Literature DB >> 19172652

Activated region fitting: a robust high-power method for fMRI analysis using parameterized regions of activation.

Wouter D Weeda1, Lourens J Waldorp, Ingrid Christoffels, Hilde M Huizenga.   

Abstract

An important issue in the analysis of fMRI is how to account for the spatial smoothness of activated regions. In this article a method is proposed to accomplish this by modeling activated regions with Gaussian shapes. Hypothesis tests on the location, spatial extent, and amplitude of these regions are performed instead of hypothesis tests of individual voxels. This increases power and eases interpretation. Simulation studies show robust hypothesis tests under misspecification of the shape model, and increased power over standard techniques especially at low signal-to-noise ratios. An application to real single-subject data also indicates that the method has increased power over standard methods. (c) 2009 Wiley-Liss, Inc.

Mesh:

Year:  2009        PMID: 19172652      PMCID: PMC6870927          DOI: 10.1002/hbm.20697

Source DB:  PubMed          Journal:  Hum Brain Mapp        ISSN: 1065-9471            Impact factor:   5.038


  21 in total

1.  Anatomically informed basis functions.

Authors:  S J Kiebel; R Goebel; K J Friston
Journal:  Neuroimage       Date:  2000-06       Impact factor: 6.556

2.  Spatial mixture modeling of fMRI data.

Authors:  N V Hartvig; J L Jensen
Journal:  Hum Brain Mapp       Date:  2000-12       Impact factor: 5.038

3.  Thresholding of statistical maps in functional neuroimaging using the false discovery rate.

Authors:  Christopher R Genovese; Nicole A Lazar; Thomas Nichols
Journal:  Neuroimage       Date:  2002-04       Impact factor: 6.556

4.  Mixtures of general linear models for functional neuroimaging.

Authors:  Will Penny; Karl Friston
Journal:  IEEE Trans Med Imaging       Date:  2003-04       Impact factor: 10.048

Review 5.  Controlling the familywise error rate in functional neuroimaging: a comparative review.

Authors:  Thomas Nichols; Satoru Hayasaka
Journal:  Stat Methods Med Res       Date:  2003-10       Impact factor: 3.021

6.  Dealing with the shortcomings of spatial normalization: multi-subject parcellation of fMRI datasets.

Authors:  Bertrand Thirion; Guillaume Flandin; Philippe Pinel; Alexis Roche; Philippe Ciuciu; Jean-Baptiste Poline
Journal:  Hum Brain Mapp       Date:  2006-08       Impact factor: 5.038

7.  The parcellation of cortical areas using replicator dynamics in fMRI.

Authors:  Jane Neumann; D Yves von Cramon; Birte U Forstmann; Stefan Zysset; Gabriele Lohmann
Journal:  Neuroimage       Date:  2006-04-27       Impact factor: 6.556

8.  Neural correlates of verbal feedback processing: an fMRI study employing overt speech.

Authors:  Ingrid K Christoffels; Elia Formisano; Niels O Schiller
Journal:  Hum Brain Mapp       Date:  2007-09       Impact factor: 5.038

9.  Bayesian kernel methods for analysis of functional neuroimages.

Authors:  Ana S Lukic; Miles N Wernick; Dimitris G Tzikas; Xu Chen; Aristidis Likas; Nikolas P Galatsanos; Yongyi Yang; Fuqiang Zhao; Stephen C Strother
Journal:  IEEE Trans Med Imaging       Date:  2007-12       Impact factor: 10.048

10.  Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference.

Authors:  Stephen M Smith; Thomas E Nichols
Journal:  Neuroimage       Date:  2008-04-11       Impact factor: 6.556

View more
  4 in total

1.  Characterizing cross-subject spatial interaction patterns in functional magnetic resonance imaging studies: A two-stage point-process model.

Authors:  Adél Lee; Aila Särkkä; Tara M Madhyastha; Thomas J Grabowski
Journal:  Biom J       Date:  2017-07-12       Impact factor: 2.207

2.  Robust and unbiased variance of GLM coefficients for misspecified autocorrelation and hemodynamic response models in fMRI.

Authors:  Lourens Waldorp
Journal:  Int J Biomed Imaging       Date:  2009-09-06

3.  Optimizing the performance of local canonical correlation analysis in fMRI using spatial constraints.

Authors:  Dietmar Cordes; Mingwu Jin; Tim Curran; Rajesh Nandy
Journal:  Hum Brain Mapp       Date:  2011-08-30       Impact factor: 5.038

4.  3D spatially-adaptive canonical correlation analysis: Local and global methods.

Authors:  Zhengshi Yang; Xiaowei Zhuang; Karthik Sreenivasan; Virendra Mishra; Tim Curran; Richard Byrd; Rajesh Nandy; Dietmar Cordes
Journal:  Neuroimage       Date:  2017-12-14       Impact factor: 6.556

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.