ABSTRACT
Computer simulations of spike trains generated by brain neurons have been a useful tool to generate questions in the field of computational neuroscience. There is, however, a paucity of such methods in the study of complex behaviors, including analyses of kinematics parameters from movement trajectories embedded in natural purposeful behaviors. This chapter explores new data types and computational techniques leading to the simulation of patterns present in actual empirical data, along with synthetic patterns generated by computational models. We discuss their utility in setting normative bounds to compare modeled data with actual data obtained from individuals with the pathology of the developing nervous systems leading to a diagnosis of autism spectrum disorder (ASD).
