2017
DOI: 10.1186/s12859-017-1788-4
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Reconstruction and visualization of large-scale volumetric models of neocortical circuits for physically-plausible in silico optical studies

Abstract: BackgroundWe present a software workflow capable of building large scale, highly detailed and realistic volumetric models of neocortical circuits from the morphological skeletons of their digitally reconstructed neurons. The limitations of the existing approaches for creating those models are explained, and then, a multi-stage pipeline is discussed to overcome those limitations. Starting from the neuronal morphologies, we create smooth piecewise watertight polygonal models that can be efficiently utilized to s… Show more

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Cited by 11 publications
(18 citation statements)
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“…During the interactive visualization session, the user can manually apply other repairs, if required, and perform other visual analytics tasks. Afterwards, the repaired skeleton is used to reconstruct a three-dimensional surface mesh using piecewise watertight meshing ( Abdellah et al , 2017b ). The resulting mesh can be exported into various file formats for applying simulation data on a vertex basis.…”
Section: Architecturementioning
confidence: 99%
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“…During the interactive visualization session, the user can manually apply other repairs, if required, and perform other visual analytics tasks. Afterwards, the repaired skeleton is used to reconstruct a three-dimensional surface mesh using piecewise watertight meshing ( Abdellah et al , 2017b ). The resulting mesh can be exported into various file formats for applying simulation data on a vertex basis.…”
Section: Architecturementioning
confidence: 99%
“…Due to the fuzzy definition of the soma, the relevant information contained in generic morphology skeletons that describe the soma is usually insufficient to reconstruct a realistic representation of it ( Brito et al , 2013 ; Luengo-Sanchez et al , 2015 ). In those morphologies, the soma is merely represented by a centroid, a radius that approximates the average distance between this centroid and the initial segments of each neurite, and a projective profile that is traced along a two-dimensional plane ( Abdellah et al , 2017b ; Halavi et al , 2008 ; Lasserre et al , 2012 ). In certain studies, the soma is not modeled based on the reported data in the morphological skeleton, but rather represented by an implicit surface for convenience ( Ostroumov, 2007 ).…”
Section: Architecturementioning
confidence: 99%
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“…For example, simulating tissue imaging with optical microscopy entails integrating the optical properties of brain structures into the tissue model to be capable of simulating the light interaction with the tissue. In the context of this workflow stage, a novel physically plausible method was designed and applied to visualize the tissue models by simulating the imaging pipelines of three different optical microscopes including brightfield, epi-fluorescence and light sheet fluorescence microscopy ( Abdellah et al, 2017a , b ).…”
Section: Process Descriptionmentioning
confidence: 99%
“…Figure 13A shows an in silico fluorescence image of a single neocortical neuron tagged virtually with green fluorescent protein (GFP), and Figure 13B shows imaging a large scale digital slice of few thousands of cells at a specific focal distance. The tissue reconstruction ( Abdellah et al, 2017b ) is implemented in three steps: creating piecewise watertight mesh models from the morphological models of the neurons, creating volumetric models from the mesh ones, and finally the volumes are tagged with the optical properties of the brain at the somatosensory cortical region and also with the fluorescent proteins that are expressed in the tissue.…”
Section: Process Descriptionmentioning
confidence: 99%