MCA Pilot PUI: From glomeruli to pollination: vertical integration of neural encoding through ecologically-relevant behavior

About This Grant

Ecological degradation driven by human behavior and the resultant disruptions to sensory processing is a major focus of conservation neuroscience. The impacts of odor pollution have come under increasing scrutiny in recent decades. Agrochemical scent pollution has been found to disrupt bumblebee behavior, a particularly alarming finding in light of their critical role as pollinators in agricultural and natural ecosystems. These findings imply that neural processing of floral odors is impacted by odor pollution. One barrier for understanding these impacts of agrochemicals on bumblebee foraging behavior is that there are no concrete computational structures for representing and exploring odor perception, as current methods are statistical in nature. This means pollution cannot be easily measured, or quantified; which makes it challenging to develop agricultural recommendations. This project is building upon earlier work that established a quantification mechanism for complex odors (i.e. odors made up of many molecules) to establish an algorithm for representing bumblebee odor perception. The established “Compounds with Borders” (CWB) method allows the difference between any two odors to be represented as an angular distance, and has been used to establish a ‘safe zone’ of odor pollution for complex odors: polluted-odors within a 20-30 degree range are generalized. Next steps include expanding CWB into a more comprehensive geometry that can accurately account for simpler odors as well. This work will be performed at a ‘primarily undergraduate institution’, incorporating valuable research experiences for the next generation of STEM professionals. Given the neurophysiological organization of odor processing, the relative importance of molecular-identity versus -feature of odorants is linked to stimulus complexity, with encoding of simpler odors correlating with identity and more complex odors correlating with features. “Compounds with Borders” is particularly effective for complex blends because it quantifies the amount of sensory energy that is distributed across molecular features in an odor using a Euclidean approach where ‘dimensions’ in odor space represent those features. The next hurdle is to expand the geometry of this odor-space to incorporate molecular identity. This is not logistically tractable without data that delineate what level of odor complexity shifts the primary-processing output from ‘identity’ to ‘feature’ correlation. This project aims to develop a more comprehensive geometry using associative odor learning paradigms combined with recording neural activity at both the input (antennae) and output (antennal lobe tracts) from primary olfactory processing. Gas Chromatography-Electroantennographic recordings will establish a species specific odor-salience across molecular identities and features. Spike-resolved multi-unit recordings from the antennal lobe tracts will assay odor information as it moves forward to integration and action centers. Comparing the point at which odor responses shift from correlating with molecular identity to molecular feature at a neurophysiological and behavioral level will inform an expanded geometry that utilizes stimulus complexity to shape dimensional weighting. Thus, this work aims to establish a novel paradigm for vertical integration of neural encoding through behavior in olfaction. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.