English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  An automated pipeline for constructing personalized virtual brains from multimodal neuroimaging data

Schirner, M., Rothmeier, S., Jirsa, V. K., McIntosh, A. R., & Ritter, P. (2015). An automated pipeline for constructing personalized virtual brains from multimodal neuroimaging data. NeuroImage, 117, 343-357. doi:10.1016/j.neuroimage.2015.03.055.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0025-AD84-B Version Permalink: http://hdl.handle.net/21.11116/0000-0003-141F-5
Genre: Journal Article

Files

show Files
hide Files
:
Schirner_2015.pdf (Publisher version), 3MB
Name:
Schirner_2015.pdf
Description:
-
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show

Creators

show
hide
 Creators:
Schirner, Michael1, 2, Author
Rothmeier, Simon1, 2, Author
Jirsa, Viktor K.3, Author
McIntosh, Anthony Randal4, Author
Ritter, Petra1, 2, 5, 6, Author              
Affiliations:
1Department of Neurology, Charité University Medicine Berlin, Germany, ou_persistent22              
2Bernstein Focus: State Dependencies of Learning, Berlin, Germany, ou_persistent22              
3Institut de Neurosciences des Systèmes, Aix-Marseille Université Faculté de Médecine, Marseille, France, ou_persistent22              
4Rotman Research Institute, University of Toronto, ON, Canada, ou_persistent22              
5Minerva Research Group Brain Modes, MPI for Human Cognitive and Brain Sciences, Max Planck Society, Leipzig, DE, ou_751546              
6Berlin School of Mind and Brain, Humboldt University Berlin, Germany, ou_persistent22              

Content

show
hide
Free keywords: The Virtual Brain; Connectome; Tractography; Diffusion MRI; Multimodal imaging; Computational modeling
 Abstract: 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 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 that incorporate intra- and intercortical interaction on the basis of cortical surface triangulations and white matter tractograpy. 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.

Details

show
hide
Language(s): eng - English
 Dates: 2014-10-272015-03-192015-03-312015-08-15
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.neuroimage.2015.03.055
PMID: 25837600
Other: Epub 2015
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: NeuroImage
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 117 Sequence Number: - Start / End Page: 343 - 357 Identifier: ISSN: 1053-8119
CoNE: https://pure.mpg.de/cone/journals/resource/954922650166