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      High speed functional imaging with source localized multifocal two-photon microscopy

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          Abstract

          Multifocal two-photon microscopy (MTPM) increases imaging speed over single-focus scanning by parallelizing fluorescence excitation. The imaged fluorescence’s susceptibility to crosstalk, however, severely degrades contrast in scattering tissue. Here we present a source-localized MTPM scheme optimized for high speed functional fluorescence imaging in scattering mammalian brain tissue. A rastered line array of beamlets excites fluorescence imaged with a complementary metal-oxide-semiconductor (CMOS) camera. We mitigate scattering-induced crosstalk by temporally oversampling the rastered image, generating grouped images with structured illumination, and applying Richardson-Lucy deconvolution to reassign scattered photons. Single images are then retrieved with a maximum intensity projection through the deconvolved image groups. This method increased image contrast at depths up to 112 μm in scattering brain tissue and reduced functional crosstalk between pixels during neuronal calcium imaging. Source-localization did not affect signal-to-noise ratio (SNR) in densely labeled tissue under our experimental conditions. SNR decreased at low frame rates in sparsely labeled tissue, with no effect at frame rates above 50 Hz. Our non-descanned source-localized MTPM system enables high SNR, 100 Hz capture of fluorescence transients in scattering brain, increasing the scope of MTPM to faster and smaller functional signals.

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          Diffuse radiation in the Galaxy

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            Acute brain slice methods for adult and aging animals: application of targeted patch clamp analysis and optogenetics.

            The development of the living acute brain slice preparation for analyzing synaptic function roughly a half century ago was a pivotal achievement that greatly influenced the landscape of modern neuroscience. Indeed, many neuroscientists regard brain slices as the gold-standard model system for detailed cellular, molecular, and circuitry level analysis and perturbation of neuronal function. A critical limitation of this model system is the difficulty in preparing slices from adult and aging animals, and over the past several decades few substantial methodological improvements have emerged to facilitate patch clamp analysis in the mature adult stage. In this chapter we describe a robust and practical protocol for preparing brain slices from mature adult mice that are suitable for patch clamp analysis. This method reduces swelling and damage in superficial layers of the slices and improves the success rate for targeted patch clamp recordings, including recordings from fluorescently labeled populations in slices derived from transgenic mice. This adult brain slice method is suitable for diverse experimental applications, including both monitoring and manipulating neuronal activity with genetically encoded calcium indicators and optogenetic actuators, respectively. We describe the application of this adult brain slice platform and associated methods for screening kinetic properties of Channelrhodopsin (ChR) variants expressed in genetically defined neuronal subtypes.
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              A new criterion for automatic multilevel thresholding.

              A new criterion for multilevel thresholding is proposed. The criterion is based on the consideration of two factors. The first one is the discrepancy between the thresholded and original images and the second one is the number of bits required to represent the thresholded image. Based on a new maximum correlation criterion for bilevel thresholding, the discrepancy is defined and then a cost function that takes both factors into account is proposed for multilevel thresholding. By minimizing the cost function, the classification number that the gray-levels should be classified and the threshold values can be determined automatically. In addition, the cost function is proven to possess a unique minimum under very mild conditions. Computational analyses indicate that the number of required mathematical operations in the implementation of our algorithm is much less than that of maximum entropy criterion. Finally, simulation results are included to demonstrate their effectiveness.
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                Author and article information

                Journal
                Biomed Opt Express
                Biomed Opt Express
                BOE
                Biomedical Optics Express
                Optical Society of America
                2156-7085
                12 July 2018
                01 August 2018
                12 July 2018
                : 9
                : 8
                : 3678-3693
                Affiliations
                [1 ]Department of Bioengineering, Imperial College London, SW7 2AZ, UK
                [2 ]Centre for Neurotechnology, Imperial College London, SW7 2AZ, UK
                [3 ]Department of Electrical and Electronic Engineering, Imperial College London, SW7 2AZ, UK
                [4 ]Department of Physics, Imperial College London, SW7 2AZ, UK
                [5 ]Department of Medicine, Imperial College London, SW7 2AZ, UK
                Author notes
                Article
                319174
                10.1364/BOE.9.003678
                6191622
                ecb1bc2e-b0d8-4782-a247-518e5194b02d
                Published by The Optical Society under the terms of the Creative Commons Attribution 4.0 License. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

                Published by The Optical Society under the terms of the Creative Commons Attribution 4.0 License. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

                History
                : 19 March 2018
                : 04 May 2018
                : 04 June 2018
                Funding
                Funded by: Biotechnology and Biological Sciences Research Council (BBSRC) 10.13039/501100000268
                Award ID: BB/K001817/1
                Funded by: Engineering and Physical Sciences Research Council (EPSRC) 10.13039/501100000266
                Award ID: EP/K503733/1
                Award ID: EP/L016737/1
                Funded by: National Institutes of Health (NIH) 10.13039/100000002
                Award ID: U01MH109091
                Award ID: U01NS090501
                Award ID: U01NS099573
                Funded by: Royal Academy of Engineering 10.13039/501100000287
                Award ID: RF1415\14\26
                Funded by: Wellcome Trust 10.13039/100010269
                Award ID: 201964/Z/16/Z
                Categories
                Article

                Vision sciences
                (100.0100) image processing,(110.0110) imaging systems,(180.0180) microscopy

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