Semiparametric detection of significant activation for brain fMRI

DOI10.1214/07-AOS519zbMath1142.62026arXiv0808.0989OpenAlexW3102001600MaRDI QIDQ939660

Chunming Zhang, Tao Yu

Publication date: 28 August 2008

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0808.0989

zbMATH Keywords

local polynomial regressiondeconvolutionspatio-temporal datastimulitime resolution

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Computational methods for sparse matrices (65F50) Parametric inference under constraints (62F30) Biomedical imaging and signal processing (92C55)

Related Items (10)

On optimal fMRI designs for correlated errors ⋮ Optimal and efficient designs for functional brain imaging experiments ⋮ Bootstrap consistency for general semiparametric \(M\)-estimation ⋮ On the optimality of extended maximal length linear feedback shift register sequences ⋮ Semi-parametric inference for large-scale data with temporally dependent noise ⋮ Multiple testing via \(\mathrm{FDR}_L\) for large-scale imaging data ⋮ Assessing mean and median filters in multiple testing for large-scale imaging data ⋮ False discovery rates for large-scale model checking under certain dependence ⋮ Statistical inference of minimum BD estimators and classifiers for varying-dimensional models ⋮ Functional convolution models

Uses Software

• AFNI
• FSL
• FMRISTAT

Cites Work

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• Mathematical Statistics
• Calibrating the Degrees of Freedom for Automatic Data Smoothing and Effective Curve Checking
• A Direct Approach to False Discovery Rates
• Statistical Issues in fMRI for Brain Imaging

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