A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Filters
Collective sparse symmetric non-negative matrix factorization for identifying overlapping communities in resting-state brain functional networks
2018
NeuroImage
Preserved Fulltext
To comprehensively validate cssNMF, a simulated fMRI dataset with ground-truth, a real rs-fMRI dataset with two repeated sessions and another different real rs-fMRI dataset have been used for performance ...
Resting-state functional magnetic resonance imaging (rs-fMRI) provides a valuable tool to study spontaneous brain activity. ...
Xinian Zuo for providing the CoRR dataset and his help in data preprocessing and analysis. This work was supported in part by the National Basic Research Program of China under ...
doi:10.1016/j.neuroimage.2017.11.003
pmid:29117581
fatcat:3he4fcrsbrfefdyfexte76gi74
A method for evaluating dynamic functional network connectivity and task-modulation: application to schizophrenia
2010
Magnetic Resonance Materials in Physics, Biology and Medicine
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Materials and methods-We study the theoretical basis of the approach, perform a simulation analysis and apply it to fMRI data from schizophrenia patients (SP) and healthy controls (HC). ...
Analyses on the fMRI data include: (a) group sICA to determine regions of significant task-related activity, (b) static and dynamic FNC analysis among these networks by using maximal laggedcorrelation ...
The results based on the resting-state data analysis are not included in this paper and they are the subject of a separate study. ...
doi:10.1007/s10334-010-0197-8
pmid:20162320
pmcid:PMC2891285
fatcat:uctd7odovrgjthvbm5urgxmpju
Characterization of neuromagnetic brain rhythms over time scales of minutes using spatial independent component analysis
2011
Human Brain Mapping
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
In functional magnetic resonance imaging (fMRI), by contrast, most studies use spatial ICA: each time point constitutes a row of the data matrix, and independence of the spatial patterns is maximized. ...
The resulting method, spatial Fourier-ICA, provides a concise summary of the spatiotemporal and spectral content of spontaneous neuromagnetic oscillations in cortical source space over time scales of minutes ...
Sanna Malinen for the original stimuli and Maarit Aro for contributing the Presentation TM code. ...
doi:10.1002/hbm.21303
pmid:21915941
fatcat:pmpm6iwxmbcuba5x3o32ltrtci
Shift-Invariant Canonical Polyadic Decomposition of Complex-Valued Multi-Subject fMRI Data with a Phase Sparsity Constraint
2019
IEEE Transactions on Medical Imaging
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
The results from both the simulated and experimental fMRI data demonstrate improvements of the proposed method over three complex-valued algorithms, namely, tensor-based spatial ICA, shift-invariant CPD ...
When comparing with a real-valued algorithm combining shift-invariant CPD and ICA, the proposed method detects 178.7% more contiguous task-related activations. ...
We use the simulated fMRI data to evaluate the effects of spatial and temporal changes and the noise effect on pcsCPD, csCPD, CPD, and T-sICA.
B. ...
doi:10.1109/tmi.2019.2936046
pmid:31425066
pmcid:PMC7473454
fatcat:4v5s2ftpbncr3bwjf5wogsooou
Robust Data Driven Model Order Estimation for Independent Component Analysis of fMRI Data with Low Contrast to Noise
2014
PLoS ONE
Preserved Fulltext
The Internet Archive has a preservation copy of this work in our general collections.
The file type is application/pdf.
Independent component analysis (ICA) has been successfully utilized for analysis of functional MRI (fMRI) data for task related as well as resting state studies. ...
However, there has been no consensus on the optimal method for nIC selection, and many studies utilize arbitrarily chosen values for nIC. ...
The content is solely the responsibility of the authors and does not necessarily represent the official views of these institutions. ...
doi:10.1371/journal.pone.0094943
pmid:24788636
pmcid:PMC4005775
fatcat:6j7bt5d6ungdpp45zfpq47kkci
Impact of autocorrelation on functional connectivity
2014
NeuroImage
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
In this paper, first we assess the effect of autocorrelation on Pearson correlation coefficient through theoretical approximation and simulation. Then we present this effect on real fMRI data. ...
Some recent studies based on results from economics have questioned the conventional estimation of functional connectivity and argue that not correcting for autocorrelation in fMRI time-series results ...
Acknowledgments We would like to acknowledge the efforts of all parties responsible for designing and implementing the experiment, collecting the data, and facilitating the brain imaging that made this ...
doi:10.1016/j.neuroimage.2014.07.045
pmid:25072392
pmcid:PMC4253536
fatcat:oxskide3ifacvdige2w2dwppj4
A Data-Driven Sparse GLM for fMRI Analysis Using Sparse Dictionary Learning With MDL Criterion
2011
IEEE Transactions on Medical Imaging
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2011; you can also visit the original URL.
The file type is application/pdf.
Using simulation and real fMRI experiments, we show that the proposed method can adapt individual variation better compared to the conventional ICA methods. ...
The main contribution of this paper is, therefore, a new data driven fMRI analysis that is derived solely based upon the sparsity of the signals. ...
ACKNOWLEDGMENT This research was supported by the Korea Science and Engineering Foundation, Grant No.:2010-N01100084. We thank Dr. Yong Jeong and Mr. ...
doi:10.1109/tmi.2010.2097275
pmid:21138799
fatcat:ewpwapekdfgv7lam44dxxpplge
Wavelet-based fMRI analysis: 3-D denoising, signal separation, and validation metrics
2011
NeuroImage
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
We verified our method using simulated as well as real fMRI data and compared our results against the conventional scheme (Gaussian smoothing + spatial ICA: s-ICA). ...
