Automated identification of mouse visual areas with intrinsic signal imaging

This protocol describes how to produce retinotopic maps of mouse visual cortex using intrinsic signal optical imaging and a segmentation algorithm. Intrinsic signal optical imaging (ISI) is a rapid and noninvasive method for observing brain activity in vivo over a large area of the cortex. Here we d...

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Published inNature protocols Vol. 12; no. 1; pp. 32 - 43
Main Authors Juavinett, Ashley L, Nauhaus, Ian, Garrett, Marina E, Zhuang, Jun, Callaway, Edward M
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 01.01.2017
Nature Publishing Group
Subjects
14
59
631/136/334/1874/345
631/1647/245/2226
631/378/2613
631/378/3917
Algorithms
Analytical Chemistry
Animals
Automation
Biological Techniques
Brain
Brain architecture
Brain mapping
Computational Biology/Bioinformatics
Computational neuroscience
Hemodynamics
Image segmentation
In vivo methods and tests
Innovations
Laboratories
Life Sciences
Mapping
Medical examination
Mice
Mice, Inbred C57BL
Microarrays
Neuroimaging
Neurosciences
Optical communication
Optical Imaging - instrumentation
Optical Imaging - methods
Optical tomography
Organic Chemistry
Protocol
Retina
Signal Transduction
Source code
Topography
Visual cortex
Visual Cortex - cytology
Visual Cortex - physiology
Visual field
Visual Fields
Visual pathways
Visual signals
Visual stimuli
United States > US
Online AccessGet full text
ISSN1754-2189
1750-2799
1750-2799
DOI10.1038/nprot.2016.158

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Abstract This protocol describes how to produce retinotopic maps of mouse visual cortex using intrinsic signal optical imaging and a segmentation algorithm. Intrinsic signal optical imaging (ISI) is a rapid and noninvasive method for observing brain activity in vivo over a large area of the cortex. Here we describe our protocol for mapping retinotopy to identify mouse visual cortical areas using ISI. First, surgery is performed to attach a head frame to the mouse skull (∼1 h). The next day, intrinsic activity across the visual cortex is recorded during the presentation of a full-field drifting bar in the horizontal and vertical directions (∼2 h). Horizontal and vertical retinotopic maps are generated by analyzing the response of each pixel during the period of the stimulus. Last, an algorithm uses these retinotopic maps to compute the visual field sign and coverage, and automatically construct visual borders without human input. Compared with conventional retinotopic mapping with episodic presentation of adjacent stimuli, a continuous, periodic stimulus is more resistant to biological artifacts. Furthermore, unlike manual hand-drawn approaches, we present a method for automatically segmenting visual areas, even in the small mouse cortex. This relatively simple procedure and accompanying open-source code can be implemented with minimal surgical and computational experience, and is useful to any laboratory wishing to target visual cortical areas in this increasingly valuable model system.
AbstractList Intrinsic signal optical imaging (ISI) is a rapid and noninvasive method for observing brain activity in vivo over a large area of the cortex. Here we describe our protocol for mapping retinotopy to identify mouse visual cortical areas using ISI. First, surgery is performed to attach a head frame to the mouse skull ([similar]1 h). The next day, intrinsic activity across the visual cortex is recorded during the presentation of a full-field drifting bar in the horizontal and vertical directions ([similar]2 h). Horizontal and vertical retinotopic maps are generated by analyzing the response of each pixel during the period of the stimulus. Last, an algorithm uses these retinotopic maps to compute the visual field sign and coverage, and automatically construct visual borders without human input. Compared with conventional retinotopic mapping with episodic presentation of adjacent stimuli, a continuous, periodic stimulus is more resistant to biological artifacts. Furthermore, unlike manual hand-drawn approaches, we present a method for automatically segmenting visual areas, even in the small mouse cortex. This relatively simple procedure and accompanying open-source code can be implemented with minimal surgical and computational experience, and is useful to any laboratory wishing to target visual cortical areas in this increasingly valuable model system. Keywords: Mouse visual cortex, intrinsic signal optical imaging, striate cortex, extrastriate cortex, brain, mouse brain, ISI, retinotopy, retinotopic map, retinal map, retinal mapping intrinsic activity, neuron, Retinotopic mapping, visual field map, visual cortex, Functional mapping, MATLAB, mouse, visual field, intrinsic signal imaging
Intrinsic signal optical imaging (ISI) is a rapid and noninvasive method for observing brain activity in vivo over a large area of the cortex. Here we describe our protocol for mapping retinotopy to identify mouse visual cortical areas using ISI. First, surgery is performed to attach a head frame to the mouse skull (∼1 h). The next day, intrinsic activity across the visual cortex is recorded during the presentation of a full-field drifting bar in the horizontal and vertical directions (∼2 h). Horizontal and vertical retinotopic maps are generated by analyzing the response of each pixel during the period of the stimulus. Last, an algorithm uses these retinotopic maps to compute the visual field sign and coverage, and automatically construct visual borders without human input. Compared with conventional retinotopic mapping with episodic presentation of adjacent stimuli, a continuous, periodic stimulus is more resistant to biological artifacts. Furthermore, unlike manual hand-drawn approaches, we present a method for automatically segmenting visual areas, even in the small mouse cortex. This relatively simple procedure and accompanying open-source code can be implemented with minimal surgical and computational experience, and is useful to any laboratory wishing to target visual cortical areas in this increasingly valuable model system.
