10.3389/fninf.2019.00068.s001 Dezhe Z. Jin Dezhe Z. Jin Ting Zhao Ting Zhao David L. Hunt David L. Hunt Rachel P. Tillage Rachel P. Tillage Ching-Lung Hsu Ching-Lung Hsu Nelson Spruston Nelson Spruston Data_Sheet_1_ShuTu: Open-Source Software for Efficient and Accurate Reconstruction of Dendritic Morphology.pdf Frontiers 2019 neuron morphology reconstruction dendrite automatic reconstruction method software 2019-10-31 04:02:34 Dataset https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_ShuTu_Open-Source_Software_for_Efficient_and_Accurate_Reconstruction_of_Dendritic_Morphology_pdf/10093700 <p>Neurons perform computations by integrating inputs from thousands of synapses—mostly in the dendritic tree—to drive action potential firing in the axon. One fruitful approach to studying this process is to record from neurons using patch-clamp electrodes, fill the recorded neurons with a substance that allows subsequent staining, reconstruct the three-dimensional architectures of the dendrites, and use the resulting functional and structural data to develop computer models of dendritic integration. Accurately producing quantitative reconstructions of dendrites is typically a tedious process taking many hours of manual inspection and measurement. Here we present ShuTu, a new software package that facilitates accurate and efficient reconstruction of dendrites imaged using bright-field microscopy. The program operates in two steps: (1) automated identification of dendritic processes, and (2) manual correction of errors in the automated reconstruction. This approach allows neurons with complex dendritic morphologies to be reconstructed rapidly and efficiently, thus facilitating the use of computer models to study dendritic structure-function relationships and the computations performed by single neurons.</p>