The BrainMap strategy for standardization, sharing, and meta-analysis of neuroimaging data

BMC Research Notes

Peter T Fox⁶  Jack L Lancaster⁶  Peter E Turkeltaub⁵  Jessica A Turner⁴  Jennifer L Robinson¹  Robert W Laird²  Danilo Bzdok³  D Reese McKay⁶  Juan J Saenz²  Kimberly L Ray⁶  Angela M Uecker⁶  P Mickle Fox⁶  Simon B Eickhoff³  Angela R Laird⁶ 

[1] Texas A&M Health Science Center, College of Medicine, Temple, TX, USA;Department of Physics and Earth Sciences, St. Mary's University, San Antonio, TX, USA;Institute of Neuroscience and Medicine (INM - 2), Research Center Jülich, Jülich, Germany;The Mind Research Network, Albuquerque, NM, USA;Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA;Research Imaging Institute, University of Texas Health Science Center, San Antonio, TX, USA

关键词: ALE;    activation likelihood estimation;    neuroinformatics;    BrainMap;    meta-analysis;    structural neuroimaging;    functional neuroimaging;   

Others  :  1167185
DOI  :  10.1186/1756-0500-4-349

 received in 2011-05-26, accepted in 2011-09-09,  发布年份 2011

【 摘 要 】

Background

Neuroimaging researchers have developed rigorous community data and metadata standards that encourage meta-analysis as a method for establishing robust and meaningful convergence of knowledge of human brain structure and function. Capitalizing on these standards, the BrainMap project offers databases, software applications, and other associated tools for supporting and promoting quantitative coordinate-based meta-analysis of the structural and functional neuroimaging literature.

Findings

In this report, we describe recent technical updates to the project and provide an educational description for performing meta-analyses in the BrainMap environment.

Conclusions

The BrainMap project will continue to evolve in response to the meta-analytic needs of biomedical researchers in the structural and functional neuroimaging communities. Future work on the BrainMap project regarding software and hardware advances are also discussed.

【 授权许可】

   
2011 Laird et al; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

Figure 2.

Figure 3.

