---
_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for useful discussions, and R. Friedrich and S. Wiechert for sharing unpublished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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page: 830-842
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:
- 2662-8457
publication_status: published
publisher: Springer Nature
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related_material:
link:
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status: public
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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: '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. Journal of Neuroscience Methods. 2021;357(6). doi:10.1016/j.jneumeth.2021.109125'
apa: 'Zhang, X., Schlögl, A., Vandael, D. H., & Jonas, P. M. (2021). MOD: A
novel machine-learning optimal-filtering method for accurate and efficient detection
of subthreshold synaptic events in vivo. Journal of Neuroscience Methods.
Elsevier. https://doi.org/10.1016/j.jneumeth.2021.109125'
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.” Journal of Neuroscience Methods.
Elsevier, 2021. https://doi.org/10.1016/j.jneumeth.2021.109125.'
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,” Journal of Neuroscience Methods, 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.”
Journal of Neuroscience Methods, vol. 357, no. 6, 109125, Elsevier, 2021,
doi:10.1016/j.jneumeth.2021.109125.'
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
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file_name: 2021_JourNeuroscienceMeth_Zhang.pdf
file_size: 6924738
relation: main_file
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has_accepted_license: '1'
intvolume: ' 357'
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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
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(CC BY-NC-ND 4.0)
short: CC BY-NC-ND (4.0)
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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: 2024-03-25T23:30:07Z
day: '16'
ddc:
- '005'
department:
- _id: PeJo
- _id: ScienComp
doi: 10.15479/AT:ISTA:10110
file:
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checksum: f92f8931cad0aa7e411c1715337bf408
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creator: cchlebak
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publisher: IST Austria
related_material:
link:
- description: News on IST Webpage
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: '8001'
abstract:
- lang: eng
text: Post-tetanic potentiation (PTP) is an attractive candidate mechanism for hippocampus-dependent
short-term memory. Although PTP has a uniquely large magnitude at hippocampal
mossy fiber-CA3 pyramidal neuron synapses, it is unclear whether it can be induced
by natural activity and whether its lifetime is sufficient to support short-term
memory. We combined in vivo recordings from granule cells (GCs), in vitro paired
recordings from mossy fiber terminals and postsynaptic CA3 neurons, and “flash
and freeze” electron microscopy. PTP was induced at single synapses and showed
a low induction threshold adapted to sparse GC activity in vivo. PTP was mainly
generated by enlargement of the readily releasable pool of synaptic vesicles,
allowing multiplicative interaction with other plasticity forms. PTP was associated
with an increase in the docked vesicle pool, suggesting formation of structural
“pool engrams.” Absence of presynaptic activity extended the lifetime of the potentiation,
enabling prolonged information storage in the hippocampal network.
acknowledged_ssus:
- _id: SSU
acknowledgement: This project received funding from the European Research Council
(ERC) under the European Union Horizon 2020 Research and Innovation Program (grant
agreement 692692 to P.J.) and the Fond zur Förderung der Wissenschaftlichen Forschung
( Z 312-B27 , Wittgenstein award to P.J. and V 739-B27 to C.B.-M.). We thank Drs.
Jozsef Csicsvari, Jose Guzman, Erwin Neher, and Ryuichi Shigemoto for commenting
on earlier versions of the manuscript. We are grateful to Walter Kaufmann, Daniel
Gütl, and Vanessa Zheden for EM training; Alois Schlögl for programming; Florian
Marr for excellent technical assistance and cell reconstruction; Christina Altmutter
for technical help; Eleftheria Kralli-Beller for manuscript editing; Taija Makinen
for providing the Prox1-CreERT2 mouse line; and the Scientific Service Units of
IST Austria for 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: Carolina
full_name: Borges Merjane, Carolina
id: 4305C450-F248-11E8-B48F-1D18A9856A87
last_name: Borges Merjane
orcid: 0000-0003-0005-401X
- first_name: Xiaomin
full_name: Zhang, Xiaomin
id: 423EC9C2-F248-11E8-B48F-1D18A9856A87
last_name: Zhang
- 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, Borges Merjane C, Zhang X, Jonas PM. Short-term plasticity at hippocampal
mossy fiber synapses is induced by natural activity patterns and associated with
vesicle pool engram formation. Neuron. 2020;107(3):509-521. doi:10.1016/j.neuron.2020.05.013
apa: Vandael, D. H., Borges Merjane, C., Zhang, X., & Jonas, P. M. (2020). Short-term
plasticity at hippocampal mossy fiber synapses is induced by natural activity
patterns and associated with vesicle pool engram formation. Neuron. Elsevier.
https://doi.org/10.1016/j.neuron.2020.05.013
chicago: Vandael, David H, Carolina Borges Merjane, Xiaomin Zhang, and Peter M Jonas.
