Manifold learning for olfactory habituation to strongly fluctuating backgrounds.

ABSTRACT: Animals rely on their sense of smell to survive, but important olfactory cues are mixed with confounding background odors that fluctuate due to atmospheric turbulence. It is unclear how the olfactory system habituates to such stochastic backgrounds to detect behaviorally important odors. Here, we explicitly consider the high-dimensional nature of odor coding, the natural statistics of odor fluctuations and the architecture of the early olfactory pathway. We show that their combination favors a manifold learning mechanism for olfactory habituation over alternatives based on predictive filtering. Manifold learning is implemented in our model by a biologically plausible network of inhibitory interneurons in the early olfactory pathway. We demonstrate that plasticity rules based on IBCM or onl

SUBMITTER: Bourassa FXP 

PROVIDER: S-EPMC12154897 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature