Spatiotemporal analysis of optical imaging data

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 si...

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Bibliographic Details
Published in:NeuroImage (Orlando, Fla.) Fla.), 2003-03, Vol.18 (3), p.610-621
Main Authors: Sornborger, A., Sailstad, C., Kaplan, E., Sirovich, L.
Format: Article
Language:English
Subjects:
Animals
Attention - physiology
Brain Mapping - methods
Cats
Computer Simulation
Economic models
Electroencephalography - statistics & numerical data
Evoked Potentials, Visual - physiology
Experiments
Harmonic analysis
Image Interpretation, Computer-Assisted - methods
Imaging, Three-Dimensional
Mathematical Computing
Methods
Noise
Orientation - physiology
Pattern Recognition, Visual - physiology
Photography - statistics & numerical data
Principal Component Analysis
Principal components analysis
Time series
Visual Cortex - physiology
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Summary: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.
ISSN:1053-8119
1095-9572
DOI:10.1016/S1053-8119(02)00045-9