---
_id: '9329'
abstract:
- lang: eng
  text: "Background: To understand information coding in single neurons, it is necessary
    to analyze subthreshold synaptic events, action potentials (APs), and their interrelation
    in different behavioral states. However, detecting excitatory postsynaptic potentials
    (EPSPs) or currents (EPSCs) in behaving animals remains challenging, because of
    unfavorable signal-to-noise ratio, high frequency, fluctuating amplitude, and
    variable time course of synaptic events.\r\nNew method: We developed a method
    for synaptic event detection, termed MOD (Machine-learning Optimal-filtering Detection-procedure),
    which combines concepts of supervised machine learning and optimal Wiener filtering.
    Experts were asked to manually score short epochs of data. The algorithm was trained
    to obtain the optimal filter coefficients of a Wiener filter and the optimal detection
    threshold. Scored and unscored data were then processed with the optimal filter,
    and events were detected as peaks above threshold.\r\nResults: We challenged MOD
    with EPSP traces in vivo in mice during spatial navigation and EPSC traces in
    vitro in slices under conditions of enhanced transmitter release. The area under
    the curve (AUC) of the receiver operating characteristics (ROC) curve was, on
    average, 0.894 for in vivo and 0.969 for in vitro data sets, indicating high detection
    accuracy and efficiency.\r\nComparison with existing methods: When benchmarked
    using a (1 − AUC)−1 metric, MOD outperformed previous methods (template-fit, deconvolution,
    and Bayesian methods) by an average factor of 3.13 for in vivo data sets, but
    showed comparable (template-fit, deconvolution) or higher (Bayesian) computational
    efficacy.\r\nConclusions: MOD may become an important new tool for large-scale,
    real-time analysis of synaptic activity."
acknowledged_ssus:
- _id: SSU
acknowledgement: This project has received funding from the European Research Council
  (ERC) under the European Union’s Horizon 2020 research and innovation programme
  (grant agreement number 692692 to P.J.) and the Fond zur Förderung der Wissenschaftlichen
  Forschung (Z 312-B27, Wittgenstein award to P.J.). We thank Drs. Jozsef Csicsvari,
  Christoph Lampert, and Federico Stella for critically reading previous manuscript
  versions. We are also grateful to Drs. Josh Merel and Ben Shababo for their help
  with applying the Bayesian detection method to our data. We also thank Florian Marr
  for technical assistance, Eleftheria Kralli-Beller for manuscript editing, and the
  Scientific Service Units of IST Austria for efficient support.
article_number: '109125'
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Xiaomin
  full_name: Zhang, Xiaomin
  id: 423EC9C2-F248-11E8-B48F-1D18A9856A87
  last_name: Zhang
- first_name: Alois
  full_name: Schlögl, Alois
  id: 45BF87EE-F248-11E8-B48F-1D18A9856A87
  last_name: Schlögl
  orcid: 0000-0002-5621-8100
- first_name: David H
  full_name: Vandael, David H
  id: 3AE48E0A-F248-11E8-B48F-1D18A9856A87
  last_name: Vandael
  orcid: 0000-0001-7577-1676
- first_name: Peter M
  full_name: Jonas, Peter M
  id: 353C1B58-F248-11E8-B48F-1D18A9856A87
  last_name: Jonas
  orcid: 0000-0001-5001-4804
citation:
  ama: 'Zhang X, Schlögl A, Vandael DH, Jonas PM. MOD: A novel machine-learning optimal-filtering
    method for accurate and efficient detection of subthreshold synaptic events in
    vivo. <i>Journal of Neuroscience Methods</i>. 2021;357(6). doi:<a href="https://doi.org/10.1016/j.jneumeth.2021.109125">10.1016/j.jneumeth.2021.109125</a>'
  apa: 'Zhang, X., Schlögl, A., Vandael, D. H., &#38; Jonas, P. M. (2021). MOD: A
    novel machine-learning optimal-filtering method for accurate and efficient detection
    of subthreshold synaptic events in vivo. <i>Journal of Neuroscience Methods</i>.
    Elsevier. <a href="https://doi.org/10.1016/j.jneumeth.2021.109125">https://doi.org/10.1016/j.jneumeth.2021.109125</a>'
  chicago: 'Zhang, Xiaomin, Alois Schlögl, David H Vandael, and Peter M Jonas. “MOD:
    A Novel Machine-Learning Optimal-Filtering Method for Accurate and Efficient Detection
    of Subthreshold Synaptic Events in Vivo.” <i>Journal of Neuroscience Methods</i>.
    Elsevier, 2021. <a href="https://doi.org/10.1016/j.jneumeth.2021.109125">https://doi.org/10.1016/j.jneumeth.2021.109125</a>.'
  ieee: 'X. Zhang, A. Schlögl, D. H. Vandael, and P. M. Jonas, “MOD: A novel machine-learning
    optimal-filtering method for accurate and efficient detection of subthreshold
    synaptic events in vivo,” <i>Journal of Neuroscience Methods</i>, vol. 357, no.
