The Neuro Bureau Preprocessing Initiative: open sharing of preprocessed neuroimaging data and derivatives

Event Abstract Back to Event The Neuro Bureau Preprocessing Initiative: open sharing of preprocessed neuroimaging data and derivatives Cameron Craddock1, 2, 3*, Yassine Benhajali4, 5, Carlton Chu3, Francois Chouinard5, 6, Alan Evans6, András Jakab3, 7, Budhachandra S. Khundrakpam6, John D. Lewis6, Qingyang Li1, Michael Milham1, 2, Chaogan Yan2, 3 and Pierre Bellec3, 5, 8 1 Child Mind Institute, Center for the Developing Brain, United States 2 Nathan Kline Institute for Psychiatric Research, United States 3 The Neuro Bureau Research Institute, United States 4 Université de Montréal, Département d’anthropologie, Canada 5 Centre de recherche de l’institut de gériatrie de Montréal, Canada 6 McGill University, Montreal Neurological Insitute, Canada 7 University of Debrecen Medical and Health Sciences Centre, Hungary 8 Université de Montréal, Département d’informatique et de recherche opérationnelle, Canada Introduction Grass-roots initiatives such as the 1000 Functional Connectomes Project (FCP) and International Neuroimaging Data- sharing Initiative (INDI) [1] are successfully amassing and sharing large-scale brain imaging datasets, with the goal of recruiting the broader scientific community into the fold of neuroimaging research. Unfortunately, despite the increasing breadth and scale of openly available data, the vast domain-specific knowledge and computational resources necessary to derive scientifically meaningful information from unprocessed neuroimaging data has limited their accessibility. The Neuro Bureau Preprocessing Initiative [2] has taken on this challenge, generating and openly sharing preprocessed data and common derivatives for the large-scale ADHD-200 dataset [3]. This initiative has grown to include preprocessed DTI data and derivatives for 180 healthy individuals from INDI’s Beijing Enhanced Sample [4]. The next planned release will include resting state and structural data from the 1,112 subject Autism Brain Imaging Data Exchange (ABIDE) dataset [5]. Methods Four teams are currently participating in the preprocessing initiative, each one using different toolsets and preprocessing strategies (fig. 1). Preprocessed data, derivatives, and quality control metrics are made openly available for download through the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) [6]. The ADHD-200 release included two fMRI preprocessing pipelines as well as maps of grey matter density for voxel-based morphometry (fig. 1). The Beijing diffusion imaging release includes DTI scalars along with voxel specific diffusion distributions for performing probabilistic tractography. Figure 2 illustrates various derivatives generated through these initiatives. The future ABIDE preprocessing initiative will incorporate three functional preprocessing piplines and cortical measures (fig. 3). The analytical procedures employed in the preprocessing are extensively documented on the NITRC website [2]. The Neuro Bureau preprocessing initiative also includes an on-going working group to release derivatives, which can be readily compared across different preprocessing strategies, so that investigators can directly test the impact of the method- ological choices on the scientific outcome of a study. Most of the ong-going work consists of improving and harmonizing the quality control procedures and the derivatives generated by different processing pipelines. Interested teams are welcome to join the effort and contribute new analytical pipelines for future release. Results Intended to buttress the ADHD-200 Global Competition [7] and accelerate ADHD imaging research, the ADHD-200 preprocessing effort has yielded more than 6,500 downloads from 780 unique IP address globally (see fig. 4), inspired a team of biostatisticians to win the competition and resulted in eight peer-reviewed publications - with many more in preparation or submission. The DTI preprocessing initiative has resulted in 572 downloads from 134 unique IP addresses. Based on the success of the previous preprocessing efforts four teams have agreed to continue this effort by preprocessing the recently released ABIDE dataset (fig 3). Conclusion By openly sharing a wide range of preprocessed data and derivatives, the Neuro Bureau Preprocessing Initiative seeks to make neuroimaging research accessible to a wider audience of researchers. It has already enabled computer scientists, mathematicians, and statisticians who lack neuroimaging expertise to develop and test novel data analysis strategies. We see several important benefits to our initiative: (1) facilitate the generation and test of novel hypotheses about brain function, (2) provide a resource to train future generations of neuroimaging researchers and, (3) facilitate the replication of published results by providing a benchmark set of test images. By providing a breadth of derivatives and preprocessing strategies, we also hope to establish a platform for comparing their relative merits, as well as testing the robustness of neuroscientific findings. This already broad resource will soon be enhanced by the inclusion of the phenotypically rich ABIDE dataset which consists of data from an important clinical population. Figure 1 Figure 2 Figure 3 Figure 4 References [1] http://fcon_1000.projects.nitrc.org [2] http://neurobureau.projects.nitrc.org/ADHD200/Introduction.html [3] http://fcon_1000.projects.nitrc.org/indi/adhd200/index.html [4] http://fcon_1000.projects.nitrc.org/indi/retro/BeijingEnhanced.html [5] http://fcon_1000.projects.nitrc.org/indi/abide [6] http://www.nitrc.org [7] http://fcon_1000.projects.nitrc.org/indi/adhd200/index.html Keywords: data sharing, fMRI, analysis, functional connectivity, MRI, cortical thickness, Quality control Conference: Neuroinformatics 2013, Stockholm, Sweden, 27 Aug - 29 Aug, 2013. Presentation Type: Oral presentation Topic: Neuroimaging Citation: Craddock C, Benhajali Y, Chu C, Chouinard F, Evans A, Jakab A, Khundrakpam BS, Lewis JD, Li Q, Milham M, Yan C and Bellec P (2013). The Neuro Bureau Preprocessing Initiative: open sharing of preprocessed neuroimaging data and derivatives . Front. Neuroinform. Conference Abstract: Neuroinformatics 2013. doi: 10.3389/conf.fninf.2013.09.00041 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: 30 Apr 2013; Published Online: 11 Jul 2013. * Correspondence: Dr. Cameron Craddock, Child Mind Institute, Center for the Developing Brain, New York, New York, 10022, United States, cameron.craddock@austin.utexas.edu Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Cameron Craddock Yassine Benhajali Carlton Chu Francois Chouinard Alan Evans András Jakab Budhachandra S Khundrakpam John D Lewis Qingyang Li Michael Milham Chaogan Yan Pierre Bellec Google Cameron Craddock Yassine Benhajali Carlton Chu Francois Chouinard Alan Evans András Jakab Budhachandra S Khundrakpam John D Lewis Qingyang Li Michael Milham Chaogan Yan Pierre Bellec Google Scholar Cameron Craddock Yassine Benhajali Carlton Chu Francois Chouinard Alan Evans András Jakab Budhachandra S Khundrakpam John D Lewis Qingyang Li Michael Milham Chaogan Yan Pierre Bellec PubMed Cameron Craddock Yassine Benhajali Carlton Chu Francois Chouinard Alan Evans András Jakab Budhachandra S Khundrakpam John D Lewis Qingyang Li Michael Milham Chaogan Yan Pierre Bellec Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. 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