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Denoising scanner effects from multimodal MRI data using linked independent component analysis

Huanjie Li, Stephen M. Smith, Staci Gruber, Scott E. Lukas, Marisa M. Silveri, Kevin P. Hill, William D.S. Killgore, Lisa D. Nickerson
2019 NeuroImage  
In this study, we propose a novel denoising approach that implements a data-driven linked independent component analysis (LICA) to identify scanner-related effects for removal from multimodal MRI to denoise  ...  Pooling magnetic resonance imaging (MRI) data across research studies, or utilizing shared data from imaging repositories, presents exceptional opportunities to advance and enhance reproducibility of neuroscience  ...  Data collection was supported by National Institutes of Health grants DA016695 (SG), DA021241 (SG), DA024007 (SEL), DA029115 (KPH) and AA014651 (MMS), and by DARPA-12-12-11-YFA11-FP-029 (WDSK).  ... 
doi:10.1016/j.neuroimage.2019.116388 pmid:31765802 fatcat:vi2trksk3vaq3mbwy3bxiyp2hq

Combining Multi-Site/Multi-Study MRI Data: Linked-ICA Denoising for Removing Scanner and Site Variability from Multimodal MRI Data [article]

Huanjie Li, Stephen M Smith, Staci A Gruber, Scott E Lukas, Marisa M Silveri, Kevin P Hill, William D.S. Killgore, Lisa D Nickerson
2018 bioRxiv   pre-print
In this study, we propose a novel denoising approach for multi-site multimodal MRI data that implements a data-driven linked independent component analysis (LICA) to efficiently identify scanner/site-related  ...  We use data from six different studies collected on the same scanner across major hardware (gradient and head coil) and software upgrades to demonstrate our LICA-based denoising approach.  ...  A second approach that has been used to a lesser extent is modality-specific independent component analysis (ICA) for denoising.  ... 
doi:10.1101/337576 fatcat:7ta55swnq5dmlkq5fqftaekkum

Integrated analysis of gray and white matter alterations in attention-deficit/hyperactivity disorder

Winke Francx, Alberto Llera, Maarten Mennes, Marcel P. Zwiers, Stephen V. Faraone, Jaap Oosterlaan, Dirk Heslenfeld, Pieter J. Hoekstra, Catharina A. Hartman, Barbara Franke, Jan K. Buitelaar, Christian F. Beckmann
2016 NeuroImage: Clinical  
This data-driven analysis decomposes the data into multimodal independent components reflecting common inter-subject variation across imaging modalities.  ...  independent component analysis.  ...  Linked independent component analysis Linked independent component analysis (linked ICA, (Groves et al., 2011) is a data-driven approach aimed at relating common components across multiple imaging modalities  ... 
doi:10.1016/j.nicl.2016.03.005 pmid:27298764 pmcid:PMC4893015 fatcat:oxgs7vsekzha7fkxkm6c26z4dm

Brain multimodal co-alterations related to delay discounting: a multimodal MRI fusion analysis in persons with and without cocaine use disorder

Christina S. Meade, Xiang Li, Sheri L. Towe, Ryan P. Bell, Vince D. Calhoun, Jing Sui
2021 BMC Neuroscience  
With delay discounting as the reference, multimodal canonical component analysis plus joint independent component analysis was used to identify co-alterations in brain structure and function.  ...  Innovative analytic approaches that integrate information from multiple neuroimaging modalities can provide new insights into the complex effects of drug use on the brain.  ...  The rs-fMRI data were preprocessed and denoised using a standard pipeline in FSL [63, 68, 69] .  ... 
doi:10.1186/s12868-021-00654-z pmid:34416865 pmcid:PMC8377830 fatcat:4l6qujig55altevaynsruz3abm

Multimodal Fusion With Reference: Searching for Joint Neuromarkers of Working Memory Deficits in Schizophrenia

Shile Qi, Vince D. Calhoun, Theo G. M. van Erp, Juan Bustillo, Eswar Damaraju, Jessica A. Turner, Yuhui Du, Jian Yang, Jiayu Chen, Qingbao Yu, Daniel H. Mathalon, Judith M. Ford (+8 others)
2018 IEEE Transactions on Medical Imaging  
Two independent cohorts (294 and 83 subjects respectively) were used.  ...  Multimodal fusion is an effective approach to take advantage of cross-information among multiple imaging data to better understand brain diseases.  ...  Joint independent component analysis (ICA), and linked ICA perform well in spatial decomposition by maximizing the joint independence, but all modalities share a common profile.  ... 
doi:10.1109/tmi.2017.2725306 pmid:28708547 pmcid:PMC5750081 fatcat:37lnuob67ncbfmjuf336oedszy

