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An Image-Free Opto-Mechanical System for Creating Virtual Environments and Imaging Neuronal Activity in Freely Moving Caenorhabditis elegans

Overview of attention for article published in PLOS ONE, September 2011
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Title
An Image-Free Opto-Mechanical System for Creating Virtual Environments and Imaging Neuronal Activity in Freely Moving Caenorhabditis elegans
Published in
PLOS ONE, September 2011
DOI 10.1371/journal.pone.0024666
Pubmed ID
Authors

Serge Faumont, Gary Rondeau, Tod R. Thiele, Kristy J. Lawton, Kathryn E. McCormick, Matthew Sottile, Oliver Griesbeck, Ellie S. Heckscher, William M. Roberts, Chris Q. Doe, Shawn R. Lockery

Abstract

Non-invasive recording in untethered animals is arguably the ultimate step in the analysis of neuronal function, but such recordings remain elusive. To address this problem, we devised a system that tracks neuron-sized fluorescent targets in real time. The system can be used to create virtual environments by optogenetic activation of sensory neurons, or to image activity in identified neurons at high magnification. By recording activity in neurons of freely moving C. elegans, we tested the long-standing hypothesis that forward and reverse locomotion are generated by distinct neuronal circuits. Surprisingly, we found motor neurons that are active during both types of locomotion, suggesting a new model of locomotion control in C. elegans. These results emphasize the importance of recording neuronal activity in freely moving animals and significantly expand the potential of imaging techniques by providing a mean to stabilize fluorescent targets.

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Mendeley readers

The data shown below were compiled from readership statistics for 182 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 3%
United Kingdom 2 1%
Austria 1 <1%
Japan 1 <1%
Netherlands 1 <1%
Unknown 171 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 58 32%
Researcher 34 19%
Student > Master 19 10%
Student > Bachelor 13 7%
Professor > Associate Professor 12 7%
Other 25 14%
Unknown 21 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 73 40%
Neuroscience 24 13%
Engineering 18 10%
Physics and Astronomy 14 8%
Biochemistry, Genetics and Molecular Biology 11 6%
Other 20 11%
Unknown 22 12%