We present an analytics-based framework for simultaneous visualization of large surface data collections arising in clinical neuroimaging studies. Termed Informatics Visualization for Neuroimaging (INVIZIAN), this framework allows the visualization of both cortical surfaces characteristics and feature relatedness in unison. It also uses dimension reduction methods to derive new coordinate systems using a Jensen-Shannon divergence metric for positioning cortical surfaces in a metric space such that the proximity in location is proportional to neuroanatomical similarity. Feature data such as thickness and volume are colored on the cortical surfaces and used to display both subject-specific feature values and global trends within the population. Additionally, a query-based framework allows the neuroscience researcher to investigate probable correlations between neuroanatomical and subject patient attribute values such as age and diagnosis.