Automatic independent component labeling for artifact removal in fMRI.
about
On the plurality of (methodological) worlds: estimating the analytic flexibility of FMRI experimentsEffect of modafinil on learning and task-related brain activity in methamphetamine-dependent and healthy individualsNeural components underlying behavioral flexibility in human reversal learningResting-State fMRI in MS: General Concepts and Brief Overview of Its ApplicationNative language experience shapes neural basis of addressed and assembled phonologies.Denoising the speaking brain: toward a robust technique for correcting artifact-contaminated fMRI data under severe motion.Temporal Non-Local Means Filtering Reveals Real-Time Whole-Brain Cortical Interactions in Resting fMRIRobust presurgical functional MRI at 7 T using response consistencyImplications of cortical balanced excitation and inhibition, functional heterogeneity, and sparseness of neuronal activity in fMRI.Merging clinical neuropsychology and functional neuroimaging to evaluate the construct validity and neural network engagement of the n-back task.An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity dataImpact of in-scanner head motion on multiple measures of functional connectivity: relevance for studies of neurodevelopment in youth.The role of contralesional dorsal premotor cortex after stroke as studied with concurrent TMS-fMRI.Resting-state fMRI: a review of methods and clinical applicationsResting state networks and consciousness: alterations of multiple resting state network connectivity in physiological, pharmacological, and pathological consciousness States.Single trial decoding of belief decision making from EEG and fMRI data using independent components features.Longitudinal changes of amygdala and default mode activation in adolescents prenatally exposed to cocaine.Resting state FMRI research in child psychiatric disorders.Automatic denoising of functional MRI data: combining independent component analysis and hierarchical fusion of classifiers.Does functional MRI detect activation in white matter? A review of emerging evidence, issues, and future directions.A correlation-based method for extracting subject-specific components and artifacts from group-fMRI data.Effective artifact removal in resting state fMRI data improves detection of DMN functional connectivity alteration in Alzheimer's disease.Optimizing preprocessing and analysis pipelines for single-subject fMRI: 2. Interactions with ICA, PCA, task contrast and inter-subject heterogeneity.Large-scale functional network overlap is a general property of brain functional organization: Reconciling inconsistent fMRI findings from general-linear-model-based analyses.Classification and Extraction of Resting State Networks Using Healthy and Epilepsy fMRI Data.Methods for cleaning the BOLD fMRI signal.Reduction of Motion Artifacts and Noise Using Independent Component Analysis in Task-Based Functional MRI for Preoperative Planning in Patients with Brain Tumor.Biomarkers, designs, and interpretations of resting-state fMRI in translational pharmacological research: A review of state-of-the-Art, challenges, and opportunities for studying brain chemistry.Visual inspection of independent components: defining a procedure for artifact removal from fMRI data.Advances and pitfalls in the analysis and interpretation of resting-state FMRI data.A comparison of statistical methods for detecting context-modulated functional connectivity in fMRIThe impact of prior risk experiences on subsequent risky decision-making: the role of the insulaThe joyful, yet balanced, amygdala: moderated responses to positive but not negative stimuli in trait happiness.Reliable intrinsic connectivity networks: test-retest evaluation using ICA and dual regression approach.Impact of automated ICA-based denoising of fMRI data in acute stroke patientsBrain mediators of the effects of noxious heat on pain.Deconvolution filtering: temporal smoothing revisited.Inhibitory motor control in response stopping and response switching.Decoding developmental differences and individual variability in response inhibition through predictive analyses across individuals.Effective connectivity among the working memory regions during preparation for and during performance of the n-back task.
P2860
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P2860
Automatic independent component labeling for artifact removal in fMRI.
description
2007 nî lūn-bûn
@nan
2007年の論文
@ja
2007年論文
@yue
2007年論文
@zh-hant
2007年論文
@zh-hk
2007年論文
@zh-mo
2007年論文
@zh-tw
2007年论文
@wuu
2007年论文
@zh
2007年论文
@zh-cn
name
Automatic independent component labeling for artifact removal in fMRI.
@ast
Automatic independent component labeling for artifact removal in fMRI.
@en
type
label
Automatic independent component labeling for artifact removal in fMRI.
@ast
Automatic independent component labeling for artifact removal in fMRI.
@en
prefLabel
Automatic independent component labeling for artifact removal in fMRI.
@ast
Automatic independent component labeling for artifact removal in fMRI.
@en
P2860
P50
P1433
P1476
Automatic independent component labeling for artifact removal in fMRI.
@en
P2093
Adam R Aron
Sabrina M Tom
P2860
P304
P356
10.1016/J.NEUROIMAGE.2007.10.013
P407
P577
2007-10-25T00:00:00Z