title: Spatiotemporal analysis of optical imaging data.
abstract: Previous methods for analyzing optical imaging data have relied heavily on temporal averaging. However, response dynamics are rich sources of information. Here, we develop and present a method that combines principal component analysis and multitaper harmonic analysis to extract the statistically significant spatial and temporal response from optical imaging data. We apply the method to both simulated data and experimental optical imaging data from the cat primary visual cortex.
authors.affiliation: Laboratory of Applied Mathematics, Biomathematical Sciences Division, Mt Sinai School of Medicine, One Gustave L. Levy Place, New York, NY 10029, USA. ats@camelot.mssm.edu
authors.forename: A
authors.initials: A
authors.lastname: Sornborger
authors.forename: C
authors.initials: C
authors.lastname: Sailstad
authors.forename: E
authors.initials: E
authors.lastname: Kaplan
authors.forename: L
authors.initials: L
authors.lastname: Sirovich
mesh_terms: D000818:Animals; D001288:Attention / Q000502:physiology; D001931:Brain Mapping / Q000379:methods*; D002415:Cats; D003198:Computer Simulation; D004569:Electroencephalography / Q000706:statistics & numerical data*; D005074:Evoked Potentials, Visual / Q000502:physiology; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional; D008432:Mathematical Computing; D009949:Orientation / Q000502:physiology; D010364:Pattern Recognition, Visual / Q000502:physiology*; D010781:Photography / Q000706:statistics & numerical data*; D025341:Principal Component Analysis; D014793:Visual Cortex / Q000502:physiology*