Olfactory Evidence Accumulation in Mice

Abstract

In nature, odor cues from distant objects are sparse and highly fluctuating due to turbulent airflow. Animals may integrate odor concentration sampled over time rather than rely on transient odor concentration to effectively locate an object. To study how animals integrate and weigh discrete olfactory evidence over time, I developed a new behavioral task in which mice make binary decisions under fluctuating odor stimuli over many seconds. A custom-built device allowed the precise delivery of discrete, short pulses of odors at arbitrary Poisson-distributed pulse rates. I found that trained mice can readily differentiate stochastic odor stimuli with different average pulse rates presented over many seconds. In order to investigate how active, discrete sniff-based sampling of a stochastically varying environmental cue affects the neural representation and perceptual interpretation of the cue, calcium imaging in the axon terminals of olfactory sensory neurons (OSNs) in the glomeruli of olfactory bulb (OB) was performed. I discovered that OSN activity was highly modulated by the phase of the sniffing cycle. Regression of behavioral outcome against the timing of odor pulses in the breathing cycle revealed a kernel that weighted pulses arriving during the inhalation cycle more than during exhalation. This kernel matched the OSN activity kernel over breathing cycle, suggesting that the strength of the perception elicited by single pulses was directly related to the strength of the OSN responses. Decision noise scaled with the number of pulses presented. Tetrode recordings of single-unit neural activities in the anterior piriform cortex (APC) showed high correlations with transient odor pulses, but not the accumulated evidence. The neural activities in APC exhibited diverse dependency on the phase of sniffing, ranging from being strongly modulated by the sniff cycles to sniff-cycle invariant. My study indicates that mice integrate discrete olfactory inputs over several seconds to make decisions and that perceptual evidence is weighted by the intensity of the OSN response to the input. Furthermore, the platform described in this dissertation introduces a new paradigm in perceptual decision-making in which I can, unlike in vision or audition, record neural activity at all levels, from the first layer of sensory neurons to the decision-making networks.