ArticleProceedings of the National Academy of Sciences of the United States of America2019
Optimal compressed sensing strategies for an array of nonlinear olfactory receptor neurons with and without spontaneous activity.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed, 27 citations in OpenAlex.
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- Simultaneous detection and estimation in olfactory sensing.bioRxiv : the preprint server for biology · 2025Article
- When noncanonical olfaction is optimal.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Convergent motifs of early olfactory processing are recapitulated by layer-wise efficient coding.bioRxiv : the preprint server for biology · 2025Article
- Limits on the computational expressivity of non-equilibrium biophysical processes.Nature communications · 2025Article
- Signal integration and adaptive sensory diversity tuning in Escherichia coli chemotaxis.Cell systems · 2024Article
- Specific connectivity optimizes learning in thalamocortical loops.Cell reports · 2024Article
- Neural Circuits for Fast Poisson Compressed Sensing in the Olfactory Bulb.bioRxiv : the preprint server for biology · 2023Article
- Functional imaging and quantification of multineuronal olfactory responses inScience advances · 2023Article
- Neural Circuits for Fast Poisson Compressed Sensing in the Olfactory Bulb.Advances in neural information processing systems · 2023Article
- Mapping enzyme catalysis with metabolic biosensing.Nature communications · 2021Article
- What the odor is not: Estimation by elimination.Physical review. E · 2021Article
- Nonlinear convergence boosts information coding in circuits with parallel outputs.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Neurotoxicity of nanoparticles entering the brain via sensory nerve-to-brain pathways: injuries and mechanisms.Archives of toxicology · 2020Review
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Authors and funding
4 authors at 2 institutions in 2 countries.
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Abstract
There are numerous different odorant molecules in nature but only a relatively small number of olfactory receptor neurons (ORNs) in brains. This "compressed sensing" challenge is compounded by the constraint that ORNs are nonlinear sensors with a finite dynamic range. Here, we investigate possible optimal olfactory coding strategies by maximizing mutual information between odor mixtures and ORNs' responses with respect to the bipartite odor-receptor interaction network (ORIN) characterized by sensitivities between all odorant-ORN pairs. For ORNs without spontaneous (basal) activity, we find that the optimal ORIN is sparse-a finite fraction of sensitives are zero, and the nonzero sensitivities follow a broad distribution that depends on the odor statistics. We show analytically that sparsity in the optimal ORIN originates from a trade-off between the broad tuning of ORNs and possible interference. Furthermore, we show that the optimal ORIN enhances performances of downstream learning tasks (reconstruction and classification). For ORNs with a finite basal activity, we find that having inhibitory odor-receptor interactions increases the coding capacity and the fraction of inhibitory interactions increases with the ORN basal activity. We argue that basal activities in sensory receptors in different organisms are due to the trade-off between the increase in coding capacity and the cost of maintaining the spontaneous basal activity. Our theoretical findings are consistent with existing experiments and predictions are made to further test our theory. The optimal coding model provides a unifying framework to understand the peripheral olfactory systems across different organisms.
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