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Updated: Aug 8, 2026

An Acute Retinal Model for Evaluating Blood Retinal Barrier Breach and Potential Drugs for Treatment
Published on: September 13, 2016
Retinal waves are governed by collective network properties
D A Butts1, M B Feller, C J Shatz
1Physical Biosciences Division, Lawrence Berkeley National Laboratory, and the Department of Physics, University of California, Berkeley, California 94720-7300, USA. dbutts@physics.berkeley.edu
Abstract:
Propagating neural activity in the developing mammalian retina is required for the normal patterning of retinothalamic connections. This activity exhibits a complex spatiotemporal pattern of initiation, propagation, and termination. Here, we discuss the behavior of a model of the developing retina using a combination of simulation and analytic calculation. Our model produces spatially and temporally restricted waves without requiring inhibition, consistent with the early depolarizing action of neurotransmitters in the retina. We find that highly correlated, temporally regular, and spatially restricted activity occurs over a range of network parameters; this ensures that such spatiotemporal patterns can be produced robustly by immature neural networks in which synaptic transmission by individual neurons may be unreliable. Wider variation of these parameters, however, results in several different regimes of wave behavior. We also present evidence that wave properties are locally determined by a single variable, the fraction of recruitable (i.e., nonrefractory) cells within the dendritic field of a retinal neuron. From this perspective, a given local area's ability to support waves with a wide range of propagation velocities-as observed in experiment-reflects the variability in the local state of excitability of that area. This prediction is supported by whole-cell voltage-clamp recordings, which measure significant wave-to-wave variability in the amount of synaptic input a cell receives when it participates in a wave. This approach to describing the developing retina provides unique insight into how the organization of a neural circuit can lead to the generation of complex correlated activity patterns.
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