1. Neuroscience

Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data

  1. Pengcheng Zhou  Is a corresponding author
  2. Shanna L Resendez
  3. Jose Rodriguez-Romaguera
  4. Jessica C Jimenez
  5. Shay Q Neufeld
  6. Andrea Giovannucci
  7. Johannes Friedrich
  8. Eftychios A Pnevmatikakis
  9. Garret D Stuber
  10. Rene Hen
  11. Mazen A Kheirbek
  12. Bernardo L Sabatini
  13. Robert E Kass
  14. Liam Paninski
  1. Carnegie Mellon University, United States
  2. University of North Carolina at Chapel Hill, United States
  3. Columbia University, United States
  4. Harvard Medical School, United States
  5. Flatiron Institute, Simons Foundation, United States
  6. University of California, San Francisco, United States
https://doi.org/10.7554/eLife.28728
Share this article
Cite this article
  1. Pengcheng Zhou
  2. Shanna L Resendez
  3. Jose Rodriguez-Romaguera
  4. Jessica C Jimenez
  5. Shay Q Neufeld
  6. Andrea Giovannucci
  7. Johannes Friedrich
  8. Eftychios A Pnevmatikakis
  9. Garret D Stuber
  10. Rene Hen
  11. Mazen A Kheirbek
  12. Bernardo L Sabatini
  13. Robert E Kass
  14. Liam Paninski
(2018)
Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data
eLife 7:e28728.
https://doi.org/10.7554/eLife.28728
  2. Download BibTeX
  3. Download .RIS

Abstract

In vivo calcium imaging through microendoscopic lenses enables imaging of previously inaccessible neuronal populations deep within the brains of freely moving animals. However, it is computationally challenging to extract single-neuronal activity from microendoscopic data, because of the very large background fluctuations and high spatial overlaps intrinsic to this recording modality. Here, we describe a new constrained matrix factorization approach to accurately separate the background and then demix and denoise the neuronal signals of interest. We compared the proposed method against previous independent components analysis and constrained nonnegative matrix factorization approaches. On both simulated and experimental data recorded from mice, our method substantially improved the quality of extracted cellular signals and detected more well-isolated neural signals, especially in noisy data regimes. These advances can in turn significantly enhance the statistical power of downstream analyses, and ultimately improve scientific conclusions derived from microendoscopic data.

Data availability

The following data sets were generated

Article and author information

Author details

  1. Pengcheng Zhou

    Center for the Neural Basis of Cognition and Machine Learning Department, Carnegie Mellon University, Pittsburgh, United States
    For correspondence
    zhoupc1988@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1237-3931

  2. Shanna L Resendez

    Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, United States
    Competing interests
    The authors declare that no competing interests exist.

  3. Jose Rodriguez-Romaguera

    Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, United States
    Competing interests
    The authors declare that no competing interests exist.

  4. Jessica C Jimenez

    Department of Neuroscience, Columbia University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.

  5. Shay Q Neufeld

    Department of Neurobiology, Harvard Medical School, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.

  6. Andrea Giovannucci

    Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, United States
    Competing interests
    The authors declare that no competing interests exist.

  7. Johannes Friedrich

    Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1321-5866

  8. Eftychios A Pnevmatikakis

    Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, United States
    Competing interests
    The authors declare that no competing interests exist.

  9. Garret D Stuber

    Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1730-4855

  10. Rene Hen

    Department of Neuroscience, Columbia University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.

  11. Mazen A Kheirbek

    Department of Psychiatry, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.

  12. Bernardo L Sabatini

    Department of Neurobiology, Harvard Medical School, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.

  13. Robert E Kass

    Center for the Neural Basis of Cognition and Machine Learning Department, Carnegie Mellon University, Pittsburgh, United States
    Competing interests
    The authors declare that no competing interests exist.

  14. Liam Paninski

    Department of Statistics, Columbia University, Columbia, United States
    Competing interests
    The authors declare that no competing interests exist.

Funding

National Institute of Mental Health

  • Pengcheng Zhou
  • Jessica C Jimenez
  • Rene Hen
  • Mazen A Kheirbek
  • Robert E Kass

New York State Stem Cell Science

  • Jessica C Jimenez
  • Rene Hen

Hope for Depression Research Foundation

  • Jessica C Jimenez
  • Rene Hen

Canadian Institutes of Health Research

  • Shay Q Neufeld

Simons Foundation

  • Andrea Giovannucci
  • Johannes Friedrich
  • Eftychios A Pnevmatikakis
  • Garret D Stuber
  • Liam Paninski

International Mental Health Research Organization

  • Mazen A Kheirbek

National Institute of Neurological Disorders and Stroke

  • Bernardo L Sabatini

National Institute on Drug Abuse

  • Pengcheng Zhou
  • Jose Rodriguez-Romaguera
  • Garret D Stuber

Intelligence Advanced Research Projects Activity

  • Pengcheng Zhou
  • Liam Paninski

Defense Advanced Research Projects Agency

  • Liam Paninski

Army Research Office

  • Liam Paninski

National Institute of Biomedical Imaging and Bioengineering

  • Liam Paninski

Eunice Kennedy Shriver National Institute of Child Health and Human Development

  • Shanna L Resendez
  • Garret D Stuber

Howard Hughes Medical Institute

  • Jessica C Jimenez

National Institute on Aging

  • Jessica C Jimenez
  • Rene Hen

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

Reviewing Editor

  1. David C Van Essen, Washington University in St. Louis, United States

Ethics

Animal experimentation: These procedures were conducted in accordance with the Guide for the Care and Use of Laboratory Animals, as adopted by the NIH, and with approval from the Harvard Standing Committee on Animal Care (protocol number: IS00000571 ), or the University of North Carolina Institutional Animal Care and Use Committee (UNC IACUC, protocol number: 16-075.0), or the New York State Psychiatric Institutional Animal Care and Use Committee (protocol number: NYSPI-1412 ).

