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A resting state fMRI analysis pipeline for pooling inference across diverse cohorts: an ENIGMA rs-fMRI protocol

Bhim M. Adhikari, Neda Jahanshad, Dinesh Shukla, Jessica Turner, Dominik Grotegerd, Udo Dannlowski, Harald Kugel, Jennifer Engelen, Bruno Dietsche, Axel Krug, Tilo Kircher, Els Fieremans (+21 others)
2018 Brain Imaging and Behavior  
Large-scale consortium efforts such as Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) and other collaborative efforts show that combining statistical data from multiple independent studies  ...  A meta-analysis would pool effects from studies conducted in a similar manner, yet to date, no such harmonized protocol exists for resting state fMRI (rsfMRI) data.  ...  Advanced denoising techniques can improve SNR characteristics by taking advantage of the spatial and temporal dimensions of the fMRI data (Du et al. 2016) .  ... 
doi:10.1007/s11682-018-9941-x pmid:30191514 fatcat:jlg5yzhmmngqzdkropkju34mnm

The developing Human Connectome Project (dHCP) automated resting-state functional processing framework for newborn infants

Sean P. Fitzgibbon, Samuel J. Harrison, Mark Jenkinson, Luke Baxter, Emma C. Robinson, Matteo Bastiani, Jelena Bozek, Vyacheslav Karolis, Lucilio Cordero Grande, Anthony N. Price, Emer Hughes, Antonios Makropoulos (+15 others)
2020 NeuroImage  
This is being achieved through the acquisition of multi-modal MRI data from over 1000 in- and ex-utero subjects combined with the development of optimised pre-processing pipelines.  ...  In this paper we present an automated and robust pipeline to minimally pre-process highly confounded neonatal resting-state fMRI data, robustly, with low failure rates and high quality-assurance.  ...  Mark Chiew for advice on multi-band artefacts, and Assoc. Prof. Kenneth Pope for assistance with the neonatal HRF.  ... 
doi:10.1016/j.neuroimage.2020.117303 pmid:32866666 pmcid:PMC7762845 fatcat:f2xibrg5snfczhvwe2rruhd5cm

The developing Human Connectome Project (dHCP) automated resting-state functional processing framework for newborn infants [article]

Sean Patrick Fitzgibbon, Samuel J Harrison, Mark Jenkinson, Luke Baxter, Emma Claire Robinson, Matteo Bastiani, Jelena Bozek, Vyacheslav Karolis, Lucilio Cordero Grande, Anthony N Price, Emer Hughes, Antonios Makropoulos (+15 others)
2019 bioRxiv   pre-print
This is being achieved through the acquisition of multi-modal MRI data from over 1000 in- and ex-utero subjects combined with the development of optimised pre-processing pipelines.  ...  In this paper we present an automated and robust pipeline to minimally pre-process highly confounded neonatal resting-state fMRI data, robustly, with low failure rates and high quality-assurance.  ...  Acknowledgements We are grateful to Dr Mark Chiew for advice on multi-band artefacts, and Assoc. Prof. Kenneth Pope for assistance with the neonatal HRF.  ... 
doi:10.1101/766030 fatcat:j6xg3n7lfjhrrfujmpqf7juv54

ICA-based Denoising Strategies in Breath-Hold Induced Cerebrovascular Reactivity Mapping with Multi Echo BOLD fMRI

Stefano Moia, Maite Termenon, Eneko Uruñuela, Gang Chen, Rachael C. Stickland, Molly G. Bright, César Caballero-Gaudes
2021 NeuroImage  
This work demonstrate the usefulness of multi-echo based fMRI acquisitions and independent component analysis denoising for precision mapping of CVR in single subjects based on BH paradigms, fostering  ...  In this study, we evaluate the performance of multiple analysis strategies based on lagged general linear models applied on multi-echo BOLD fMRI data, acquired in ten subjects performing a BH task during  ...  Acknowledgments The authors would like to thank Vicente Ferrer for collaborating in data acquisition and two anonymous reviewers for helping improving the quality of the paper.  ... 
doi:10.1016/j.neuroimage.2021.117914 pmid:33684602 fatcat:5lo2khetwvddtipzlp7ou5aon4

Quality and denoising in real‐time functional magnetic resonance imaging neurofeedback: A methods review

