滤波器模型动态传递到 MC 尖峰统计信息,并发现反鼻输入导致的线性滤波器大于正鼻输入。最后,我们的模型表明,ORN 的时间分布对于捕捉我们的数据至关重要,因此是正鼻和反鼻刺激之间的一个区别特征,即使在 OB 也是如此。使用数据驱动的建模,我们详细描述了 ORN 输入如何导致 OB 动力学和 MC 尖峰统计信息的差异。这些差异最终可能会影响到正鼻和反鼻气味的编码方式。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/783c/8483419/f4a6f94491c2/pcbi.1009169.g001.jpg

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