Source abstract
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.
Source: crossref · Quality: baseline
Affiliations
Massachusetts Institute of Technology 1 Department of Mechanical Engineering, , Cambridge, MA, USA
Dankook University 2 Department of Mechanical Engineering, , Korea
Massachusetts Institute of Technology 3 Picower Institute for Learning and Memory, , Cambridge, MA, USA
Massachusetts Institute of Technology 4 Departments of Brain and Cognitive Sciences, and Biology, , Cambridge, MA, USA
Massachusetts Institute of Technology 5 Department of Biological Engineering, , Cambridge, MA, USA
Funding
Hamamatsu Corp. · Koch Institute for Integrative Cancer Research Bridge Project Initiative · MIT SkolTech Initiative · Singapore MIT Alliance 2 · National Science Foundation · National Institutes of Health