Abstract

Epifluorescence miniature microscopes ('miniscopes') are widely used for in vivo calcium imaging of neural population activity. Imaging data is typically collected during a behavioral task and stored for later offline analysis, but emerging techniques for online imaging can support novel closed-loop experiments in which neural population activity is decoded in real time to trigger neurostimulation or sensory feedback. To achieve short feedback latencies, online imaging systems must be optimally designed to maximize computational speed and efficiency while minimizing errors in population decoding. Here we introduce DeCalciOn, an open-source device for real-time imaging and population decoding of in vivo calcium signals that is hardware compatible with all miniscopes that use the UCLA Data Acquisition (DAQ) interface. DeCalciOn performs online motion stabilization, neural enhancement, calcium trace extraction, and decoding of up to 1024 traces per frame at latencies of <50 ms after fluorescence photons arrive at the miniscope image sensor. We show that DeCalciOn can accurately decode the position of rats (n=12) running on a linear track from calcium fluorescence in the hippocampal CA1 layer, and can categorically classify behaviors performed by rats (n=2) during an instrumental task from calcium fluorescence in orbitofrontal cortex (OFC). DeCalciOn achieves high decoding accuracy at short latencies using innovations such as field-programmable gate array (FPGA) hardware for real time image processing and contour-free methods to efficiently extract calcium traces from sensor images. In summary, our system offers an affordable plug-and-play solution for real-time calcium imaging experiments in behaving animals.

Data availability

All hardware, software, and firmware are openly available through miniscope.org and at github.com/zhe-ch/ACTEV.

The following data sets were generated

Article and author information

Author details

  1. Zhe Chen

    Department of Electrical and Computer Engineering, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    No competing interests declared.
  2. Garrett J Blair

    Department of Psychology, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2724-8914
  3. Changliang Guo

    David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    No competing interests declared.
  4. Jim Zhou

    Department of Electrical and Computer Engineering, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    No competing interests declared.
  5. Juan-Luis Romero-Sosa

    Department of Psychology, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    No competing interests declared.
  6. Alicia Izquierdo

    Department of Psychology, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    Alicia Izquierdo, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9897-2091
  7. Peyman Golshani

    David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    No competing interests declared.
  8. Jason Cong

    Department of Electrical and Computer Engineering, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    No competing interests declared.
  9. Daniel Aharoni

    Department of Neurology, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4931-8514
  10. Hugh T Blair

    Department of Psychology, University of California, Los Angeles, Los Angeles, United States
    For correspondence
    tadblair@g.ucla.edu
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8256-5109

Funding

NSF NeuroNex (1707408)

  • Peyman Golshani
  • Jason Cong
  • Daniel Aharoni
  • Hugh T Blair

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 (#2017-038) of the University of California Los Angeles. The protocol was approved by the Committee on the Ethics of Animal Experiments of UCLA. All surgery was performed under deep isoflurane anesthesia, and every effort was made to minimize suffering, including administration of pre- and post-surgical analgesia.

Copyright

© 2023, Chen 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

  • 3,006
    views
  • 351
    downloads
  • 10
    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. Zhe Chen
  2. Garrett J Blair
  3. Changliang Guo
  4. Jim Zhou
  5. Juan-Luis Romero-Sosa
  6. Alicia Izquierdo
  7. Peyman Golshani
  8. Jason Cong
  9. Daniel Aharoni
  10. Hugh T Blair
(2023)
A hardware system for real time decoding of in vivo calcium imaging data
eLife 12:e78344.
https://doi.org/10.7554/eLife.78344

Share this article

https://doi.org/10.7554/eLife.78344

Further reading

    1. Computational and Systems Biology
    2. Genetics and Genomics
    Jia-Ying Su, Yun-Lin Wang ... Chien-Ling Lin
    Research Article

    Untranslated regions (UTRs) contain crucial regulatory elements for RNA stability, translation and localization, so their integrity is indispensable for gene expression. Approximately 3.7% of genetic variants associated with diseases occur in UTRs, yet a comprehensive understanding of UTR variant functions remains limited due to inefficient experimental and computational assessment methods. To systematically evaluate the effects of UTR variants on RNA stability, we established a massively parallel reporter assay on 6555 UTR variants reported in human disease databases. We examined the RNA degradation patterns mediated by the UTR library in two cell lines, and then applied LASSO regression to model the influential regulators of RNA stability. We found that UA dinucleotides and UA-rich motifs are the most prominent destabilizing element. Gain of UA dinucleotide outlined mutant UTRs with reduced stability. Studies on endogenous transcripts indicate that high UA-dinucleotide ratios in UTRs promote RNA degradation. Conversely, elevated GC content and protein binding on UA dinucleotides protect high-UA RNA from degradation. Further analysis reveals polarized roles of UA-dinucleotide-binding proteins in RNA protection and degradation. Furthermore, the UA-dinucleotide ratio of both UTRs is a common characteristic of genes in innate immune response pathways, implying a coordinated stability regulation through UTRs at the transcriptomic level. We also demonstrate that stability-altering UTRs are associated with changes in biobank-based health indices, underscoring the importance of precise UTR regulation for wellness. Our study highlights the importance of RNA stability regulation through UTR primary sequences, paving the way for further exploration of their implications in gene networks and precision medicine.

    1. Computational and Systems Biology
    2. Medicine
    Hong Yang, Cheng Zhang ... Adil Mardinoglu
    Research Article

    Excessive consumption of sucrose, in the form of sugar-sweetened beverages, has been implicated in the pathogenesis of metabolic dysfunction‐associated fatty liver disease (MAFLD) and other related metabolic syndromes. The c-Jun N-terminal kinase (JNK) pathway plays a crucial role in response to dietary stressors, and it was demonstrated that the inhibition of the JNK pathway could potentially be used in the treatment of MAFLD. However, the intricate mechanisms underlying these interventions remain incompletely understood given their multifaceted effects across multiple tissues. In this study, we challenged rats with sucrose-sweetened water and investigated the potential effects of JNK inhibition by employing network analysis based on the transcriptome profiling obtained from hepatic and extrahepatic tissues, including visceral white adipose tissue, skeletal muscle, and brain. Our data demonstrate that JNK inhibition by JNK-IN-5A effectively reduces the circulating triglyceride accumulation and inflammation in rats subjected to sucrose consumption. Coexpression analysis and genome-scale metabolic modeling reveal that sucrose overconsumption primarily induces transcriptional dysfunction related to fatty acid and oxidative metabolism in the liver and adipose tissues, which are largely rectified after JNK inhibition at a clinically relevant dose. Skeletal muscle exhibited minimal transcriptional changes to sucrose overconsumption but underwent substantial metabolic adaptation following the JNK inhibition. Overall, our data provides novel insights into the molecular basis by which JNK inhibition exerts its metabolic effect in the metabolically active tissues. Furthermore, our findings underpin the critical role of extrahepatic metabolism in the development of diet-induced steatosis, offering valuable guidance for future studies focused on JNK-targeting for effective treatment of MAFLD.