1. Neuroscience
Download icon

Brain-wide mapping of neural activity controlling zebrafish exploratory locomotion

  1. Timothy W Dunn
  2. Yu Mu
  3. Sujatha Narayan
  4. Owen Randlett
  5. Eva A Naumann
  6. Chao-Tsung Yang
  7. Alexander F Schier
  8. Jeremy Freeman
  9. Florian Engert
  10. Misha B Ahrens  Is a corresponding author
  1. Harvard University, United States
  2. Janelia Research Campus, Howard Hughes Medical Institute, United States
Research Article
  • Cited 121
  • Views 12,674
  • Annotations
Cite this article as: eLife 2016;5:e12741 doi: 10.7554/eLife.12741

Abstract

In the absence of salient sensory cues to guide behavior, animals must still execute sequences of motor actions in order to forage and explore. How such successive motor actions are coordinated to form global locomotion trajectories is unknown. We mapped the structure of larval zebrafish swim trajectories in homogeneous environments and found that trajectories were characterized by alternating sequences of repeated turns to the left and to the right. Using whole-brain light-sheet imaging, we identified activity relating to the behavior in specific neural populations that we termed the anterior rhombencephalic turning region (ARTR). ARTR perturbations biased swim direction and reduced the dependence of turn direction on turn history, indicating that the ARTR is part of a network generating the temporal correlations in turn direction. We also find suggestive evidence for ARTR mutual inhibition and ARTR projections to premotor neurons. Finally, simulations suggest the observed turn sequences may underlie efficient exploration of local environments.

Article and author information

Author details

  1. Timothy W Dunn

    Department of Molecular and Cellular Biology, Center for Brain Science, Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Yu Mu

    Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Sujatha Narayan

    Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Owen Randlett

    Department of Molecular and Cellular Biology, Center for Brain Science, Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Eva A Naumann

    Department of Molecular and Cellular Biology, Center for Brain Science, Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Chao-Tsung Yang

    Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Alexander F Schier

    Department of Molecular and Cellular Biology, Center for Brain Science, Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Jeremy Freeman

    Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Florian Engert

    Department of Molecular and Cellular Biology, Center for Brain Science, Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Misha B Ahrens

    Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
    For correspondence
    ahrensm@janelia.hhmi.org
    Competing interests
    The authors declare that no competing interests exist.

Ethics

Animal experimentation: All experiments presented in this study were conducted in accordance with the animal research guidelines from the National Institutes of Health and were approved by the Institutional Animal Care and Use Committee (#13-98) and Institutional Biosafety Committee of Janelia Research Campus.

Reviewing Editor

  1. Ronald L Calabrese, Emory University, United States

Publication history

  1. Received: November 3, 2015
  2. Accepted: March 9, 2016
  3. Accepted Manuscript published: March 22, 2016 (version 1)
  4. Version of Record published: April 19, 2016 (version 2)

Copyright

© 2016, Dunn 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

  • 12,674
    Page views
  • 2,619
    Downloads
  • 121
    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)

Further reading

    1. Neuroscience
    Wucheng Tao et al.
    Research Article Updated

    Long-term potentiation (LTP) is arguably the most compelling cellular model for learning and memory. While the mechanisms underlying the induction of LTP (‘learning’) are well understood, the maintenance of LTP (‘memory’) has remained contentious over the last 20 years. Here, we find that Ca2+-calmodulin-dependent kinase II (CaMKII) contributes to synaptic transmission and is required LTP maintenance. Acute inhibition of CaMKII erases LTP and transient inhibition of CaMKII enhances subsequent LTP. These findings strongly support the role of CaMKII as a molecular storage device.

    1. Medicine
    2. Neuroscience
    Zifei Liang et al.
    Tools and Resources

    1H MRI maps brain structure and function non-invasively through versatile contrasts that exploit inhomogeneity in tissue micro-environments. Inferring histopathological information from MRI findings, however, remains challenging due to absence of direct links between MRI signals and cellular structures. Here, we show that deep convolutional neural networks, developed using co-registered multi-contrast MRI and histological data of the mouse brain, can estimate histological staining intensity directly from MRI signals at each voxel. The results provide three-dimensional maps of axons and myelin with tissue contrasts that closely mimics target histology and enhanced sensitivity and specificity compared to conventional MRI markers. Furthermore, the relative contribution of each MRI contrast within the networks can be used to optimize multi-contrast MRI acquisition. We anticipate our method to be a starting point for translation of MRI results into easy-to-understand virtual histology for neurobiologists and provide resources for validating novel MRI techniques.