XVI International Symposium on Olfaction and Taste - ecro

<strong>XVI</strong> <strong>International</strong> <strong>Symposium</strong> on Olfaction and Taste
Poster session I Poster #293
The effect of repeated testing, sex, and the menstrual cycle on electrogustometric
thresholds.
E. Leslie Cameron 1 , Jessica S. Conderman 1 and Richard L. Doty 2
1 Carthage College, Psychology, Kenosha, WI, USA
2 Univeristy of Pennsylvania School of Medicine, Smell & Taste Center, Philadelphia, PA, USA
lcameron@carthage.edu
Introduction: Enhancement in discriminative responses following exposure to specific stimuli has been investigated in
most sensory systems. The effect of prior exposure and potential perceptual learning on taste thresholds, particularly as
measured by electrogustometry, appears less well studied. The current study was designed primarily to examine the
effect of repeated testing on electrogustometic thresholds. A second goal was to explore sex differences in such
thresholds and a third goal was to explore whether these thresholds are affected by the menstrual cycle.
Method: Thresholds were studied longitudinally. Testing occurred every other day for 1 month in 6 young adults (3
males, 3 females) aged 19 to 21 years (Exp 1), every day for 5 weeks in 13 young adult females (Exp 2) and three times
over the course of one menstrual cycle in 34 females of childbearing age (Exp 3). Taste thresholds were measured at 2
locations at the back of the tongue (Exp. 2) or 4 locations at the front and back of the tongue (Exps 1 and 3) corresponding
to the left and right chorda tympani and glossopharyngeal nerves using a standard 1-up, 2-down staircase method.
Phase of the menstrual cycle was determined by basal body temperature and One Step LH Urine Test, which indicates
a surge in luteinizing hormone.
Results: Thresholds decreased across test sessions in all three experiments (a trend in Exp. 3). Thresholds were lower
in females than males at all tongue locations (Exp. 1). Menstrual cycle data (from all three experiments) suggest a
decrease in threshold at mid-cycle, but are not conclusive.
Conclusion: Overall females exhibited higher taste sensitivity. Both sexes demonstrated enhancement in discriminative
responses across test sessions. The effect of the menstrual cycle is suggestive, and further research is needed to explore
the influence of hormones on taste sensitivity.
Poster session I Poster #89
Functional imaging of population coding in olfaction: neural activity to perception
Robert A. Campbell 1 , Kyle S. Honegger 1 , Hongtao Qin 1 , Wanhe Li 1 , Ebru Demir 1 , and Glenn C. Turner 1
1
Cold Spring Harbor Laboratory, Cold Spring Harbor, NY
glenncturner@gmail.com
A central goal in neuroscience is to understand the relationship between neural activity and sensory perception. How
different do two response patterns have to be in order to be perceived as distinct? This difference can be considered a
unit of the neural code - the smallest difference in activity that the animal can perceive. We have addressed this question
in the olfactory system of Drosophila, focusing on a brain area known as the Mushroom Body (MB), which is essential
for learned olfactory discrimination. Using imaging techniques to track over half the population of MB neurons, we
address this question with a completeness not currently feasible in mammalian systems.
We compared behavioral measures of olfactory discrimination with neural activity patterns monitored using calcium
imaging. Flies were trained to form a Pavlovian association with one odor, and then chose between the trained odor and a
different odor in a T-maze. To track neural activity, we targeted expression of the calcium sensor, GCaMP 3.0,
specifically to MB neurons using genetic tools available in Drosophila. We used two-photon imaging to record activity
patterns, incorporating a piezoelectric z-motor to image the entire MB in a 3-dimensional volume during a single odor
presentation. This approach enabled us to routinely monitor neural activity of ~75% of the total population of MB
neurons. By measuring odor responses on a trial-by-trial basis, we could accurately quantify response variability. This
enabled us to construct an algorithm to classify odors based on the patterns of active neurons, taking into account the
noise inherent in neuronal responses.
MB odor responses were sparse, consistent with electrophysiological recordings. Different monomolecular odors could
be readily distinguished from one another based on activity patterns, even when odors evoked exceptionally similar
41