Literature DB >> 14630228

Independent component analysis of functional MRI: what is signal and what is noise?

Martin J McKeown1, Lars Kai Hansen, Terrence J Sejnowsk.   

Abstract

Many sources of fluctuation contribute to the functional magnetic resonance imaging (fMRI) signal, complicating attempts to infer those changes that are truly related to brain activation. Unlike methods of analysis of fMRI data that test the time course of each voxel against a hypothesized waveform, data-driven methods, such as independent component analysis and clustering, attempt to find common features within the data. This exploratory approach can be revealing when the brain activation is difficult to predict beforehand, such as with complex stimuli and internal shifts of activation that are not time-locked to an easily specified sensory or motor event. These methods can be further improved by incorporating prior knowledge regarding the temporal and spatial extent of brain activation.

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Year:  2003        PMID： 14630228      PMCID： PMC2925426          DOI： 10.1016/j.conb.2003.09.012

Source DB:  PubMed          Journal:  Curr Opin Neurobiol        ISSN： 0959-4388            Impact factor:   6.627


  61 in total

1.  Improved detection of time windows of brain responses in fMRI using modified temporal clustering analysis.

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2.  Improved optimization for the robust and accurate linear registration and motion correction of brain images.

Authors:  Mark Jenkinson; Peter Bannister; Michael Brady; Stephen Smith
Journal:  Neuroimage       Date:  2002-10       Impact factor: 6.556

3.  The evaluation of preprocessing choices in single-subject BOLD fMRI using NPAIRS performance metrics.

Authors:  Stephen LaConte; Jon Anderson; Suraj Muley; James Ashe; Sally Frutiger; Kelly Rehm; Lars Kai Hansen; Essa Yacoub; Xiaoping Hu; David Rottenberg; Stephen Strother
Journal:  Neuroimage       Date:  2003-01       Impact factor: 6.556

4.  Deterministic and stochastic features of fMRI data: implications for analysis of event-related experiments.

Authors:  Martin J McKeown; Vijay Varadarajan; Scott Huettel; Gregory McCarthy
Journal:  J Neurosci Methods       Date:  2002-08-30       Impact factor: 2.390

5.  Spatiotemporal pattern of neural processing in the human auditory cortex.

Authors:  Erich Seifritz; Fabrizio Esposito; Franciszek Hennel; Henrietta Mustovic; John G Neuhoff; Deniz Bilecen; Gioacchino Tedeschi; Klaus Scheffler; Francesco Di Salle
Journal:  Science       Date:  2002-09-06       Impact factor: 47.728

6.  Analysis of fMRI data by blind separation into independent spatial components.

Authors:  M J McKeown; S Makeig; G G Brown; T P Jung; S S Kindermann; A J Bell; T J Sejnowski
Journal:  Hum Brain Mapp       Date:  1998       Impact factor: 5.038

7.  Fuzzy clustering of gradient-echo functional MRI in the human visual cortex. Part II: quantification.

Authors:  E Moser; M Diemling; R Baumgartner
Journal:  J Magn Reson Imaging       Date:  1997 Nov-Dec       Impact factor: 4.813

8.  Empirical analyses of BOLD fMRI statistics. I. Spatially unsmoothed data collected under null-hypothesis conditions.

Authors:  E Zarahn; G K Aguirre; M D'Esposito
Journal:  Neuroimage       Date:  1997-04       Impact factor: 6.556

9.  An information-maximization approach to blind separation and blind deconvolution.

Authors:  A J Bell; T J Sejnowski
Journal:  Neural Comput       Date:  1995-11       Impact factor: 2.026

Review 10.  Searching for a baseline: functional imaging and the resting human brain.

Authors:  D A Gusnard; M E Raichle; M E Raichle
Journal:  Nat Rev Neurosci       Date:  2001-10       Impact factor: 34.870
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  113 in total

1.  A novel group ICA approach based on multi-scale individual component clustering. Application to a large sample of fMRI data.

Authors:  Mikaël Naveau; Gaëlle Doucet; Nicolas Delcroix; Laurent Petit; Laure Zago; Fabrice Crivello; Gaël Jobard; Emmanuel Mellet; Nathalie Tzourio-Mazoyer; Bernard Mazoyer; Marc Joliot
Journal:  Neuroinformatics       Date:  2012-07

2.  Group ICA of resting-state data: a comparison.

Authors:  Veronika Schöpf; Christian Windischberger; Christian H Kasess; Rupert Lanzenberger; Ewald Moser
Journal:  MAGMA       Date:  2010-06-03       Impact factor: 2.310

Review 3.  The chronoarchitecture of the cerebral cortex.

Authors:  Andreas Bartels; Semir Zeki
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2005-04-29       Impact factor: 6.237

4.  Functional neural circuits for mental timekeeping.

Authors:  Michael C Stevens; Kent A Kiehl; Godfrey Pearlson; Vince D Calhoun
Journal:  Hum Brain Mapp       Date:  2007-05       Impact factor: 5.038

5.  Detecting functional nodes in large-scale cortical networks with functional magnetic resonance imaging: a principal component analysis of the human visual system.

Authors:  Christine Ecker; Emanuelle Reynaud; Steven C Williams; Michael J Brammer
Journal:  Hum Brain Mapp       Date:  2007-09       Impact factor: 5.038

6.  Automatic independent component labeling for artifact removal in fMRI.

Authors:  Jussi Tohka; Karin Foerde; Adam R Aron; Sabrina M Tom; Arthur W Toga; Russell A Poldrack
Journal:  Neuroimage       Date:  2007-10-25       Impact factor: 6.556

7.  Visual target modulation of functional connectivity networks revealed by self-organizing group ICA.

Authors:  Vincent van de Ven; Christoph Bledowski; David Prvulovic; Rainer Goebel; Elia Formisano; Francesco Di Salle; David E J Linden; Fabrizio Esposito
Journal:  Hum Brain Mapp       Date:  2008-12       Impact factor: 5.038

8.  Ultra-Slow Single-Vessel BOLD and CBV-Based fMRI Spatiotemporal Dynamics and Their Correlation with Neuronal Intracellular Calcium Signals.

Authors:  Yi He; Maosen Wang; Xuming Chen; Rolf Pohmann; Jonathan R Polimeni; Klaus Scheffler; Bruce R Rosen; David Kleinfeld; Xin Yu
Journal:  Neuron       Date:  2018-02-21       Impact factor: 17.173

9.  Independent Component Analysis Involving Autocorrelated Sources With an Application to Functional Magnetic Resonance Imaging.

Authors:  Seonjoo Lee; Haipeng Shen; Young Truong; Mechelle Lewis; Xuemei Huang
Journal:  J Am Stat Assoc       Date:  2012-01-24       Impact factor: 5.033

10.  Method for multimodal analysis of independent source differences in schizophrenia: combining gray matter structural and auditory oddball functional data.

Authors:  V D Calhoun; T Adali; N R Giuliani; J J Pekar; K A Kiehl; G D Pearlson
Journal:  Hum Brain Mapp       Date:  2006-01       Impact factor: 5.038
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