---
OA_place: repository
OA_type: gold
_id: '18991'
abstract:
- lang: eng
text: Research data for the article "Learning reshapes the hippocampal representation
hierarchy" from Chiossi et al. (PNAS, 2025). The data includes hippocampal CA1
unit activity and behaviour tracking of 5 Long Evans rats during the learning
of an associative memory task. Detailed information can be found in the 'readme.txt'
file.
acknowledged_ssus:
- _id: PreCl
- _id: M-Shop
acknowledgement: Thanks to Rebecca Morse for performing one of the experiments under
H.S.C.C. supervision and Jago Wallenschus for technical support, especially with
maze design.
article_processing_charge: No
author:
- first_name: Heloisa
full_name: Chiossi, Heloisa
id: 2BBA502C-F248-11E8-B48F-1D18A9856A87
last_name: Chiossi
orcid: 0009-0004-2973-278X
citation:
ama: Chiossi HSC. Research data for the publication “Learning reshapes the hippocampal
representation hierarchy.” 2025. doi:10.15479/AT:ISTA:18991
apa: Chiossi, H. S. C. (2025). Research data for the publication “Learning reshapes
the hippocampal representation hierarchy.” Institute of Science and Technology
Austria. https://doi.org/10.15479/AT:ISTA:18991
chicago: Chiossi, Heloisa S. C. “Research Data for the Publication ‘Learning Reshapes
the Hippocampal Representation Hierarchy.’” Institute of Science and Technology
Austria, 2025. https://doi.org/10.15479/AT:ISTA:18991.
ieee: H. S. C. Chiossi, “Research data for the publication ‘Learning reshapes the
hippocampal representation hierarchy.’” Institute of Science and Technology Austria,
2025.
ista: Chiossi HSC. 2025. Research data for the publication ‘Learning reshapes the
hippocampal representation hierarchy’, Institute of Science and Technology Austria,
10.15479/AT:ISTA:18991.
mla: Chiossi, Heloisa S. C. Research Data for the Publication “Learning Reshapes
the Hippocampal Representation Hierarchy.” Institute of Science and Technology
Austria, 2025, doi:10.15479/AT:ISTA:18991.
short: H.S.C. Chiossi, (2025).
contributor:
- contributor_type: researcher
first_name: Michele
id: 30BD0376-F248-11E8-B48F-1D18A9856A87
last_name: Nardin
orcid: 0000-0001-8849-6570
- contributor_type: supervisor
first_name: Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- contributor_type: supervisor
first_name: Jozsef L
id: 3FA14672-F248-11E8-B48F-1D18A9856A87
last_name: Csicsvari
orcid: 0000-0002-5193-4036
corr_author: '1'
date_created: 2025-02-04T10:36:18Z
date_published: 2025-02-04T00:00:00Z
date_updated: 2026-05-06T13:12:00Z
day: '04'
ddc:
- '570'
department:
- _id: GradSch
- _id: JoCs
- _id: GaTk
doi: 10.15479/AT:ISTA:18991
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date_created: 2025-02-04T10:18:33Z
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keyword:
- hippocampus
- electrophysiology
- behavior
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
month: '02'
oa: 1
oa_version: Published Version
publisher: Institute of Science and Technology Austria
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relation: used_in_publication
status: public
status: public
title: Research data for the publication "Learning reshapes the hippocampal representation
hierarchy"
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image: /images/cc_by_nc_nd.png
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short: CC BY-NC-ND (4.0)
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abstract:
- lang: eng
text: A key feature of biological and artificial neural networks is the progressive
refinement of their neural representations with experience. In neuroscience, this
fact has inspired several recent studies in sensory and motor systems. However,
less is known about how higher associational cortical areas, such as the hippocampus,
modify representations throughout the learning of complex tasks. Here, we focus
on associative learning, a process that requires forming a connection between
the representations of different variables for appropriate behavioral response.
