Construction of odor representations by olfactory bulb microcircuits

Like other sensory systems, the olfactory system transduces specific features of the external environment and must construct an organized sensory representation from these highly fragmented inputs. As with these other systems, this representation is not accurate per se, but is constructed for utility, and emphasizes certain, presumably useful, features over others. I here describe the cellular and circuit mechanisms of the peripheral olfactory system that underlie this process of sensory construction, emphasizing the distinct architectures and properties of the two prominent computational layers in the olfactory bulb. Notably, while the olfactory system solves essentially similar conceptual problems to other sensory systems, such as contrast enhancement, activity normalization, and extending dynamic range, its peculiarities often require qualitatively different computational algorithms than are deployed in other sensory modalities. In particular, the olfactory modality is intrinsically high dimensional, and lacks a simple, externally defined basis analogous to wavelength or pitch on which elemental odor stimuli can be quantitatively compared. Accordingly, the quantitative similarities of the receptive fields of different odorant receptors (ORs) vary according to the statistics of the odor environment. To resolve these unusual challenges, the olfactory bulb appears to utilize unique nontopographical computations and intrinsic learning mechanisms to perform the necessary high-dimensional, similarity-dependent computations. In sum, the early olfactory system implements a coordinated set of early sensory transformations directly analogous to those in other sensory systems, but accomplishes these with unique circuit architectures adapted to the properties of the olfactory modality.