A Statistical Model for Multiphoton Calcium Imaging of the Brain
Author(s)
Brown, Emery N.; Sur, Mriganka; Schummers, James; Malik, Wasim Qamar
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Multiphoton calcium fluorescence imaging has gained prominence as a valuable tool for the study of brain cells, but the corresponding analytical regimes remain rather naive. In this paper, we develop a statistical framework that facilitates principled quantitative analysis of multiphoton images. The proposed methods discriminate the stimulus-evoked response of a neuron from the background firing and image artifacts. We develop a harmonic regression model with colored noise, and estimate the model parameters with computationally efficient algorithms. We apply this model to in vivo characterization of cells from the ferret visual cortex. The results demonstrate substantially improved tuning curve fitting and image contrast.
Date issued
2009-11Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences; Picower Institute for Learning and MemoryJournal
Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009. EMBC 2009.
Publisher
Institute of Electrical and Electronics Engineers
Citation
Malik, W.Q. et al. “A statistical model for multiphoton calcium imaging of the brain.” Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE. 2009. 7002-7005. © 2009 IEEE
Version: Final published version
ISBN
978-1-4244-3296-7
ISSN
1557-170X