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YE, BING (contact); DIERSSEN, MARA New methods and theories to interrogate organizational principles from single cell to neuronal networks EB028159
Our project “New Methods and Theories to interrogate Organizational Principles from Single Cell to Neuronal Networks” aims to develop a user-friendly modeling toolset to study how single neurons morphology can determine the connectivity pattern of the network and shed light to the rules linking both. The connectivity patterns of a particular brain region will be estimated by generating a morphological neural network model that uses both neural population data and single neuronal reconstruction data extracted from fluorescent whole brain images. We already developed a population analysis tool to compute the location and orientation of each neuron relative to a reference coordinate system. Our tool is able to overcome the three limitations that are commonly found in cell detection algorithms: undetected neurons, false positives in axonal regions and out of memory errors that arise while processing whole brain images. Our software is Open Source; the source code of our population analysis tool, mainly written in Python, will be available in GitHub. User Friendly, as it can be managed through Graphical User Interface (GUI) or Command Line Interface (CLI). Cross-platform, as it can be executed over Linux and Windows. Big Data oriented: our algorithm is able to compute in reasonable time neuronal location and orientation from whole brain images with a resolution of tenths of microns per voxel and a memory size around the order of tens of Terabytes. Computational Tractability: it is able to split whole brain images into small overlapping 3D-images to avoid runtime out of memory errors. Computational Efficiency: the user can select parallel computing parameters to speed up computing time. Hardware Scalability. The performance is scalable to available computing resources and can be executed on a regular laptop, a workstation or a computer cluster. Vaa3d visualization: the location of detected neurons can be stored in a file format allowing visualization using the rendering power of Vaa3D software. The beta version of the Population Analysis Tool will be released very soon and 1) We are seeking labs interested on using our software to evaluate the usability of the tool and to identify those missing functionalities. 2) We need mesoscopic image datasets taken from different microscopes to evaluate the robustness of the tool and to provide support for more image formats and 3) we are interested in whole brain images with high density neural labeling.