Effect of Data Normalization on the Creation of Neuro-Probabilistic Atlases

In the past 15 years, rapid improvements in imaging technology and methodology have had a tremendous impact on how we study the human brain. During deep brain stimulation surgeries, detailed anatomical images can be combined with physiological data obtained by microelectrode recordings and microstimulations to address questions relating to the location of specific motor or sensorial functions. The main advantage of techniques such as microelectrode recordings and microstimulations over brain imaging is their ability to localize patient physiological activity with a high degree of spatial resolution. Aggregating data acquired from large populations permits to build what are commonly referred to as statistical atlases. Data points from statistical atlases can be combined to produce probabilistic maps. A crucial step in this process is the intersubject spatial normalization that is required to relate a position in one subject's brain to a position in another subject's brain. In this paper, we study the impact of spatial normalization techniques on building statistical atlases. We find that the Talairach or anterior-posterior commissure coordinate system commonly used in the medical literature produces atlases that are more dispersed than those obtained with normalization methods that rely on nonlinear volumetric image registration. We also find that the maps produced using nonlinear techniques correlate with their expected anatomic positions.