“Short-Term Plasticity at Hippocampal Mossy Fiber Synapses Is Induced by Natural
Activity Patterns and Associated with Vesicle Pool Engram Formation.” Neuron.
Elsevier, 2020. https://doi.org/10.1016/j.neuron.2020.05.013.
ieee: D. H. Vandael, C. Borges Merjane, X. Zhang, and P. M. Jonas, “Short-term plasticity
at hippocampal mossy fiber synapses is induced by natural activity patterns and
associated with vesicle pool engram formation,” Neuron, vol. 107, no. 3.
Elsevier, pp. 509–521, 2020.
ista: Vandael DH, Borges Merjane C, Zhang X, Jonas PM. 2020. Short-term plasticity
at hippocampal mossy fiber synapses is induced by natural activity patterns and
associated with vesicle pool engram formation. Neuron. 107(3), 509–521.
mla: Vandael, David H., et al. “Short-Term Plasticity at Hippocampal Mossy Fiber
Synapses Is Induced by Natural Activity Patterns and Associated with Vesicle Pool
Engram Formation.” Neuron, vol. 107, no. 3, Elsevier, 2020, pp. 509–21,
doi:10.1016/j.neuron.2020.05.013.
short: D.H. Vandael, C. Borges Merjane, X. Zhang, P.M. Jonas, Neuron 107 (2020)
509–521.
date_created: 2020-06-22T13:29:05Z
date_published: 2020-08-05T00:00:00Z
date_updated: 2023-08-22T07:45:25Z
day: '05'
ddc:
- '570'
department:
- _id: PeJo
doi: 10.1016/j.neuron.2020.05.013
ec_funded: 1
external_id:
isi:
- '000556135600004'
pmid:
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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
- _id: 2696E7FE-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: V00739
name: Structural plasticity at mossy fiber-CA3 synapses
publication: Neuron
publication_identifier:
eissn:
- '10974199'
issn:
- 0896-6273
publication_status: published
publisher: Elsevier
quality_controlled: '1'
related_material:
link:
- description: News on IST Homepage
relation: press_release
url: https://ist.ac.at/en/news/possible-physical-trace-of-short-term-memory-found/
scopus_import: '1'
status: public
title: Short-term plasticity at hippocampal mossy fiber synapses is induced by natural
activity patterns and associated with vesicle pool engram formation
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...
---
_id: '8261'
abstract:
- lang: eng
text: Dentate gyrus granule cells (GCs) connect the entorhinal cortex to the hippocampal
CA3 region, but how they process spatial information remains enigmatic. To examine
the role of GCs in spatial coding, we measured excitatory postsynaptic potentials
(EPSPs) and action potentials (APs) in head-fixed mice running on a linear belt.
Intracellular recording from morphologically identified GCs revealed that most
cells were active, but activity level varied over a wide range. Whereas only ∼5%
of GCs showed spatially tuned spiking, ∼50% received spatially tuned input. Thus,
the GC population broadly encodes spatial information, but only a subset relays
this information to the CA3 network. Fourier analysis indicated that GCs received
conjunctive place-grid-like synaptic input, suggesting code conversion in single
neurons. GC firing was correlated with dendritic complexity and intrinsic excitability,
but not extrinsic excitatory input or dendritic cable properties. Thus, functional
maturation may control input-output transformation and spatial code conversion.
