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>