---
_id: '9438'
abstract:
- lang: eng
text: Rigorous investigation of synaptic transmission requires analysis of unitary
synaptic events by simultaneous recording from presynaptic terminals and postsynaptic
target neurons. However, this has been achieved at only a limited number of model
synapses, including the squid giant synapse and the mammalian calyx of Held. Cortical
presynaptic terminals have been largely inaccessible to direct presynaptic recording,
due to their small size. Here, we describe a protocol for improved subcellular
patch-clamp recording in rat and mouse brain slices, with the synapse in a largely
intact environment. Slice preparation takes ~2 h, recording ~3 h and post hoc
morphological analysis 2 d. Single presynaptic hippocampal mossy fiber terminals
are stimulated minimally invasively in the bouton-attached configuration, in which
the cytoplasmic content remains unperturbed, or in the whole-bouton configuration,
in which the cytoplasmic composition can be precisely controlled. Paired pre–postsynaptic
recordings can be integrated with biocytin labeling and morphological analysis,
allowing correlative investigation of synapse structure and function. Paired recordings
can be obtained from mossy fiber terminals in slices from both rats and mice,
implying applicability to genetically modified synapses. Paired recordings can
also be performed together with axon tract stimulation or optogenetic activation,
allowing comparison of unitary and compound synaptic events in the same target
cell. Finally, paired recordings can be combined with spontaneous event analysis,
permitting collection of miniature events generated at a single identified synapse.
In conclusion, the subcellular patch-clamp techniques detailed here should facilitate
analysis of biophysics, plasticity and circuit function of cortical synapses in
the mammalian central nervous system.
acknowledged_ssus:
- _id: M-Shop
acknowledgement: This project received funding from the European Research Council
(ERC) under the European Union’s Horizon 2020 research and innovation programme
(grant agreement no. 692692 to P.J.) and the Fond zur Förderung der Wissenschaftlichen
Forschung (Z 312-B27, Wittgenstein award to P.J., V 739-B27 to C.B.M.). We are grateful
to F. Marr and C. Altmutter for excellent technical assistance and cell reconstruction,
E. Kralli-Beller for manuscript editing, and the Scientific Service Units of IST
Austria, especially T. Asenov and Miba machine shop, for maximally efficient support.
article_processing_charge: No
article_type: original
author:
- 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: Yuji
full_name: Okamoto, Yuji
id: 3337E116-F248-11E8-B48F-1D18A9856A87
last_name: Okamoto
orcid: 0000-0003-0408-6094
- first_name: Carolina
full_name: Borges Merjane, Carolina
id: 4305C450-F248-11E8-B48F-1D18A9856A87
last_name: Borges Merjane
orcid: 0000-0003-0005-401X
- first_name: Victor M
full_name: Vargas Barroso, Victor M
id: 2F55A9DE-F248-11E8-B48F-1D18A9856A87
last_name: Vargas Barroso
- first_name: Benjamin
full_name: Suter, Benjamin
id: 4952F31E-F248-11E8-B48F-1D18A9856A87
last_name: Suter
orcid: 0000-0002-9885-6936
- 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: Vandael DH, Okamoto Y, Borges Merjane C, Vargas Barroso VM, Suter B, Jonas
PM. Subcellular patch-clamp techniques for single-bouton stimulation and simultaneous
pre- and postsynaptic recording at cortical synapses. Nature Protocols.
2021;16(6):2947–2967. doi:10.1038/s41596-021-00526-0
apa: Vandael, D. H., Okamoto, Y., Borges Merjane, C., Vargas Barroso, V. M., Suter,
B., & Jonas, P. M. (2021). Subcellular patch-clamp techniques for single-bouton
stimulation and simultaneous pre- and postsynaptic recording at cortical synapses.
Nature Protocols. Springer Nature. https://doi.org/10.1038/s41596-021-00526-0
chicago: Vandael, David H, Yuji Okamoto, Carolina Borges Merjane, Victor M Vargas
Barroso, Benjamin Suter, and Peter M Jonas. “Subcellular Patch-Clamp Techniques
for Single-Bouton Stimulation and Simultaneous Pre- and Postsynaptic Recording
at Cortical Synapses.” Nature Protocols. Springer Nature, 2021. https://doi.org/10.1038/s41596-021-00526-0.
ieee: D. H. Vandael, Y. Okamoto, C. Borges Merjane, V. M. Vargas Barroso, B. Suter,
and P. M. Jonas, “Subcellular patch-clamp techniques for single-bouton stimulation
and simultaneous pre- and postsynaptic recording at cortical synapses,” Nature
Protocols, vol. 16, no. 6. Springer Nature, pp. 2947–2967, 2021.
ista: Vandael DH, Okamoto Y, Borges Merjane C, Vargas Barroso VM, Suter B, Jonas
PM. 2021. Subcellular patch-clamp techniques for single-bouton stimulation and
simultaneous pre- and postsynaptic recording at cortical synapses. Nature Protocols.