【 参考文献 】

• [1]Hrynaszkiewicz I: A call for BMC Research Notes contributions promoting best practice in data standardization, sharing, and publication. BMC Res Notes 2010, 3:235. BioMed Central Full Text
• [2]The Biomedical Informatics Research Network [http://nbirn.net] webcite
• [3]Keator DB, Grethe JS, Marcus D, Ozyurt B, Gadde S, Murphy S, Pieper S, Greve D, Notestine R, Bockholt HJ, Papadopoulos P, BIRN: A national human neuroimaging collaboratory enabled by the Biomedical Informatics Research Network (BIRN). IEEE Trans Inf Technol Biomed 2008, 12:162-72.
• [4]XNAT Central [http://central.xnat.org] webcite
• [5]Marcus DS, Olsen TR, Ramaratnam M, Buckner RL: The Extensible Neuroimaging Archive Toolkit: An informatics platform for managing, exploring, and sharing neuroimaging data. Neuroinformatics 2007, 5:11-34.
• [6]The Alzheimer's Disease Neuroimaging Initiative [http://www.adni-info.org] webcite
• [7]Butcher J: Alzheimer's researchers open the doors to data sharing. The Lancet Neurology 2007, 6:480-481.
• [8]The Human Connectome Project [http://humanconnectome.org] webcite
• [9]Akil H, Martone ME, Van Essen DC: Challenges and opportunities in mining neuroscience data. Science 2011, 331:708-712.
• [10]Mackenzie-Graham AJ, Van Horn JD, Woods RP, Crawford KL, Toga AW: Provenance in neuroimaging. NeuroImage 2008, 42:178-195.
• [11]Fox PT, Lancaster JL: Mapping context and content: The BrainMap model. Nat Rev Neurosci 2002, 3:319-321.
• [12]Laird AR, Lancaster JL, Fox PT: BrainMap: The social evolution of a human brain mapping database. Neuroinformatics 2005, 3:65-78.
• [13]Laird AR, Lancaster JL, Fox PT: Lost in localization? The focus is meta-analysis. Neuroimage 2009, 48:18-20.
• [14]Laird AR, Eickhoff SB, Kurth F, Fox PM, Uecker AM, Turner JA, Robinson JL, Lancaster JL, Fox PT: ALE meta-analysis workflows via the BrainMap database: Progress towards a probabilistic functional brain atlas. Front Neuroinformatics 2009, 3:23.
• [15]FMRIB Software Library [http://www.fmrib.ox.ac.uk/fsl] webcite
• [16]Statistical Parametric Mapping [http://www.fil.ion.ucl.ac.uk/spm] webcite
• [17]Analysis of Functional NeuroImages [http://afni.nimh.nih.gov/afni] webcite
• [18]Fox PT: Spatial normalization origins: Objectives, applications, and alternatives. Hum Brain Mapping 1995, 3:161-164.
• [19]Talairach J, Tournoux P: Co-planar stereotaxic atlas of the human brain: 3-dimensional proportional system: An approach to cerebral imaging. Stuttgart: Georg Thieme 1988.
• [20]Collins DL, Neelin P, Peters TM, Evans AC: Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. J Comput Assist Tomogr 1994, 18:192-205.
• [21]Lancaster JL, Tordesillas-Gutiérrez D, Martinez M, Salinas F, Evans A, Zilles K, Mazziotta JC, Fox PT: Bias between MNI and Talairach coordinates analyzed using the ICBM-152 brain template. Hum Brain Mapp 2007, 28:1194-1205.
• [22]Brett M, Johnsrude IS, Owen AM: The problem of functional localization in the human brain. Nat Rev Neurosci 2002, 3:243-249.
• [23]Laird AR, Robinson JL, McMillan KM, Tordesillas-Gutiérrez D, Moran ST, Gonzales SM, Ray KL, Franklin C, Glahn DC, Fox PT, Lancaster JL: Comparison of the disparity between Talairach and MNI coordinates in functional neuroimaging data: validation of the Lancaster transform. NeuroImage 2010, 51:677-683.
• [24]fMRI Methods Working Group [http://www.fmrimethods.org] webcite
• [25]Fox PT, Lancaster JL: Neuroscience on the net. Science 1994, 266:994-996.
• [26]BrainMap Publications (1994-Present) [http://brainmap.org/pubs] webcite
• [27]Derrfuss J, Mar RA: Lost in localization: The need for a universal coordinate database. NeuroImage 2009, 48:1-7.
• [28]Glahn DC, Laird AR, Ellison-Wright I, Thelen SM, Robinson JL, Lancaster JL, Bullmore E, Fox PT: Meta-analysis of gray matter anomalies in schizophrenia: Application of anatomic likelihood estimation and network analysis. Biol Psychiatry 2008, 64:774-781.
• [29]Ellison-Wright I, Glahn DC, Laird AR, Thelen SM, Bullmore ET: The anatomy of first-episode and chronic schizophrenia: An anatomical likelihood estimation meta-analysis. Am J Psych 2008, 165:1015-1023.
• [30]Nickl-Jockschat T, Habel U, Michel TM, Manning J, Laird A, Fox PT, Schneider F, Eickhoff SB: Brain structure anomalies in autism spectrum disorder (ASD): A meta-analysis of VBM studies using anatomic likelihood estimation (ALE). Hum Brain Mapp, in press.
• [31]Oracle Corporation [http://www.oracle.com] webcite
• [32]Fox PT, Laird AR, Fox SP, Fox PM, Uecker AM, Crank M, Koenig SF, Lancaster JL: BrainMap taxonomy of experimental design: Description and evaluation. Hum Brain Mapp 2005, 25:185-198.
• [33]Apple iTunes [http://www.apple.com/itunes] webcite
• [34]The Neuroimaging Informatics Technology Initiative [http://nifti.nimh.nih.gov] webcite
• [35]Thomson Reuters EndNote [http://endnote.com] webcite
• [36]Turkeltaub PE, Eden GF, Jones KM, Zeffiro TA: Meta-analysis of the functional neuroanatomy of single-word reading: Method and validation. NeuroImage 2002, 16:765-780.
• [37]Laird AR, Fox M, Price CJ, Glahn DC, Uecker AM, Lancaster JL, Turkeltaub PE, Kochunov P, Fox PT: ALE meta-analysis: Controlling the false discovery rate and performing statistical contrasts. Hum Brain Mapp 2005, 25:155-164.