Refinement by integration: aggregated effects of multimodal imaging markers on adult ADHD

Thomas Wolfers, Alberto Llera Arenas, A. Marten H. Onnink, Janneke Dammers, Martine Hoogman, Marcel P. Zwiers, Jan K. Buitelaar, Barbara Franke, Andre F. Marquand, Christian F. Beckmann
2017 Journal of Psychiatry & Neuroscience  
Methods: We analyzed a sample of adults with persistent ADHD and healthy controls using an advanced multimodal linked independent component analysis approach.  ...  Diffusion and structural MRI data were fused to form imaging markers reflecting independ ent components that explain variation across modalities.  ...  Throughout the text, we refer to the independent components derived from linked ICA analysis as imaging markers or simply markers.  ... 
doi:10.1503/jpn.160240 pmid:28832320 pmcid:PMC5662460 fatcat:c4pri4d7gzacvpqxfclpjolsra

Multimodal neuromarkers in schizophrenia via cognition-guided MRI fusion

Jing Sui, Shile Qi, Theo G. M. van Erp, Juan Bustillo, Rongtao Jiang, Dongdong Lin, Jessica A. Turner, Eswar Damaraju, Andrew R. Mayer, Yue Cui, Zening Fu, Yuhui Du (+13 others)
2018 Nature Communications  
A supervised learning strategy is used to guide three-way multimodal magnetic resonance imaging (MRI) fusion in two independent cohorts including both healthy individuals and individuals with schizophrenia  ...  These modality-specific brain regions define-in three separate cohorts-promising co-varying multimodal signatures that can be used as predictors of multi-domain cognition.  ...  with reference plus joint independent component analysis).  ... 
doi:10.1038/s41467-018-05432-w pmid:30072715 pmcid:PMC6072778 fatcat:4w3zoj4y7vg6vm3bpcxhl6q4ue

In Search of Multimodal Neuroimaging Biomarkers of Cognitive Deficits in Schizophrenia

Jing Sui, Godfrey D. Pearlson, Yuhui Du, Qingbao Yu, Thomas R. Jones, Jiayu Chen, Tianzi Jiang, Juan Bustillo, Vince D. Calhoun
2015 Biological Psychiatry  
magnetic resonance imaging (MRI), grey matter density (GM) from structural MRI and fractional anisotropy (FA) from diffusion MRI, were investigated by using multi-set canonical correlation analysis in  ...  data from 47 schizophrenia patients treated with antipsychotic medications and 50 age-matched healthy controls.  ...  Only one study examined MCCB correlates of fused neuroimaging data (MEG and DTI) by joint independent component analysis (6) .  ... 
doi:10.1016/j.biopsych.2015.02.017 pmid:25847180 pmcid:PMC4547923 fatcat:ac6lut3ps5gijcgehrrpngizse

Multimodal Evaluation of Neurovascular Functionality in Early Parkinson's Disease

Maria Marcella Laganà, Alice Pirastru, Laura Pelizzari, Federica Rossetto, Sonia Di Tella, Niels Bergsland, Raffaello Nemni, Mario Meloni, Francesca Baglio
2020 Frontiers in Neurology  
A multimodal MRI study was implemented by acquiring resting state functional MRI (rsfMRI) and arterial spin labeling (ASL) datasets on a group of 26 early PD (66.8 ± 8 years, 22 males, median [interquartile  ...  After a standard preprocessing, resting state networks (RSNs) and CBF maps were extracted from rsfMRI and ASL dataset, respectively.  ...  DJJ Wang and SIEMENS Healthineers helped in setting the sequence on our scanner.  ... 
doi:10.3389/fneur.2020.00831 pmid:32982906 pmcid:PMC7479303 fatcat:rrz2wjpjifhc7afshi7cren46u

Multimodal Imaging Brain Markers in Early Adolescence Are Linked with a Physically Active Lifestyle

Piergiorgio Salvan, Thomas Wassenaar, Catherine Wheatley, Nicholas Beale, Michiel Cottaar, Daniel Papp, Matteo Bastiani, Sean Fitzgibbon, Euguene Duff, Jesper Andersson, Anderson M. Winkler, Gwenaëlle Douaud (+4 others)
2021 Journal of Neuroscience  
Using canonical correlation analysis, we unravel a latent mode of brain-physical covariation, independent of demographics, school, or socioeconomic status.  ...  Showing that a physically active lifestyle is linked with systems-level brain MRI metrics, these results suggest widespread associations relating to several biological processes.  ...  FSL MELODIC was then used to estimate 50 group-average independent components.  ... 
doi:10.1523/jneurosci.1260-20.2020 pmid:33436528 pmcid:PMC7880281 fatcat:o2msk5hmnzeyrgordetf2qhe5u

