Null models for spatial autocorrelation

COEX 

Imaging technologies are increasingly used to generate high-resolution maps of brain structure and function. Comparing these brain maps with one another is becoming a popular analysis in neuroscience and facilitates cross-disciplinary scientific discovery. Methods to construct null models that account for spatial autocorrelation - an inherent and fundamental property of the brain - have recently been developed and are quickly being adopted by researchers. In this educational workshop I will present multiple spatial autocorrelation-preserving null models, from spatial permutation tests (“spin test”) to parametrized data models. This workshop will cover the theory underlying these models, including when to use them, why to use them, and their limitations (lecture style), as well as how to generate these nulls in an analysis (hands-on coding demonstration).