A toolbox for navigating and analyzing the spatiotemporal properties of retinal waves

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Abstract

The precise development of the visual system is driven by retinal waves, which are bursts of spontaneous activity that propagate across retinal neurons in a wave-like fashion. In mice, retinal waves begin embryonically and continue until eye opening at the end of the second postnatal week. During this time, the mechanisms for generating and propagating retinal waves are changing, thus causing retinal waves to exhibit highly dynamic spatiotemporal properties from one day to the next. Critically, the spatiotemporal properties of retinal waves have been shown to instruct the development of the visual system, including eye-specific segregation, retinotopic mapping, direction selectivity, and potentially retinal vascularization. Currently, there is no method for the automatic detection and high-throughput analysis of the spatiotemporal properties of retinal waves. To overcome this barrier, we have created a toolbox to automatically detect retinal waves and analyze their spatiotemporal properties from data collected using multielectrode arrays or calcium imaging. We apply this toolbox to enrich our understanding of retinal waves. First, we recapitulate and uncover novel dynamic spatiotemporal properties of retinal waves in the first two postnatal weeks. Second, we apply this toolbox on ultra long physiological recordings to demonstrate that the spatiotemporal properties of waves change throughout the day in an age-dependent manner. Third, we demonstrate that this toolbox can detect waves in the presence of pharmacological agents that increase the baseline firing of neurons, potentially enabling the discovery of novel factors that perturb retinal waves and visual development. Our toolbox is an intuitive interface that provides a systemized method to segregate and analyze retinal waves and other wave-like data.

One Sentence Summary

We present a toolbox for the automatic detection and analysis of retinal waves, which accurately captures their spatiotemporal dynamics across development and reveals new insights.

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