16(6), 2947–2967.
mla: Vandael, David H., et al. “Subcellular Patch-Clamp Techniques for Single-Bouton
Stimulation and Simultaneous Pre- and Postsynaptic Recording at Cortical Synapses.”
Nature Protocols, vol. 16, no. 6, Springer Nature, 2021, pp. 2947–2967,
doi:10.1038/s41596-021-00526-0.
short: D.H. Vandael, Y. Okamoto, C. Borges Merjane, V.M. Vargas Barroso, B. Suter,
P.M. Jonas, Nature Protocols 16 (2021) 2947–2967.
date_created: 2021-05-30T22:01:24Z
date_published: 2021-06-01T00:00:00Z
date_updated: 2023-08-10T22:30:51Z
day: '01'
ddc:
- '570'
department:
- _id: PeJo
doi: 10.1038/s41596-021-00526-0
ec_funded: 1
external_id:
isi:
- '000650528700003'
pmid:
- '33990799'
file:
- access_level: open_access
checksum: 7eb580abd8893cdb0b410cf41bc8c263
content_type: application/pdf
creator: cziletti
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date_updated: 2021-12-02T23:30:05Z
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oa: 1
oa_version: Submitted Version
page: 2947–2967
pmid: 1
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
- _id: 2696E7FE-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: V00739
name: Structural plasticity at mossy fiber-CA3 synapses
publication: Nature Protocols
publication_identifier:
eissn:
- '17502799'
issn:
- '17542189'
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Subcellular patch-clamp techniques for single-bouton stimulation and simultaneous
pre- and postsynaptic recording at cortical synapses
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 16
year: '2021'
...
---
_id: '10816'
abstract:
- lang: eng
text: Pattern separation is a fundamental brain computation that converts small
differences in input patterns into large differences in output patterns. Several
synaptic mechanisms of pattern separation have been proposed, including code expansion,
inhibition and plasticity; however, which of these mechanisms play a role in the
entorhinal cortex (EC)–dentate gyrus (DG)–CA3 circuit, a classical pattern separation
circuit, remains unclear. Here we show that a biologically realistic, full-scale
EC–DG–CA3 circuit model, including granule cells (GCs) and parvalbumin-positive
inhibitory interneurons (PV+-INs) in the DG, is an efficient pattern separator.
Both external gamma-modulated inhibition and internal lateral inhibition mediated
by PV+-INs substantially contributed to pattern separation. Both local connectivity
and fast signaling at GC–PV+-IN synapses were important for maximum effectiveness.
Similarly, mossy fiber synapses with conditional detonator properties contributed
to pattern separation. By contrast, perforant path synapses with Hebbian synaptic
plasticity and direct EC–CA3 connection shifted the network towards pattern completion.
Our results demonstrate that the specific properties of cells and synapses optimize
higher-order computations in biological networks and might be useful to improve
the deep learning capabilities of technical networks.
acknowledged_ssus:
- _id: SSU
acknowledgement: We thank A. Aertsen, N. Kopell, W. Maass, A. Roth, F. Stella and
T. Vogels for critically reading earlier versions of the manuscript. We are grateful
to F. Marr and C. Altmutter for excellent technical assistance, E. Kralli-Beller
for manuscript editing, and the Scientific Service Units of IST Austria for efficient
support. Finally, we thank T. Carnevale, L. Erdös, M. Hines, D. Nykamp and D. Schröder
for useful discussions, and R. Friedrich and S. Wiechert for sharing unpublished
data. This project received funding from the European Research Council (ERC) under
the European Union’s Horizon 2020 research and innovation programme (grant agreement
no. 692692, P.J.) and the Fond zur Förderung der Wissenschaftlichen Forschung (Z
312-B27, Wittgenstein award to P.J. and P 31815 to S.J.G.).
