Non-descanned multifocal multiphoton microscopy with a multianode photomultiplier tube
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So_Non-descanned.pdf
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Author(s)
Cha, Jae Won
Subramanian, Jaichandar
Nedivi, Elly
So, Peter T. C.
Yew, Yan Seng Elijah
Kim, Daekeun, Ph. D. Massachusetts Institute of Technology
Date Issued
March 2015
Journal
AIP Advances
Publisher
American Institute of Physics (AIP)
Citation
Cha, Jae Won, Elijah Y. S. Yew, Daekeun Kim, Jaichandar Subramanian, Elly Nedivi, and Peter T. C. So. “Non-Descanned Multifocal Multiphoton Microscopy with a Multianode Photomultiplier Tube.” AIP Advances 5, no. 8 (August 2015): 084802.
Version
Final published version
Abstract
Multifocal multiphoton microscopy (MMM) improves imaging speed over a point scanning approach by parallelizing the excitation process. Early versions of MMM relied on imaging detectors to record emission signals from multiple foci simultaneously. For many turbid biological specimens, the scattering of emission photons results in blurred images and degrades the signal-to-noise ratio (SNR). We have recently demonstrated that a multianode photomultiplier tube (MAPMT) placed in a descanned configuration can effectively collect scattered emission photons from each focus into their corresponding anodes significantly improving image SNR for highly scattering specimens. Unfortunately, a descanned MMM has a longer detection path resulting in substantial emission photon loss. Optical design constraints in a descanned geometry further results in significant optical aberrations especially for large field-of-view (FOV), high NA objectives. Here, we introduce a non-descanned MMM based on MAPMT that substantially overcomes most of these drawbacks. We show that we improve signal efficiency up to fourfold with limited image SNR degradation due to scattered emission photons. The excitation foci can also be spaced wider to cover the full FOV of the objective with minimal aberrations. The performance of this system is demonstrated by imaging interneuron morphological structures deep in the brains of living mice.
MIT Department
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Biology
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Massachusetts Institute of Technology. Department of Mechanical Engineering
Picower Institute for Learning and Memory
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DOI of Published Version
https://doi.org/10.1063/1.4916040
