Related Experiment Video
Updated: Jul 15, 2026

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
Published on: October 24, 2012
Tuning and comparing spatial normalization methods
Steven Robbins1, Alan C Evans, D Louis Collins
1McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, 3801 University Street, Montreal, Que., H3A 2B4, Canada.
Abstract:
Spatial normalization is a key process in cross-sectional studies of brain structure and function using MRI, fMRI, PET and other imaging techniques. A wide range of 2D surface and 3D image deformation algorithms have been developed, all of which involve design choices that are subject to debate. Moreover, most have numerical parameters whose value must be specified by the user. This paper proposes a principled method for evaluating design choices and choosing parameter values. This method can also be used to compare competing spatial normalization algorithms. We demonstrate the method through a performance analysis of a nonaffine registration algorithm for 3D images and a registration algorithm for 2D cortical surfaces.
Related Concept Videos
Instrument Calibration
Analytical Balance Calibration
An analytical balance measures mass and requires regular calibration to...
Distance Corrections
Introduction and Methods of Leveling
The Normal and Binormal Vectors
Methods of Medium Optimization

