Bio-physically plausible visualization of highly scattering fluorescent neocortical models for in silico experimentation

Handle URI:
http://hdl.handle.net/10754/623518
Title:
Bio-physically plausible visualization of highly scattering fluorescent neocortical models for in silico experimentation
Authors:
Abdellah, Marwan; Bilgili, Ahmet; Eilemann, Stefan; Shillcock, Julian; Markram, Henry; Schürmann, Felix
Abstract:
Background We present a visualization pipeline capable of accurate rendering of highly scattering fluorescent neocortical neuronal models. The pipeline is mainly developed to serve the computational neurobiology community. It allows the scientists to visualize the results of their virtual experiments that are performed in computer simulations, or in silico. The impact of the presented pipeline opens novel avenues for assisting the neuroscientists to build biologically accurate models of the brain. These models result from computer simulations of physical experiments that use fluorescence imaging to understand the structural and functional aspects of the brain. Due to the limited capabilities of the current visualization workflows to handle fluorescent volumetric datasets, we propose a physically-based optical model that can accurately simulate light interaction with fluorescent-tagged scattering media based on the basic principles of geometric optics and Monte Carlo path tracing. We also develop an automated and efficient framework for generating dense fluorescent tissue blocks from a neocortical column model that is composed of approximately 31000 neurons. Results Our pipeline is used to visualize a virtual fluorescent tissue block of 50 μm3 that is reconstructed from the somatosensory cortex of juvenile rat. The fluorescence optical model is qualitatively analyzed and validated against experimental emission spectra of different fluorescent dyes from the Alexa Fluor family. Conclusion We discussed a scientific visualization pipeline for creating images of synthetic neocortical neuronal models that are tagged virtually with fluorescent labels on a physically-plausible basis. The pipeline is applied to analyze and validate simulation data generated from neuroscientific in silico experiments.
Citation:
Abdellah M, Bilgili A, Eilemann S, Shillcock J, Markram H, et al. (2017) Bio-physically plausible visualization of highly scattering fluorescent neocortical models for in silico experimentation. BMC Bioinformatics 18. Available: http://dx.doi.org/10.1186/s12859-016-1444-4.
Publisher:
Springer Nature
Journal:
BMC Bioinformatics
Issue Date:
15-Feb-2017
DOI:
10.1186/s12859-016-1444-4
Type:
Article
ISSN:
1471-2105
Sponsors:
Research reported in this publication was supported by competitive research funding from King Abdullah University of Science and Technology (KAUST).
Appears in Collections:
Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorAbdellah, Marwanen
dc.contributor.authorBilgili, Ahmeten
dc.contributor.authorEilemann, Stefanen
dc.contributor.authorShillcock, Julianen
dc.contributor.authorMarkram, Henryen
dc.contributor.authorSchürmann, Felixen
dc.date.accessioned2017-05-15T10:35:06Z-
dc.date.available2017-05-15T10:35:06Z-
dc.date.issued2017-02-15en
dc.identifier.citationAbdellah M, Bilgili A, Eilemann S, Shillcock J, Markram H, et al. (2017) Bio-physically plausible visualization of highly scattering fluorescent neocortical models for in silico experimentation. BMC Bioinformatics 18. Available: http://dx.doi.org/10.1186/s12859-016-1444-4.en
dc.identifier.issn1471-2105en
dc.identifier.doi10.1186/s12859-016-1444-4en
dc.identifier.urihttp://hdl.handle.net/10754/623518-
dc.description.abstractBackground We present a visualization pipeline capable of accurate rendering of highly scattering fluorescent neocortical neuronal models. The pipeline is mainly developed to serve the computational neurobiology community. It allows the scientists to visualize the results of their virtual experiments that are performed in computer simulations, or in silico. The impact of the presented pipeline opens novel avenues for assisting the neuroscientists to build biologically accurate models of the brain. These models result from computer simulations of physical experiments that use fluorescence imaging to understand the structural and functional aspects of the brain. Due to the limited capabilities of the current visualization workflows to handle fluorescent volumetric datasets, we propose a physically-based optical model that can accurately simulate light interaction with fluorescent-tagged scattering media based on the basic principles of geometric optics and Monte Carlo path tracing. We also develop an automated and efficient framework for generating dense fluorescent tissue blocks from a neocortical column model that is composed of approximately 31000 neurons. Results Our pipeline is used to visualize a virtual fluorescent tissue block of 50 μm3 that is reconstructed from the somatosensory cortex of juvenile rat. The fluorescence optical model is qualitatively analyzed and validated against experimental emission spectra of different fluorescent dyes from the Alexa Fluor family. Conclusion We discussed a scientific visualization pipeline for creating images of synthetic neocortical neuronal models that are tagged virtually with fluorescent labels on a physically-plausible basis. The pipeline is applied to analyze and validate simulation data generated from neuroscientific in silico experiments.en
dc.description.sponsorshipResearch reported in this publication was supported by competitive research funding from King Abdullah University of Science and Technology (KAUST).en
dc.publisherSpringer Natureen
dc.subjectModeling and simulationen
dc.subjectHighly scattering volumesen
dc.subjectFluorescence rendering and visualizationen
dc.subjectNeocortical brain modelsen
dc.subjectIn silico neuroscienceen
dc.titleBio-physically plausible visualization of highly scattering fluorescent neocortical models for in silico experimentationen
dc.typeArticleen
dc.identifier.journalBMC Bioinformaticsen
dc.contributor.institutionBlue Brain Project (BBP), École Polytechnique Fédérale de Lausanne (EPFL), Biotech Campusen
All Items in KAUST are protected by copyright, with all rights reserved, unless otherwise indicated.