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2014 IEEE Transactions on Biomedical Engineering  
Matusiewicz 396 A Constrained ICA Approach for Real-Time Cardiac Artifact Rejection in Magnetoencephalography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ...  Goldberger 273 Real-Time, Simultaneous Myoelectric Control Using Force and Position-Based Training Paradigms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ... 
doi:10.1109/tbme.2014.2298152 fatcat:aac4pspujbg7vkfz2klfjuiqae

Removal of Artifacts from EEG Signals: A Review

Xiao Jiang, Gui-Bin Bian, Zean Tian
2019 Sensors  
Lastly, a comparative analysis is provided for choosing a suitable methods according to particular application.  ...  Electroencephalogram (EEG) plays an important role in identifying brain activity and behavior.  ...  In 2016, a new method for real-time detection of eyeblink artifacts using an automatic thresholding algorithm was introduced [116] .  ... 
doi:10.3390/s19050987 fatcat:aaj7kldei5clrl7j7g7xi66ih4

A Review of Issues Related to Data Acquisition and Analysis in EEG/MEG Studies

Aina Puce, Matti Hämäläinen
2017 Brain Sciences  
Given the increase in methodological complexity in EEG/MEG, it is important to gather data that are of high quality and that are as artifact free as possible.  ...  Electroencephalography (EEG) and magnetoencephalography (MEG) are non-invasive electrophysiological methods, which record electric potentials and magnetic fields due to electric currents in synchronously-active  ...  Acknowledgments: M.S.H. was financially supported by National Institutes of Health/National Institute for Biomedical Imaging and Bioengineering (P41EB015896 and 5R01EB009048).  ... 
doi:10.3390/brainsci7060058 pmid:28561761 pmcid:PMC5483631 fatcat:bp2o5cph6zgs7b3zz5luslltb4

Autoreject: Automated artifact rejection for MEG and EEG data [article]

Mainak Jas, Denis A. Engemann, Yousra Bekhti, Federico Raimondo, Alexandre Gramfort
2017 arXiv   pre-print
We present an automated algorithm for unified rejection and repair of bad trials in magnetoencephalography (MEG) and electroencephalography (EEG) signals.  ...  This approach is then extended to a more sophisticated algorithm which estimates this threshold for each sensor yielding trial-wise bad sensors.  ...  Acknowledgement We thank Lionel Naccache for providing us with dramatic examples of artifact-ridden clinical EEG data which considerably stimulated the research presented in this study.  ... 
arXiv:1612.08194v3 fatcat:f4owhcy53nafhglywypqtdbxpm

Modern Methods for Interrogating the Human Connectome

Mark J. Lowe, Ken E. Sakaie, Erik B. Beall, Vince D. Calhoun, David A. Bridwell, Mikail Rubinov, Stephen M. Rao
2016 Journal of the International Neuropsychological Society  
We also review the most common analytical approaches used for examining brain interconnectivity associated with these various imaging methods.Results:This review presents a critical analysis of the assumptions  ...  techniques used to measure functional and structural connectivity, including resting state functional MRI, diffusion MRI, and electroencephalography and magnetoencephalography coherence.  ...  Acknowledgments We thank Sally Durgerian for her technical assistance.  ... 
doi:10.1017/s1355617716000060 pmid:26888611 pmcid:PMC4827018 fatcat:kx3kjuue5retbjr3klnnj6ziq4

Autoreject: Automated artifact rejection for MEG and EEG data

Mainak Jas, Denis A. Engemann, Yousra Bekhti, Federico Raimondo, Alexandre Gramfort
2017 NeuroImage  
We present an automated algorithm for unified rejection and repair of bad trials in magnetoencephalography (MEG) and electroencephalography (EEG) signals.  ...  This approach is then extended to a more sophisticated algorithm which estimates this threshold for each sensor yielding trial-wise bad sensors.  ...  Acknowledgement We thank Lionel Naccache for providing us with dramatic examples of artifact-ridden clinical EEG data which considerably stimulated the research presented in this study.  ... 
doi:10.1016/j.neuroimage.2017.06.030 pmid:28645840 pmcid:PMC7243972 fatcat:tfk63426wnf3xkfazgyirzoj7i

EEG-fMRI reciprocal functional neuroimaging

Lin Yang, Zhongming Liu, Bin He
2010 Clinical Neurophysiology  
Methods-This approach starts with using the independent component analysis (ICA) to decompose the spatio-temporal EEG data into a linear combination of scalp potential maps and time courses.  ...  Results-In the simulation study, reliable reconstruction of the localization, time-frequency feature and cortical functional connection were achieved for the simulated oscillatory and event-related activities  ...  Acknowledgments This work was supported in part by NIH RO1EB006433 and RO1EB007920, and NSF CBET-0933067.  ... 
doi:10.1016/j.clinph.2010.02.153 pmid:20378397 pmcid:PMC2904837 fatcat:4tmjlbrgfzfb3npmdinifkxmcu

A wavelet-based method for measuring the oscillatory dynamics of resting-state functional connectivity in MEG

Avniel Singh Ghuman, Jonathan R. McDaniel, Alex Martin
2011 NeuroImage  
However, there is a lack of consensus as to the best method for examining connectivity in resting state MEG data.  ...  We test this method by simulating phase-locked oscillations at various points on the cortical surface, which illustrates a substantial artifact that results from imperfections in the inverse solution.  ...  assistance with data collection, Gang Chen for assistance with statistics, Zhongming Liu for assistance with the cardiac artifact removal procedure, and Ziad Saad for assistance with MRI processing.  ... 
doi:10.1016/j.neuroimage.2011.01.046 pmid:21256967 pmcid:PMC3391564 fatcat:mi6xqumirnh6pjpmqkmx4y7any