    6. Elsevier, 2021.'
  ista: 'Zhang X, Schlögl A, Vandael DH, Jonas PM. 2021. MOD: A novel machine-learning
    optimal-filtering method for accurate and efficient detection of subthreshold
    synaptic events in vivo. Journal of Neuroscience Methods. 357(6), 109125.'
  mla: 'Zhang, Xiaomin, et al. “MOD: A Novel Machine-Learning Optimal-Filtering Method
    for Accurate and Efficient Detection of Subthreshold Synaptic Events in Vivo.”
    <i>Journal of Neuroscience Methods</i>, vol. 357, no. 6, 109125, Elsevier, 2021,
    doi:<a href="https://doi.org/10.1016/j.jneumeth.2021.109125">10.1016/j.jneumeth.2021.109125</a>.'
  short: X. Zhang, A. Schlögl, D.H. Vandael, P.M. Jonas, Journal of Neuroscience Methods
    357 (2021).
date_created: 2021-04-18T22:01:39Z
date_published: 2021-03-09T00:00:00Z
date_updated: 2023-08-07T14:36:14Z
day: '09'
ddc:
- '570'
department:
- _id: PeJo
- _id: ScienComp
doi: 10.1016/j.jneumeth.2021.109125
ec_funded: 1
external_id:
  isi:
  - '000661088500005'
file:
- access_level: open_access
  checksum: 2a5800d91b96d08b525e17319dcd5e44
  content_type: application/pdf
  creator: dernst
  date_created: 2021-04-19T08:30:22Z
  date_updated: 2021-04-19T08:30:22Z
  file_id: '9339'
  file_name: 2021_JourNeuroscienceMeth_Zhang.pdf
  file_size: 6924738
  relation: main_file
  success: 1
file_date_updated: 2021-04-19T08:30:22Z
has_accepted_license: '1'
intvolume: '       357'
isi: 1
issue: '6'
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
project:
- _id: 25B7EB9E-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '692692'
  name: Biophysics and circuit function of a giant cortical glumatergic synapse
- _id: 25C5A090-B435-11E9-9278-68D0E5697425
  call_identifier: FWF
  grant_number: Z00312
  name: The Wittgenstein Prize
publication: Journal of Neuroscience Methods
publication_identifier:
  eissn:
  - 1872-678X
  issn:
  - 0165-0270
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'MOD: A novel machine-learning optimal-filtering method for accurate and efficient
  detection of subthreshold synaptic events in vivo'
tmp:
  image: /images/cc_by_nc_nd.png
  legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
  name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
    (CC BY-NC-ND 4.0)
  short: CC BY-NC-ND (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 357
year: '2021'
...
---
_id: '7406'
abstract:
- lang: eng
  text: "Background\r\nSynaptic vesicles (SVs) are an integral part of the neurotransmission
    machinery, and isolation of SVs from their host neuron is necessary to reveal
    their most fundamental biochemical and functional properties in in vitro assays.
    Isolated SVs from neurons that have been genetically engineered, e.g. to introduce
    genetically encoded indicators, are not readily available but would permit new
    insights into SV structure and function. Furthermore, it is unclear if cultured
    neurons can provide sufficient starting material for SV isolation procedures.\r\n\r\nNew
    method\r\nHere, we demonstrate an efficient ex vivo procedure to obtain functional
    SVs from cultured rat cortical neurons after genetic engineering with a lentivirus.\r\n\r\nResults\r\nWe
    show that ∼108 plated cortical neurons allow isolation of suitable SV amounts
    for functional analysis and imaging. We found that SVs isolated from cultured
    neurons have neurotransmitter uptake comparable to that of SVs isolated from intact
    cortex. Using total internal reflection fluorescence (TIRF) microscopy, we visualized
    an exogenous SV-targeted marker protein and demonstrated the high efficiency of
    SV modification.\r\n\r\nComparison with existing methods\r\nObtaining SVs from
    genetically engineered neurons currently generally requires the availability of
    transgenic animals, which is constrained by technical (e.g. cost and time) and
    biological (e.g. developmental defects and lethality) limitations.\r\n\r\nConclusions\r\nThese
    results demonstrate the modification and isolation of functional SVs using cultured
    neurons and viral transduction. The ability to readily obtain SVs from genetically
    engineered neurons will permit linking in situ studies to in vitro experiments
    in a variety of genetic contexts."
