bioRxivNeurosciencePreprint
Invariances in a combinatorial olfactory receptor code
Guangwei SiiD, Jessleen K KanwaliD, Yu HuiD, Christopher J. TaboneiD, Jacob Baron, Matthew Berck, Gaëtan VignoudiD, Aravinthan D.T. Samuel
Abstract
Animals can identify an odorant type across a wide range of concentrations, as well as detect changes in concentration for individual odorant type. How olfactory representations are structured to support these functions remains poorly understood. Here, we studied how a full complement of ORNs in the Drosophila larva encodes a broad input space of odorant types and concentrations. We find that dose-response relationships across odorants and ORN types follow the Hill function with shared cooperativity but different activation thresholds. These activation thresholds are drawn from a power law statistical distribution. A fixed activation function and power law distribution of activation thresholds underlie invariances in the encoding of odorant identity and intensity. Moreover, we find similar temporal response filters of ORNs across odorant types and concentrations. Such uniformity in the temporal filter may allow identity invariant coding in fluctuating or turbulent odor environments. Common patterns in ligand-receptor binding and sensory transduction across olfactory receptors may give rise to these observed invariances in the olfactory combinatorial code. Invariant patterns in the activity responses of individual ORNs and the ORN ensemble may simplify decoding by downstream circuits.
- organism: Drosophila
- assay: electronic health records
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: cell-cell communication
- approach: statistical model
- Citations
- 2
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