Classification of Upper Arm Movements from EEG signals using Machine Learning with ICA Analysis [article]

Pranali Kokate, Sidharth Pancholi, Amit M. Joshi
2021 arXiv   pre-print
Therefore, a novel approach was approached to remove the artifacts using Independent Components Analysis which boosted the performance.  ...  The Brain-Computer Interface system is a profoundly developing area of experimentation for Motor activities which plays vital role in decoding cognitive activities.  ...  Further, the pre-processing approaches have been elaborated, followed by artifact identification and rejection.  ... 
arXiv:2107.08514v1 fatcat:4aijbhssk5dejehq2uuvx4527e

Magnetic Source Imaging and Infant MEG: Current Trends and Technical Advances

Chieh Kao, Yang Zhang
2019 Brain Sciences  
Magnetoencephalography (MEG) is known for its temporal precision and good spatial resolution in cognitive brain research.  ...  A selection of infant MEG research in auditory, speech, vision, motor, sleep, cross-modality, and clinical application is then summarized and discussed with a focus on the source localization analyses.  ...  Another potential artifact may stem from smaller body size, which results in stronger cardiac artifacts in infant MEG recordings than those from adults [52, 53] .  ... 
doi:10.3390/brainsci9080181 pmid:31357668 pmcid:PMC6721320 fatcat:re24z2r7uff7bg4wordc3xexum

MEG and EEG data analysis with MNE-Python

Alexandre Gramfort
2013 Frontiers in Neuroscience  
Magnetoencephalography and electroencephalography (M/EEG) measure the weak electromagnetic signals generated by neuronal activity in the brain.  ...  Using these signals to characterize and locate neural activation in the brain is a challenge that requires expertise in physics, signal processing, statistics, and numerical methods.  ...  This allows any MNE-Python analysis to be performed on the ICA time series. A simplified ICA workflow for identifying, visualizing and removing cardiac artifacts is illustrated in Table 2 .  ... 
doi:10.3389/fnins.2013.00267 pmid:24431986 pmcid:PMC3872725 fatcat:unycmng6p5bu3hvadnedzgplua

MNE software for processing MEG and EEG data

Alexandre Gramfort, Martin Luessi, Eric Larson, Denis A. Engemann, Daniel Strohmeier, Christian Brodbeck, Lauri Parkkonen, Matti S. Hämäläinen
2014 NeuroImage  
Magnetoencephalography and electroencephalography (M/EEG) measure the weak electromagnetic signals originating from neural currents in the brain.  ...  including preprocessing, source estimation, time-frequency analysis, statistical analysis, and several methods to estimate functional connectivity between distributed brain regions.  ...  The first time series (index 0) displayed in the upper-left window clearly resembles a cardiac signal. The time series 7 closely matches the EOG signal.  ... 
doi:10.1016/j.neuroimage.2013.10.027 pmid:24161808 pmcid:PMC3930851 fatcat:ml3wu4vhu5ajjbmcr3te4vlgla

Exploring the Variability of Single Trials in Somatosensory Evoked Responses Using Constrained Source Extraction and RMT

A. Koutras, G. K. Kostopoulos, A. A. Ioannides
2008 IEEE Transactions on Biomedical Engineering  
Index Terms-Constrained source extraction, electroencephalography (EEG), Independent Component Analysis (ICA), magnetoencephalography (MEG), random matrix theory.  ...  Temporal constrained source extraction using sparse decomposition identifies signal topographies that closely match the shape characteristics of a reference signal, one response for each ST.  ...  Stavrinou, and members of the laboratory for Human Brain Dynamics for the data acquisition of combined EEG and MEG.  ... 
doi:10.1109/tbme.2008.915708 pmid:18334387 fatcat:fzqafxjinreqjlikzituj6axuy

Good practice for conducting and reporting MEG research

Joachim Gross, Sylvain Baillet, Gareth R. Barnes, Richard N. Henson, Arjan Hillebrand, Ole Jensen, Karim Jerbi, Vladimir Litvak, Burkhard Maess, Robert Oostenveld, Lauri Parkkonen, Jason R. Taylor (+3 others)
2013 NeuroImage  
However, the rapidly increasing level of complexity of the different steps in a MEG study make it difficult for novices, and sometimes even for experts, to stay aware of possible limitations and caveats  ...  This manuscript aims at making recommendations for a number of important data acquisition and data analysis steps and suggests details that should be specified in manuscripts reporting MEG studies.  ...  , for example in traditional analysis of variance (ANOVA) approaches for analyzing the mean amplitude of an evoked response across a specified peristimulus time window, in which each channel is a level  ... 
doi:10.1016/j.neuroimage.2012.10.001 pmid:23046981 pmcid:PMC3925794 fatcat:yvnmhlx3trgdvfxb226ojva7ye

Comments and Controversies

1998 NeuroImage  
However, the rapidly increasing level of complexity of the different steps in a MEG study make it difficult for novices, and sometimes even for experts, to stay aware of possible limitations and caveats  ...  This manuscript aims at making recommendations for a number of important data acquisition and data analysis steps and suggests details that should be specified in manuscripts reporting MEG studies.  ...  , for example in traditional analysis of variance (ANOVA) approaches for analyzing the mean amplitude of an evoked response across a specified peristimulus time window, in which each channel is a level  ... 
doi:10.1006/nimg.1998.0374 pmid:9740753 fatcat:utxzhd4b4zcz7doimfgufj27km
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