article_processing_charge: No
article_type: original
author:
- first_name: José
full_name: Guzmán, José
id: 30CC5506-F248-11E8-B48F-1D18A9856A87
last_name: Guzmán
orcid: 0000-0003-2209-5242
- first_name: Alois
full_name: Schlögl, Alois
id: 45BF87EE-F248-11E8-B48F-1D18A9856A87
last_name: Schlögl
orcid: 0000-0002-5621-8100
- first_name: 'Claudia '
full_name: 'Espinoza Martinez, Claudia '
id: 31FFEE2E-F248-11E8-B48F-1D18A9856A87
last_name: Espinoza Martinez
orcid: 0000-0003-4710-2082
- first_name: Xiaomin
full_name: Zhang, Xiaomin
id: 423EC9C2-F248-11E8-B48F-1D18A9856A87
last_name: Zhang
- first_name: Benjamin
full_name: Suter, Benjamin
id: 4952F31E-F248-11E8-B48F-1D18A9856A87
last_name: Suter
orcid: 0000-0002-9885-6936
- 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: Guzmán J, Schlögl A, Espinoza Martinez C, Zhang X, Suter B, Jonas PM. How connectivity
rules and synaptic properties shape the efficacy of pattern separation in the
entorhinal cortex–dentate gyrus–CA3 network. Nature Computational Science.
2021;1(12):830-842. doi:10.1038/s43588-021-00157-1
apa: Guzmán, J., Schlögl, A., Espinoza Martinez, C., Zhang, X., Suter, B., &
Jonas, P. M. (2021). How connectivity rules and synaptic properties shape the
efficacy of pattern separation in the entorhinal cortex–dentate gyrus–CA3 network.
Nature Computational Science. Springer Nature. https://doi.org/10.1038/s43588-021-00157-1
chicago: Guzmán, José, Alois Schlögl, Claudia Espinoza Martinez, Xiaomin Zhang,
Benjamin Suter, and Peter M Jonas. “How Connectivity Rules and Synaptic Properties
Shape the Efficacy of Pattern Separation in the Entorhinal Cortex–Dentate Gyrus–CA3
Network.” Nature Computational Science. Springer Nature, 2021. https://doi.org/10.1038/s43588-021-00157-1.
ieee: J. Guzmán, A. Schlögl, C. Espinoza Martinez, X. Zhang, B. Suter, and P. M.
Jonas, “How connectivity rules and synaptic properties shape the efficacy of pattern
separation in the entorhinal cortex–dentate gyrus–CA3 network,” Nature Computational
Science, vol. 1, no. 12. Springer Nature, pp. 830–842, 2021.
ista: Guzmán J, Schlögl A, Espinoza Martinez C, Zhang X, Suter B, Jonas PM. 2021.
How connectivity rules and synaptic properties shape the efficacy of pattern separation
in the entorhinal cortex–dentate gyrus–CA3 network. Nature Computational Science.
1(12), 830–842.
mla: Guzmán, José, et al. “How Connectivity Rules and Synaptic Properties Shape
the Efficacy of Pattern Separation in the Entorhinal Cortex–Dentate Gyrus–CA3
Network.” Nature Computational Science, vol. 1, no. 12, Springer Nature,
2021, pp. 830–42, doi:10.1038/s43588-021-00157-1.
short: J. Guzmán, A. Schlögl, C. Espinoza Martinez, X. Zhang, B. Suter, P.M. Jonas,
Nature Computational Science 1 (2021) 830–842.
date_created: 2022-03-04T08:32:36Z
date_published: 2021-12-16T00:00:00Z
date_updated: 2023-08-10T22:30:10Z
day: '16'
ddc:
- '610'
department:
- _id: PeJo
doi: 10.1038/s43588-021-00157-1
ec_funded: 1
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project:
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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: Nature Computational Science
publication_identifier:
issn:
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quality_controlled: '1'
related_material:
link:
- relation: press_release
url: https://ista.ac.at/en/news/spot-the-difference/
record:
- id: '10110'
relation: software
status: public
scopus_import: '1'
status: public
title: How connectivity rules and synaptic properties shape the efficacy of pattern
separation in the entorhinal cortex–dentate gyrus–CA3 network
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 1
year: '2021'
...
---
_id: '10110'
abstract:
- lang: eng
text: Pattern separation is a fundamental brain computation that converts small
differences in input patterns into large differences in output patterns. Several
synaptic mechanisms of pattern separation have been proposed, including code expansion,
inhibition and plasticity; however, which of these mechanisms play a role in the
entorhinal cortex (EC)–dentate gyrus (DG)–CA3 circuit, a classical pattern separation
circuit, remains unclear. Here we show that a biologically realistic, full-scale
EC–DG–CA3 circuit model, including granule cells (GCs) and parvalbumin-positive
inhibitory interneurons (PV+-INs) in the DG, is an efficient pattern separator.
