Person: Pecot, Matthew
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Pecot
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Pecot, Matthew
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Publication Strategies for assembling columns and layers in the Drosophila visual system(BioMed Central, 2018) Millard, S. Sean; Pecot, MatthewA striking feature of neural circuit structure is the arrangement of neurons into regularly spaced ensembles (i.e. columns) and neural connections into parallel layers. These patterns of organization are thought to underlie precise synaptic connectivity and provide a basis for the parallel processing of information. In this article we discuss in detail specific findings that contribute to a framework for understanding how columns and layers are assembled in the Drosophila visual system, and discuss their broader implications.Publication Drosophila Fezf coordinates laminar-specific connectivity through cell-intrinsic and cell-extrinsic mechanisms(eLife Sciences Publications, Ltd, 2018) Peng, Jing; Santiago, Ivan; Ahn, Curie; Gur, Burak; Tsui, C Kimberly; Su, Zhixiao; Xu, Chundi; Karakhanyan, Aziz; Silies, Marion; Pecot, MatthewLaminar arrangement of neural connections is a fundamental feature of neural circuit organization. Identifying mechanisms that coordinate neural connections within correct layers is thus vital for understanding how neural circuits are assembled. In the medulla of the Drosophila visual system neurons form connections within ten parallel layers. The M3 layer receives input from two neuron types that sequentially innervate M3 during development. Here we show that M3-specific innervation by both neurons is coordinated by Drosophila Fezf (dFezf), a conserved transcription factor that is selectively expressed by the earlier targeting input neuron. In this cell, dFezf instructs layer specificity and activates the expression of a secreted molecule (Netrin) that regulates the layer specificity of the other input neuron. We propose that employment of transcriptional modules that cell-intrinsically target neurons to specific layers, and cell-extrinsically recruit other neurons is a general mechanism for building layered networks of neural connections.