Constructing subject-specific virtual brains from multimodal neuroimaging data

Abstract

Event Abstract Back to Event Constructing subject-specific virtual brains from multimodal neuroimaging data Michael Schirner1, 2, Simon Rothmeier1, 2 and Petra Ritter1, 2* 1 Charité Berlin, Germany 2 Bernstein Center for Computational Neuroscience, Bernstein Focus State Dependencies of Learning, Germany Large amounts of multimodal neuroimaging data are acquired every year worldwide. In order to extract high dimensional information for computational neuroscience applications standardized data fusion and efficient reduction into integrative data structures are required. Such self-consistent multimodal data sets can be used for computational brain modeling to constrain models with individual measurable features of the brain, such as done with The Virtual Brain (TVB). TVB is a simulation platform that uses empirical structural and functional data to build full brain models of individual humans. For convenient model construction, we developed a shell scripted processing pipeline for structural, functional and diffusion-weighted magnetic resonance imaging (MRI) and optionally electroencephalography (EEG) data. The pipeline combines several state-of-the-art neuroinformatics tools to generate subject-specific cortical and subcortical parcellations, surface-tessellations, structural and functional connectomes, lead field matrices, electrical source activity estimates and region-wise aggregated blood oxygen level dependent (BOLD) functional MRI (fMRI) time-series. The output files of the pipeline can be directly uploaded to TVB to create and simulate individualized large-scale network models. We detail the pitfalls of the individual processing streams and discuss ways of validation. With the pipeline we also introduce novel ways of estimating the transmission strengths of fiber tracts in whole-brain structural connectivity (SC) networks and compare the outcomes of different tractography or parcellation approaches. We tested the functionality of the pipeline on 50 multimodal data sets. In order to quantify the robustness of the connectome extraction part of the pipeline we computed several metrics that quantify its rescan reliability and compared them to other tractography approaches. Together with the pipeline we present several principles to guide future efforts to standardize brain model construction. The code of the pipeline and the fully processed data sets are made available to the public via The Virtual Brain website (thevirtualbrain.org) and via Github (https://github.com/BrainModes/TVB-empirical-data-pipeline). Furthermore, the pipeline can be directly used with High Performance Computing (HPC) resources on the Neuroscience Gateway Portal (http://www.nsgportal.org) through a convenient web-interface. References Michael Schirner, Simon Rothmeier, Viktor K. Jirsa, Anthony Randal McIntosh, Petra Ritter, An automated pipeline for constructing personalized virtual brains from multimodal neuroimaging data, NeuroImage, Available online 31 March 2015, ISSN 1053-8119, http://dx.doi.org/10.1016/j.neuroimage.2015.03.055 Keywords: multi modal data, the virtual brain, connectome, tractography, computational modeling Conference: Neuroinformatics 2015, Cairns, Australia, 20 Aug - 22 Aug, 2015. Presentation Type: Poster, to be considered for oral presentation Topic: Computational neuroscience Citation: Schirner M, Rothmeier S and Ritter P (2015). Constructing subject-specific virtual brains from multimodal neuroimaging data. Front. Neurosci. Conference Abstract: Neuroinformatics 2015. doi: 10.3389/conf.fnins.2015.91.00005 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 29 May 2015; Published Online: 05 Aug 2015. * Correspondence: Dr. Petra Ritter, Charité Berlin, Berlin, Germany, petra.ritter@charite.de Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract Supplemental Data The Authors in Frontiers Michael Schirner Simon Rothmeier Petra Ritter Google Michael Schirner Simon Rothmeier Petra Ritter Google Scholar Michael Schirner Simon Rothmeier Petra Ritter PubMed Michael Schirner Simon Rothmeier Petra Ritter Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.