ArticlePLoS computational biology2021
Paradoxical relationship between speed and accuracy in olfactory figure-background segregation.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed.
- Detection of Solid-Phase Explosives Using an Electroantennogram-Based Biohybrid Sensor with Active Sniffing.Analytical chemistry · 2026Article
- Sparse input representations explain odor discrimination in complex, concentration-varying mixtures.bioRxiv : the preprint server for biology · 2026Article
- Integrated Ising model with global inhibition for decision-making.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Article
- Spatiotemporal dynamics of locomotor decisions inbioRxiv : the preprint server for biology · 2024Article
- Adaptive olfactory circuitry restores function despite severe olfactory bulb degeneration.Current biology : CB · 2023Article
- Haploinsufficiency ofThe Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Neural Circuits for Fast Poisson Compressed Sensing in the Olfactory Bulb.bioRxiv : the preprint server for biology · 2023Article
- Experience-dependent evolution of odor mixture representations in piriform cortex.PLoS biology · 2023Article
- Robust odor identification in novel olfactory environments in mice.Nature communications · 2023Article
- Neural Circuits for Fast Poisson Compressed Sensing in the Olfactory Bulb.Advances in neural information processing systems · 2023Article
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
In natural settings, many stimuli impinge on our sensory organs simultaneously. Parsing these sensory stimuli into perceptual objects is a fundamental task faced by all sensory systems. Similar to other sensory modalities, increased odor backgrounds decrease the detectability of target odors by the olfactory system. The mechanisms by which background odors interfere with the detection and identification of target odors are unknown. Here we utilized the framework of the Drift Diffusion Model (DDM) to consider possible interference mechanisms in an odor detection task. We first considered pure effects of background odors on either signal or noise in the decision-making dynamics and showed that these produce different predictions about decision accuracy and speed. To test these predictions, we trained mice to detect target odors that are embedded in random background mixtures in a two-alternative choice task. In this task, the inter-trial interval was independent of behavioral reaction times to avoid motivating rapid responses. We found that increased backgrounds reduce mouse performance but paradoxically also decrease reaction times, suggesting that noise in the decision making process is increased by backgrounds. We further assessed the contributions of background effects on both noise and signal by fitting the DDM to the behavioral data. The models showed that background odors affect both the signal and the noise, but that the paradoxical relationship between trial difficulty and reaction time is caused by the added noise.
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