We trained rats in a space-context associative task and monitored hippocampal
neural activity throughout the entire learning period, over several days. This
allowed us to assess changes in the representations of context, movement direction,
and position, as well as their relationship to behavior. We identified a hierarchical
representational structure in the encoding of these three task variables that
was preserved throughout learning. Nevertheless, we also observed changes at the
lower levels of the hierarchy where context was encoded. These changes were local
in neural activity space and restricted to physical positions where context identification
was necessary for correct decision-making, supporting better context decoding
and contextual code compression. Our results demonstrate that the hippocampal
code not only accommodates hierarchical relationships between different variables
but also enables efficient learning through minimal changes in neural activity
space. Beyond the hippocampus, our work reveals a representation learning mechanism
that might be implemented in other biological and artificial networks performing
similar tasks.
acknowledgement: We would like to thank Rebecca Morse for performing the recordings
in one of the animals under the supervision of H.S.C.C., Jago Wallenschus for the
technical support, especially with maze design, Wiktor Mlynarski for the advice
and discussions and Andrea Cumpelik for suggestions during the writing. M.N. was
supported by the Howard Hughes Medical Institute. H.S.C.C. received funding from
the European Union’s Horizon 2020 research and innovation programme under the Marie
Skłodowska-Curie grant agreement No 665385.
article_number: e2417025122
article_processing_charge: Yes (in subscription journal)
article_type: original
author:
- first_name: Heloisa
full_name: Chiossi, Heloisa
id: 2BBA502C-F248-11E8-B48F-1D18A9856A87
last_name: Chiossi
orcid: 0009-0004-2973-278X
- first_name: Michele
full_name: Nardin, Michele
id: 30BD0376-F248-11E8-B48F-1D18A9856A87
last_name: Nardin
orcid: 0000-0001-8849-6570
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- first_name: Jozsef L
full_name: Csicsvari, Jozsef L
id: 3FA14672-F248-11E8-B48F-1D18A9856A87
last_name: Csicsvari
orcid: 0000-0002-5193-4036
citation:
ama: Chiossi HSC, Nardin M, Tkačik G, Csicsvari JL. Learning reshapes the hippocampal
representation hierarchy. Proceedings of the National Academy of Sciences.
2025;122(11). doi:10.1073/pnas.2417025122
apa: Chiossi, H. S. C., Nardin, M., Tkačik, G., & Csicsvari, J. L. (2025). Learning
reshapes the hippocampal representation hierarchy. Proceedings of the National
Academy of Sciences. National Academy of Sciences. https://doi.org/10.1073/pnas.2417025122
chicago: Chiossi, Heloisa S. C., Michele Nardin, Gašper Tkačik, and Jozsef L Csicsvari.
“Learning Reshapes the Hippocampal Representation Hierarchy.” Proceedings of
the National Academy of Sciences. National Academy of Sciences, 2025. https://doi.org/10.1073/pnas.2417025122.
ieee: H. S. C. Chiossi, M. Nardin, G. Tkačik, and J. L. Csicsvari, “Learning reshapes
the hippocampal representation hierarchy,” Proceedings of the National Academy
of Sciences, vol. 122, no. 11. National Academy of Sciences, 2025.
ista: Chiossi HSC, Nardin M, Tkačik G, Csicsvari JL. 2025. Learning reshapes the
hippocampal representation hierarchy. Proceedings of the National Academy of Sciences.
122(11), e2417025122.
mla: Chiossi, Heloisa S. C., et al. “Learning Reshapes the Hippocampal Representation
Hierarchy.” Proceedings of the National Academy of Sciences, vol. 122,
no. 11, e2417025122, National Academy of Sciences, 2025, doi:10.1073/pnas.2417025122.
short: H.S.C. Chiossi, M. Nardin, G. Tkačik, J.L. Csicsvari, Proceedings of the
National Academy of Sciences 122 (2025).
corr_author: '1'
date_created: 2025-03-25T07:38:35Z
date_published: 2025-03-10T00:00:00Z
date_updated: 2026-05-06T13:12:01Z
day: '10'
ddc:
- '570'
department:
- _id: GaTk
- _id: JoCs
doi: 10.1073/pnas.2417025122
ec_funded: 1
external_id:
isi:
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pmid:
- '40063792'
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creator: dernst
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date_updated: 2025-03-25T07:49:04Z
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success: 1
file_date_updated: 2025-03-25T07:49:04Z
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issue: '11'
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
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call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication: Proceedings of the National Academy of Sciences
publication_identifier:
eissn:
- 1091-6490
issn:
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publication_status: published
publisher: National Academy of Sciences
quality_controlled: '1'
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- relation: software
url: https://github.com/hchiossi/hpc-hierarchy
record:
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relation: research_data
status: public
scopus_import: '1'
status: public
title: Learning reshapes the hippocampal representation hierarchy
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: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 122
year: '2025'
...
