Sparse decomposition light-field microscopy for high speed imaging of neuronal activity
Name
optica-7-10-1457.pdf
Description
Published version
Size
3.77 MB
Format
Adobe PDF
Checksum (MD5)
8acb6655b29a12a65197e3884c264e34
Author(s)
Yoon, Young-Gyu
Wang, Zeguan
Pak, Nikita
Park, Demian
Dai, Peilun
Kang, Jeong Seuk
Suk, Ho-Jun
Symvoulidis, Panagiotis
Guner-Ataman, Burcu
Wang, Kai
Date Issued
October 2020
Journal
Optica
Publisher
The Optical Society
Citation
Yoon, Young-Gyu et al. Sparse decomposition light-field microscopy for high speed imaging of neuronal activity. "Sparse decomposition light-field microscopy for high speed imaging of neuronal activity." 7, 10 (October 2020): 1457-1468 © 2020 Optical Society of America
Version
Final published version
Abstract
One of the major challenges in large scale optical imaging of neuronal activity is to simultaneously achieve sufficient temporal and spatial resolution across a large volume. Here, we introduce sparse decomposition light-field microscopy (SDLFM), a computational imaging technique based on light-field microscopy (LFM) that takes algorithmic advantage of the high temporal resolution of LFM and the inherent temporal sparsity of spikes to improve effective spatial resolution and signal-to-noise ratios (SNRs). With increased effective spatial resolution and SNRs, neuronal activity at the single-cell level can be recovered over a large volume. We demonstrate the single-cell imaging capability of SDLFM with in vivo imaging of neuronal activity of whole brains of larval zebrafish with estimated lateral and axial resolutions of ∼3.5 µm and ∼7.4 µm, respectively, acquired at volumetric imaging rates up to 50 Hz. We also show that SDLFM increases the quality of neural imaging in adult fruit flies.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Center for Neurobiological Engineering
Massachusetts Institute of Technology. Department of Mechanical Engineering
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Massachusetts Institute of Technology. Department of Biological Engineering
McGovern Institute for Brain Research at MIT
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Koch Institute for Integrative Cancer Research at MIT
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1364/optica.392805
