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license: MIT

license_type: permissive

branch_name: refs/heads/master

extension: bib


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@Article{power2012,
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}

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   author = {Whitfield-Gabrieli, Susan and Ford, Judith M.},
   title = {Default Mode Network Activity and Connectivity in Psychopathology},
   journal = {Annual Review of Clinical Psychology},
   volume = {8},
   number = {1},
   pages = {49--76},
   DOI = {10.1146/annurev-clinpsy-032511-143049},
   url = {http://dx.doi.org/10.1146/annurev-clinpsy-032511-143049},
   year = {2012},
   type = {Journal Article}
}

@article{Wood2014,
   author = {Wood, Dylan and King, Margaret and Landis, Drew and Courtney, William and Wang, Runtang and Kelly, Ross and Turner, Jessica A. and Calhoun, Vince D.},
   title = {Harnessing modern web application technology to create intuitive and efficient data visualization and sharing tools},
   journal = {Front. Neuroinform.},
   volume = {8},
   DOI = {10.3389/fninf.2014.00071},
   url = {http://dx.doi.org/10.3389/fninf.2014.00071},
   year = {2014},
   type = {Journal Article}
}

@Article{yan2013,
   Author="Yan, C. G.  and Cheung, B.  and Kelly, C.  and Colcombe, S.  and Craddock, R. C.  and Di Martino, A.  and Li, Q.  and Zuo, X. N.  and Castellanos, F. X.  and Milham, M. P. ",
   Title="{{A} comprehensive assessment of regional variation in the impact of head micromovements on functional connectomics}",
   Journal="Neuroimage",
   Year="2013",
   Volume="76",
   Pages="183--201",
   Month="Aug",
   Abstract={Functional connectomics is one of the most rapidly expanding areas of neuroimaging research. Yet, concerns remain regarding the use of resting-state fMRI (R-fMRI) to characterize inter-individual variation in the functional connectome. In particular, recent findings that "micro" head movements can introduce artifactual inter-individual and group-related differences in R-fMRI metrics have raised concerns. Here, we first build on prior demonstrations of regional variation in the magnitude of framewise displacements associated with a given head movement, by providing a comprehensive voxel-based examination of the impact of motion on the BOLD signal (i.e., motion-BOLD relationships). Positive motion-BOLD relationships were detected in primary and supplementary motor areas, particularly in low motion datasets. Negative motion-BOLD relationships were most prominent in prefrontal regions, and expanded throughout the brain in high motion datasets (e.g., children). Scrubbing of volumes with FD>0.2 effectively removed negative but not positive correlations; these findings suggest that positive relationships may reflect neural origins of motion while negative relationships are likely to originate from motion artifact. We also examined the ability of motion correction strategies to eliminate artifactual differences related to motion among individuals and between groups for a broad array of voxel-wise R-fMRI metrics. Residual relationships between motion and the examined R-fMRI metrics remained for all correction approaches, underscoring the need to covary motion effects at the group-level. Notably, global signal regression reduced relationships between motion and inter-individual differences in correlation-based R-fMRI metrics; Z-standardization (mean-centering and variance normalization) of subject-level maps for R-fMRI metrics prior to group-level analyses demonstrated similar advantages. Finally, our test-retest (TRT) analyses revealed significant motion effects on TRT reliability for R-fMRI metrics. Generally, motion compromised reliability of R-fMRI metrics, with the exception of those based on frequency characteristics - particularly, amplitude of low frequency fluctuations (ALFF). The implications of our findings for decision-making regarding the assessment and correction of motion are discussed, as are insights into potential differences among volume-based metrics of motion.}
}

@article{Zhang2001,
   author = {Zhang, Y. and Brady, M. and Smith, S.},
   title = {Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm},
   journal = {IEEE Transactions on Medical Imaging},
   volume = {20},
   number = {1},
   pages = {45--57},
   DOI = {10.1109/42.906424},
   url = {http://dx.doi.org/10.1109/42.906424},
   year = {2001},
   type = {Journal Article}
}

