1. Neuroscience
Download icon

Rapid whole brain imaging of neural activity in freely behaving larval zebrafish (Danio rerio)

  1. Lin Cong
  2. Zeguan Wang
  3. Yuming Chai
  4. Wei Hang
  5. Chunfeng Shang
  6. Wenbin Yang
  7. Lu Bai
  8. Jiulin Du
  9. Kai Wang  Is a corresponding author
  10. Quan Wen  Is a corresponding author
  1. Chinese Academy of Sciences, China
  2. Hefei National Laboratory for Physical Sciences at Microscale, China
Tools and Resources
  • Cited 99
  • Views 10,766
  • Annotations
Cite this article as: eLife 2017;6:e28158 doi: 10.7554/eLife.28158

Abstract

The internal brain dynamics that link sensation and action are arguably better studied during natural animal behaviors. Here we report on a novel volume imaging and 3D tracking technique that monitors whole brain neural activity in freely swimming larval zebrafish (Danio rerio). We demonstrated the capability of our system through functional imaging of neural activity during visually evoked and prey capture behaviors in larval zebrafish.

Article and author information

Author details

  1. Lin Cong

    Insitute of Neuroscience, Chinese Academy of Sciences, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.

  2. Zeguan Wang

    Center for Integrative Imaging, Hefei National Laboratory for Physical Sciences at Microscale, Hefei, China
    Competing interests
    The authors declare that no competing interests exist.

  3. Yuming Chai

    Center for Integrative Imaging, Hefei National Laboratory for Physical Sciences at Microscale, Hefei, China
    Competing interests
    The authors declare that no competing interests exist.

  4. Wei Hang

    Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.

  5. Chunfeng Shang

    Insitute of Neuroscience, Chinese Academy of Sciences, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.

  6. Wenbin Yang

    Center for Integrative Imaging, Hefei National Laboratory for Physical Sciences at Microscale, Hefei, China
    Competing interests
    The authors declare that no competing interests exist.

  7. Lu Bai

    Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.

  8. Jiulin Du

    Insitute of Neuroscience, Chinese Academy of Sciences, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.

  9. Kai Wang

    Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China
    For correspondence
    wangkai@ion.ac.cn
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7858-944X

  10. Quan Wen

    Center for Integrative Imaging, Hefei National Laboratory for Physical Sciences at Microscale, Hefei, China
    For correspondence
    qwen@ustc.edu.cn
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0268-8403

Funding

Strategic Priority Research Program of the Chinese Academy of Sciences (XDB02060012)

  • Kai Wang

National Science Foundation of China (NSFC-31471051)

  • Quan Wen

China Thousand Talents Program

  • Kai Wang

CAS Pioneer Hundred Talents Program

  • Quan Wen

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Animal experimentation: Zebrafish handling procedures were approved by the Institute of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences.(permit number: USTCACUC1103013).

Reviewing Editor

  1. Ronald L Calabrese, Emory University, United States

Publication history

  1. Received: April 28, 2017
  2. Accepted: September 11, 2017
  3. Accepted Manuscript published: September 20, 2017 (version 1)
  4. Version of Record published: October 17, 2017 (version 2)

Copyright

© 2017, Cong et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 10,766
    Page views
  • 1,391
    Downloads
  • 99
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, Scopus, PubMed Central.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)

Categories and tags

Research organism

Further reading

    1. Developmental Biology
    2. Neuroscience

    The development of active binocular vision under normal and alternate rearing conditions

    Lukas Klimmasch et al.
    Research Article Updated

    The development of binocular vision is an active learning process comprising the development of disparity tuned neurons in visual cortex and the establishment of precise vergence control of the eyes. We present a computational model for the learning and self-calibration of active binocular vision based on the Active Efficient Coding framework, an extension of classic efficient coding ideas to active perception. Under normal rearing conditions with naturalistic input, the model develops disparity tuned neurons and precise vergence control, allowing it to correctly interpret random dot stereograms. Under altered rearing conditions modeled after neurophysiological experiments, the model qualitatively reproduces key experimental findings on changes in binocularity and disparity tuning. Furthermore, the model makes testable predictions regarding how altered rearing conditions impede the learning of precise vergence control. Finally, the model predicts a surprising new effect that impaired vergence control affects the statistics of orientation tuning in visual cortical neurons.

    1. Neuroscience

    The BigBrainWarp toolbox for integration of BigBrain 3D histology with multimodal neuroimaging

    Casey Paquola et al.
    Tools and Resources Updated

    Neuroimaging stands to benefit from emerging ultrahigh-resolution 3D histological atlases of the human brain; the first of which is ‘BigBrain’. Here, we review recent methodological advances for the integration of BigBrain with multi-modal neuroimaging and introduce a toolbox, ’BigBrainWarp’, that combines these developments. The aim of BigBrainWarp is to simplify workflows and support the adoption of best practices. This is accomplished with a simple wrapper function that allows users to easily map data between BigBrain and standard MRI spaces. The function automatically pulls specialised transformation procedures, based on ongoing research from a wide collaborative network of researchers. Additionally, the toolbox improves accessibility of histological information through dissemination of ready-to-use cytoarchitectural features. Finally, we demonstrate the utility of BigBrainWarp with three tutorials and discuss the potential of the toolbox to support multi-scale investigations of brain organisation.

    1. Neuroscience

    Classification and genetic targeting of cell types in the primary taste and premotor center of the adult Drosophila brain

    Gabriella R Sterne et al.
    Tools and Resources Updated

    Neural circuits carry out complex computations that allow animals to evaluate food, select mates, move toward attractive stimuli, and move away from threats. In insects, the subesophageal zone (SEZ) is a brain region that receives gustatory, pheromonal, and mechanosensory inputs and contributes to the control of diverse behaviors, including feeding, grooming, and locomotion. Despite its importance in sensorimotor transformations, the study of SEZ circuits has been hindered by limited knowledge of the underlying diversity of SEZ neurons. Here, we generate a collection of split-GAL4 lines that provides precise genetic targeting of 138 different SEZ cell types in adult Drosophila melanogaster, comprising approximately one third of all SEZ neurons. We characterize the single-cell anatomy of these neurons and find that they cluster by morphology into six supergroups that organize the SEZ into discrete anatomical domains. We find that the majority of local SEZ interneurons are not classically polarized, suggesting rich local processing, whereas SEZ projection neurons tend to be classically polarized, conveying information to a limited number of higher brain regions. This study provides insight into the anatomical organization of the SEZ and generates resources that will facilitate further study of SEZ neurons and their contributions to sensory processing and behavior.