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Lag normalization in an electrically coupled neural network

Nature Neuroscience volume 16, pages 154–156 (2013)Cite this article

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Abstract

Moving objects can cover large distances while they are processed by the eye, usually resulting in a spatially lagged retinal response. We identified a network of electrically coupled motion–coding neurons in mouse retina that act collectively to register the leading edges of moving objects at a nearly constant spatial location, regardless of their velocity. These results reveal a previously unknown neurophysiological substrate for lag normalization in the visual system.

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Figure 1: Lag normalization in the electrically coupled population of upward coding ON-OFF DSGCs.
Figure 2: Gap junctions between upward coding DSGCs mediate lateral excitation.
Figure 3: Serial interactions between multiple electrically coupled DSGCs are required for lag normalization.

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Acknowledgements

We thank W.H. Baldridge, B. Chow and K.R. Delaney for comments, K. Johnson for writing routines in Matlab and Z. Shi for maintaining mouse colonies. This work was supported in part by US National Science Foundation PHY-1058202 and EF-0928048 (V.B.) and was completed at the Aspen Center for Physics, which is supported by National Science Foundation PHY-1066293. This work was also supported by Canadian Institutes of Health Research 342202-2007 and Foundation for Fighting Blindness (Canada) (G.B.A.).

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Authors and Affiliations

  1. Department of Biology, University of Victoria, Victoria, British Columbia, Canada

    Stuart Trenholm & Gautam B Awatramani

  2. Department of Physics, Princeton University, Princeton, New Jersey, USA

    David J Schwab

  3. David Rittenhouse Laboratory, University of Pennsylvania, Philadelphia, Pennsylvania, USA

    Vijay Balasubramanian

  4. Laboratoire de Physique Théorique, Ecole Normale Supérieure, Paris, France

    Vijay Balasubramanian

Authors
  1. Stuart Trenholm
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  2. David J Schwab
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  3. Vijay Balasubramanian
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  4. Gautam B Awatramani
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Contributions

All experiments were performed and analyzed by S.T. and were designed by S.T. and G.B.A. The computational model was developed by D.J.S., V.B. and G.B.A. The paper was written by S.T., V.B. and G.B.A.

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Correspondence to Gautam B Awatramani.

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The authors declare no competing financial interests.

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Trenholm, S., Schwab, D., Balasubramanian, V. et al. Lag normalization in an electrically coupled neural network. Nat Neurosci 16, 154–156 (2013). https://doi.org/10.1038/nn.3308

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