This protocol describes how to produce retinotopic maps of mouse visual cortex using intrinsic signal optical imaging and a segmentation algorithm.Intrinsic signal optical imaging (ISI) is a rapid and noninvasive method for observing brain activity in vivo over a large area of the cortex. Here we describe our protocol for mapping retinotopy to identify mouse visual cortical areas using ISI. First, surgery is performed to attach a head frame to the mouse skull (∼1 h). The next day, intrinsic activity across the visual cortex is recorded during the presentation of a full-field drifting bar in the horizontal and vertical directions (∼2 h). Horizontal and vertical retinotopic maps are generated by analyzing the response of each pixel during the period of the stimulus. Last, an algorithm uses these retinotopic maps to compute the visual field sign and coverage, and automatically construct visual borders without human input. Compared with conventional retinotopic mapping with episodic presentation of adjacent stimuli, a continuous, periodic stimulus is more resistant to biological artifacts. Furthermore, unlike manual hand-drawn approaches, we present a method for automatically segmenting visual areas, even in the small mouse cortex. This relatively simple procedure and accompanying open-source code can be implemented with minimal surgical and computational experience, and is useful to any laboratory wishing to target visual cortical areas in this increasingly valuable model system.
Intrinsic signal optical imaging (ISI) is a rapid and noninvasive method for observing brain activity in vivo over a large area of the cortex. Here we describe our protocol for mapping retinotopy to identify mouse visual cortical areas using ISI. First, surgery is performed to attach a head frame to the mouse skull ([similar]1 h). The next day, intrinsic activity across the visual cortex is recorded during the presentation of a full-field drifting bar in the horizontal and vertical directions ([similar]2 h). Horizontal and vertical retinotopic maps are generated by analyzing the response of each pixel during the period of the stimulus. Last, an algorithm uses these retinotopic maps to compute the visual field sign and coverage, and automatically construct visual borders without human input. Compared with conventional retinotopic mapping with episodic presentation of adjacent stimuli, a continuous, periodic stimulus is more resistant to biological artifacts. Furthermore, unlike manual hand-drawn approaches, we present a method for automatically segmenting visual areas, even in the small mouse cortex. This relatively simple procedure and accompanying open-source code can be implemented with minimal surgical and computational experience, and is useful to any laboratory wishing to target visual cortical areas in this increasingly valuable model system.
Intrinsic signal optical imaging (ISI) is a rapid and noninvasive method for observing brain activity in vivo over a large area of the cortex. Here we describe our protocol for mapping retinotopy to identify mouse visual cortical areas using ISI. First, surgery is performed to attach a head frame to the mouse skull (~1 h). The next day, intrinsic activity across the visual cortex is recorded during the presentation of a full-field drifting bar in the horizontal and vertical directions (~2 h). Horizontal and vertical retinotopic maps are generated by analyzing the response of each pixel during the period of the stimulus. Last, an algorithm uses these retinotopic maps to compute the visual field sign and coverage, and automatically construct visual borders without human input. Compared with conventional retinotopic mapping with episodic presentation of adjacent stimuli, a continuous, periodic stimulus is more resistant to biological artifacts. Furthermore, unlike manual hand-drawn approaches, we present a method for automatically segmenting visual areas, even in the small mouse cortex. This relatively simple procedure and accompanying open-source code can be implemented with minimal surgical and computational experience, and is useful to any laboratory wishing to target visual cortical areas in this increasingly valuable model system.
Intrinsic signal optical imaging (ISI) is a rapid and noninvasive method for observing brain activity in vivo over a large area of the cortex. Here we describe our protocol for mapping retinotopy to identify mouse visual cortical areas using ISI. First, surgery is performed to attach a head frame to the mouse skull (∼1 h). The next day, intrinsic activity across the visual cortex is recorded during the presentation of a full-field drifting bar in the horizontal and vertical directions (∼2 h). Horizontal and vertical retinotopic maps are generated by analyzing the response of each pixel during the period of the stimulus. Last, an algorithm uses these retinotopic maps to compute the visual field sign and coverage, and automatically construct visual borders without human input. Compared with conventional retinotopic mapping with episodic presentation of adjacent stimuli, a continuous, periodic stimulus is more resistant to biological artifacts. Furthermore, unlike manual hand-drawn approaches, we present a method for automatically segmenting visual areas, even in the small mouse cortex. This relatively simple procedure and accompanying open-source code can be implemented with minimal surgical and computational experience, and is useful to any laboratory wishing to target visual cortical areas in this increasingly valuable model system.Intrinsic signal optical imaging (ISI) is a rapid and noninvasive method for observing brain activity in vivo over a large area of the cortex. Here we describe our protocol for mapping retinotopy to identify mouse visual cortical areas using ISI. First, surgery is performed to attach a head frame to the mouse skull (∼1 h). The next day, intrinsic activity across the visual cortex is recorded during the presentation of a full-field drifting bar in the horizontal and vertical directions (∼2 h). Horizontal and vertical retinotopic maps are generated by analyzing the response of each pixel during the period of the stimulus. Last, an algorithm uses these retinotopic maps to compute the visual field sign and coverage, and automatically construct visual borders without human input. Compared with conventional retinotopic mapping with episodic presentation of adjacent stimuli, a continuous, periodic stimulus is more resistant to biological artifacts. Furthermore, unlike manual hand-drawn approaches, we present a method for automatically segmenting visual areas, even in the small mouse cortex. This relatively simple procedure and accompanying open-source code can be implemented with minimal surgical and computational experience, and is useful to any laboratory wishing to target visual cortical areas in this increasingly valuable model system.
