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The ability to smell is crucial for most species as it enables the detection of environmental threats like smoke, fosters social interactions, and contributes to the sensory evaluation of food and eating behavior. The high prevalence of smell disturbances throughout the life span calls for a continuous effort to improve tools for quick and reliable assessment of olfactory function. Odor-dispensing pens, called Sniffin' Sticks, are an established method to deliver olfactory stimuli during diagnostic evaluation. We tested the suitability of a Bayesian adaptive algorithm (QUEST) to estimate olfactory sensitivity using Sniffin' Sticks by comparing QUEST sensitivity thresholds with those obtained using a procedure based on an established standard staircase protocol. Thresholds were measured twice with both procedures in two sessions (Test and Retest). Overall, both procedures exhibited considerable overlap, with QUEST displaying slightly higher test-retest correlations, less variability between measurements, and reduced testing duration. Notably, participants were more frequently presented with the highest concentration during QUEST, which may foster adaptation and habituation effects. We conclude that further research is required to better understand and optimize the procedure for assessment of olfactory performance.
Pubmed ID: 31195704
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Open source application to allow the presentation of stimuli and collection of data for a wide range of neuroscience, psychology and psychophysics experiments. It is intended as a free, powerful alternative to Presentation or e-Prime.
View all literature mentionsA Python-based environment of open-source software for mathematics, science, and engineering. The core packages of SciPy include: NumPy, a base N-dimensional array package; SciPy Library, a fundamental library for scientific computing; and IPython, an enhanced interactive console.
View all literature mentionsPython 2D plotting library which produces publication quality figures in variety of hardcopy formats and interactive environments across platforms. Used in python scripts, web application servers, and six graphical user interface toolkits. Used to generate plots, histograms, power spectra, bar charts, error charts, scatter plots.
View all literature mentionsWelcome to the Neuroscience Information Framework Project, designed to serve the biomedical research community. NIF maintains the largest searchable collection of neuroscience data, the largest catalog of biomedical resources, and the largest ontology for neuroscience on the web. We welcome all feedback and suggestions and are actively looking for resource providers to make their resources accessible through NIF. Learn about the tools available to help you share your data and discover a dynamic inventory of Web-based neuroscience resources.
