Sun, 06 Jul 2008 02:49:33 BST CiteULike: svbcrypto's statistics http://www.citeulike.org/user/svbcrypto/tag/statistics CiteULike.org en-gb Copyright © 2004-2008 citeulike.org http://www.citeulike.org/user/svbcrypto/article/707484 <i>NeuroImage, Vol. 9, No. 3. (March 1999), pp. 311-329.</i><br /><br />The complicated structure of fMRI signals and associated noise sources make it difficult to assess the validity of various steps involved in the statistical analysis of brain activation. Most methods used for fMRI analysis assume that observations are independent and that the noise can be treated as white gaussian noise. These assumptions are usually not true but it is difficult to assess how severely these assumptions are violated and what are their practical consequences. In this study a direct comparison is made between the power of various analytical methods used to detect activations, without reference to estimates of statistical significance. The statistics used in fMRI are treated as metrics designed to detect activations and are not interpreted probabilistically. The receiver operator characteristic (ROC) method is used to compare the efficacy of various steps in calculating an activation map in the study of a single subject based on optimizing the ratio of the number of detected activations to the number of false-positive findings. The main findings are as follows:Preprocessing.The removal of intensity drifts and high-pass filtering applied on the voxel time-course level is beneficial to the efficacy of analysis. Temporal normalization of the global image intensity, smoothing in the temporal domain, and low-pass filtering do not improve power of analysis.Choices of statistics.the cross-correlation coefficient andt-statistic, as well as nonparametric Mann-Whitney statistics, prove to be the most effective and are similar in performance, by our criterion.Task design.the proper design of task protocols is shown to be crucial. In an alternating block design the optimal block length is be approximately 18 s.Spatial clustering.an initial spatial smoothing of images is more efficient than cluster filtering of the statistical parametric activation maps. ROC Analysis of Statistical Methods Used in Functional MRI: Individual Subjects Pawel Skudlarski Todd Constable John Gore doi:10.1006/nimg.1999.0402 NeuroImage, Vol. 9, No. 3. (March 1999), pp. 311-329. 2006-06-22T15:41:16-00:00 1999 NeuroImage 9 3 311 329 fmri methods statistics http://www.citeulike.org/user/svbcrypto/article/890123 <i>J Neurosci Methods, Vol. 118, No. 2. (30 August 2002), pp. 115-128.</i><br /><br />Estimation of statistical power in functional MRI (fMRI) requires knowledge of the expected percent signal change between two conditions as well as estimates of the variability in percent signal change. Variability can be divided into intra-subject variability, reflecting noise within the time series, and inter-subject variability, reflecting subject-to-subject differences in activation. The purpose of this study was to obtain estimates of percent signal change and the two sources of variability from fMRI data, and then use these parameter estimates in simulation experiments in order to generate power curves. Of interest from these simulations were conclusions concerning how many subjects are needed and how many time points within a scan are optimal in an fMRI study of cognitive function. Intra-subject variability was estimated from resting conditions, and inter-subject variability and percent signal change were estimated from verbal working memory data. Simulations derived from these parameters illustrate how percent signal change, intra- and inter-subject variability, and number of time points affect power. An empirical test experiment, using fMRI data acquired during somatosensory stimulation, showed good correspondence between the simulation-based power predictions and the power observed within somatosensory regions of interest. Our analyses suggested that for a liberal threshold of 0.05, about 12 subjects were required to achieve 80% power at the single voxel level for typical activations. At more realistic thresholds, that approach those used after correcting for multiple comparisons, the number of subjects doubled to maintain this level of power. Estimating sample size in functional MRI (fMRI) neuroimaging studies: statistical power analyses. JE Desmond GH Glover J Neurosci Methods, Vol. 118, No. 2. (30 August 2002), pp. 115-128. 2006-10-09T13:33:03-00:00 2002 J Neurosci Methods 0165-0270 118 2 115 128 fmri statistics