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The Journal of Neuroscience, January 28, 2009, 29(4):1077-1086; doi:10.1523/JNEUROSCI.4880-08.2009

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Development/Plasticity/Repair
Early-Stage Waves in the Retinal Network Emerge Close to a Critical State Transition between Local and Global Functional Connectivity

Matthias H. Hennig,¹ Christopher Adams,² David Willshaw,¹ and Evelyne Sernagor²

¹Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, United Kingdom, and ²Institute of Neuroscience, Medical Sciences, University of Newcastle upon Tyne, Newcastle upon Tyne NE2 4HH, United Kingdom

Correspondence should be addressed to Matthias H. Hennig, Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, 10 Crichton Street, Edinburgh EH8 9AB, UK. Email: m.hennig{at}ed.ac.uk

A novel, biophysically realistic model for early-stage, acetylcholine-mediated retinal waves is presented. In this model, neural excitability is regulated through a slow after-hyperpolarization (sAHP) operating on two different temporal scales. As a result, the simulated network exhibits competition between a desynchronizing effect of spontaneous, cell-intrinsic bursts, and the synchronizing effect of synaptic transmission during retinal waves. Cell-intrinsic bursts decouple the retinal network through activation of the sAHP current, and we show that the network is capable of operating at a transition point between purely local and global functional connectedness, which corresponds to a percolation phase transition. Multielectrode array recordings show that, at this point, the properties of retinal waves are reliably predicted by the model. These results indicate that early spontaneous activity in the developing retina is regulated according to a very specific principle, which maximizes randomness and variability in the resulting activity patterns.

Key words: retinal development; retinal waves; computational model; percolation; phase transition; correlated activity

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Received Oct. 9, 2008; revised Dec. 19, 2008; accepted Dec. 22, 2008.

Correspondence should be addressed to Matthias H. Hennig, Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, 10 Crichton Street, Edinburgh EH8 9AB, UK. Email: m.hennig{at}ed.ac.uk

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