Stephan Heunis, Rolf Lamerichs, Svitlana Zinger, Cesar Caballero‐Gaudes, Jacobus F. A. Jansen, Bert Aldenkamp, Marcel Breeuwer
2020 Human Brain Mapping  
To this end, we recommend that future rtfMRI-NF studies: (a) report implementation of a set of standard real-time fMRI denoising steps according to a proposed COBIDAS-style checklist (https://osf.io/kjwhf  ...  in the form of methods and data sharing and support of open-source rtfMRI-NF software.  ...  | METHODS TO IMPROVE SIGNAL QUALITY AND DENOISING IN REAL-TIME FMRI NEUROFEEDBACK This section addresses the third research question of this review: which methods for denoising data and improving data  ... 
doi:10.1002/hbm.25010 pmid:32333624 pmcid:PMC7375116 fatcat:xddngwjzyvea3pobc5i6q6ddp4

Heritability estimates on resting state fMRI data using ENIGMA analysis pipeline

Bhim M. Adhikari, Neda Jahanshad, Dinesh Shukla, David C. Glahn, John Blangero, Richard C. Reynolds, Robert W. Cox, Els Fieremans, Jelle Veraart, Dmitry S. Novikov, Thomas E. Nichols, L. Elliot Hong (+2 others)
2017 Biocomputing 2018  
We analyzed two independent cohorts, GOBS (Genetics of Brain Structure) and HCP (the Human Connectome Project), which collected data using conventional and connectomics oriented fMRI protocols, respectively  ...  An effective harmonization should provide optimal measures for data of different qualities.  ...  Louis for allowing the use of their computational facility for this project.  ... 
doi:10.1142/9789813235533_0029 fatcat:6sr7azhcozdyjajax2koykwcv4

Heritability estimates on resting state fMRI data using ENIGMA analysis pipeline

Bhim M Adhikari, Neda Jahanshad, Dinesh Shukla, David C Glahn, John Blangero, Richard C Reynolds, Robert W Cox, Els Fieremans, Jelle Veraart, Dmitry S Novikov, Thomas E Nichols, L Elliot Hong (+2 others)
2018 Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing  
We analyzed two independent cohorts, GOBS (Genetics of Brain Structure) and HCP (the Human Connectome Project), which collected data using conventional and connectomics oriented fMRI protocols, respectively  ...  An effective harmonization should provide optimal measures for data of different qualities.  ...  Louis for allowing the use of their computational facility for this project.  ... 
pmid:29218892 pmcid:PMC5728672 fatcat:k43mab5eyresbiyuuivky73eje

ENIGMA HALFpipe: Interactive, reproducible, and efficient analysis for resting-state and task-based fMRI data [article]

Lea Waller, Susanne Erk, Elena Pozzi, Yara J. Toenders, Courtney C. Haswell, Marc Büttner, Paul M. Thompson, Lianne Schmaal, Rajendra A. Morey, Henrik Walter, Ilya M. Veer
2021 bioRxiv   pre-print
and resting-state fMRI data through uniform application of preprocessing, quality assessment, single-subject feature extraction, and group-level statistics.  ...  data, while broadening core principles of data analysis for producing reproducible results.  ...  For fMRI data, HALFpipe can perform denoising via ICA-AROMA (Pruim et al., 2015) .  ... 
doi:10.1101/2021.05.07.442790 fatcat:6seux5ybkncl7dpdlhj2ccsnx4

rt-me-fMRI: a task and resting state dataset for real-time, multi-echo fMRI methods development and validation

Stephan Heunis, Marcel Breeuwer, César Caballero-Gaudes, Lydia Hellrung, Willem Huijbers, Jacobus F.A. Jansen, Rolf Lamerichs, Svitlana Zinger, Albert P. Aldenkamp
2021 F1000Research  
Its main purpose is to advance the development of methods for real-time multi-echo functional magnetic resonance imaging (rt-me-fMRI) analysis with applications in neurofeedback, real-time quality control  ...  The dataset itself can be accessed via a data use agreement on DataverseNL at https://dataverse.nl/dataverse/rt-me-fmri.  ...  Acknowledgements A previous version of this article is available on bioRxiv: https://doi.org/10.1101/2020.12.07.414490  ... 
doi:10.12688/f1000research.29988.1 fatcat:hytvkg3mvjejpdkp4g3f27datm

Heritability estimates on resting state fMRI data using the ENIGMA analysis pipeline [article]

Bhim M. Adhikari, Neda Jahanshad, Dinesh Shukla, Dinesh Shukla, Richard C. Reynolds, Robert W. Cox, Els Fieremans, Jelle Veraart, Dmitry S. Novikov, L. Elliot Hong, Paul M. Thompson, Peter Kochunov
2017 arXiv   pre-print
We analyzed two independent cohorts, GOBS (Genetics of Brain Structure) and HCP (the Human Connectome Project), which collected data using conventional and connectomics oriented fMRI protocols.  ...  We used the single-modality ENIGMA rsfMRI pipeline based on model-free Marchenko-Pastor PCA based denoising to verify and replicate findings of significant heritability of measures from resting state networks  ...  The first step is the application of principal components analysis (PCA)-based denoising [8, 9] , to improve signalto noise ratio (SNR) and temporal SNR (tSNR) properties of the time series data, with  ... 
arXiv:1709.08578v1 fatcat:czgl5evf4zagxeaou52ycerznm

