ESTIMATING SMOOTHNESS IN STATISTICAL PARAMETRIC MAPS - VARIABILITY OFP-VALUES

Objective: The smoothness parameter that characterises the spatial dep endence of pixel values in functional brain images is usually estimate d empirically from the data. Since this parameter is essential for the assessment of significant changes in brain activity, it is important to know (a) the variance of its estimator and (b) how this variability affects the results of the ensuing statistical analysis. Materials an d Methods: In this article, we derive an approximate expression for th e variance of the smoothness estimator and investigate the effects of this variability on assessing the significance of cerebral activation in statistical parametric maps using a verbal fluency PET activation e xperiment. Results: Our results suggest that, for p values around 0.05 , the variability in the p value (due to smoothness estimation) is sim ilar to 20%. Conclusion: The effect of the assessment of the spatial d ependency of the data is far from being negligible, and this suggests a more comprehensive methodology for functional imaging than the one u sed so far. This work provides a simple tool for taking into account t his effect.