acknowledged_ssus:
- _id: Bio
- _id: EM-Fac
article_processing_charge: No
article_type: original
author:
- first_name: Catherine
  full_name: Mckenzie, Catherine
  id: 3EEDE19A-F248-11E8-B48F-1D18A9856A87
  last_name: Mckenzie
- first_name: Miroslava
  full_name: Spanova, Miroslava
  id: 44A924DC-F248-11E8-B48F-1D18A9856A87
  last_name: Spanova
- first_name: Alexander J
  full_name: Johnson, Alexander J
  id: 46A62C3A-F248-11E8-B48F-1D18A9856A87
  last_name: Johnson
  orcid: 0000-0002-2739-8843
- first_name: Stephanie
  full_name: Kainrath, Stephanie
  id: 32CFBA64-F248-11E8-B48F-1D18A9856A87
  last_name: Kainrath
- first_name: Vanessa
  full_name: Zheden, Vanessa
  id: 39C5A68A-F248-11E8-B48F-1D18A9856A87
  last_name: Zheden
  orcid: 0000-0002-9438-4783
- first_name: Harald H.
  full_name: Sitte, Harald H.
  last_name: Sitte
- first_name: Harald L
  full_name: Janovjak, Harald L
  id: 33BA6C30-F248-11E8-B48F-1D18A9856A87
  last_name: Janovjak
  orcid: 0000-0002-8023-9315
citation:
  ama: Mckenzie C, Spanova M, Johnson AJ, et al. Isolation of synaptic vesicles from
    genetically engineered cultured neurons. <i>Journal of Neuroscience Methods</i>.
    2019;312:114-121. doi:<a href="https://doi.org/10.1016/j.jneumeth.2018.11.018">10.1016/j.jneumeth.2018.11.018</a>
  apa: Mckenzie, C., Spanova, M., Johnson, A. J., Kainrath, S., Zheden, V., Sitte,
    H. H., &#38; Janovjak, H. L. (2019). Isolation of synaptic vesicles from genetically
    engineered cultured neurons. <i>Journal of Neuroscience Methods</i>. Elsevier.
    <a href="https://doi.org/10.1016/j.jneumeth.2018.11.018">https://doi.org/10.1016/j.jneumeth.2018.11.018</a>
  chicago: Mckenzie, Catherine, Miroslava Spanova, Alexander J Johnson, Stephanie
    Kainrath, Vanessa Zheden, Harald H. Sitte, and Harald L Janovjak. “Isolation of
    Synaptic Vesicles from Genetically Engineered Cultured Neurons.” <i>Journal of
    Neuroscience Methods</i>. Elsevier, 2019. <a href="https://doi.org/10.1016/j.jneumeth.2018.11.018">https://doi.org/10.1016/j.jneumeth.2018.11.018</a>.
  ieee: C. Mckenzie <i>et al.</i>, “Isolation of synaptic vesicles from genetically
    engineered cultured neurons,” <i>Journal of Neuroscience Methods</i>, vol. 312.
    Elsevier, pp. 114–121, 2019.
  ista: Mckenzie C, Spanova M, Johnson AJ, Kainrath S, Zheden V, Sitte HH, Janovjak
    HL. 2019. Isolation of synaptic vesicles from genetically engineered cultured
    neurons. Journal of Neuroscience Methods. 312, 114–121.
  mla: Mckenzie, Catherine, et al. “Isolation of Synaptic Vesicles from Genetically
    Engineered Cultured Neurons.” <i>Journal of Neuroscience Methods</i>, vol. 312,
    Elsevier, 2019, pp. 114–21, doi:<a href="https://doi.org/10.1016/j.jneumeth.2018.11.018">10.1016/j.jneumeth.2018.11.018</a>.
  short: C. Mckenzie, M. Spanova, A.J. Johnson, S. Kainrath, V. Zheden, H.H. Sitte,
    H.L. Janovjak, Journal of Neuroscience Methods 312 (2019) 114–121.
date_created: 2020-01-30T09:12:19Z
date_published: 2019-01-15T00:00:00Z
date_updated: 2023-09-06T15:27:29Z
day: '15'
department:
- _id: HaJa
- _id: Bio
doi: 10.1016/j.jneumeth.2018.11.018
ec_funded: 1
external_id:
  isi:
  - '000456220900013'
  pmid:
  - '30496761'
intvolume: '       312'
isi: 1
language:
- iso: eng
month: '01'
oa_version: None
page: 114-121
pmid: 1
project:
- _id: 25548C20-B435-11E9-9278-68D0E5697425
  call_identifier: FP7
  grant_number: '303564'
  name: Microbial Ion Channels for Synthetic Neurobiology
- _id: 26538374-B435-11E9-9278-68D0E5697425
  call_identifier: FWF
  grant_number: I03630
  name: Molecular mechanisms of endocytic cargo recognition in plants
- _id: 2548AE96-B435-11E9-9278-68D0E5697425
  call_identifier: FWF
  grant_number: W1232-B24
  name: Molecular Drug Targets
publication: Journal of Neuroscience Methods
publication_identifier:
  issn:
  - 0165-0270
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: Isolation of synaptic vesicles from genetically engineered cultured neurons
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 312
year: '2019'
...
