---
_id: '6363'
abstract:
- lang: eng
text: "Distinguishing between similar experiences is achieved by the brain
\ in a process called pattern separation. In the hippocampus, pattern
\ separation reduces the interference of memories and increases the storage
capacity by decorrelating similar inputs patterns of neuronal activity into
\ non-overlapping output firing patterns. Winners-take-all (WTA) mechanism
\ is a theoretical model for pattern separation in which a \"winner\"
\ cell suppresses the activity of the neighboring neurons through feedback
inhibition. However, if the network properties of the dentate gyrus support WTA
as a biologically conceivable model remains unknown. Here, we showed that the
connectivity rules of PV+interneurons and their synaptic properties are optimizedfor
efficient pattern separation. We found using multiple whole-cell in vitrorecordings
that PV+interneurons mainly connect to granule cells (GC) through lateral inhibition,
a form of feedback inhibition in which a GC inhibits other GCs but not
\ itself through the activation of PV+interneurons. Thus, lateral inhibition
between GC–PV+interneurons was ~10 times more abundant than recurrent connections.
Furthermore, the GC–PV+interneuron connectivity was more spatially confined
\ but less abundant than PV+interneurons–GC connectivity, leading to an
\ asymmetrical distribution of excitatory and inhibitory connectivity. Our
network model of the dentate gyrus with incorporated real connectivity rules efficiently
decorrelates neuronal activity patterns using WTA as the primary mechanism.
\ This process relied on lateral inhibition, fast-signaling properties of
\ PV+interneurons and the asymmetrical distribution of excitatory and inhibitory
connectivity. Finally, we found that silencing the activity of PV+interneurons
in vivoleads to acute deficits in discrimination between similar environments,
suggesting that PV+interneuron networks are necessary for behavioral relevant
computations. Our results demonstrate that PV+interneurons possess unique
connectivity and fast signaling properties that confer to the dentate
\ gyrus network properties that allow the emergence of pattern separation. Thus,
our results contribute to the knowledge of how specific forms of network organization
underlie sophisticated types of information processing. \r\n"
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: 'Claudia '
full_name: 'Espinoza Martinez, Claudia '
id: 31FFEE2E-F248-11E8-B48F-1D18A9856A87
last_name: Espinoza Martinez
orcid: 0000-0003-4710-2082
citation:
ama: Espinoza Martinez C. Parvalbumin+ interneurons enable efficient pattern separation
in hippocampal microcircuits. 2019. doi:10.15479/AT:ISTA:6363
apa: Espinoza Martinez, C. (2019). Parvalbumin+ interneurons enable efficient
pattern separation in hippocampal microcircuits. Institute of Science and
Technology Austria. https://doi.org/10.15479/AT:ISTA:6363
chicago: Espinoza Martinez, Claudia . “Parvalbumin+ Interneurons Enable Efficient
Pattern Separation in Hippocampal Microcircuits.” Institute of Science and Technology
Austria, 2019. https://doi.org/10.15479/AT:ISTA:6363.
ieee: C. Espinoza Martinez, “Parvalbumin+ interneurons enable efficient pattern
separation in hippocampal microcircuits,” Institute of Science and Technology
Austria, 2019.
ista: Espinoza Martinez C. 2019. Parvalbumin+ interneurons enable efficient pattern
separation in hippocampal microcircuits. Institute of Science and Technology Austria.
mla: Espinoza Martinez, Claudia. Parvalbumin+ Interneurons Enable Efficient Pattern
Separation in Hippocampal Microcircuits. Institute of Science and Technology
Austria, 2019, doi:10.15479/AT:ISTA:6363.
short: C. Espinoza Martinez, Parvalbumin+ Interneurons Enable Efficient Pattern
Separation in Hippocampal Microcircuits, Institute of Science and Technology Austria,
2019.
date_created: 2019-04-30T11:56:10Z
date_published: 2019-04-30T00:00:00Z
date_updated: 2023-09-15T12:03:48Z
day: '30'
ddc:
- '570'
degree_awarded: PhD
department:
- _id: PeJo
doi: 10.15479/AT:ISTA:6363
file:
- access_level: open_access
checksum: 77c6c05cfe8b58c8abcf1b854375d084
content_type: application/pdf
creator: cespinoza
date_created: 2019-05-07T16:00:39Z
date_updated: 2021-02-11T11:17:15Z
embargo: 2020-05-09
file_id: '6389'
file_name: Espinozathesis_all2.pdf
file_size: 13966891
relation: main_file
- access_level: closed
checksum: f6aa819f127691a2b0fc21c76eb09746
content_type: application/vnd.openxmlformats-officedocument.wordprocessingml.document
creator: cespinoza
date_created: 2019-05-07T16:00:48Z
date_updated: 2020-07-14T12:47:28Z
embargo_to: open_access
file_id: '6390'
file_name: Espinoza_Thesis.docx
file_size: 11159900
relation: source_file
file_date_updated: 2021-02-11T11:17:15Z
has_accepted_license: '1'
language:
- iso: eng
month: '04'
oa: 1
oa_version: Published Version
page: '140'
publication_identifier:
isbn:
- 978-3-99078-000-8
issn:
- 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '21'
relation: part_of_dissertation
status: public
status: public
supervisor:
- first_name: Peter M
full_name: Jonas, Peter M
id: 353C1B58-F248-11E8-B48F-1D18A9856A87
last_name: Jonas
orcid: 0000-0001-5001-4804
title: Parvalbumin+ interneurons enable efficient pattern separation in hippocampal
microcircuits
type: dissertation
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
year: '2019'
...