Before revision:  Here we describe an automated approach for analyzing large ( GB/subject) datasets of simultaneously recorded human electrocorticography (ECoG) and naturalistic behavior video data  for 12 subjects .
After revision:  Here we describe an automated approach for analyzing large ( GB/subject) datasets of simultaneously recorded human electrocorticography (ECoG) and naturalistic behavior video data . We take a behavior-first approach to analyzing the long-term recordings. Using a combination of computer vision, discrete latent-variable modeling, and string pattern-matching on the behavioral video data, we find and annotate spontaneous human upper-limb movement events. We show results from our approach applied to data collected for 12 subjects .