A Physiologically-Grounded, Computationally-Efficient Model of the Human Hippocampus

Niccolò Calcini; Vitalii Kyzym; Renaud B. Jolivet

doi:10.1007/978-3-031-82439-5_4

A Physiologically-Grounded, Computationally-Efficient Model of the Human Hippocampus

Niccolò Calcini^*, Vitalii Kyzym, Renaud B. Jolivet

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review

Abstract

The hippocampus is a central structure of the vertebrate brain, and plays a key role in the formation and processing of memories. Comprised of several highly interconnected sub-regions, it is characterized by a complex network architecture involving both feed-forward and feedback loops. In the past, various computational models of the hippocampus have been proposed. However, these were either lacking in physiological details, or required significant computational resources. With this work, we propose a novel human hippocampal model, which is both solidly grounded in physiological details, and has low computational requirements, allowing for the investigation of various physiological or pathological conditions. Here, we describe the model in detail, and demonstrate how its architecture supports firing rates typical of a resting hippocampus, and the spontaneous generation of characteristic hippocampal theta oscillations.

Original language	English
Title of host publication	Complex Networks and Their Applications 13th - Proceedings of The 13th International Conference on Complex Networks and their Applications: COMPLEX NETWORKS 2024
Editors	Hocine Cherifi, Murat Donduran, Luis M. Rocha, Chantal Cherifi, Onur Varol
Publisher	Springer Verlag
Pages	39-50
Number of pages	12
Volume	1190 SCI
ISBN (Print)	9783031824388
DOIs	https://doi.org/10.1007/978-3-031-82439-5_4
Publication status	Published - 1 Jan 2025
Event	13th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2024 - Istanbul, Turkey Duration: 10 Dec 2024 → 12 Dec 2024 https://www.comses.net/events/735/

Publication series

Series	Studies in Computational Intelligence
Volume	1190 SCI
ISSN	1860-949X

Conference

Conference	13th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2024
Abbreviated title	COMPLEX NETWORKS 2024
Country/Territory	Turkey
City	Istanbul
Period	10/12/24 → 12/12/24
Internet address	https://www.comses.net/events/735/

Keywords

Complex Systems
Hippocampus
Oscillations
Simulation

Access to Document

10.1007/978-3-031-82439-5_4

Cite this

Calcini, N., Kyzym, V., & Jolivet, R. B. (2025). A Physiologically-Grounded, Computationally-Efficient Model of the Human Hippocampus. In H. Cherifi, M. Donduran, L. M. Rocha, C. Cherifi, & O. Varol (Eds.), Complex Networks and Their Applications 13th - Proceedings of The 13th International Conference on Complex Networks and their Applications: COMPLEX NETWORKS 2024 (Vol. 1190 SCI, pp. 39-50). Springer Verlag. https://doi.org/10.1007/978-3-031-82439-5_4

Calcini, Niccolò ; Kyzym, Vitalii ; Jolivet, Renaud B. / A Physiologically-Grounded, Computationally-Efficient Model of the Human Hippocampus. Complex Networks and Their Applications 13th - Proceedings of The 13th International Conference on Complex Networks and their Applications: COMPLEX NETWORKS 2024. editor / Hocine Cherifi ; Murat Donduran ; Luis M. Rocha ; Chantal Cherifi ; Onur Varol. Vol. 1190 SCI Springer Verlag, 2025. pp. 39-50 (Studies in Computational Intelligence, Vol. 1190 SCI).

