The Peripheral Representation of Odor Space

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Summary (Project 1: The peripheral representation of odor space) Progress towards an understanding of olfactory coding has been hampered by long-standing hurdles created by the nature of the stimulus and the complexity of the underlying sensory biology. At the same time, a description of olfactory coding in mammals would provide a unique window into how multidimensional stimuli are represented by the mammalian brain. Olfactory systems use large families of odorant receptors to detect a vast number of chemical stimuli. An important challenge that must be overcome to better understand olfaction is to establish a comprehensive description of what features of olfactory stimuli are represented by the system. Doing so requires that we overcome previously insurmountable technical challenges in identifying the stimulus specificity of a large number of receptors to a large number of odorants, and that we generate a theoretical framework for quantifying and exploring the multidimensional “space” of odors and receptors. Here, we propose an interdisciplinary effort to comprehensively characterize the odorant response properties of a large number of odorant receptors in vivo, and to use this information to explicitly and rigorously test novel models of odor coding. This project exploits the one-to-one correspondence between odorant receptors and glomeruli in the olfactory bulb of mice. Aim 1 will characterize the sensitivities of a large number of receptors (glomeruli) in awake, intact animals using functional imaging. Aim 2 will map these glomerular responses to specific receptors using emerging spatial transcriptomics methods. Aim 3 will use a powerful genomics-based assay to identify the highest affinity receptors for a large set of individual odors. Aim 4 will test a novel theoretical framework for understanding how odor features are represented. This large-scale in vivo multidisciplinary approach will provide long-sought data and analytical tools to rigorously explore potential models of odor coding.