IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0015517.html
   My bibliography  Save this article

Novel Use of Matched Filtering for Synaptic Event Detection and Extraction

Author

Listed:
  • Yulin Shi
  • Zoran Nenadic
  • Xiangmin Xu

Abstract

Efficient and dependable methods for detection and measurement of synaptic events are important for studies of synaptic physiology and neuronal circuit connectivity. As the published methods with detection algorithms based upon amplitude thresholding and fixed or scaled template comparisons are of limited utility for detection of signals with variable amplitudes and superimposed events that have complex waveforms, previous techniques are not applicable for detection of evoked synaptic events in photostimulation and other similar experimental situations. Here we report on a novel technique that combines the design of a bank of approximate matched filters with the detection and estimation theory to automatically detect and extract photostimluation-evoked excitatory postsynaptic currents (EPSCs) from individually recorded neurons in cortical circuit mapping experiments. The sensitivity and specificity of the method were evaluated on both simulated and experimental data, with its performance comparable to that of visual event detection performed by human operators. This new technique was applied to quantify and compare the EPSCs obtained from excitatory pyramidal cells and fast-spiking interneurons. In addition, our technique has been further applied to the detection and analysis of inhibitory postsynaptic current (IPSC) responses. Given the general purpose of our matched filtering and signal recognition algorithms, we expect that our technique can be appropriately modified and applied to detect and extract other types of electrophysiological and optical imaging signals.

