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Object-oriented olfaction: challenges for chemosensation and for chemosensory research.
- Source :
-
Trends in Neurosciences . Oct2024, Vol. 47 Issue 10, p834-848. 15p. - Publication Year :
- 2024
-
Abstract
- Recognizing objects by smell is a crucial ability for many species. To accomplish this, the brain must associate activity patterns of olfactory sensory neurons with the objects that elicited them. Recognition is hard because objects are dynamic entities whose molecular composition varies due to extrinsic and intrinsic factors and because background odors are often present. These factors lead to variability in receptor activation patterns evoked by any given object. Currently, the behavioral ability to overcome these sources of variance and the underlying neuronal mechanisms are poorly understood. We propose that extraction of invariant object representations is a major function of the elaborate olfactory cortical network. Revealing the limits of olfactory capabilities, and the neuronal mechanisms that enable them, calls for integration of natural sources of stimulus variability in experimental paradigms. Many animal species use olfaction to extract information about objects in their environment. Yet, the specific molecular signature that any given object emits varies due to various factors. Here, we detail why such variability makes chemosensory-mediated object recognition such a hard problem, and we propose that a major function of the elaborate chemosensory network is to overcome it. We describe previous work addressing different elements of the problem and outline future research directions that we consider essential for a full understanding of object-oriented olfaction. In particular, we call for extensive representation of olfactory object variability in chemical, behavioral, and electrophysiological analyses. While written with an emphasis on macrosmatic mammalian species, our arguments apply to all organisms that employ chemosensation to navigate complex environments. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01662236
- Volume :
- 47
- Issue :
- 10
- Database :
- Academic Search Index
- Journal :
- Trends in Neurosciences
- Publication Type :
- Academic Journal
- Accession number :
- 180133983
- Full Text :
- https://doi.org/10.1016/j.tins.2024.08.008