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Computer Generated Holography with Intensity-Graded Patterns

Computer Generated Holography achieves patterned illumination at the sample plane through phase modulation of the laser beam at the objective back aperture. This is obtained by using liquid crystal-based spatial light modulators (LC-SLMs), which modulate the spatial phase of the incident laser beam....

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Autores principales: Conti, Rossella, Assayag, Osnath, de Sars, Vincent, Guillon, Marc, Emiliani, Valentina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5065964/
https://www.ncbi.nlm.nih.gov/pubmed/27799896
http://dx.doi.org/10.3389/fncel.2016.00236
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author Conti, Rossella
Assayag, Osnath
de Sars, Vincent
Guillon, Marc
Emiliani, Valentina
author_facet Conti, Rossella
Assayag, Osnath
de Sars, Vincent
Guillon, Marc
Emiliani, Valentina
author_sort Conti, Rossella
collection PubMed
description Computer Generated Holography achieves patterned illumination at the sample plane through phase modulation of the laser beam at the objective back aperture. This is obtained by using liquid crystal-based spatial light modulators (LC-SLMs), which modulate the spatial phase of the incident laser beam. A variety of algorithms is employed to calculate the phase modulation masks addressed to the LC-SLM. These algorithms range from simple gratings-and-lenses to generate multiple diffraction-limited spots, to iterative Fourier-transform algorithms capable of generating arbitrary illumination shapes perfectly tailored on the base of the target contour. Applications for holographic light patterning include multi-trap optical tweezers, patterned voltage imaging and optical control of neuronal excitation using uncaging or optogenetics. These past implementations of computer generated holography used binary input profile to generate binary light distribution at the sample plane. Here we demonstrate that using graded input sources, enables generating intensity graded light patterns and extend the range of application of holographic light illumination. At first, we use intensity-graded holograms to compensate for LC-SLM position dependent diffraction efficiency or sample fluorescence inhomogeneity. Finally we show that intensity-graded holography can be used to equalize photo evoked currents from cells expressing different levels of chanelrhodopsin2 (ChR2), one of the most commonly used optogenetics light gated channels, taking into account the non-linear dependence of channel opening on incident light.
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spelling pubmed-50659642016-10-31 Computer Generated Holography with Intensity-Graded Patterns Conti, Rossella Assayag, Osnath de Sars, Vincent Guillon, Marc Emiliani, Valentina Front Cell Neurosci Neuroscience Computer Generated Holography achieves patterned illumination at the sample plane through phase modulation of the laser beam at the objective back aperture. This is obtained by using liquid crystal-based spatial light modulators (LC-SLMs), which modulate the spatial phase of the incident laser beam. A variety of algorithms is employed to calculate the phase modulation masks addressed to the LC-SLM. These algorithms range from simple gratings-and-lenses to generate multiple diffraction-limited spots, to iterative Fourier-transform algorithms capable of generating arbitrary illumination shapes perfectly tailored on the base of the target contour. Applications for holographic light patterning include multi-trap optical tweezers, patterned voltage imaging and optical control of neuronal excitation using uncaging or optogenetics. These past implementations of computer generated holography used binary input profile to generate binary light distribution at the sample plane. Here we demonstrate that using graded input sources, enables generating intensity graded light patterns and extend the range of application of holographic light illumination. At first, we use intensity-graded holograms to compensate for LC-SLM position dependent diffraction efficiency or sample fluorescence inhomogeneity. Finally we show that intensity-graded holography can be used to equalize photo evoked currents from cells expressing different levels of chanelrhodopsin2 (ChR2), one of the most commonly used optogenetics light gated channels, taking into account the non-linear dependence of channel opening on incident light. Frontiers Media S.A. 2016-10-17 /pmc/articles/PMC5065964/ /pubmed/27799896 http://dx.doi.org/10.3389/fncel.2016.00236 Text en Copyright © 2016 Conti, Assayag, de Sars, Guillon and Emiliani. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Conti, Rossella
Assayag, Osnath
de Sars, Vincent
Guillon, Marc
Emiliani, Valentina
Computer Generated Holography with Intensity-Graded Patterns
title Computer Generated Holography with Intensity-Graded Patterns
title_full Computer Generated Holography with Intensity-Graded Patterns
title_fullStr Computer Generated Holography with Intensity-Graded Patterns
title_full_unstemmed Computer Generated Holography with Intensity-Graded Patterns
title_short Computer Generated Holography with Intensity-Graded Patterns
title_sort computer generated holography with intensity-graded patterns
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5065964/
https://www.ncbi.nlm.nih.gov/pubmed/27799896
http://dx.doi.org/10.3389/fncel.2016.00236
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