@article{Zuo2014,
   author = {Zuo, Xi-Nian and Anderson, Jeffrey S and Bellec, Pierre and Birn, Rasmus M and Biswal, Bharat B and Blautzik, Janusch and Breitner, John C. S and Buckner, Randy L and Calhoun, Vince D and Castellanos, F. Xavier and Chen, Antao and Chen, Bing and Chen, Jiangtao and Chen, Xu and Colcombe, Stanley J and Courtney, William and Craddock, R Cameron and Martino, Adriana Di and Dong, Hao-Ming and Fu, Xiaolan and Gong, Qiyong and Gorgolewski, Krzysztof J and Han, Ying and He, Ye and He, Yong and Ho, Erica and Holmes, Avram and Hou, Xiao-Hui and Huckins, Jeremy and Jiang, Tianzi and Jiang, Yi and Kelley, William and Kelly, Clare and King, Margaret and LaConte, Stephen M and Lainhart, Janet E and Lei, Xu and Li, Hui-Jie and Li, Kaiming and Li, Kuncheng and Lin, Qixiang and Liu, Dongqiang and Liu, Jia and Liu, Xun and Liu, Yijun and Lu, Guangming and Lu, Jie and Luna, Beatriz and Luo, Jing and Lurie, Daniel and Mao, Ying and Margulies, Daniel S and Mayer, Andrew R and Meindl, Thomas and Meyerand, Mary E and Nan, Weizhi and Nielsen, Jared A and O'Connor, David and Paulsen, David and Prabhakaran, Vivek and Qi, Zhigang and Qiu, Jiang and Shao, Chunhong and Shehzad, Zarrar and Tang, Weijun and Villringer, Arno and Wang, Huiling and Wang, Kai and Wei, Dongtao and Wei, Gao-Xia and Weng, Xu-Chu and Wu, Xuehai and Xu, Ting and Yang, Ning and Yang, Zhi and Zang, Yu-Feng and Zhang, Lei and Zhang, Qinglin and Zhang, Zhe and Zhang, Zhiqiang and Zhao, Ke and Zhen, Zonglei and Zhou, Yuan and Zhu, Xing-Ting and Milham, Michael P},
   title = {An open science resource for establishing reliability and reproducibility in functional connectomics},
   journal = {Scientific Data},
   volume = {1},
   pages = {140049},
   DOI = {10.1038/sdata.2014.49},
   url = {http://dx.doi.org/10.1038/sdata.2014.49},
   year = {2014},
   type = {Journal Article}
}

@misc{fmrib_RSNS,
author = {Oxford Centre for Functional MRI of the Brain},
title = {Correspondence between BrainMap and Resting-FMRI ICA components},
year = {accessed October 7, 2016},
howpublished = "\url{http://fsl.fmrib.ox.ac.uk/analysis/brainmap+rsns/}"}

@article{Veale_2014,
author = {Jaimie F. Veale},
title = {Edinburgh Handedness Inventory â Short Form: A revised version based on confirmatory factor analysis},
journal = {Laterality: Asymmetries of Body, Brain and Cognition},
volume = {19},
number = {2},
pages = {164-177},
year = {2014},
doi = {10.1080/1357650X.2013.783045},
    note ={PMID: 23659650},

URL = {
        http://dx.doi.org/10.1080/1357650X.2013.783045

},
eprint = {
        http://dx.doi.org/10.1080/1357650X.2013.783045

}
,
    abstract = { While the Edinburgh Handedness Inventory has been widely used, there have been few studies assessing its factorial validity. There is evidence that the original instructions and response options are difficult to understand. Using simplified instructions and response options, the Edinburgh Handedness Inventory was administered on a sample of 1514 participants using an online questionnaire. In accordance with previous research, a model of the 10-item inventory had poor fit for the data. This study also detected model misspecification in the previously-proposed 7-item modification. A 4-item Edinburgh Handedness Inventory â Short Form had good model fit with items modelled as both continuous and ordinal. Despite its brevity, it showed very good reliability, factor score determinacy, and correlation with scores on the 10-item inventory. By eliminating items that were modelled with considerable measurement error, the short form alleviates the concern of the 10-item inventory over-categorising mixed handers. Evidence was found for factorial invariance across level of education, age groups, and regions (USA and Australia/New Zealand). There generally appeared to be invariance across genders for the 4-item inventory. The proposed Edinburgh Handedness Inventory â Short Form measures a single handedness factor with an inventory that has brief and simple instructions and a small number of items. }
}