Understanding learning and memory is one of the great challenges of neuroscience, and olfactory learning and memory is only a small corner of a field dominated by work in hippocampus, amygdala, cerebellum, and prefrontal cortex. What we seek to contribute to this larger field is a rich and effective way to study naturalistic, repetitive, representational learning. Much of what is known about the cellular mechanisms of learning comes from the very efficient one-trial learning paradigms of fear conditioning. Based on the findings of these studies, we seek to study the more gradual, conditional learning of everyday experience, primarily via the learning of odor-reward associations paired with experimental interventions. Also, olfactory learning can be studied as representational learning; that is, as a given odor is progressively learned, and acquires meaning, it is possible to observe the corresponding changes in the ensemble of neurons that it activates and to infer what these changes imply (for example, is it simply the most weakly-activated neurons that are being shut down, or is it the neurons that convey the least useful information for distinguishing an odor from a similar odor with different implications)?
Presently, we are studying the odor learning-dependent activation of immediate-early genes (c-Fos and Egr1), the timecourses of multiple learning-dependent cascades that may determine the persistence of memory (including the determination of whether, and to what extent, to construct protein synthesis-dependent long-term memories), and the local amnestic effects of isoflurane and related mechanisms within OB. Our techniques include behavioral pharmacology, three-dimensional immediate-early gene expression mapping in optically cleared brains (including pairing FosTRAP transgenic mice with Fos immunohistochemistry), thin-section immunohistochemistry, quantitative RT-PCR to measure mRNA transcript levels of BDNF and other candidate signaling molecules over time, and RNAseq to look for additional genes reliably expressed by parameters of odor learning. Our RT-qPCR and RNAseq work is done in collaboration with the Pleiss lab in Cornell’s Department of Molecular Biology and Genetics.