---
_id: '3517'
abstract:
- lang: eng
  text: 'A modular multichannel microdrive (''hyperdrive'') is described. The microdrive
    uses printed circuit board technology and flexible fused silica capillaries. The
    modular design allows for the fabrication of 4-32 independently movable electrodes
    or `tetrodes''. The drives are re-usable and re-loading the drive with electrodes
    is simple. '
article_processing_charge: No
article_type: original
author:
- first_name: Imre
  full_name: Szabo, Imre
  last_name: Szabo
- first_name: András
  full_name: Czurkó, András
  last_name: Czurkó
- first_name: Jozsef L
  full_name: Csicsvari, Jozsef L
  id: 3FA14672-F248-11E8-B48F-1D18A9856A87
  last_name: Csicsvari
  orcid: 0000-0002-5193-4036
- first_name: Hajima
  full_name: Hirase, Hajima
  last_name: Hirase
- first_name: Xavier
  full_name: Leinekugel, Xavier
  last_name: Leinekugel
- first_name: György
  full_name: Buzsáki, György
  last_name: Buzsáki
citation:
  ama: Szabo I, Czurkó A, Csicsvari JL, Hirase H, Leinekugel X, Buzsáki G. The application
    of printed circuit board technology for fabrication of multi-channel micro-drives.
    <i>Journal of Neuroscience Methods</i>. 2001;105(1):105-110. doi:<a href="https://doi.org/10.1016/S0165-0270(00)00362-9">10.1016/S0165-0270(00)00362-9</a>
  apa: Szabo, I., Czurkó, A., Csicsvari, J. L., Hirase, H., Leinekugel, X., &#38;
    Buzsáki, G. (2001). The application of printed circuit board technology for fabrication
    of multi-channel micro-drives. <i>Journal of Neuroscience Methods</i>. Elsevier.
    <a href="https://doi.org/10.1016/S0165-0270(00)00362-9">https://doi.org/10.1016/S0165-0270(00)00362-9</a>
  chicago: Szabo, Imre, András Czurkó, Jozsef L Csicsvari, Hajima Hirase, Xavier Leinekugel,
    and György Buzsáki. “The Application of Printed Circuit Board Technology for Fabrication
    of Multi-Channel Micro-Drives.” <i>Journal of Neuroscience Methods</i>. Elsevier,
    2001. <a href="https://doi.org/10.1016/S0165-0270(00)00362-9">https://doi.org/10.1016/S0165-0270(00)00362-9</a>.
  ieee: I. Szabo, A. Czurkó, J. L. Csicsvari, H. Hirase, X. Leinekugel, and G. Buzsáki,
    “The application of printed circuit board technology for fabrication of multi-channel
    micro-drives,” <i>Journal of Neuroscience Methods</i>, vol. 105, no. 1. Elsevier,
    pp. 105–110, 2001.
  ista: Szabo I, Czurkó A, Csicsvari JL, Hirase H, Leinekugel X, Buzsáki G. 2001.
    The application of printed circuit board technology for fabrication of multi-channel
    micro-drives. Journal of Neuroscience Methods. 105(1), 105–110.
  mla: Szabo, Imre, et al. “The Application of Printed Circuit Board Technology for
    Fabrication of Multi-Channel Micro-Drives.” <i>Journal of Neuroscience Methods</i>,
    vol. 105, no. 1, Elsevier, 2001, pp. 105–10, doi:<a href="https://doi.org/10.1016/S0165-0270(00)00362-9">10.1016/S0165-0270(00)00362-9</a>.
  short: I. Szabo, A. Czurkó, J.L. Csicsvari, H. Hirase, X. Leinekugel, G. Buzsáki,
    Journal of Neuroscience Methods 105 (2001) 105–110.
date_created: 2018-12-11T12:03:45Z
date_published: 2001-01-30T00:00:00Z
date_updated: 2023-05-15T10:50:39Z
day: '30'
doi: 10.1016/S0165-0270(00)00362-9
extern: '1'
external_id:
  pmid:
  - '11166371'
intvolume: '       105'
issue: '1'
language:
- iso: eng
month: '01'
oa_version: None
page: 105 - 110
pmid: 1
publication: Journal of Neuroscience Methods
publication_identifier:
  issn:
  - 0165-0270
publication_status: published
publisher: Elsevier
publist_id: '2868'
quality_controlled: '1'
scopus_import: '1'
status: public
title: The application of printed circuit board technology for fabrication of multi-channel
  micro-drives
type: journal_article
user_id: ea97e931-d5af-11eb-85d4-e6957dddbf17
volume: 105
year: '2001'
...