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Deconstructing Odorant Identity via Primacy in Dual Networks
- Source :
- Neural Comput
- Publication Year :
- 2019
-
Abstract
- In the olfactory system, odor percepts retain their identity despite substantial variations in concentration, timing, and background. We propose a novel strategy for encoding intensity-invariant stimuli identity that is based on representing relative rather than absolute values of the stimulus features. Because, in this scheme, stimulus identity depends on relative amplitudes of stimulus features, identity becomes invariant with respect to variations in intensity and monotonous non-linearities of neuronal responses. In the olfactory system, stimulus identity can be represented by the identities of the p strongest responding odorant receptor types out of a species dependent complement. We show that this information is sufficient to recover sparse stimuli (odorants) via elastic net loss minimization. Such a minimization has to be performed under constraints imposed by the relationships between stimulus features. We map this problem onto the dual problem of minimizing a functional of Lagrange multipliers. The dual problem, in turn, can be solved by a neural network whose Lyapunov function represents the dual Lagrangian. We thus propose that networks in the piriform cortex compute odorant identity and implement dual computations with the sparse activities of individual neurons representing the Lagrange multipliers.<br />10 pages, 1 figure
- Subjects :
- Olfactory system
Cognitive Neuroscience
Models, Neurological
Identity (social science)
Action Potentials
Receptors, Odorant
Olfactory Receptor Neurons
Article
03 medical and health sciences
0302 clinical medicine
Arts and Humanities (miscellaneous)
Animals
Humans
030304 developmental biology
Mathematics
0303 health sciences
Communication
Quantitative Biology::Neurons and Cognition
business.industry
Extramural
Olfactory Pathways
DUAL (cognitive architecture)
Olfactory Perception
Smell
Odor
Odor recognition
FOS: Biological sciences
Quantitative Biology - Neurons and Cognition
Odorants
Neurons and Cognition (q-bio.NC)
business
Neuroscience
030217 neurology & neurosurgery
Algorithms
Subjects
Details
- ISSN :
- 1530888X
- Volume :
- 31
- Issue :
- 4
- Database :
- OpenAIRE
- Journal :
- Neural computation
- Accession number :
- edsair.doi.dedup.....4fe0683ff342b6f92d2e76aa6078fcb4