Controlling and measuring dynamic odorant stimuli in the laboratory

Abstract

Animals experience complex odorant stimuli that vary widely in composition, intensity and temporal properties. However, stimuli used to study olfaction in the laboratory are much simpler. This mismatch arises from the challenges in measuring and controlling them precisely and accurately. Even simple pulses can have diverse kinetics that depend on their molecular identity. Here, we introduce a model to describe how stimulus kinetics depend on the molecular identity of the odorant and the geometry of the delivery system. We describe methods to deliver dynamic odorant stimuli of several types, including broadly distributed stimuli that reproduce some of the statistics of naturalistic plumes, in a reproducible and precise manner. Finally, we introduce a method to calibrate a Photo-Ionization Detector to any odorant it can detect, using no additional components. Our approaches are affordable and flexible and can be used to advance our understanding of how olfactory neurons encode real-world odor signals.

An olfactory pattern generator for on-demand combinatorial control of receptor activities

“…Microfluidic systems are appropriate for aqueous delivery of odorants to animals like C. elegans , Drosophila larvae, and zebrafish. For animals like adult flies or vertebrates, the recent development of gas-based olfactometers with high flexibility 35 and dynamic control 36 allows the construction of similar pattern generators. Olfactory pattern generation with primary odorants is an ideal way to probe combinatorial codes in olfaction.…”

Odor Stimuli: Not Just Chemical Identity

“…Future experiments may eventually all have to consider the entire environment-perception-action loop (Wallach et al, 2016), including, for instance, how wing movements might implement strategies for active sensing of odor plumes (Koehl, 2006; Li et al, 2018). However, it is an immediate objective for the community to define protocols for more viable and precise spatio-temporal stimulus generation in the lab (e.g., Gorur-Shandilya et al, 2019).…”

“…To this aim, a big technological effort is needed to measure odor mixtures at a high spatio-temporal resolution (Davies et al, 2000; Myrick et al, 2009). This could then feed into lab experiments for which advanced stimulation devices for arbitrary time series are under development (Kim et al, 2011, 2015; Jacob et al, 2017; Gorur-Shandilya et al, 2019).…”

“…To avoid the issue of depletion few adjustments should be and nowadays are applied: (1) Taking the odorant-saturated headspace of a sufficiently large reservoir of pure odorant, (2) Using a much larger headspace volume than the stimulus-volume in order to avoid measurable dilution of the odorant with air when replacing the removed odorant volume, and (3) Using a device (e.g., Mass Flow Controllers) to regulate the air flow removing the odor from the headspace in order to regulate the odorant concentration. The superior stability of repeated odor stimuli obtained with these adjustments can be seen in Gorur-Shandilya et al (2019).…”

“…Alternatively, PIDs were calibrated assuming to know the concentration based on a theoretical approach, using Raoult’s and Henry’s law for odorants diluted in a solvent (Olsson et al, 2011); or for pure odorants, simply Raoult’s law (e.g., van Breugel and Dickinson, 2014); of course, this approach can be affected by the problems related to the inconsistency of vapor pressure (see above and Figure 2). In a recent attempt (Gorur-Shandilya et al, 2019) proposed to calibrate PIDs based on the measurement of known masses of chemicals (similar to gas chromatograph calibration).…”