Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain

Advances in functional and structural MR image analysis and implementation as FSL.

Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268

https://www.fil.ion.ucl.ac.uk/~karl/Voxel-Based%20Morphometry.pdf

Voxel-Based Morphometry—The Methods

https://www.sfs.uni-tuebingen.de/~hbaayen/publications/baayenDavidsonBates.pdf

Mixed-effects modeling with crossed random effects for subjects and items

1MRC Cyclotron Unit, Hammersmith Hospital, Correspondence to: Dr M. Samuel, MRC Cyclotron Unit, 2The Wellcome Department of Cognitive Neurology, Hammersmith Hospital, Du Cane Road, London 3Institute of Neurology, London, UK, 4Neurologische Klinik W12 0NN, UK der Technischen Universitat, Munchen, Germany, 5Centro de Neurologia y Neurocirguia Functional, Clinica Quiron, San Sebastian, Spain, 6Department of Neurology, Emory University, Atlanta, USA

Pallidotomy in Parkinson's disease increases supplementary motor area and prefrontal activation during performance of volitional movements

OBJECTIVE The smoothness parameter that characterises the spatial dependence of pixel values in functional brain images is usually estimated 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 AND METHODS In this article, we derive an approximate expression for the 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 experiment. RESULTS Our results suggest that, for p values around 0.05, the variability in the p value (due to smoothness estimation) is approximately 20%. CONCLUSION The effect of the assessment of the spatial dependency of the data is far from being negligible, and this suggests a more comprehensive methodology for functional imaging than the one used so far. This work provides a simple tool for taking into account this effect.

Andrew P. Holmes

Papers

Pallidotomy in Parkinson's disease increases supplementary motor area and prefrontal activation during performance of volitional movements

Estimating smoothness in statistical parametric maps: variability of p values.

Reproducibility of PET Activation Studies: Lessons from a Multi-Center European Experiment: EU Concerted Action on Functional Imaging

Thalamic stimulation for parkinsonian tremor: correlation between regional cerebral blood flow and physiological tremor characteristics.

Statistical issues in functional brain mapping.