This protocol describes how to produce retinotopic maps of mouse visual cortex using intrinsic signal optical imaging and a segmentation algorithm. Intrinsic signal optical imaging (ISI) is a rapid and noninvasive method for observing brain activity in vivo over a large area of the cortex. Here we describe our protocol for mapping retinotopy to identify mouse visual cortical areas using ISI. First, surgery is performed to attach a head frame to the mouse skull (∼1 h). The next day, intrinsic activity across the visual cortex is recorded during the presentation of a full-field drifting bar in the horizontal and vertical directions (∼2 h). Horizontal and vertical retinotopic maps are generated by analyzing the response of each pixel during the period of the stimulus. Last, an algorithm uses these retinotopic maps to compute the visual field sign and coverage, and automatically construct visual borders without human input. Compared with conventional retinotopic mapping with episodic presentation of adjacent stimuli, a continuous, periodic stimulus is more resistant to biological artifacts. Furthermore, unlike manual hand-drawn approaches, we present a method for automatically segmenting visual areas, even in the small mouse cortex. This relatively simple procedure and accompanying open-source code can be implemented with minimal surgical and computational experience, and is useful to any laboratory wishing to target visual cortical areas in this increasingly valuable model system.
Audience Academic
Author Juavinett, Ashley L
Callaway, Edward M
Nauhaus, Ian
Zhuang, Jun
Garrett, Marina E
AuthorAffiliation 1 Salk Institute for Biological Studies, La Jolla, California, USA
3 The Allen Institute for Brain Science, Seattle, Washington, USA
2 The University of Texas at Austin, Austin, Texas, USA
AuthorAffiliation_xml – name: 3 The Allen Institute for Brain Science, Seattle, Washington, USA
– name: 1 Salk Institute for Biological Studies, La Jolla, California, USA
– name: 2 The University of Texas at Austin, Austin, Texas, USA
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  givenname: Ashley L
  surname: Juavinett
  fullname: Juavinett, Ashley L
  organization: Salk Institute for Biological Studies
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  givenname: Ian
  surname: Nauhaus
  fullname: Nauhaus, Ian
  organization: The University of Texas at Austin
– sequence: 3
  givenname: Marina E
  surname: Garrett
  fullname: Garrett, Marina E
  organization: The Allen Institute for Brain Science
– sequence: 4
  givenname: Jun
  surname: Zhuang
  fullname: Zhuang, Jun
  organization: The Allen Institute for Brain Science
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  givenname: Edward M
  surname: Callaway
  fullname: Callaway, Edward M
  email: callaway@salk.edu
  organization: Salk Institute for Biological Studies
BackLink https://www.ncbi.nlm.nih.gov/pubmed/27906169$$D View this record in MEDLINE/PubMed
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Snippet This protocol describes how to produce retinotopic maps of mouse visual cortex using intrinsic signal optical imaging and a segmentation algorithm. Intrinsic...
Intrinsic signal optical imaging (ISI) is a rapid and noninvasive method for observing brain activity in vivo over a large area of the cortex. Here we describe...
This protocol describes how to produce retinotopic maps of mouse visual cortex using intrinsic signal optical imaging and a segmentation algorithm.Intrinsic...
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StartPage 32
SubjectTerms 14
59
631/136/334/1874/345
631/1647/245/2226
631/378/2613
631/378/3917
Algorithms
Analytical Chemistry
Animals
Automation
Biological Techniques
Brain
Brain architecture
Brain mapping
Computational Biology/Bioinformatics
Computational neuroscience
Hemodynamics
Image segmentation
In vivo methods and tests
Innovations
Laboratories
Life Sciences
Mapping
Medical examination
Mice
Mice, Inbred C57BL
Microarrays
Neuroimaging
Neurosciences
Optical communication
Optical Imaging - instrumentation
Optical Imaging - methods
Optical tomography
Organic Chemistry
Protocol
Retina
Signal Transduction
Source code
Topography
Visual cortex
Visual Cortex - cytology
Visual Cortex - physiology
Visual field
Visual Fields
Visual pathways
Visual signals
Visual stimuli
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Title Automated identification of mouse visual areas with intrinsic signal imaging
URI https://link.springer.com/article/10.1038/nprot.2016.158
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