Sampling & Statistics
Research on optimization of statistical criteria in neuroimaging began early and through close collaboration with the late professor Keith Worsley, who introduced the Random Field Theory in neuroimaging–a pioneering approach for addressing the problem of false positives and multiple comparisons.
In the last decade, an alternative to “Talairach space” has been widely adopted in the brain mapping field, the so-called “MNI space”. This latter space has evolved through various phases.
To characterize the underlying architectures of brain networks is central to current neuroimaging research. Mathematical modeling provides generalizable definitions for the structural and functional organization of the human brain.
Population studies in neurodegenerative disease and neurodevelopment are supported by ongoing development of feature-specific and sensitive methods that help detect statistical deviations of the anatomical features from the “normal” brain.