PT  - JOURNAL ARTICLE
AU  - Daniel A. Butts
AU  - Marla B. Feller
AU  - Carla J. Shatz
AU  - Daniel S. Rokhsar
TI  - Retinal Waves Are Governed by Collective Network Properties
AID  - 10.1523/JNEUROSCI.19-09-03580.1999
DP  - 1999 May 01
TA  - The Journal of Neuroscience
PG  - 3580--3593
VI  - 19
IP  - 9
4099  - http://www.jneurosci.org/content/19/9/3580.short
4100  - http://www.jneurosci.org/content/19/9/3580.full
SO  - J. Neurosci.1999 May 01; 19
AB  - 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.