Abstract:
:The problem of evaluating an averaged functional magnetic resonance imaging (fMRI) response for repeated block design experiments was considered within a semiparametric regression model with autocorrelated residuals. We applied functional data analysis (FDA) techniques that use a least-squares fitting of B-spline expansions with Tikhonov regularization. To deal with the noise autocorrelation, we proposed a regularization parameter selection method based on the idea of combining temporal smoothing with residual whitening. A criterion based on a generalized chi(2)-test of the residuals for white noise was compared with a generalized cross-validation scheme. We evaluated and compared the performance of the two criteria, based on their effect on the quality of the fMRI response. We found that the regularization parameter can be tuned to improve the noise autocorrelation structure, but the whitening criterion provides too much smoothing when compared with the cross-validation criterion. The ultimate goal of the proposed smoothing techniques is to facilitate the extraction of temporal features in the hemodynamic response for further analysis. In particular, these FDA methods allow us to compute derivatives and integrals of the fMRI signal so that fMRI data may be correlated with behavioral and physiological models. For example, positive and negative hemodynamic responses may be easily and robustly identified on the basis of the first derivative at an early time point in the response. Ultimately, these methods allow us to verify previously reported correlations between the hemodynamic response and the behavioral measures of accuracy and reaction time, showing the potential to recover new information from fMRI data.
journal_name
Stat Medjournal_title
Statistics in medicineauthors
Vakorin VA,Borowsky R,Sarty GEdoi
10.1002/sim.2981subject
Has Abstractpub_date
2007-09-20 00:00:00pages
3830-44issue
21eissn
0277-6715issn
1097-0258journal_volume
26pub_type
杂志文章abstract::Quality of life (QOL) assessment is a key component of many clinical studies and frequently requires the use of single global summary measures that capture the overall balance of findings from a potentially wide-ranging assessment of QOL issues. We propose and evaluate an irregular multilevel latent variable model sui...
journal_title:Statistics in medicine
pub_type: 杂志文章
doi:10.1002/sim.4455
更新日期:2012-05-20 00:00:00
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pub_type: 杂志文章
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journal_title:Statistics in medicine
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journal_title:Statistics in medicine
pub_type: 临床试验,杂志文章,随机对照试验
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pub_type: 传,历史文章,杂志文章
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pub_type: 杂志文章
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更新日期:2004-02-28 00:00:00
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journal_title:Statistics in medicine
pub_type: 杂志文章
doi:10.1002/sim.5741
更新日期:2013-07-20 00:00:00
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journal_title:Statistics in medicine
pub_type: 杂志文章
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journal_title:Statistics in medicine
pub_type: 杂志文章
doi:10.1002/sim.3520
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pub_type: 杂志文章
doi:10.1002/sim.3175
更新日期:2008-06-15 00:00:00
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pub_type: 杂志文章
doi:10.1002/sim.2399
更新日期:2005-12-30 00:00:00
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pub_type: 杂志文章
doi:10.1002/sim.4780101209
更新日期:1991-12-01 00:00:00
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journal_title:Statistics in medicine
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更新日期:2007-06-15 00:00:00
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pub_type: 杂志文章
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更新日期:2018-06-15 00:00:00
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journal_title:Statistics in medicine
pub_type: 杂志文章
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更新日期:1999-08-15 00:00:00
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journal_title:Statistics in medicine
pub_type: 杂志文章
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更新日期:1996-01-30 00:00:00
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journal_title:Statistics in medicine
pub_type: 杂志文章
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更新日期:2013-06-15 00:00:00
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