acknowledged_ssus:
- _id: M-Shop
- _id: ScienComp
- _id: PreCl
acknowledgement: This project has received funding from the European Research Council
(ERC) under the European Union’s Horizon 2020 research and innovation program (grant
agreement 692692, P.J.) and the Fond zur Förderung der Wissenschaftlichen Forschung
(Z 312-B27, Wittgenstein award, P.J.). We thank Gyorgy Buzsáki, Jozsef Csicsvari,
Juan Ramirez Villegas, and Federico Stella for commenting on earlier versions of
this manuscript. We also thank Katie Bittner, Michael Brecht, Albert Lee, Jeffery
Magee, and Alejandro Pernía-Andrade for sharing expertise in in vivo patch-clamp
recording. We are grateful to Florian Marr for cell labeling, cell reconstruction,
and technical assistance; Ben Suter for helpful discussions; Christina Altmutter
for technical support; Eleftheria Kralli-Beller for manuscript editing; and Todor
Asenov (Machine Shop) for device construction. We also thank the Scientific Service
Units (SSUs) of IST Austria (Machine Shop, Scientific Computing, and Preclinical
Facility) for efficient support.
article_processing_charge: No
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: 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, Jonas PM. Selective routing of spatial information flow
from input to output in hippocampal granule cells. Neuron. 2020;107(6):1212-1225.
doi:10.1016/j.neuron.2020.07.006
apa: Zhang, X., Schlögl, A., & Jonas, P. M. (2020). Selective routing of spatial
information flow from input to output in hippocampal granule cells. Neuron.
Elsevier. https://doi.org/10.1016/j.neuron.2020.07.006
chicago: Zhang, Xiaomin, Alois Schlögl, and Peter M Jonas. “Selective Routing of
Spatial Information Flow from Input to Output in Hippocampal Granule Cells.” Neuron.
Elsevier, 2020. https://doi.org/10.1016/j.neuron.2020.07.006.
ieee: X. Zhang, A. Schlögl, and P. M. Jonas, “Selective routing of spatial information
flow from input to output in hippocampal granule cells,” Neuron, vol. 107,
no. 6. Elsevier, pp. 1212–1225, 2020.
ista: Zhang X, Schlögl A, Jonas PM. 2020. Selective routing of spatial information
flow from input to output in hippocampal granule cells. Neuron. 107(6), 1212–1225.
mla: Zhang, Xiaomin, et al. “Selective Routing of Spatial Information Flow from
Input to Output in Hippocampal Granule Cells.” Neuron, vol. 107, no. 6,
Elsevier, 2020, pp. 1212–25, doi:10.1016/j.neuron.2020.07.006.
short: X. Zhang, A. Schlögl, P.M. Jonas, Neuron 107 (2020) 1212–1225.
date_created: 2020-08-14T09:36:05Z
date_published: 2020-09-23T00:00:00Z
date_updated: 2023-08-22T08:30:55Z
day: '23'
ddc:
- '570'
department:
- _id: PeJo
- _id: ScienComp
doi: 10.1016/j.neuron.2020.07.006
ec_funded: 1
external_id:
isi:
- '000579698700009'
pmid:
- '32763145'
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creator: dernst
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date_updated: 2020-12-04T09:29:21Z
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file_name: 2020_Neuron_Zhang.pdf
file_size: 3011120
relation: main_file
success: 1
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intvolume: ' 107'
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issue: '6'
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
page: 1212-1225
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
publication: Neuron
publication_identifier:
issn:
- 0896-6273
publication_status: published
publisher: Elsevier
quality_controlled: '1'
related_material:
link:
- description: News on IST Website
relation: press_release
url: https://ist.ac.at/en/news/the-bouncer-in-the-brain/
status: public
title: Selective routing of spatial information flow from input to output in hippocampal
granule cells
tmp:
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legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
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short: CC BY-NC-ND (4.0)
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...
