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brainhack-report.bib
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@Article{Tomasi2010,
Author="Tomasi, D. and Volkow, N. D. ",
Title="{{F}unctional connectivity density mapping}",
Journal="Proc. Natl. Acad. Sci. U.S.A.",
Year="2010",
Volume="107",
Number="21",
Pages="9885--9890",
Month="May",
Abstract={Brain networks with energy-efficient hubs might support the high cognitive performance of humans and a better understanding of their organization is likely of relevance for studying not only brain development and plasticity but also neuropsychiatric disorders. However, the distribution of hubs in the human brain is largely unknown due to the high computational demands of comprehensive analytical methods. Here we propose a 10(3) times faster method to map the distribution of the local functional connectivity density (lFCD) in the human brain. The robustness of this method was tested in 979 subjects from a large repository of MRI time series collected in resting conditions. Consistently across research sites, a region located in the posterior cingulate/ventral precuneus (BA 23/31) was the area with the highest lFCD, which suggest that this is the most prominent functional hub in the brain. In addition, regions located in the inferior parietal cortex (BA 18) and cuneus (BA 18) had high lFCD. The variability of this pattern across subjects was <36% and within subjects was 12%. The power scaling of the lFCD was consistent across research centers, suggesting that that brain networks have a "scale-free" organization.},
DOI={10.1073/pnas.1001414107}
}
@Article{Rubinov2010,
Author="Rubinov, M. and Sporns, O. ",
Title="{{C}omplex network measures of brain connectivity: uses and interpretations}",
Journal="Neuroimage",
Year="2010",
Volume="52",
Number="3",
Pages="1059--1069",
Month="Sep",
Abstract={Brain connectivity datasets comprise networks of brain regions connected by anatomical tracts or by functional associations. Complex network analysis-a new multidisciplinary approach to the study of complex systems-aims to characterize these brain networks with a small number of neurobiologically meaningful and easily computable measures. In this article, we discuss construction of brain networks from connectivity data and describe the most commonly used network measures of structural and functional connectivity. We describe measures that variously detect functional integration and segregation, quantify centrality of individual brain regions or pathways, characterize patterns of local anatomical circuitry, and test resilience of networks to insult. We discuss the issues surrounding comparison of structural and functional network connectivity, as well as comparison of networks across subjects. Finally, we describe a Matlab toolbox (http://www.brain-connectivity-toolbox.net) accompanying this article and containing a collection of complex network measures and large-scale neuroanatomical connectivity datasets.},
DOI={10.1016/j.neuroimage.2009.10.003}
}
@article{Cox1996,
Author="Cox, R. W. ",
Title="{{A}{F}{N}{I}: software for analysis and visualization of functional magnetic resonance neuroimages}",
Journal="Comput. Biomed. Res.",
Year="1996",
Volume="29",
Number="3",
Pages="162--173",
Month="Jun",
Abstract={A package of computer programs for analysis and visualization of three-dimensional human brain functional magnetic resonance imaging (FMRI) results is described. The software can color overlay neural activation maps onto higher resolution anatomical scans. Slices in each cardinal plane can be viewed simultaneously. Manual placement of markers on anatomical landmarks allows transformation of anatomical and functional scans into stereotaxic (Talairach-Tournoux) coordinates. The techniques for automatically generating transformed functional data sets from manually labeled anatomical data sets are described. Facilities are provided for several types of statistical analyses of multiple 3D functional data sets. The programs are written in ANSI C and Motif 1.2 to run on Unix workstations.}
}
@article{Dagum1998,
Author = {Dagum, Leonardo and Menon, Ramesh},
Date-Added = {2014-07-24 11:13:01 +0000},
Date-Modified = {2014-07-24 11:13:01 +0000},
Journal = {Computational Science \& Engineering, IEEE},
Number = {1},
Pages = {46--55},
Publisher = {IEEE},
Title = {OpenMP: an industry standard API for shared-memory programming},
Volume = {5},
Year = {1998}}
@ARTICLE{Craddock2013c,
AUTHOR={Craddock, Cameron and Sikka, Sharad and Cheung, Brian and Khanuja, Ranjeet and Ghosh, Satrajit S and Yan, Chaogan and Li, Qingyang and Lurie, Daniel and Vogelstein, Joshua and Burns, Randal and Colcombe, Stanley and Mennes, Maarten and Kelly, Clare and Di Martino, Adriana and Castellanos, Francisco Xavier and Milham, Michael},
TITLE={Towards Automated Analysis of Connectomes: The Configurable Pipeline for the Analysis of Connectomes (C-PAC)},
JOURNAL={Frontiers in Neuroinformatics},
VOLUME={},
YEAR={2013},
NUMBER={42},
URL={http://www.frontiersin.org/neuroinformatics/10.3389/conf.fninf.2013.09.00042/full},
DOI={10.3389/conf.fninf.2013.09.00042},
ISSN={1662-5196}
}
@article{Zuo2014,
DOI = { 10.1038/sdata.2014.49 },
year = { 2014 },
volume = { 1 },
url = { http://dx.doi.org/10.1038/sdata.2014.49 },
ty = { JOUR },
title = { An open science resource for establishing reliability and reproducibility in functional connectomics },
publisher = { Macmillan Publishers Limited SN - },
pages = { 140049 },
month = { 12 },
m3 = { Data Descriptor },
l3 = { 10.1038/sdata.2014.49; http://www.nature.com/articles/sdata201449#supplementary-information },
journal = { Scientific Data },
day = { 09 },
date-modified = { 2014-12-09 16:04:41 +0000 },
date-added = { 2014-12-09 16:04:41 +0000 },
date = { 2014/12/09/online },
author = { Xi-Nian Zuo and Jeffrey S Anderson and Pierre Bellec and Rasmus M Birn and Bharat B Biswal and Janusch Blautzik and John C. S Breitner and Randy L Buckner and Vince D Calhoun and F. Xavier Castellanos and Antao Chen and Bing Chen and Jiangtao Chen and Xu Chen and Stanley J Colcombe and William Courtney and R. Cameron Craddock and Adriana Di Martino and Hao-Ming Dong and Xiaolan Fu and Qiyong Gong and Krzysztof J Gorgolewski and Ying Han and Ye He and Yong He and Erica Ho and Avram Holmes and Xiao-Hui Hou and Jeremy Huckins and Tianzi Jiang and Yi Jiang and William Kelley and Clare Kelly and Margaret King and Stephen M LaConte and Janet E Lainhart and Xu Lei and Hui-Jie Li and Kaiming Li and Kuncheng Li and Qixiang Lin and Dongqiang Liu and Jia Liu and Xun Liu and Yijun Liu and Guangming Lu and Jie Lu and Beatriz Luna and Jing Luo and Daniel Lurie and Ying Mao and Daniel S Margulies and Andrew R Mayer and Thomas Meindl and Mary E Meyerand and Weizhi Nan and Jared A Nielsen and David O'Connor and David Paulsen and Vivek Prabhakaran and Zhigang Qi and Jiang Qiu and Chunhong Shao and Zarrar Shehzad and Weijun Tang and Arno Villringer and Huiling Wang and Kai Wang and Dongtao Wei and Gao-Xia Wei and Xu-Chu Weng and Xuehai Wu and Ting Xu and Ning Yang and Zhi Yang and Yu-Feng Zang and Lei Zhang and Qinglin Zhang and Zhe Zhang and Zhiqiang Zhang and Ke Zhao and Zonglei Zhen and Yuan Zhou and Xing-Ting Zhu and Michael P Milham },
}