An Optimized Clustering Technique for Functional Parcellation of Hippocampus

Arabinda Mishra¹, James C. Gatenby¹, Allen T. Newton¹, John C. Gore¹, Baxter P. Rogers¹

Functional sub-divisions of important anatomic regions in the human brain are normally done based on disparities in structural connectivity patterns or functional connectivity maps. However, quantification of functional heterogeneity, and determining the appropriate number of sub-regions, has rarely been a focus of study. This work evaluates the use of self organized maps (SOM) to classify the functionally different regions in the hippocampus, which exhibits functional and sometimes anatomical differences in patients with disorders such as schizophrenia and bipolar disorder etc. Using voxel based connectivity maps we successfully parcellated left hippocampus and found performance of SOM to be superior in comparison to kmeans clustering.