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Automated long-term recording and analysis of neural activity in behaving animals

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Cite as: eLife 2017;6:e27702 doi: 10.7554/eLife.27702

Abstract

Addressing how neural circuits underlie behavior is routinely done by measuring electrical activity from single neurons in experimental sessions. While such recordings yield snapshots of neural dynamics during specified tasks, they are ill-suited for tracking single-unit activity over longer timescales relevant for most developmental and learning processes, or for capturing neural dynamics across different behavioral states. Here we describe an automated platform for continuous long-term recordings of neural activity and behavior in freely moving rodents. An unsupervised algorithm identifies and tracks the activity of single units over weeks of recording, dramatically simplifying the analysis of large datasets. Months-long recordings from motor cortex and striatum made and analyzed with our system revealed remarkable stability in basic neuronal properties, such as firing rates and inter-spike interval distributions. Interneuronal correlations and the representation of different movements and behaviors were similarly stable. This establishes the feasibility of high-throughput long-term extracellular recordings in behaving animals.

Article and author information

Author details

  1. Ashesh K Dhawale

    Department of Organismic and Evolutionary Biology and Center for Brain Science, Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon 0000-0001-7438-1115
  2. Rajesh Poddar

    Department of Organismic and Evolutionary Biology and Center for Brain Science, Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Steffen BE Wolff

    Department of Organismic and Evolutionary Biology and Center for Brain Science, Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Valentin A Normand

    Department of Organismic and Evolutionary Biology and Center for Brain Science, Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Evi Kopelowitz

    Department of Organismic and Evolutionary Biology and Center for Brain Science, Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Bence P Ölveczky

    Department of Organismic and Evolutionary Biology and Center for Brain Science, Harvard University, Cambridge, United States
    For correspondence
    olveczky@fas.harvard.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon 0000-0003-2499-2705

Funding

Star Family Challenge Award

  • Bence P Ölveczky

Human Frontier Science Program

  • Steffen B.E Wolff

Life Sciences Research Foundation

  • Ashesh K Dhawale

Charles A. King Trust

  • Ashesh K Dhawale

National Institute of Neurological Disorders and Stroke (R01 NS099323-02)

  • Bence P Ölveczky

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

Ethics

Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to approved institutional animal care and use committee (IACUC) protocols (#29-15) of the Harvard University. All surgery was performed under isoflurane anesthesia, and every effort was made to minimize suffering.

Reviewing Editor

  1. Andrew J King, Reviewing Editor, University of Oxford, United Kingdom

Publication history

  1. Received: April 11, 2017
  2. Accepted: August 24, 2017
  3. Accepted Manuscript published: September 8, 2017 (version 1)

Copyright

© 2017, Dhawale 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.

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