Temporal processing and context dependency in C. elegans response to mechanosensation
Abstract
A quantitative understanding of how sensory signals are transformed into motor outputs places useful constraints on brain function and helps reveal the brain's underlying computations. We investigate how the nematode C. elegans responds to time-varying mechanosensory signals using a high-throughput optogenetic assay and automated behavior quantification. We find that the behavioral response is tuned to temporal properties of mechanosensory signals, like its integral and derivative, that extend over many seconds. Mechanosensory signals, even in the same neurons, can be tailored to elicit different behavioral responses. Moreover, we find that the animal's response also depends on its behavioral context. Most dramatically, the animal ignores all tested mechanosensory stimuli during turns. Finally, we present a linear-nonlinear model that predicts the animal's behavioral response to stimulus.
Data availability
Stimulus and behavior data has been made publicly available on Figshare https://doi.org/10.6084/m9.figshare.5956348 . Raw imaging data (2TB) has been made publicly available on IEEE DataPorts http://dx.doi.org/10.21227/H27944 .
Article and author information
Author details
Funding
Simons Foundation (SCGB #324285)
- Andrew Michael Leifer
National Institutes of Health (National Human Genome Research Institute Award Number T32HG003284)
- Mochi Liu
Princeton University (Dean for Research Innovation Fund)
- Josh Shaevitz
- Andrew Michael Leifer
Simons Foundation (SCGB #543003)
- Andrew Michael Leifer
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Timothy O'Leary, University of Cambridge, United Kingdom
Version history
- Received: March 6, 2018
- Accepted: June 10, 2018
- Accepted Manuscript published: June 26, 2018 (version 1)
- Version of Record published: July 20, 2018 (version 2)
Copyright
© 2018, Liu 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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