The results show significant improvements based on two important features: (1) preservation of shape of the activation region (shape metrics) and (2) receiver operating characteristic curves. ...
Traditional smoothing filters such as mean, median and Gaussian filters normally employed in the spatial domain smooth the signals with blurring effects and consequently result in loss of edge details. ...
doi:10.1016/j.neuroimage.2010.10.063
pmid:21034833
pmcid:PMC3058245
fatcat:ilh7vjkizfd63h6xcupuqcc7uy
Group-level spatial independent component analysis of Fourier envelopes of resting-state MEG data
2014
NeuroImage
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Abstract We developed a data-driven method to spatiotemporally and spectrally characterize the dynamics of brain oscillations in resting-state magnetoencephalography (MEG) data. ...
We compared this method using a simulated data set against 5 other variants of independent component analysis and found that eSFICA performed best in characterizing dynamics at time scales of the order ...
Analysis of real MEG data Based on the results from the simulations (see Section 3.1), we selected eSFICA to be applied on resting-state MEG data and studied the dynamics of the estimated components during ...
doi:10.1016/j.neuroimage.2013.10.032
pmid:24185028
fatcat:rmwxjskq5rgnbj6rkqdrngs56m
Large-scale functional network overlap is a general property of brain functional organization: Reconciling inconsistent fMRI findings from general-linear-model-based analyses
2016
Neuroscience and Biobehavioral Reviews
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
This paper selectively reviews findings of histological and electrophysiological studies and fMRI spatial independent component analysis (sICA) and reports new findings by applying sICA to two existing ...
Functional magnetic resonance imaging (fMRI) studies regularly use univariate general-linear-model-based analyses (GLM). ...
Several other studies further investigated the above-discussed finding of anti-correlations of task-positive and task-negative networks during rest condition by analyzing simulated and real fMRI data acquired ...
doi:10.1016/j.neubiorev.2016.08.035
pmid:27592153
pmcid:PMC5140707
fatcat:zycoe33nonfmjl35qh6hat5jcm
CORSICA: correction of structured noise in fMRI by automatic identification of ICA components
2007
Magnetic Resonance Imaging
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
with a high sensitivity and a specificity of 1. ...
On short-TR datasets, we validate that the proposed method of noise reduction allows a substantial improvement of the signal-to-noise ratio evaluated at the cardiac and respiratory frequencies, even in ...
This kind of simulator would allow one to really compare the different methods of noise reduction in fMRI. ...
doi:10.1016/j.mri.2006.09.042
pmid:17222713
fatcat:l7wh6zvhmraprahflrw36662oy
Modeling Resting-State Brain Functional Integration
2010
Nature Precedings
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
On the other hand, resting-state fMRI which was first studied in Biswal's paper [10] is a very good way to investigate the influence of disease and/or medication on the brain. ...
Some rs-fMRI studies indicated a resting-state FSIN [6, 30, 87, 29, 68, 33, 38] , which consists of LPFC, dACC, insula, thalamus and striatum etc. ...
Resting state fixation runs from healthy control subjects (four 7 minute runs per subject) who were part of a study on the behavioral effects of spontaneous BOLD fluctuations. ...
doi:10.1038/npre.2010.4380.1
fatcat:fuptk3khkjfv3bezdvhsk3d4di
The Chronnectome: Time-Varying Connectivity Networks as the Next Frontier in fMRI Data Discovery
2014
Neuron
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
We primarily focus on multivariate approaches developed in our group and review a number of approaches with an emphasis on matrix decompositions such as principle component analysis and independent component ...
There are a number of methodological directions that need to be developed further, but chronnectome approaches already show great promise for the study of both the healthy and the diseased brain. ...
ACKNOWLEDGMENTS We thank Elena Allen, Mohammad Arbabshirani, Sai Ma, Barnaly Rashid, Maziar Yaesoubi, and Qingbao Yu for their input and suggestions on data analysis. ...
doi:10.1016/j.neuron.2014.10.015
pmid:25374354
pmcid:PMC4372723
fatcat:l4vezjg7hnhv5pnbpuy4nn62qu
Large-scale Probabilistic Functional Modes from resting state fMRI
2015
NeuroImage
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
In this paper, we introduce a method for identifying modes of coherent activity from resting state fMRI (rfMRI) data. ...
Our model characterises a mode as the outer product of a spatial map and a time course, constrained by the nature of both the between-subject variation and the effect of the haemodynamic response function ...
, visualise, and share these data sets. ...
doi:10.1016/j.neuroimage.2015.01.013
pmid:25598050
pmcid:PMC4349633
fatcat:2opa6duuizffnbdwv2gqzrf3le
Cerebellar Functional Parcellation Using Sparse Dictionary Learning Clustering
2016
Frontiers in Neuroscience
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
We aimed to identify the functional parcellation of the cerebellum using information from resting-state functional magnetic resonance imaging (rs-fMRI). ...
SDLC integrates dictionary learning, sparse representation of rs-fMRI, and k-means clustering into one optimization problem. ...
In the last decade, resting-state functional magnetic resonance imaging (rs-fMRI) has emerged as a useful imaging technique for mapping intrinsic functional organization of the brain. ...
doi:10.3389/fnins.2016.00188
pmid:27199650
pmcid:PMC4852537
fatcat:3gjfxrdrhrc2bludmbg5pnmur4
« Previous
Showing results 1 — 15 out of 62 results