Contrast-polarity specific mapping improves efficiency of neuronal computation for collision detection
- Baylor College of Medicine, United States
- Houston Methodist Research Institute, United States
- Rice University, United States
Abstract
Neurons receive information through their synaptic inputs, but the functional significance of how those inputs are mapped on to a cell's dendrites remains unclear. We studied this question in a grasshopper visual neuron that tracks approaching objects and triggers escape behavior before an impending collision. In response to black approaching objects, the neuron receives OFF excitatory inputs that form a retinotopic map of the visual field onto compartmentalized, distal dendrites. Subsequent processing of these OFF inputs by active membrane conductances allows the neuron to discriminate the spatial coherence of such stimuli. In contrast, we show that ON excitatory synaptic inputs activated by white approaching objects map in a random manner onto a more proximal dendritic field of the same neuron. The lack of retinotopic synaptic arrangement results in the neuron’s inability to discriminate the coherence of white approaching stimuli. Yet, the neuron retains the ability to discriminate stimulus coherence for checkered stimuli of mixed ON/OFF polarity. The coarser mapping and processing of ON stimuli thus has a minimal impact, while reducing the total energetic cost of the circuit. Further, we show that these differences in ON/OFF neuronal processing are behaviorally relevant, being tightly correlated with the animal’s escape behavior to light and dark stimuli of variable coherence. Our results show that the synaptic mapping of excitatory inputs affects the fine stimulus discrimination ability of single neurons and document the resulting functional impact on behavior.
Data availability
The data and code used to generate the final figures is available from Dryad (DOI: 10.5061/dryad.prr4xgxqp). The modeling code is available from ModelDB (Accession number: 267594).
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Dataset for "Contrast-polarity specific mapping improves efficiency of neuronal computation for collision detection"Dryad Digital Repository, doi:10.5061/dryad.prr4xgxqp.
Article and author information
Author details
Richard Burkett Dewell
Margaret Eisenbrandt
Funding
National Science Foundation (DMS-1120952)
- Fabrizio Gabbiani
National Science Foundation (DBI-2021795)
- Fabrizio Gabbiani
National Eye Institute (EY-002520-37)
- Fabrizio Gabbiani
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Damon A Clark, Yale University, United States
Version history
- Received: April 26, 2022
- Preprint posted: May 10, 2022 (view preprint)
- Accepted: October 27, 2022
- Accepted Manuscript published: October 31, 2022 (version 1)
- Version of Record published: November 18, 2022 (version 2)
- Version of Record updated: February 16, 2023 (version 3)
Copyright
© 2022, Dewell et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Contrast-polarity specific mapping improves efficiency of neuronal computation for collision detection
eLife 11:e79772.
https://doi.org/10.7554/eLife.79772
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