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Directional Summation in Non-direction Selective Retinal Ganglion Cells

Overview of attention for article published in PLoS Computational Biology, March 2013
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Title
Directional Summation in Non-direction Selective Retinal Ganglion Cells
Published in
PLoS Computational Biology, March 2013
DOI 10.1371/journal.pcbi.1002969
Pubmed ID
Authors

Syed Y. Abbas, Khaldoun C. Hamade, Ellen J. Yang, Scott Nawy, Robert G. Smith, Diana L. Pettit

Abstract

Retinal ganglion cells receive inputs from multiple bipolar cells which must be integrated before a decision to fire is made. Theoretical studies have provided clues about how this integration is accomplished but have not directly determined the rules regulating summation of closely timed inputs along single or multiple dendrites. Here we have examined dendritic summation of multiple inputs along On ganglion cell dendrites in whole mount rat retina. We activated inputs at targeted locations by uncaging glutamate sequentially to generate apparent motion along On ganglion cell dendrites in whole mount retina. Summation was directional and dependent13 on input sequence. Input moving away from the soma (centrifugal) resulted in supralinear summation, while activation sequences moving toward the soma (centripetal) were linear. Enhanced summation for centrifugal activation was robust as it was also observed in cultured retinal ganglion cells. This directional summation was dependent on hyperpolarization activated cyclic nucleotide-gated (HCN) channels as blockade with ZD7288 eliminated directionality. A computational model confirms that activation of HCN channels can override a preference for centripetal summation expected from cell anatomy. This type of direction selectivity could play a role in coding movement similar to the axial selectivity seen in locust ganglion cells which detect looming stimuli. More generally, these results suggest that non-directional retinal ganglion cells can discriminate between input sequences independent of the retina network.

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Geographical breakdown

Country Count As %
Germany 1 3%
Australia 1 3%
Unknown 29 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 32%
Researcher 8 26%
Student > Master 5 16%
Professor 1 3%
Unspecified 1 3%
Other 1 3%
Unknown 5 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 42%
Neuroscience 6 19%
Engineering 2 6%
Environmental Science 1 3%
Psychology 1 3%
Other 3 10%
Unknown 5 16%