ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2019
Olfactory Navigation and the Receptor Nonlinearity.
Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed.
- Neural dynamics for working memory and evidence integration during olfactory navigation in Drosophila.Nature communications · 2026Article
- Convergent motifs of early olfactory processing are recapitulated by layer-wise efficient coding.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Noise enhances odor source localization.ArXiv · 2026Article
- Neural dynamics for working memory and evidence integration during olfactory navigation inbioRxiv : the preprint server for biology · 2025Article
- Convergent motifs of early olfactory processing are recapitulated by layer-wise efficient coding.bioRxiv : the preprint server for biology · 2025Article
- How do mammals convert dynamic odor information into neural maps for landscape navigation?PLoS biology · 2024Article
- Olfactory navigation in arthropods.Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology · 2023Review
- Model of Neuromorphic Odorant-Recognition Network.Biomimetics (Basel, Switzerland) · 2023Article
- Optimal policies for Bayesian olfactory search in turbulent flows.Physical review. E · 2023Article
- Article
- Article
- Olfactory Sensing and Navigation in Turbulent Environments.Annual review of condensed matter physics · 2022Article
- Active sensing in a dynamic olfactory world.Journal of computational neuroscience · 2022Article
- Experience-dependent plasticity modulates ongoing activity in the antennal lobe and enhances odor representations.Cell reports · 2021Article
- Using your nose to find your way: Ethological comparisons between human and non-human species.Neuroscience and biobehavioral reviews · 2021Review
- Short-Term Plasticity Regulates Both Divisive Normalization and Adaptive Responses inFrontiers in computational neuroscience · 2021Article
- Spatial information from the odour environment in mammalian olfaction.Cell and tissue research · 2021Review
- Adaptive temporal processing of odor stimuli.Cell and tissue research · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The demands on a sensory system depend not only on the statistics of its inputs but also on the task. In olfactory navigation, for example, the task is to find the plume source; allocation of sensory resources may therefore be driven by aspects of the plume that are informative about source location, rather than concentration per se. Here we explore the implications of this idea for encoding odor concentration. To formalize the notion that sensory resources are limited, we considered coding strategies that partitioned the odor concentration range into a set of discriminable intervals. We developed a dynamic programming algorithm that, given the distribution of odor concentrations at several locations, determines the partitioning that conveys the most information about location. We applied this analysis to planar laser-induced fluorescence measurements of spatiotemporal odor fields with realistic advection speeds (5-20 cm/s), with or without a nearby boundary or obstacle. Across all environments, the optimal coding strategy allocated more resources (i.e., more and finer discriminable intervals) to the upper end of the concentration range than would be expected from histogram equalization, the optimal strategy if the goal were to reconstruct the plume, rather than to navigate. Finally, we show that ligand binding, as captured by the Hill equation, transforms odorant concentration into response levels in a way that approximates information maximization for navigation. This behavior occurs when the Hill dissociation constant is near the mean odor concentration, an adaptive set-point that has been observed in the olfactory system of flies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.