Suggested Citation

  • Yulin Shi & Zoran Nenadic & Xiangmin Xu, 2010. "Novel Use of Matched Filtering for Synaptic Event Detection and Extraction," PLOS ONE, Public Library of Science, vol. 5(11), pages 1-15, November.
  • Handle: RePEc:plo:pone00:0015517
    DOI: 10.1371/journal.pone.0015517
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0015517
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0015517&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0015517?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Jay R. Gibson & Michael Beierlein & Barry W. Connors, 1999. "Two networks of electrically coupled inhibitory neurons in neocortex," Nature, Nature, vol. 402(6757), pages 75-79, November.
    2. Yumiko Yoshimura & Jami L. M. Dantzker & Edward M. Callaway, 2005. "Excitatory cortical neurons form fine-scale functional networks," Nature, Nature, vol. 433(7028), pages 868-873, February.
    3. Kenichi Ohki & Sooyoung Chung & Yeang H. Ch'ng & Prakash Kara & R. Clay Reid, 2005. "Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex," Nature, Nature, vol. 433(7026), pages 597-603, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xing, Miaomiao & Song, Xinlin & Wang, Hengtong & Yang, Zhuoqin & Chen, Yong, 2022. "Frequency synchronization and excitabilities of two coupled heterogeneous Morris-Lecar neurons," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    2. Yoav Printz & Pritish Patil & Mathias Mahn & Asaf Benjamin & Anna Litvin & Rivka Levy & Max Bringmann & Ofer Yizhar, 2023. "Determinants of functional synaptic connectivity among amygdala-projecting prefrontal cortical neurons in male mice," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    3. Yilmaz, Ergin, 2014. "Impacts of hybrid synapses on the noise-delayed decay in scale-free neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 66(C), pages 1-8.
    4. Dominic J. Vita & Fernanda S. Orsi & Nathan G. Stanko & Natalie A. Clark & Alexandre Tiriac, 2024. "Development and organization of the retinal orientation selectivity map," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    5. Javier G. Orlandi & Mohammad Abdolrahmani & Ryo Aoki & Dmitry R. Lyamzin & Andrea Benucci, 2023. "Distributed context-dependent choice information in mouse posterior cortex," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    6. Volker Pernice & Benjamin Staude & Stefano Cardanobile & Stefan Rotter, 2011. "How Structure Determines Correlations in Neuronal Networks," PLOS Computational Biology, Public Library of Science, vol. 7(5), pages 1-14, May.
    7. Elaine Tring & Konnie K. Duan & Dario L. Ringach, 2022. "ON/OFF domains shape receptive field structure in mouse visual cortex," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    8. Gabriel Koch Ocker & Ashok Litwin-Kumar & Brent Doiron, 2015. "Self-Organization of Microcircuits in Networks of Spiking Neurons with Plastic Synapses," PLOS Computational Biology, Public Library of Science, vol. 11(8), pages 1-40, August.
    9. Gabriel Koch Ocker & Krešimir Josić & Eric Shea-Brown & Michael A Buice, 2017. "Linking structure and activity in nonlinear spiking networks," PLOS Computational Biology, Public Library of Science, vol. 13(6), pages 1-47, June.
    10. Suchin S Gururangan & Alexander J Sadovsky & Jason N MacLean, 2014. "Analysis of Graph Invariants in Functional Neocortical Circuitry Reveals Generalized Features Common to Three Areas of Sensory Cortex," PLOS Computational Biology, Public Library of Science, vol. 10(7), pages 1-12, July.
    11. Haleigh N. Mulholland & Matthias Kaschube & Gordon B. Smith, 2024. "Self-organization of modular activity in immature cortical networks," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    12. Yajie Liang & Rongwen Lu & Katharine Borges & Na Ji, 2023. "Stimulus edges induce orientation tuning in superior colliculus," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    13. James Trousdale & Yu Hu & Eric Shea-Brown & Krešimir Josić, 2012. "Impact of Network Structure and Cellular Response on Spike Time Correlations," PLOS Computational Biology, Public Library of Science, vol. 8(3), pages 1-15, March.
    14. Lars Reichl & Dominik Heide & Siegrid Löwel & Justin C Crowley & Matthias Kaschube & Fred Wolf, 2012. "Coordinated Optimization of Visual Cortical Maps (I) Symmetry-based Analysis," PLOS Computational Biology, Public Library of Science, vol. 8(11), pages 1-24, November.
    15. Sichen Tao & Yuki Todo & Zheng Tang & Bin Li & Zhiming Zhang & Riku Inoue, 2022. "A Novel Artificial Visual System for Motion Direction Detection in Grayscale Images," Mathematics, MDPI, vol. 10(16), pages 1-32, August.
    16. Jimin Wu & Yuzhi Chen & Ashok Veeraraghavan & Eyal Seidemann & Jacob T. Robinson, 2024. "Mesoscopic calcium imaging in a head-unrestrained male non-human primate using a lensless microscope," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    17. Meng Wang & Ke Liu & Junxia Pan & Jialin Li & Pei Sun & Yongsheng Zhang & Longhui Li & Wenyan Guo & Qianqian Xin & Zhikai Zhao & Yurong Liu & Zhenqiao Zhou & Jing Lyu & Ting Zheng & Yunyun Han & Chunq, 2022. "Brain-wide projection reconstruction of single functionally defined neurons," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    18. Joel Bauer & Uwe Lewin & Elizabeth Herbert & Julijana Gjorgjieva & Carl E. Schoonover & Andrew J. P. Fink & Tobias Rose & Tobias Bonhoeffer & Mark Hübener, 2024. "Sensory experience steers representational drift in mouse visual cortex," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    19. Luca Sità & Marco Brondi & Pedro Lagomarsino de Leon Roig & Sebastiano Curreli & Mariangela Panniello & Dania Vecchia & Tommaso Fellin, 2022. "A deep-learning approach for online cell identification and trace extraction in functional two-photon calcium imaging," Nature Communications, Nature, vol. 13(1), pages 1-22, December.
    20. Ke Chen & Ai-Min Ding & Xiao-Hua Liang & Li-Peng Zhang & Ling Wang & Xue-Mei Song, 2015. "Effect of Contrast on Visual Spatial Summation in Different Cell Categories in Cat Primary Visual Cortex," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-14, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0015517. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.