Resampling fMRI time series.
The problem of selecting a threshold for the statistical parameter maps in functional MRI (fMRI) is a delicate issue. The use of advanced test statistics and/or the complex dependence structure of fMRI noise may preclude parametric statistical methods for finding appropriate thresholds. Non-parametric statistical methodology has been presented as a feasible alternative. In this paper, we discuss resampling methods for finding thresholds in single subject fMRI analysis. It is shown that the presence of a BOLD response in the time series biases the estimation of the temporal autocorrelation, which in turn leads to biased thresholds. Therefore, proposed resampling methods based on Fourier and wavelet transforms, which employ implicit and weak models of the temporal noise characteristic, may produce erroneous thresholds. In contrast, resampling based on a pre-whitening transform, which is driven by an explicit noise model, is robust to the presence of a BOLD response. The size of the bias is, however, largely dependent on the complexity of the experimental design. While blocked designs can induce large biases, event-related designs generate significantly smaller biases. Results supporting these claims are provided.
Friman
Ola
O
Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Thorn 323, 75 Francis Street, Boston, MA 02115, USA. friman@bwh.harvard.edu
Westin
Carl-Fredrik
CF
D016477:Artifacts; D015982:Bias; D001921:Brain / Q000098:blood supply*; D001931:Brain Mapping; D003625:Data Collection / Q000706:statistics & numerical data; D005583:Fourier Analysis; D006801:Humans; D007089:Image Enhancement; D007091:Image Processing, Computer-Assisted / Q000706:statistics & numerical data*; D008279:Magnetic Resonance Imaging / Q000295:instrumentation*; D010100:Oxygen / Q000097:blood*; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D013223:Statistics as Topic; D018709:Statistics, Nonparametric; D013997:Time Factors
D010100:Oxygen