1. Neuroscience
Download icon

Chronically-implanted Neuropixels probes enable high yield recordings in freely moving mice

  1. Ashley L Juavinett
  2. George Bekheet
  3. Anne K Churchland  Is a corresponding author
  1. University of California, San Diego, United States
  2. University of Connecticutt, United States
  3. Cold Spring Harbor Laboratory, United States
Tools and Resources
  • Cited 33
  • Views 12,176
  • Annotations
Cite this article as: eLife 2019;8:e47188 doi: 10.7554/eLife.47188

Abstract

The advent of high-yield electrophysiology using Neuropixels probes is now enabling researchers to simultaneously record hundreds of neurons with remarkably high signal to noise. However, these probes have not been well-suited to use in freely moving mice. It is critical to study neural activity in unrestricted animals for many reasons, such as leveraging ethological approaches to study neural circuits. We designed and implemented a novel device that allows Neuropixels probes to be customized for chronically-implanted experiments in freely moving mice. We demonstrate the ease and utility of this approach in recording hundreds of neurons during an ethological behavior across weeks of experiments. We provide the technical drawings and procedures for other researchers to do the same. Importantly, our approach enables researchers to explant and reuse these valuable probes, a transformative step which has not been established for recordings with any type of chronically-implanted probe.

Data availability

We have made all the materials related to this device available to the community via GitHub. The technical drawings, the methodological instructions, the photographs and supporting code will, together, allow any researcher to rapidly adopt this new technology and begin to benefit from Neuropixels probes. We are open to other sharing platforms as well (e.g. bio-protocol).We will make the data from the electrophysiological recordings available as well, via the Cold Spring Harbor Laboratory repository which is linked form our lab website.

Article and author information

Author details

  1. Ashley L Juavinett

    Division of Biological Sciences, University of California, San Diego, La Jolla, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4254-3009
  2. George Bekheet

    School of Medicine, University of Connecticutt, Farmington, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Anne K Churchland

    Department of Neuroscience, Cold Spring Harbor Laboratory, Cold Spring Harbor, United States
    For correspondence
    churchland@cshl.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3205-3794

Funding

Simons Foundation (Simons Collaboration on the Global Brain)

  • Anne K Churchland

Pew Foundation (Pew Scholars)

  • Anne K Churchland

Eleanor Schwartz Fund (Scholar award)

  • Anne K Churchland

Cold Spring Harbor Laboratory (Marie Robertson)

  • Anne K Churchland

National Science Foundation (1559816)

  • George Bekheet

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

Ethics

Animal experimentation: All surgical and behavioral procedures conformed to the guidelines established by the National Institutes of Health and were approved by the Institutional Animal Care and Use Committee of Cold Spring Harbor Laboratory (protocol # 16-13-10-7). All surgery was performed under isoflurane anesthesia and every effort was made to minimize suffering.

Reviewing Editor

  1. Laura L Colgin, University of Texas at Austin, United States

Publication history

  1. Received: March 27, 2019
  2. Accepted: August 5, 2019
  3. Accepted Manuscript published: August 14, 2019 (version 1)
  4. Version of Record published: August 23, 2019 (version 2)

Copyright

© 2019, Juavinett 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

  • 12,176
    Page views
  • 1,134
    Downloads
  • 33
    Citations

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

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
    Anirudh Wodeyar et al.
    Tools and Resources Updated

    Brain rhythms have been proposed to facilitate brain function, with an especially important role attributed to the phase of low-frequency rhythms. Understanding the role of phase in neural function requires interventions that perturb neural activity at a target phase, necessitating estimation of phase in real-time. Current methods for real-time phase estimation rely on bandpass filtering, which assumes narrowband signals and couples the signal and noise in the phase estimate, adding noise to the phase and impairing detections of relationships between phase and behavior. To address this, we propose a state space phase estimator for real-time tracking of phase. By tracking the analytic signal as a latent state, this framework avoids the requirement of bandpass filtering, separately models the signal and the noise, accounts for rhythmic confounds, and provides credible intervals for the phase estimate. We demonstrate in simulations that the state space phase estimator outperforms current state-of-the-art real-time methods in the contexts of common confounds such as broadband rhythms, phase resets, and co-occurring rhythms. Finally, we show applications of this approach to in vivo data. The method is available as a ready-to-use plug-in for the Open Ephys acquisition system, making it widely available for use in experiments.

    1. Evolutionary Biology
    2. Neuroscience
    Lucia L Prieto-Godino et al.
    Research Article

    Olfactory receptor repertoires exhibit remarkable functional diversity, but how these proteins have evolved is poorly understood. Through analysis of extant and ancestrally-reconstructed drosophilid olfactory receptors from the Ionotropic receptor (Ir) family, we investigated evolution of two organic acid-sensing receptors, Ir75a and Ir75b. Despite their low amino acid identity, we identify a common 'hotspot' in their ligand-binding pocket that has a major effect on changing the specificity of both Irs, as well as at least two distinct functional transitions in Ir75a during evolution. Moreover, we show that odor specificity is refined by changes in additional, receptor-specific sites, including those outside the ligand-binding pocket. Our work reveals how a core, common determinant of ligand-tuning acts within epistatic and allosteric networks of substitutions to lead to functional evolution of olfactory receptors.