Removing independent noise in systems neuroscience data using DeepInterpolation [article]

Jerome Lecoq, Michael Oliver, Joshua H Siegle, Natalia Orlova, Christof Koch
2020 bioRxiv   pre-print
Here, we introduce DeepInterpolation, a general-purpose denoising algorithm that trains a nonlinear interpolation model using only noisy samples from the original raw data.  ...  On fMRI datasets, DeepInterpolation increased the SNR of individual voxels 1.6-fold. All these improvements were attained without sacrificing spatial or temporal resolution.  ...  The dataset contained fMRI data from five subjects 514 with 3 types of scanning sessions: "ses-perceptionTraining", "ses-perceptionTest" and "ses-imageryTest". 515 We trained our denoiser on "ses-perceptionTraining  ... 
doi:10.1101/2020.10.15.341602 fatcat:wxba4gtjujhrfa5gn5zvundbqi

rt-me-fMRI: A task and resting state dataset for real-time, multi-echo fMRI methods development and validation [article]

Stephan Heunis, Marcel Breeuwer, Cesar Caballero Gaudes, Lydia Hellrung, Willem Huijbers, Jacobus FA Jansen, Rolf Lamerichs, Svitlana Zinger, Albert P Aldenkamp
2020 bioRxiv   pre-print
Its main purpose is to advance the development of methods for real-time multi-echo functional magnetic resonance imaging (rt-me-fMRI) analysis with applications in neurofeedback, real-time quality control  ...  The dataset itself can be accessed via a data use agreement on DataverseNL at https://dataverse.nl/dataverse/rt-me-fmri.  ...  21 validating the use of multi-echo fMRI for improved quality data.  ... 
doi:10.1101/2020.12.07.414490 fatcat:s2kakdvrsfam5d6p2natznvltu

Decentralized temporal independent component analysis: Leveraging fMRI data in collaborative settings

Bradley T. Baker, Anees Abrol, Rogers F. Silva, Eswar Damaraju, Anand D. Sarwate, Vince D. Calhoun, Sergey M. Plis
2019 NeuroImage  
We validate our method on real functional magnetic resonance imaging (fMRI) data and show that it enables collaborative large-scale temporal ICA of fMRI, a rich vein of analysis as of yet largely unexplored  ...  Additionally, though research groups are willing to grant access for collaborations, they often wish to maintain control of their data locally.  ...  The author(s) declare that there was no other financial support or compensation that could be perceived as constituting a potential conflict of interest. Bibliography  ... 
doi:10.1016/j.neuroimage.2018.10.072 pmid:30408598 pmcid:PMC7246038 fatcat:bgxrppqozvfider7gud5hnl2zm

NeoRS: a neonatal resting state fMRI data preprocessing pipeline [article]

V. Enguix, J. Kenley, D. Luck, J. Cohen-Adad, G.A. Lodygensky
2022 arXiv   pre-print
Because of the non-collaborative nature of the neonates, the differences in brain size and the reversed contrast compared to adults, neonates can't be processed with the existing adult pipelines.  ...  In neonates, where fMRI is limited to few paradigms, rsfMRI was shown to be a relevant tool to explore regional interactions of brain networks.  ...  Acknowledgements We would like to thank the Washington University -School of Medicine for sharing their templates for this project, and Jed Elison for letting us use the neonatal data from the Baby Connectome  ... 
arXiv:2204.05137v1 fatcat:onr2n26f2bfu5nfrvusowtwkme

A Survey on Deep Learning for Neuroimaging-based Brain Disorder Analysis [article]

Li Zhang and Mingliang Wang and Mingxia Liu and Daoqiang Zhang
2020 arXiv   pre-print
We first provide a comprehensive overview of deep learning techniques and popular network architectures, by introducing various types of deep neural networks and recent developments.  ...  performance improvements over traditional machine learning in computer-aided diagnosis of brain disorders.  ...  Finally, the utilization of multi-site data for disease analysis has recently attracted increasing attention [101, 130, 131] , since a large number of subjects from multiple imaging sites are beneficial  ... 
arXiv:2005.04573v1 fatcat:64ze55onzfemhgpebvsewe3fki
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