Astrocytes mediate synapse elimination through MEGF10 and MERTK pathways

To achieve its precise neural connectivity, the developing mammalian nervous system undergoes extensive activity-dependent synapse remodeling. Recently microglial cells have been shown to be responsible for a portion of synaptic remodeling, but the remaining mechanisms remain mysterious. Here we report a new role for astrocytes in actively engulfing CNS synapses. This process helps to mediate synapse elimination, requires the Megf10 and Mertk phagocytic pathways, and is strongly dependent on neuronal activity. Developing mice deficient in both astrocyte pathways fail to normally refine their retinogeniculate connections and retain excess functional synapses. Lastly, we show that in the adult mouse brain, astrocytes continuously engulf both excitatory and inhibitory synapses. These studies reveal a novel role for astrocytes in mediating synapse elimination in the developing and adult brain, identify Megf10 and Mertk as critical players in the synapse remodeling underlying neural circuit refinement, and have important implications for understanding learning and memory as well as neurological disease processes

Rearrangement of Retinogeniculate Projection Patterns after Eye-Specific Segregation in Mice

It has been of interest whether and when the rearrangement of neuronal circuits can be induced after projection patterns are formed during development. Earlier studies using cats reported that the rearrangement of retinogeniculate projections could be induced even after eye-specific segregation has occurred, but detailed and quantitative characterization of this rearrangement has been lacking. Here we delineate the structural changes of retinogeniculate projections in the C57BL/6 mouse in response to monocular enucleation (ME) after eye-specific segregation. When ME was performed after eye-specific segregation, rearrangement of retinogeniculate axons in the dorsal lateral geniculate nucleus (dLGN) was observed within 5 days. Although this rearrangement was observed both along the dorsomedial-ventrolateral and outer-inner axes in the dLGN, it occurred more rapidly along the outer-inner axis. We also examined the critical period for this rearrangement and found that the rearrangement became almost absent by the beginning of the critical period for ocular dominance plasticity in the primary visual cortex. Taken together, our findings serve as a framework for the assessment of phenotypes of genetically altered mouse strains as well as provide insights into the mechanisms underlying the rearrangement of retinogeniculate projections

Burst-Time-Dependent Plasticity Robustly Guides ON/OFF Segregation in the Lateral Geniculate Nucleus

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