High-speed, multi-Z confocal microscopy for voltage imaging in densely labeled neuronal populations

Weber, T.; Moya, Maria V.; Mertz, Jérôme; Economo, Michael N.

doi:10.1101/2021.12.10.472140

Cited by 9 publications

(9 citation statements)

References 26 publications

(31 reference statements)

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“…In recent years, there has been a push to develop microscopes capable of imaging populations of cells within extended volumes at high spatiotemporal resolution. One such microscope is based on confocal imaging with multiple axially distributed pinholes, enabling simultaneous multiplane imaging 48 , 49 . However, in its most simple implementation, multi-z confocal microscopy is based on low NA illumination and provides only limited spatial resolution, roughly 2.6 μm lateral and 15 μm axial.…”

Section: Resultsmentioning

confidence: 99%

Resolution enhancement with deblurring by pixel reassignment

Zhao,

Mertz

2023

Adv. Photon.

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Improving the spatial resolution of a fluorescence microscope has been an ongoing challenge in the imaging community. To address this challenge, a variety of approaches have been taken, ranging from instrumentation development to image postprocessing. An example of the latter is deconvolution, where images are numerically deblurred based on a knowledge of the microscope point spread function. However, deconvolution can easily lead to noise-amplification artifacts. Deblurring by postprocessing can also lead to negativities or fail to conserve local linearity between sample and image. We describe here a simple image deblurring algorithm based on pixel reassignment that inherently avoids such artifacts and can be applied to general microscope modalities and fluorophore types. Our algorithm helps distinguish nearby fluorophores, even when these are separated by distances smaller than the conventional resolution limit, helping facilitate, for example, the application of single-molecule localization microscopy in dense samples. We demonstrate the versatility and performance of our algorithm under a variety of imaging conditions.

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Section: Resultsmentioning

confidence: 99%

Resolution enhancement with deblurring by pixel reassignment

Zhao,

Mertz

2023

Adv. Photon.

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“…One such microscope is based on confocal imaging with multiple axially distributed pinholes, enabling simultaneous multiplane imaging. 48, 49 However, in its most simple implementation, multi-z confocal microscopy is based on low-NA illumination and provides only limited spatial resolution, roughly 2.6 µ m lateral and 15 µ m axial. While such resolution is adequate for distinguishing neuronal somata in animals like mice and zebrafish, it is inadequate for distinguishing, for example, nearby dendritic processes.…”

Section: Resultsmentioning

confidence: 99%

Resolution enhancement with deblurring by pixel reassignment (DPR)

Zhao¹,

Mertz²

2023

Preprint

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Improving the spatial resolution of a fluorescence microscope has been an ongoing challenge in the imaging community. To address this challenge, a variety of approaches have been taken, ranging from instrumentation development to image post-processing. An example of the latter is deconvolution, where images are numerically deblurred based on a knowledge of the microscope point spread function. However, deconvolution can easily lead to noise-amplification artifacts. Deblurring by post-processing can also lead to negativities or fail to conserve local linearity between sample and image. We describe here a simple image deblurring algorithm based on pixel reassignment that inherently avoids such artifacts and can be applied to general microscope modalities and fluorophore types. Our algorithm helps distinguish nearby fluorophores even when these are separated by distances smaller than the conventional resolution limit, helping facilitate, for example, the application of single-molecule localization microscopy in dense samples. We demonstrate the versatility and performance of our algorithm under a variety of imaging conditions.

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“…Random access scanning [15] and multiplane confocal scanning [16] have recently attempted to expand voltage imaging to 3D volumes but remain limited by either the number of cells that can be recorded in parallel or the accessible volume owing to the limitations of point scanning approaches. Here we developed FLIPR, a technique that combines a light efficient optical design for remote focusing with the advantages of high speed camera based readouts to potentially measure hundreds of neurons from large volumes.…”

Section: Discussionmentioning

confidence: 99%

Fast and light efficient remote focusing for volumetric voltage imaging

Böhm,

Judkewitz

2023

Preprint

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Voltage imaging holds great potential for biomedical research by enabling noninvasive recording of the electrical activity of excitable cells such as neurons or cardiomyocytes. Camera-based detection can record from hundreds of cells in parallel, but imaging entire volumes is limited by the need to focus through the sample at high speeds. Remote focusing techniques can remedy this drawback, but have so far been either too slow or light inefficient. Here, we introduce FLIPR, a new approach for remote focusing that doubles the light efficiency and enables high-speed volumetric voltage imaging at 500 volumes/s. We show the potential of our approach by combining it with lightsheet imaging in the zebrafish spinal cord to record from >100 spontaneously active neurons in parallel.

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High-speed, multi-Z confocal microscopy for voltage imaging in densely labeled neuronal populations

Cited by 9 publications

References 26 publications

Resolution enhancement with deblurring by pixel reassignment

Resolution enhancement with deblurring by pixel reassignment

Resolution enhancement with deblurring by pixel reassignment (DPR)

Fast and light efficient remote focusing for volumetric voltage imaging

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