A statistical model for multiphoton calcium imaging of the brain
Name
Brown-A Statistical Model for Multiphoton.pdf
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534.22 KB
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Author(s)
Malik, Wasim Qamar
Schummers, James
Sur, Mriganka
Brown, Emery Neal
Date Issued
November 2009
Journal
Proceedings of the 31st 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.” in Proceedings of the 31st Annual International Conference of the IEEE EMBS
Minneapolis, Minnesota, USA, September 2-6, 2009. 7002–7005.
Version
Author's final manuscript
Abstract
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.
MIT Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Picower Institute for Learning and Memory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike 3.0
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DOI of Published Version
https://doi.org/10.1109/IEMBS.2009.5333848
