Presentation Details
Manipulating synthetic optogenetic odors reveals the coding logic of olfactory perception

Edmund Chong1, Monica Moroni2, 3, Shy Shoham1, 4, 5, Stefano Panzeri2, Dmitry Rinberg1.4.

1Neuroscience Institute, NYU Langone Health, New York, NY, USA.2Neural Computation Laboratory, Istituto Italiano di Tecnologia, Rovereto, Italy.3CIMeC, University of Trento, Rovereto, Italy.4Center for Neural Science, New York University, New York, NY, USA.5Tech4Health Institute, NYU Langone Health, New York, NY, USA


How does neural activity generate perception? The spatial identities and temporal latencies of activated units correlate with external sensory features, but finding the subspace of activity that is consequential for perception, remains challenging. We trained mice to recognize synthetic odors: optogenetically-driven spatiotemporal patterns of glomerular activity in the olfactory bulb.  We then performed precise spatial or temporal perturbations on trained patterns and measured how recognition changes. Changes in recognition reflect the perceptual relevance of the modified feature. We modeled recognition as the matching of glomerular activity to learned templates, and uncovered what forms a perceptually-meaningful pattern template: activation sequences ordered by latencies relative to each other, with surprisingly minimal effect of sniff. Within templates, spatially-identified glomeruli contribute additively, with larger contributions from earlier-activated glomeruli.  Template matching with these perceptually-meaningful features can account for animals’ responses, with the degree of mismatch predicting changes in recognition. The model accurately generalizes to novel spatio-temporal manipulations of patterns, and produces non-linear responses that resemble the non-linear responses in the data. This is the first report to our knowledge, that not only establishes a causal role for neural activity sequences in perception, but also uncovers the perceptually-relevant coding schemes governing these sequences. Our synthetic approach reveals the fundamental logic of the olfactory code, and provides a general framework for testing links between sensory activity and perception.

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