A population of gap junction-coupled neurons drives recurrent network activity in a developing visual circuit

间隙连接偶联神经元群驱动视觉回路发育过程中的循环网络活动

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作者:Zhenyu Liu, Christopher M Ciarleglio, Ali S Hamodi, Carlos D Aizenman, Kara G Pratt

Abstract

In many regions of the vertebrate brain, microcircuits generate local recurrent activity that aids in the processing and encoding of incoming afferent inputs. Local recurrent activity can amplify, filter, and temporally and spatially parse out incoming input. Determining how these microcircuits function is of great interest because it provides glimpses into fundamental processes underlying brain computation. Within the Xenopus tadpole optic tectum, deep layer neurons display robust recurrent activity. Although the development and plasticity of this local recurrent activity has been well described, the underlying microcircuitry is not well understood. Here, using a whole brain preparation that allows for whole cell recording from neurons of the superficial tectal layers, we identified a physiologically distinct population of excitatory neurons that are gap junctionally coupled and through this coupling gate local recurrent network activity. Our findings provide a novel role for neuronal coupling among excitatory interneurons in the temporal processing of visual stimuli.

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