---
_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
  orcid: 0000-0003-0256-6529
- 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:<a href="https://doi.org/10.15479/AT:ISTA:10110">10.15479/AT:ISTA:10110</a>
  apa: Guzmán, J., Schlögl, A., Espinoza Martinez, C., Zhang, X., Suter, B., &#38;
    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. <a href="https://doi.org/10.15479/AT:ISTA:10110">https://doi.org/10.15479/AT:ISTA:10110</a>
  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. <a href="https://doi.org/10.15479/AT:ISTA:10110">https://doi.org/10.15479/AT:ISTA:10110</a>.
  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, <a href="https://doi.org/10.15479/AT:ISTA:10110">10.15479/AT:ISTA:10110</a>.
  mla: Guzmán, José, et al. <i>How Connectivity Rules and Synaptic Properties Shape
    the Efficacy of Pattern Separation in the Entorhinal Cortex–Dentate Gyrus–CA3
    Network</i>. IST Austria, 2021, doi:<a href="https://doi.org/10.15479/AT:ISTA:10110">10.15479/AT:ISTA:10110</a>.
  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: 2026-07-15T22:30:45Z
day: '16'
ddc:
- '005'
department:
- _id: PeJo
- _id: ScienComp
doi: 10.15479/AT:ISTA:10110
file:
- access_level: open_access
  checksum: f92f8931cad0aa7e411c1715337bf408
  content_type: application/x-zip-compressed
  creator: cchlebak
  date_created: 2021-10-08T08:46:04Z
  date_updated: 2021-10-08T08:46:04Z
  file_id: '10114'
  file_name: patternseparation-main (1).zip
  file_size: 332990101
  relation: main_file
  success: 1
file_date_updated: 2021-10-08T08:46:04Z
has_accepted_license: '1'
license: https://opensource.org/licenses/GPL-3.0
month: '12'
oa: 1
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:
  - id: '10816'
    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'
...