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Times Cited: 410
Times Cited: 410
Times Cited
Times Co-cited
Similarity
fMRIPrep: a robust preprocessing pipeline for functional MRI.
Oscar Esteban, Christopher J Markiewicz, Ross W Blair, Craig A Moodie, A Ilkay Isik, Asier Erramuzpe, James D Kent, Mathias Goncalves, Elizabeth DuPre, Madeleine Snyder,[...]. Nat Methods 2019
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EEG-BIDS, an extension to the brain imaging data structure for electroencephalography.
Cyril R Pernet, Stefan Appelhoff, Krzysztof J Gorgolewski, Guillaume Flandin, Christophe Phillips, Arnaud Delorme, Robert Oostenveld. Sci Data 2019
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Best practices in data analysis and sharing in neuroimaging using MRI.
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MRIQC: Advancing the automatic prediction of image quality in MRI from unseen sites.
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BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods.
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The first step for neuroimaging data analysis: DICOM to NIfTI conversion.
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FSL.
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AFNI: software for analysis and visualization of functional magnetic resonance neuroimages.
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The WU-Minn Human Connectome Project: an overview.
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The minimal preprocessing pipelines for the Human Connectome Project.
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N4ITK: improved N3 bias correction.
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Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in python.
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Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain.
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Scanning the horizon: towards transparent and reproducible neuroimaging research.
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The FAIR Guiding Principles for scientific data management and stewardship.
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Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion.
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iEEG-BIDS, extending the Brain Imaging Data Structure specification to human intracranial electrophysiology.
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Local-Global Parcellation of the Human Cerebral Cortex from Intrinsic Functional Connectivity MRI.
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Machine learning for neuroimaging with scikit-learn.
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Variability in the analysis of a single neuroimaging dataset by many teams.
Rotem Botvinik-Nezer, Felix Holzmeister, Colin F Camerer, Anna Dreber, Juergen Huber, Magnus Johannesson, Michael Kirchler, Roni Iwanir, Jeanette A Mumford, R Alison Adcock,[...]. Nature 2020
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A reproducible evaluation of ANTs similarity metric performance in brain image registration.
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MEG-BIDS, the brain imaging data structure extended to magnetoencephalography.
Guiomar Niso, Krzysztof J Gorgolewski, Elizabeth Bock, Teon L Brooks, Guillaume Flandin, Alexandre Gramfort, Richard N Henson, Mainak Jas, Vladimir Litvak, Jeremy T Moreau,[...]. Sci Data 2018
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EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis.
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An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.
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The organization of the human cerebral cortex estimated by intrinsic functional connectivity.
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Methods to detect, characterize, and remove motion artifact in resting state fMRI.
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Jonathan D Power, Anish Mitra, Timothy O Laumann, Abraham Z Snyder, Bradley L Schlaggar, Steven E Petersen. Neuroimage 2014
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Accurate and robust brain image alignment using boundary-based registration.
Douglas N Greve, Bruce Fischl. Neuroimage 2009
Douglas N Greve, Bruce Fischl. Neuroimage 2009
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Image processing and Quality Control for the first 10,000 brain imaging datasets from UK Biobank.
Fidel Alfaro-Almagro, Mark Jenkinson, Neal K Bangerter, Jesper L R Andersson, Ludovica Griffanti, Gwenaëlle Douaud, Stamatios N Sotiropoulos, Saad Jbabdi, Moises Hernandez-Fernandez, Emmanuel Vallee,[...]. Neuroimage 2018
Fidel Alfaro-Almagro, Mark Jenkinson, Neal K Bangerter, Jesper L R Andersson, Ludovica Griffanti, Gwenaëlle Douaud, Stamatios N Sotiropoulos, Saad Jbabdi, Moises Hernandez-Fernandez, Emmanuel Vallee,[...]. Neuroimage 2018
8
Power failure: why small sample size undermines the reliability of neuroscience.
Katherine S Button, John P A Ioannidis, Claire Mokrysz, Brian A Nosek, Jonathan Flint, Emma S J Robinson, Marcus R Munafò. Nat Rev Neurosci 2013
Katherine S Button, John P A Ioannidis, Claire Mokrysz, Brian A Nosek, Jonathan Flint, Emma S J Robinson, Marcus R Munafò. Nat Rev Neurosci 2013
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Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm.
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FieldTrip: Open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data.
Robert Oostenveld, Pascal Fries, Eric Maris, Jan-Mathijs Schoffelen. Comput Intell Neurosci 2011
Robert Oostenveld, Pascal Fries, Eric Maris, Jan-Mathijs Schoffelen. Comput Intell Neurosci 2011
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ICA-AROMA: A robust ICA-based strategy for removing motion artifacts from fMRI data.
Raimon H R Pruim, Maarten Mennes, Daan van Rooij, Alberto Llera, Jan K Buitelaar, Christian F Beckmann. Neuroimage 2015
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The Human Connectome Project: a data acquisition perspective.
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The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism.
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Functional connectivity in the motor cortex of resting human brain using echo-planar MRI.
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Advances in functional and structural MR image analysis and implementation as FSL.
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Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain.
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Harmonization of cortical thickness measurements across scanners and sites.
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Making big data open: data sharing in neuroimaging.
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Data sharing in neuroimaging research.
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Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity.
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Data sharing and privacy issues in neuroimaging research: Opportunities, obstacles, challenges, and monsters under the bed.
Tonya White, Elisabet Blok, Vince D Calhoun. Hum Brain Mapp 2022
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Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates.
Anders Eklund, Thomas E Nichols, Hans Knutsson. Proc Natl Acad Sci U S A 2016
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MEG and EEG data analysis with MNE-Python.
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Building a Science of Individual Differences from fMRI.
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Co-cited is the co-citation frequency, indicating how many articles cite the article together with the query article. Similarity is the co-citation as percentage of the times cited of the query article or the article in the search results, whichever is the lowest. These numbers are calculated for the last 100 citations when articles are cited more than 100 times.