• [38]Eickhoff SB, Laird AR, Grefkes C, Wang LE, Zilles K, Fox PT: Coordinate-based activation likelihood estimation meta-analysis of neuroimaging data: A random-effects approach based on empirical estimates of spatial uncertainty. Hum Brain Mapp 2009, 30:2907-2926.
• [39]Turkeltaub PE, Eickhoff SB, Laird AR, Fox M, Wiener M, Fox P: Minimizing within-experiment and within-group effects in activation likelihood estimation meta-analyses. Hum Brain Mapp, in press.
• [40]Eickhoff SB, Bzdok D, Laird AR, Roski C, Caspers S, Zilles K, Fox PT: Co-activation patterns distinguish cortical modules, their connectivity and functional differentiation. Neuroimage, in press.
• [41]BrainMap Project [http://www.brainmap.org] webcite
• [42][http://www.brainmap.org:9000/bmapWeb] webciteBrainMapWeb.
• [43]The icbm2tal Transform [http://www.brainmap.org/icbm2tal] webcite
• [44][http://ric.uthscsa.edu/mango] webciteMango.
• [45]Lancaster JL, Rainey LH, Summerlin JL, Freitas CS, Fox PT, Evans AC, Toga AW, Mazziotta JC: Automated labeling of the human brain: A preliminary report on the development and evaluation of a forward-transform method. Hum Brain Mapp 1997, 5:238-242.
• [46]Lancaster JL, Woldorff MG, Parsons LM, Liotti M, Freitas CS, Rainey L, Kochunov PV, Nickerson D, Mikiten SA, Fox PT: Automated Talairach Atlas labels for functional brain mapping. Hum Brain Mapp 2000, 10:120-131.
• [47]The Talairach Daemon [http://www.talairach.org] webcite
• [48]The Anatomy Toolbox [http:/ / www.fz-juelich.de/ inm/ inm-1/ DE/ Forschung/ _docs/ SPMAnantomyToolbox/ SPMAnantomyToolbox_node.html] webcite
• [49]Eickhoff S, Stephan KE, Mohlberg H, Grefkes C, Fink GR, Amunts K, Zilles K: A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data. NeuroImage 2005, 25:1325-1335.
• [50]Eickhoff SB, Paus T, Caspers S, Grosbras MH, Evans A, Zilles K, Amunts K: Assignment of functional activations to probabilistic cytoarchitectonic areas revisited. NeuroImage 2007, 36:511-521.
• [51]Eickhoff SB, Heim S, Zilles K, Amunts K: Testing anatomically specified hypotheses in functional imaging using cytoarchitectonic maps. NeuroImage 2006, 32:570-582.
• [52]The Cognitive Paradigm Ontology [http://www.cogpo.org] webcite
• [53]Turner JA, Laird AR: The Cognitive Paradigm Ontology: Design and application. Neuroinformatics, in press.
• [54]Keator DB, Wei D, Gadde S, Bockholt J, Grethe JS, Marcus D, Aucoin N, Ozyurt IB: Derived data storage and exchange workflow for large-scale neuroimaging analyses on the BIRN Grid. Front Neuroinformatics 2009, 8:231-249.
• [55]The CogPO Wiki [http://www.wiki.cogpo.org] webcite
• [56]The CogPO, Version 1 [http://www.cogpo.org/ontologies/CogPOver1.owl] webcite
• [57]The Neuroscience Information Framework NeuroLex Wiki [http://neurolex.org/wiki] webcite
• [58]The National Center for Biomedical Ontology [http://www.bioportal.ncbo.org] webciteBioPortal
• [59]Biswal B, Yetkin FZ, Haughton VM, Hyde JS: Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med 1995, 34:537-541.
• [60]Xiong J, Parsons LM, Gao JH, Fox PT: Interregional connectivity to primary motor cortex revealed using MRI resting state images. Hum Brain Mapp 1999, 8:151-156.
• [61]Cordes D, Haughton VM, Arfanakis K, Wendt GJ, Turski PA, Moritz CH, Quigley MA, Meyerand ME: Mapping functionally related regions of brain with functional connectivity MR imaging. AJNR Am J Neuroradiol 2000, 21:1636-1644.
• [62]Robinson JL, Laird AR, Glahn DC, Lovallo WR, Fox PT: Meta-analytic connectivity modelling: Delineating the functional connectivity of the human amygdala. Hum Brain Mapp 2010, 31:173-184.
• [63]Eickhoff S, Jbabdi S, Caspers S, Laird AR, Fox PT, Zilles K, Behrens T: Anatomical and functional connectivity of cytoarchitectonic areas within the human parietal operculum. J Neurosci 2010, 30:6409-6421.
• [64]Laird AR, Eickhoff SB, Li K, Robin DA, Glahn DC, Fox PT: Investigating the functional heterogeneity of the default mode network using coordinate-based meta-analytic modeling. J Neurosci 2009, 29:14496-14505.
• [65]Cauda F, Cavanna AE, D'agata F, Sacco K, Duca S, Geminiani GC: Functional connectivity and coactivation of the nucleus accumbens: A combined functional connectivity and structure-based meta-analysis. J Cogn Neurosci, in press.
• [66]Smith SM, Jenkinson M, Woolrich MW, Beckmann CF, Behrens TE, Johansen-Berg H, Bannister PR, De Luca M, Drobnjak I, Flitney DE, Niazy RK, Saunders J, Vickers J, Zhang Y, De Stefano N, Brady JM, Matthews PM: Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 2004, 23:S208-S219.
• [67]Caspers S, Zilles K, Laird AR, Eickhoff SB: ALE meta-analysis of action observation and imitation in the human brain. Neuroimage 2010, 50:1148-1167.
• [68]Friston KJ, Harrison L, Penny W: Dynamic causal modelling. Neuroimage 2003, 19:1273-1302.
• [69]McIntosh A, Gonzales-Lima F: Structural equation modeling and its application to network analysis in functional brain imaging. Hum Brain Mapp 1994, 2:2-22.
• [70]Smith SM, Fox PT, Miller KL, Glahn DC, Fox PM, Mackay CE, Filippini N, Watkins KE, Toro R, Laird AR, Beckmann CF: Correspondence of the brain's functional architecture during activation and rest. Proc Natl Acad Sci USA 2009, 106:13040-13045.
• [71]Laird AR, Fox PM, Eickhoff SB, Turner JA, Ray KL, McKay DR, Glahn DC, Beckmann CF, Smith SM, Fox PT: Behavioral interpretations of intrinsic connectivity networks. J Cogn Neurosci, in press.