Resting-State Functional Brain Connectivity Best Predicts the Personality Dimension of Openness to Experience

Julien Dubois, Paola Galdi, Yanting Han, Lynn K. Paul, Ralph Adolphs
2018 Personality Neuroscience  
We also derived two superordinate personality factors ("α" and "β") from a principal components analysis of the Neuroticism/Extraversion/Openness Five-Factor Inventory factor scores, thereby reducing noise  ...  As measurement noise is known to moderate statistical relationships, we performed final prediction analyses using average connectivity across both imaging sessions (1 hr of data), with the analysis pipeline  ...  Analysis scripts are available in the following public repository: https://github.com/adolphslab/HCP_MRI-behavior.  ... 
doi:10.1017/pen.2018.8 pmid:30225394 pmcid:PMC6138449 fatcat:ulupvsesgzc2tkmvjssvqcsq3i

Diffusion MRI Metrics and their Relation to Dementia Severity: Effects of Harmonization Approaches [article]

Sophia I. Thomopoulos, Talia M. Nir, Julio E. Villalon-Reina, Artemis Zavaliangos-Petropulu, Piyush Maiti, Hong Zheng, Elnaz Nourollahimoghadam, Neda Jahanshad, Paul M. Thompson, for the Alzheimer's Disease Neuroimaging Initiative
2021 medRxiv   pre-print
Since 2016, the Alzheimer's Disease Neuroimaging Initiative (ADNI) has collected dMRI data from three scanner manufacturers across 58 sites using 7 different protocols that vary in angular resolution,  ...  All harmonization methods gave comparable results while enabling data integration across multiple scanners and protocols.  ...  PMT and NJ received a research grant from Biogen, Inc. for research unrelated to this manuscript.  ... 
doi:10.1101/2021.10.04.21263994 fatcat:hn2y22jjhbawhmzuhkwe2pcypa

Studying Brain Organization via Spontaneous fMRI Signal

Jonathan D. Power, Bradley L. Schlaggar, Steven E. Petersen
2014 Neuron  
Another common technique for measuring signal similarity involves independent component analysis (ICA), already mentioned as a tool for denoising.  ...  Another technique is to apply independent component analysis (ICA) to the entire data set to derive a subset of signals, classify them as signals of interest and signals of noninterest, and then remove  ... 
doi:10.1016/j.neuron.2014.09.007 pmid:25459408 pmcid:PMC4254503 fatcat:7r5lawtxnfa7dndbj6l25oginq

Comprehensive ultrahigh resolution whole brain in vivo MRI dataset as a human phantom

Falk Lüsebrink, Hendrik Mattern, Renat Yakupov, Julio Acosta-Cabronero, Mohammad Ashtarayeh, Steffen Oeltze-Jafra, Oliver Speck
2021 Scientific Data  
All data are from the same participant and were acquired on the same 7 T scanner. The repository contains the unprocessed data as well as (pre-)processing results.  ...  AbstractHere, we present an extension to our previously published structural ultrahigh resolution T1-weighted magnetic resonance imaging (MRI) dataset with an isotropic resolution of 250 µm, consisting  ...  FSL MELODIC independent component analysis was performed on the data with default parameters, other than no motion correction and limiting number of components to 33 (Fig. 9 ).  ... 
doi:10.1038/s41597-021-00923-w pmid:34035308 fatcat:xa7ojefsvvgknjodkct3swzne4

Resting-state functional brain connectivity best predicts the personality dimension of openness to experience [article]

Julien Dubois, Paola Galdi, Yanting Han, Lynn K. Paul, Ralph Adolphs
2017 bioRxiv   pre-print
We also derived two superordinate personality factors ("α" and "β") from a principal components analysis of the NEO-FFI factor scores, thereby reducing noise and enhancing the precision of these measures  ...  As measurement noise is known to moderate statistical relationships, we performed final prediction analyses using average connectivity across both imaging sessions (1 h of data), with the analysis pipeline  ...  Analysis scripts are available in the following public repository: https://github.com/adolphslab/HCP_MRI-behavior .  ... 
doi:10.1101/215129 fatcat:ratswnrq3nd4looypc4tgoh2ay
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