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      Review of data processing of functional optical microscopy for neuroscience

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract.

          Functional optical imaging in neuroscience is rapidly growing with the development of optical systems and fluorescence indicators. To realize the potential of these massive spatiotemporal datasets for relating neuronal activity to behavior and stimuli and uncovering local circuits in the brain, accurate automated processing is increasingly essential. We cover recent computational developments in the full data processing pipeline of functional optical microscopy for neuroscience data and discuss ongoing and emerging challenges.

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          U-Net: Convolutional Networks for Biomedical Image Segmentation

          Olaf Ronneberger, Philipp Fischer, Thomas Brox (2015)
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            Ultra-sensitive fluorescent proteins for imaging neuronal activity

            Wen-Wen Chen, Trevor J. Wardill, Yi Sun … (2013)
            Summary Fluorescent calcium sensors are widely used to image neural activity. Using structure-based mutagenesis and neuron-based screening, we developed a family of ultra-sensitive protein calcium sensors (GCaMP6) that outperformed other sensors in cultured neurons and in zebrafish, flies, and mice in vivo. In layer 2/3 pyramidal neurons of the mouse visual cortex, GCaMP6 reliably detected single action potentials in neuronal somata and orientation-tuned synaptic calcium transients in individual dendritic spines. The orientation tuning of structurally persistent spines was largely stable over timescales of weeks. Orientation tuning averaged across spine populations predicted the tuning of their parent cell. Although the somata of GABAergic neurons showed little orientation tuning, their dendrites included highly tuned dendritic segments (5 - 40 micrometers long). GCaMP6 sensors thus provide new windows into the organization and dynamics of neural circuits over multiple spatial and temporal scales.
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              Distinctive Image Features from Scale-Invariant Keypoints

              David G. Lowe (2004)
              Article 0 comments Cited 1262 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Hadas Benisty:
                ORCID: https://orcid.org/0000-0001-6308-2267
                Alexander Song
                Gal Mishne:
                ORCID: https://orcid.org/0000-0002-5287-3626
                Adam S. Charles:
                ORCID: https://orcid.org/0000-0002-9045-3489
                Journal
                Journal ID (nlm-ta): Neurophotonics
                Journal ID (iso-abbrev): Neurophotonics
                Journal ID (coden): NEUROW
                Journal ID (publisher-id): NPh
                Title: Neurophotonics
                Publisher: Society of Photo-Optical Instrumentation Engineers
                ISSN (Print): 2329-423X
                ISSN (Electronic): 2329-4248
                Publication date (Electronic): 4 August 2022
                Publication date (Print): October 2022
                Publication date PMC-release: 4 August 2022
                Volume: 9
                Issue: 4
                Electronic Location Identifier: 041402
                Affiliations
                [a ]Yale Neuroscience , New Haven, Connecticut, United States
                [b ]Max Planck Institute for Intelligent Systems , Stuttgart, Germany
                [c ]UC San Diego , Halıcığlu Data Science Institute, Department of Electrical and Computer Engineering and the Neurosciences Graduate Program, La Jolla, California, United States
                [d ]Johns Hopkins University , Kavli Neuroscience Discovery Institute, Center for Imaging Science, Department of Biomedical Engineering, Department of Neuroscience, and Mathematical Institute for Data Science, Baltimore, Maryland, United States
                Author notes
                [* ]Address all correspondence to Adam S. Charles, adamsc@ 123456jhu.edu
                Author information
                https://orcid.org/0000-0001-6308-2267
                https://orcid.org/0000-0002-5287-3626
                https://orcid.org/0000-0002-9045-3489
                Article
                Publisher-manuscript ID: NPh-22002SSVRR Publisher ID: 22002SSVRR
                DOI: 10.1117/1.NPh.9.4.041402
                PMC ID: 9351186
                SO-VID: 2c741bba-5113-4d64-b5f6-5d36033b7ebd
                Copyright © © 2022 The Authors
                License:

                Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

                History
                Date received : 4 January 2022
                Date accepted : 15 July 2022
                Page count
                Figures: 5, Tables: 0, References: 219, Pages: 32
                Funding
                Funded by: NIH
                Award ID: R01EB026936
                Award ID: U19NS123717
                Categories
                Subject: Special Section on Computational Approaches for Neuroimaging
                Subject: Paper
                Custom metadata
                running-head Song, Mishne and Charles: Review of data processing of functional optical microscopy for neuroscience

                Keywords: fluorescence microscopy,calcium imaging,functional imaging,data analysis
                Data availability:
                Keywords: fluorescence microscopy, calcium imaging, functional imaging, data analysis

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