Sequential mechanisms underlying concentration invariance in biological olfaction.
Sequential mechanisms underlying concentration invariance in biological olfaction.
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DOI：
10.3389/fneng.2011.00021
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发表时间：
2011-11-16
期刊：
影响因子：
--
通讯作者：
Zheng F
中科院分区：
文献类型：
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作者：
Cleland TA;Chen SY;Hozer KW;Ukatu HN;Wong KJ;Zheng F
浓度不变性识别给定气味（分析物）在一定浓度范围内的能力是嗅觉模态中一个异常困难的问题。尽管如此，人类和其他动物能够识别在相当大的浓度范围内的已知气味，并且这种浓度不变性也是人工系统非常期望的特性。嗅觉系统的几个属性已经被提出来有助于浓度不变性，但没有一个单独的可以合理地实现完全的浓度不变性。在这里，我们建议，哺乳动物的嗅觉系统使用至少六个计算机制串联减少气味表征的浓度依赖性方差的水平，在不同浓度的气味引起合理相似的表示，同时保留差异所产生的气味质量的差异。我们建议，剩余的方差，然后被视为任何其他来源的刺激方差，并适当地归类为“气味”通过知觉学习。我们进一步表明，幼稚小鼠对不同浓度的气味剂的反应就好像它们是质量上的差异，这表明，在气味分类之前，学习独立的补偿机制在实现浓度不变性的能力方面是有限的。
Concentration invariance—the capacity to recognize a given odorant (analyte) across a range of concentrations—is an unusually difficult problem in the olfactory modality. Nevertheless, humans and other animals are able to recognize known odors across substantial concentration ranges, and this concentration invariance is a highly desirable property for artificial systems as well. Several properties of olfactory systems have been proposed to contribute to concentration invariance, but none of these alone can plausibly achieve full concentration invariance. We here propose that the mammalian olfactory system uses at least six computational mechanisms in series to reduce the concentration-dependent variance in odor representations to a level at which different concentrations of odors evoke reasonably similar representations, while preserving variance arising from differences in odor quality. We suggest that the residual variance then is treated like any other source of stimulus variance, and categorized appropriately into “odors” via perceptual learning. We further show that naïve mice respond to different concentrations of an odorant just as if they were differences in quality, suggesting that, prior to odor categorization, the learning-independent compensatory mechanisms are limited in their capacity to achieve concentration invariance.