---
_id: '21'
abstract:
- lang: eng
text: Parvalbumin-positive (PV+) GABAergic interneurons in hippocampal microcircuits
are thought to play a key role in several higher network functions, such as feedforward
and feedback inhibition, network oscillations, and pattern separation. Fast lateral
inhibition mediated by GABAergic interneurons may implement a winner-takes-all
mechanism in the hippocampal input layer. However, it is not clear whether the
functional connectivity rules of granule cells (GCs) and interneurons in the dentate
gyrus are consistent with such a mechanism. Using simultaneous patch-clamp recordings
from up to seven GCs and up to four PV+ interneurons in the dentate gyrus, we
find that connectivity is structured in space, synapse-specific, and enriched
in specific disynaptic motifs. In contrast to the neocortex, lateral inhibition
in the dentate gyrus (in which a GC inhibits neighboring GCs via a PV+ interneuron)
is ~ 10-times more abundant than recurrent inhibition (in which a GC inhibits
itself). Thus, unique connectivity rules may enable the dentate gyrus to perform
specific higher-order computations
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) and the Fond zur Förderung der Wissenschaftlichen Forschung
(Z 312-B27, Wittgenstein award), both to P.J..
article_number: '4605'
article_processing_charge: No
article_type: original
author:
- 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: José
full_name: Guzmán, José
id: 30CC5506-F248-11E8-B48F-1D18A9856A87
last_name: Guzmán
orcid: 0000-0003-2209-5242
- first_name: Xiaomin
full_name: Zhang, Xiaomin
id: 423EC9C2-F248-11E8-B48F-1D18A9856A87
last_name: Zhang
- 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: Espinoza Martinez C, Guzmán J, Zhang X, Jonas PM. Parvalbumin+ interneurons
obey unique connectivity rules and establish a powerful lateral-inhibition microcircuit
in dentate gyrus. Nature Communications. 2018;9(1). doi:10.1038/s41467-018-06899-3
apa: Espinoza Martinez, C., Guzmán, J., Zhang, X., & Jonas, P. M. (2018). Parvalbumin+
interneurons obey unique connectivity rules and establish a powerful lateral-inhibition
microcircuit in dentate gyrus. Nature Communications. Nature Publishing
Group. https://doi.org/10.1038/s41467-018-06899-3
chicago: Espinoza Martinez, Claudia , José Guzmán, Xiaomin Zhang, and Peter M Jonas.
“Parvalbumin+ Interneurons Obey Unique Connectivity Rules and Establish a Powerful
Lateral-Inhibition Microcircuit in Dentate Gyrus.” Nature Communications.
Nature Publishing Group, 2018. https://doi.org/10.1038/s41467-018-06899-3.
ieee: C. Espinoza Martinez, J. Guzmán, X. Zhang, and P. M. Jonas, “Parvalbumin+
interneurons obey unique connectivity rules and establish a powerful lateral-inhibition
microcircuit in dentate gyrus,” Nature Communications, vol. 9, no. 1. Nature
Publishing Group, 2018.
ista: Espinoza Martinez C, Guzmán J, Zhang X, Jonas PM. 2018. Parvalbumin+ interneurons
obey unique connectivity rules and establish a powerful lateral-inhibition microcircuit
in dentate gyrus. Nature Communications. 9(1), 4605.
mla: Espinoza Martinez, Claudia, et al. “Parvalbumin+ Interneurons Obey Unique Connectivity
Rules and Establish a Powerful Lateral-Inhibition Microcircuit in Dentate Gyrus.”
Nature Communications, vol. 9, no. 1, 4605, Nature Publishing Group, 2018,
doi:10.1038/s41467-018-06899-3.
short: C. Espinoza Martinez, J. Guzmán, X. Zhang, P.M. Jonas, Nature Communications
9 (2018).
date_created: 2018-12-11T11:44:12Z
date_published: 2018-11-02T00:00:00Z
date_updated: 2024-03-25T23:30:16Z
day: '02'
ddc:
- '570'
department:
- _id: PeJo
doi: 10.1038/s41467-018-06899-3
ec_funded: 1
external_id:
isi:
- '000449069700009'
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month: '11'
oa: 1
oa_version: Published Version
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- _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: Nature Communications
publication_status: published
publisher: Nature Publishing Group
publist_id: '8034'
quality_controlled: '1'
related_material:
link:
- description: News on IST Homepage
relation: press_release
url: https://ist.ac.at/en/news/lateral-inhibition-keeps-similar-memories-apart/
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status: public
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status: public
title: Parvalbumin+ interneurons obey unique connectivity rules and establish a powerful
lateral-inhibition microcircuit in dentate gyrus
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...