---
OA_place: publisher
_id: '14821'
abstract:
- lang: eng
text: "The hippocampus is central to memory formation, storage and retrieval over
many\r\ntimescales. Neurons in this brain area are highly selective to spatial
position as well as to many\r\nother variables of the environment. It is believed
that the selectivity patterns of hippocampal\r\nneurons reflect the structure
of tasks an animal performs. However, especially at timescales\r\nlonger than
a few minutes or hours it is not fully known how these representations evolve,
nor\r\nhow they map to behaviour in the process. In this thesis, I monitored the
evolution of\r\nhippocampal representations in a novel spatial-associative memory
task for rats. Reward\r\nlocations were associated with global sensory cues (i.e.
context); animals had to remember the\r\nassociations and dig for food in those
locations only. I used in vivo electrophysiology to record\r\nthe activity of
the hippocampus dorsal CA1 neurons during the learning period of a few days.\r\nI
report here a novel and simple method to classify behaviour performance to account\r\nfor
individual variability in learning speed and spurious performance unrelated to
true task rule\r\nlearning. Using this classification I was then able to investigate
neural responses on different\r\nstages of learning matched across animals. On
the first day of learning, I observed a fast\r\nformation of single-cell selectivity
to task variables which remained stable over days. I also\r\nobserved that reward
tuning was not a single process but dependent on task-related cognitive\r\nload.
At the population level, a linear decoding approach revealed a hierarchy in the\r\nrepresentation
of task variables that changed with learning. In the high-dimensional space of\r\npopulation
activity, the representation of contexts was specific to each position in the
maze, and\r\ncould thus be better decoded if the position was known. The decoding
of position did not improve\r\nwith knowledge of other variables. As learning
progressed, the hippocampal code underwent a\r\nreorganisation of high-variance
directions in population activity, identified by principal\r\ncomponent analysis.
I found that dominant dimensions started carrying increasing amounts of\r\ninformation
about task context specifically at those positions where it mattered for task\r\nperformance.
When I contrasted this with variables less relevant to task performance (e.g.\r\nmovement
direction), I did not observe differences in decoding quality over positions nor
a\r\nreduction of dimensionality with learning.\r\nOverall, the largest changes
in CA1 neural response with task learning happened in a\r\nmatter of a few trials;
over days, changes undetectable in single-cell statistics were responsible\r\nfor
re-structuring the hierarchy of neural representations at the population level;
these changes\r\nwere task-specific and reflected different stages of learning.
This indicates that complex task\r\nlearning may involve different magnitudes
of response modulation in CA1, which happen at\r\nspecific time scales linked
to behaviour."
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Heloisa
full_name: Chiossi, Heloisa
id: 2BBA502C-F248-11E8-B48F-1D18A9856A87
last_name: Chiossi
orcid: 0009-0004-2973-278X
citation:
ama: Chiossi HSC. Adaptive hierarchical representations in the hippocampus. 2024.
doi:10.15479/at:ista:14821
apa: Chiossi, H. S. C. (2024). Adaptive hierarchical representations in the hippocampus.
Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:14821
chicago: Chiossi, Heloisa S. C. “Adaptive Hierarchical Representations in the Hippocampus.”
Institute of Science and Technology Austria, 2024. https://doi.org/10.15479/at:ista:14821.
ieee: H. S. C. Chiossi, “Adaptive hierarchical representations in the hippocampus,”
Institute of Science and Technology Austria, 2024.
ista: Chiossi HSC. 2024. Adaptive hierarchical representations in the hippocampus.
Institute of Science and Technology Austria.
mla: Chiossi, Heloisa S. C. Adaptive Hierarchical Representations in the Hippocampus.
Institute of Science and Technology Austria, 2024, doi:10.15479/at:ista:14821.
short: H.S.C. Chiossi, Adaptive Hierarchical Representations in the Hippocampus,
Institute of Science and Technology Austria, 2024.
corr_author: '1'
date_created: 2024-01-16T14:25:21Z
date_published: 2024-01-19T00:00:00Z
date_updated: 2026-04-07T13:21:56Z
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grant_number: '665385'
name: International IST Doctoral Program
publication_identifier:
issn:
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publication_status: published
publisher: Institute of Science and Technology Austria
status: public
supervisor:
- first_name: Jozsef L
full_name: Csicsvari, Jozsef L
id: 3FA14672-F248-11E8-B48F-1D18A9856A87
last_name: Csicsvari
orcid: 0000-0002-5193-4036
title: Adaptive hierarchical representations in the hippocampus
type: dissertation
user_id: ba8df636-2132-11f1-aed0-ed93e2281fdd
year: '2024'
...