Version history

  1. Received: May 19, 2017
  2. Accepted: February 20, 2018
  3. Accepted Manuscript published: February 22, 2018 (version 1)
  4. Version of Record published: March 27, 2018 (version 2)

Copyright

© 2018, Zhou 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

  • 28,091
    views
  • 3,836
    downloads
  • 479
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

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)

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

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

  1. Pengcheng Zhou
  2. Shanna L Resendez
  3. Jose Rodriguez-Romaguera
  4. Jessica C Jimenez
  5. Shay Q Neufeld
  6. Andrea Giovannucci
  7. Johannes Friedrich
  8. Eftychios A Pnevmatikakis
  9. Garret D Stuber
  10. Rene Hen
  11. Mazen A Kheirbek
  12. Bernardo L Sabatini
  13. Robert E Kass
  14. Liam Paninski
(2018)
Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data
eLife 7:e28728.
https://doi.org/10.7554/eLife.28728

Share this article

https://doi.org/10.7554/eLife.28728

Categories and tags

Research organism

Further reading

    1. Biochemistry and Chemical Biology
    2. Neuroscience

    Deciphering the chemical language of inbred and wild mouse conspecific scents

    Maximilian Nagel, Marco Niestroj ... Marc Spehr
    Research Article

    In most mammals, conspecific chemosensory communication relies on semiochemical release within complex bodily secretions and subsequent stimulus detection by the vomeronasal organ (VNO). Urine, a rich source of ethologically relevant chemosignals, conveys detailed information about sex, social hierarchy, health, and reproductive state, which becomes accessible to a conspecific via vomeronasal sampling. So far, however, numerous aspects of social chemosignaling along the vomeronasal pathway remain unclear. Moreover, since virtually all research on vomeronasal physiology is based on secretions derived from inbred laboratory mice, it remains uncertain whether such stimuli provide a true representation of potentially more relevant cues found in the wild. Here, we combine a robust low-noise VNO activity assay with comparative molecular profiling of sex- and strain-specific mouse urine samples from two inbred laboratory strains as well as from wild mice. With comprehensive molecular portraits of these secretions, VNO activity analysis now enables us to (i) assess whether and, if so, how much sex/strain-selective ‘raw’ chemical information in urine is accessible via vomeronasal sampling; (ii) identify which chemicals exhibit sufficient discriminatory power to signal an animal’s sex, strain, or both; (iii) determine the extent to which wild mouse secretions are unique; and (iv) analyze whether vomeronasal response profiles differ between strains. We report both sex- and, in particular, strain-selective VNO representations of chemical information. Within the urinary ‘secretome’, both volatile compounds and proteins exhibit sufficient discriminative power to provide sex- and strain-specific molecular fingerprints. While total protein amount is substantially enriched in male urine, females secrete a larger variety at overall comparatively low concentrations. Surprisingly, the molecular spectrum of wild mouse urine does not dramatically exceed that of inbred strains. Finally, vomeronasal response profiles differ between C57BL/6 and BALB/c animals, with particularly disparate representations of female semiochemicals.

    1. Neuroscience

    Functional diversity of dopamine axons in prefrontal cortex during classical conditioning

    Kenta Abe, Yuki Kambe ... Tatsuo Sato
    Research Article

    Midbrain dopamine neurons impact neural processing in the prefrontal cortex (PFC) through mesocortical projections. However, the signals conveyed by dopamine projections to the PFC remain unclear, particularly at the single-axon level. Here, we investigated dopaminergic axonal activity in the medial PFC (mPFC) during reward and aversive processing. By optimizing microprism-mediated two-photon calcium imaging of dopamine axon terminals, we found diverse activity in dopamine axons responsive to both reward and aversive stimuli. Some axons exhibited a preference for reward, while others favored aversive stimuli, and there was a strong bias for the latter at the population level. Long-term longitudinal imaging revealed that the preference was maintained in reward- and aversive-preferring axons throughout classical conditioning in which rewarding and aversive stimuli were paired with preceding auditory cues. However, as mice learned to discriminate reward or aversive cues, a cue activity preference gradually developed only in aversive-preferring axons. We inferred the trial-by-trial cue discrimination based on machine learning using anticipatory licking or facial expressions, and found that successful discrimination was accompanied by sharper selectivity for the aversive cue in aversive-preferring axons. Our findings indicate that a group of mesocortical dopamine axons encodes aversive-related signals, which are modulated by both classical conditioning across days and trial-by-trial discrimination within a day.

    1. Neuroscience

    Jointly looking to the past and the future in visual working memory

    Baiwei Liu, Zampeta-Sofia Alexopoulou, Freek van Ede
    Research Article

    Working memory enables us to bridge past sensory information to upcoming future behaviour. Accordingly, by its very nature, working memory is concerned with two components: the past and the future. Yet, in conventional laboratory tasks, these two components are often conflated, such as when sensory information in working memory is encoded and tested at the same location. We developed a task in which we dissociated the past (encoded location) and future (to-be-tested location) attributes of visual contents in working memory. This enabled us to independently track the utilisation of past and future memory attributes through gaze, as observed during mnemonic selection. Our results reveal the joint consideration of past and future locations. This was prevalent even at the single-trial level of individual saccades that were jointly biased to the past and future. This uncovers the rich nature of working memory representations, whereby both past and future memory attributes are retained and can be accessed together when memory contents become relevant for behaviour.