Both external gamma-modulated inhibition and internal lateral inhibition mediated
by PV+-INs substantially contributed to pattern separation. Both local connectivity
and fast signaling at GC–PV+-IN synapses were important for maximum effectiveness.
Similarly, mossy fiber synapses with conditional detonator properties contributed
to pattern separation. By contrast, perforant path synapses with Hebbian synaptic
plasticity and direct EC–CA3 connection shifted the network towards pattern completion.
Our results demonstrate that the specific properties of cells and synapses optimize
higher-order computations in biological networks and might be useful to improve
the deep learning capabilities of technical networks.
author:
- first_name: José
full_name: Guzmán, José
id: 30CC5506-F248-11E8-B48F-1D18A9856A87
last_name: Guzmán
orcid: 0000-0003-2209-5242
- first_name: Alois
full_name: Schlögl, Alois
id: 45BF87EE-F248-11E8-B48F-1D18A9856A87
last_name: Schlögl
orcid: 0000-0002-5621-8100
- first_name: 'Claudia '
full_name: 'Espinoza Martinez, Claudia '
id: 31FFEE2E-F248-11E8-B48F-1D18A9856A87
last_name: Espinoza Martinez
orcid: 0000-0003-4710-2082
- first_name: Xiaomin
full_name: Zhang, Xiaomin
id: 423EC9C2-F248-11E8-B48F-1D18A9856A87
last_name: Zhang
- first_name: Benjamin
full_name: Suter, Benjamin
id: 4952F31E-F248-11E8-B48F-1D18A9856A87
last_name: Suter
orcid: 0000-0002-9885-6936
- 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: Guzmán J, Schlögl A, Espinoza Martinez C, Zhang X, Suter B, Jonas PM. How connectivity
rules and synaptic properties shape the efficacy of pattern separation in the
entorhinal cortex–dentate gyrus–CA3 network. 2021. doi:10.15479/AT:ISTA:10110
apa: Guzmán, J., Schlögl, A., Espinoza Martinez, C., Zhang, X., Suter, B., &
Jonas, P. M. (2021). How connectivity rules and synaptic properties shape the
efficacy of pattern separation in the entorhinal cortex–dentate gyrus–CA3 network.
IST Austria. https://doi.org/10.15479/AT:ISTA:10110
chicago: Guzmán, José, Alois Schlögl, Claudia Espinoza Martinez, Xiaomin Zhang,
Benjamin Suter, and Peter M Jonas. “How Connectivity Rules and Synaptic Properties
Shape the Efficacy of Pattern Separation in the Entorhinal Cortex–Dentate Gyrus–CA3
Network.” IST Austria, 2021. https://doi.org/10.15479/AT:ISTA:10110.
ieee: J. Guzmán, A. Schlögl, C. Espinoza Martinez, X. Zhang, B. Suter, and P. M.
Jonas, “How connectivity rules and synaptic properties shape the efficacy of pattern
separation in the entorhinal cortex–dentate gyrus–CA3 network.” IST Austria, 2021.
ista: Guzmán J, Schlögl A, Espinoza Martinez C, Zhang X, Suter B, Jonas PM. 2021.
How connectivity rules and synaptic properties shape the efficacy of pattern separation
in the entorhinal cortex–dentate gyrus–CA3 network, IST Austria, 10.15479/AT:ISTA:10110.
mla: Guzmán, José, et al. How Connectivity Rules and Synaptic Properties Shape
the Efficacy of Pattern Separation in the Entorhinal Cortex–Dentate Gyrus–CA3
Network. IST Austria, 2021, doi:10.15479/AT:ISTA:10110.
short: J. Guzmán, A. Schlögl, C. Espinoza Martinez, X. Zhang, B. Suter, P.M. Jonas,
(2021).
date_created: 2021-10-08T06:44:22Z
date_published: 2021-12-16T00:00:00Z
date_updated: 2024-03-27T23:30:11Z
day: '16'
ddc:
- '005'
department:
- _id: PeJo
- _id: ScienComp
doi: 10.15479/AT:ISTA:10110
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link:
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relation: press_release
url: https://ist.ac.at/en/news/spot-the-difference/
record:
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relation: used_for_analysis_in
status: public
status: public
title: How connectivity rules and synaptic properties shape the efficacy of pattern
separation in the entorhinal cortex–dentate gyrus–CA3 network
tmp:
legal_code_url: https://www.gnu.org/licenses/gpl-3.0.en.html
name: GNU General Public License 3.0
short: GPL 3.0
type: software
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2021'
...
