Visualizing differences in movies of cortical activity

This paper discusses techniques for visualizing structure in video data and other data sets that represent time snapshots of physical phenomena. Individual frames of a movie are treated as vectors and projected onto a low-dimensional subspace spanned by principal components. Movies can be compared and their differences visualized by analyzing the nature of the subspace and the projections of multiple movies onto the same subspace. The approach is demonstrated on an application in neurobiology in which the electrical response of a visual cortex to optical stimulation is imaged onto a high-speed photodiode array to produce a cortical movie. Techniques for sampling movies over a single trial and multiple trials are discussed. The approach provides the traditional benefits of principal component analysis (compression, noise reduction and classification) and also allows the visual separation of spatial and temporal behavior.