Darwin, olha o olho de novo: Convergência análoga de inputs sustentados e transitórios em caminhos paralelos liga e desliga para a computação do movimento retinal

segunda-feira, dezembro 26, 2016

Analogous Convergence of Sustained and Transient Inputs in Parallel On and Off Pathways for Retinal Motion Computation

Matthew J. Greene 6, Jinseop S. Kim 5,6, H. Sebastian Seung, 4


5Present address: Department of Structure and Function of Neural Networks, Korea Brain Research Institute, Daegu 700-300, Republic of Korea

6Co-first author

Published Online: February 18, 2016

Open Access




Highlights

• We analyzed serial electron microscopic images of a mouse retina

• On starburst amacrine cells (SACs) and bipolar cells (BCs) were reconstructed

• We defined an additional On BC type in the course of classifying On BCs

• Sustained and transient BC types are wired to SAC dendrites at different distances

Summary

Visual motion information is computed by parallel On and Off pathways in the retina, which lead to On and Off types of starburst amacrine cells (SACs). The approximate mirror symmetry between this pair of cell types suggests that On and Off pathways might compute motion using analogous mechanisms. To test this idea, we reconstructed On SACs and On bipolar cells (BCs) from serial electron microscopic images of a mouse retina. We defined a new On BC type in the course of classifying On BCs. Through quantitative contact analysis, we found evidence that sustained and transient On BC types are wired to On SAC dendrites at different distances from the SAC soma, mirroring our previous wiring diagram for the Off BC-SAC circuit. Our finding is consistent with the hypothesis that On and Off pathways contain parallel correlation-type motion detectors.

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Received: September 25, 2015; Received in revised form: November 20, 2015; Accepted: January 23, 2016; Published: February 18, 2016

© 2016 The Authors. Published by Elsevier Inc.

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