---
_id: '7405'
abstract:
- lang: eng
text: Biophysical modeling of neuronal networks helps to integrate and interpret
rapidly growing and disparate experimental datasets at multiple scales. The NetPyNE
tool (www.netpyne.org) provides both programmatic and graphical interfaces to
develop data-driven multiscale network models in NEURON. NetPyNE clearly separates
model parameters from implementation code. Users provide specifications at a high
level via a standardized declarative language, for example connectivity rules,
to create millions of cell-to-cell connections. NetPyNE then enables users to
generate the NEURON network, run efficiently parallelized simulations, optimize
and explore network parameters through automated batch runs, and use built-in
functions for visualization and analysis – connectivity matrices, voltage traces,
spike raster plots, local field potentials, and information theoretic measures.
NetPyNE also facilitates model sharing by exporting and importing standardized
formats (NeuroML and SONATA). NetPyNE is already being used to teach computational
neuroscience students and by modelers to investigate brain regions and phenomena.
article_number: e44494
article_processing_charge: No
article_type: original
author:
- first_name: Salvador
full_name: Dura-Bernal, Salvador
last_name: Dura-Bernal
- first_name: Benjamin
full_name: Suter, Benjamin
id: 4952F31E-F248-11E8-B48F-1D18A9856A87
last_name: Suter
orcid: 0000-0002-9885-6936
- first_name: Padraig
full_name: Gleeson, Padraig
last_name: Gleeson
- first_name: Matteo
full_name: Cantarelli, Matteo
last_name: Cantarelli
- first_name: Adrian
full_name: Quintana, Adrian
last_name: Quintana
- first_name: Facundo
full_name: Rodriguez, Facundo
last_name: Rodriguez
- first_name: David J
full_name: Kedziora, David J
last_name: Kedziora
- first_name: George L
full_name: Chadderdon, George L
last_name: Chadderdon
- first_name: Cliff C
full_name: Kerr, Cliff C
last_name: Kerr
- first_name: Samuel A
full_name: Neymotin, Samuel A
last_name: Neymotin
- first_name: Robert A
full_name: McDougal, Robert A
last_name: McDougal
- first_name: Michael
full_name: Hines, Michael
last_name: Hines
- first_name: Gordon MG
full_name: Shepherd, Gordon MG
last_name: Shepherd
- first_name: William W
full_name: Lytton, William W
last_name: Lytton
citation:
ama: Dura-Bernal S, Suter B, Gleeson P, et al. NetPyNE, a tool for data-driven multiscale
modeling of brain circuits. eLife. 2019;8. doi:10.7554/elife.44494
apa: Dura-Bernal, S., Suter, B., Gleeson, P., Cantarelli, M., Quintana, A., Rodriguez,
F., … Lytton, W. W. (2019). NetPyNE, a tool for data-driven multiscale modeling
of brain circuits. ELife. eLife Sciences Publications. https://doi.org/10.7554/elife.44494
chicago: Dura-Bernal, Salvador, Benjamin Suter, Padraig Gleeson, Matteo Cantarelli,
Adrian Quintana, Facundo Rodriguez, David J Kedziora, et al. “NetPyNE, a Tool
for Data-Driven Multiscale Modeling of Brain Circuits.” ELife. eLife Sciences
Publications, 2019. https://doi.org/10.7554/elife.44494.
ieee: S. Dura-Bernal et al., “NetPyNE, a tool for data-driven multiscale
modeling of brain circuits,” eLife, vol. 8. eLife Sciences Publications,
2019.
ista: Dura-Bernal S, Suter B, Gleeson P, Cantarelli M, Quintana A, Rodriguez F,
Kedziora DJ, Chadderdon GL, Kerr CC, Neymotin SA, McDougal RA, Hines M, Shepherd
GM, Lytton WW. 2019. NetPyNE, a tool for data-driven multiscale modeling of brain
circuits. eLife. 8, e44494.
mla: Dura-Bernal, Salvador, et al. “NetPyNE, a Tool for Data-Driven Multiscale Modeling
of Brain Circuits.” ELife, vol. 8, e44494, eLife Sciences Publications,
2019, doi:10.7554/elife.44494.
short: S. Dura-Bernal, B. Suter, P. Gleeson, M. Cantarelli, A. Quintana, F. Rodriguez,
D.J. Kedziora, G.L. Chadderdon, C.C. Kerr, S.A. Neymotin, R.A. McDougal, M. Hines,
G.M. Shepherd, W.W. Lytton, ELife 8 (2019).
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title: NetPyNE, a tool for data-driven multiscale modeling of brain circuits
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...