Abstract
Spontaneous retinal activity (known as “waves”) remodels synaptic connectivity to the lateral geniculate nucleus (LGN) during development. Analysis of retinal waves recorded with multielectrode arrays in mouse suggested that a cue for the segregation of functionally distinct (ON and OFF) retinal ganglion cells (RGCs) in the LGN may be a desynchronization in their firing, where ON cells precede OFF cells by one second. Using the recorded retinal waves as input, with two different modeling approaches we explore timing-based plasticity rules for the evolution of synaptic weights to identify key features underlying ON/OFF segregation. First, we analytically derive a linear model for the evolution of ON and OFF weights, to understand how synaptic plasticity rules extract input firing properties to guide segregation. Second, we simulate postsynaptic activity with a nonlinear integrate-and-fire model to compare findings with the linear model. We find that spike-time-dependent plasticity, which modifies synaptic weights based on millisecond-long timing and order of pre- and postsynaptic spikes, fails to segregate ON and OFF retinal inputs in the absence of normalization. Implementing homeostatic mechanisms results in segregation, but only with carefully-tuned parameters. Furthermore, extending spike integration timescales to match the second-long input correlation timescales always leads to ON segregation because ON cells fire before OFF cells. We show that burst-time-dependent plasticity can robustly guide ON/OFF segregation in the LGN without normalization, by integrating pre- and postsynaptic bursts irrespective of their firing order and over second-long timescales. We predict that an LGN neuron will become ON- or OFF-responsive based on a local competition of the firing patterns of neighboring RGCs connecting to it. Finally, we demonstrate consistency with ON/OFF segregation in ferret, despite differences in the firing properties of retinal waves. Our model suggests that diverse input statistics of retinal waves can be robustly interpreted by a burst-based rule, which underlies retinogeniculate plasticity across different species.
Highlights
During the development of the visual system, connections between neurons form and refine in a self-organized manner governed by various mechanisms
Our model shows robust behavior when applied to both mouse and ferret data, demonstrating that a common plasticity rule across species may underlie synaptic refinements in the visual system driven by spontaneous retinal activity
We have used analytical methods and computational simulations to test the hypothesis that spontaneous retinal activity guides the segregation of ON and OFF retinal ganglion cells (RGCs) in the developing mouse lateral geniculate nucleus (LGN)
Summary
During the development of the visual system, connections between neurons form and refine in a self-organized manner governed by various mechanisms. Visually-evoked activity maintains these connections; in early development when photoreceptors are functionally inactive, activity is spontaneously generated within the retina. This spontaneous activity spreads across the retina in the form of waves, and is believed to encode different cues for synapse maturation in the visual system [4]: as inappropriate connections are eliminated, appropriate connections are strengthened following Hebbian-like coincidence detection mechanisms [5,6]. There is a long-standing, and still active, debate about the relative importance of activity-dependent mechanisms in development [7,8]. Theoretical models can help inform this debate by evaluating hypotheses about the role of neural activity in the remodeling of connections
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