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keywords = "Complex Systems, Hippocampus, Oscillations, Simulation",

author = "Niccol{\`o} Calcini and Vitalii Kyzym and Jolivet, {Renaud B.}",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.; 13th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2024, COMPLEX NETWORKS 2024 ; Conference date: 10-12-2024 Through 12-12-2024",

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Calcini, N, Kyzym, V & Jolivet, RB 2025, A Physiologically-Grounded, Computationally-Efficient Model of the Human Hippocampus. in H Cherifi, M Donduran, LM Rocha, C Cherifi & O Varol (eds), Complex Networks and Their Applications 13th - Proceedings of The 13th International Conference on Complex Networks and their Applications: COMPLEX NETWORKS 2024. vol. 1190 SCI, Springer Verlag, Studies in Computational Intelligence, vol. 1190 SCI, pp. 39-50, 13th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2024, Istanbul, Turkey, 10/12/24. https://doi.org/10.1007/978-3-031-82439-5_4

A Physiologically-Grounded, Computationally-Efficient Model of the Human Hippocampus. / Calcini, Niccolò; Kyzym, Vitalii; Jolivet, Renaud B.
Complex Networks and Their Applications 13th - Proceedings of The 13th International Conference on Complex Networks and their Applications: COMPLEX NETWORKS 2024. ed. / Hocine Cherifi; Murat Donduran; Luis M. Rocha; Chantal Cherifi; Onur Varol. Vol. 1190 SCI Springer Verlag, 2025. p. 39-50 (Studies in Computational Intelligence, Vol. 1190 SCI).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review

TY - GEN

T1 - A Physiologically-Grounded, Computationally-Efficient Model of the Human Hippocampus

AU - Calcini, Niccolò

AU - Kyzym, Vitalii

AU - Jolivet, Renaud B.

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

PY - 2025/1/1

Y1 - 2025/1/1

N2 - The hippocampus is a central structure of the vertebrate brain, and plays a key role in the formation and processing of memories. Comprised of several highly interconnected sub-regions, it is characterized by a complex network architecture involving both feed-forward and feedback loops. In the past, various computational models of the hippocampus have been proposed. However, these were either lacking in physiological details, or required significant computational resources. With this work, we propose a novel human hippocampal model, which is both solidly grounded in physiological details, and has low computational requirements, allowing for the investigation of various physiological or pathological conditions. Here, we describe the model in detail, and demonstrate how its architecture supports firing rates typical of a resting hippocampus, and the spontaneous generation of characteristic hippocampal theta oscillations.

AB - The hippocampus is a central structure of the vertebrate brain, and plays a key role in the formation and processing of memories. Comprised of several highly interconnected sub-regions, it is characterized by a complex network architecture involving both feed-forward and feedback loops. In the past, various computational models of the hippocampus have been proposed. However, these were either lacking in physiological details, or required significant computational resources. With this work, we propose a novel human hippocampal model, which is both solidly grounded in physiological details, and has low computational requirements, allowing for the investigation of various physiological or pathological conditions. Here, we describe the model in detail, and demonstrate how its architecture supports firing rates typical of a resting hippocampus, and the spontaneous generation of characteristic hippocampal theta oscillations.

KW - Complex Systems

KW - Hippocampus

KW - Oscillations

KW - Simulation

U2 - 10.1007/978-3-031-82439-5_4

DO - 10.1007/978-3-031-82439-5_4

M3 - Conference article in proceeding

SN - 9783031824388

VL - 1190 SCI

T3 - Studies in Computational Intelligence

SP - 39

EP - 50

BT - Complex Networks and Their Applications 13th - Proceedings of The 13th International Conference on Complex Networks and their Applications: COMPLEX NETWORKS 2024

A2 - Cherifi, Hocine

A2 - Donduran, Murat

A2 - Rocha, Luis M.

A2 - Cherifi, Chantal

A2 - Varol, Onur

PB - Springer Verlag

T2 - 13th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2024

Y2 - 10 December 2024 through 12 December 2024

ER -

Calcini N, Kyzym V, Jolivet RB. A Physiologically-Grounded, Computationally-Efficient Model of the Human Hippocampus. In Cherifi H, Donduran M, Rocha LM, Cherifi C, Varol O, editors, Complex Networks and Their Applications 13th - Proceedings of The 13th International Conference on Complex Networks and their Applications: COMPLEX NETWORKS 2024. Vol. 1190 SCI. Springer Verlag. 2025. p. 39-50. (Studies in Computational Intelligence, Vol. 1190 SCI). doi: 10.1007/978-3-031-82439-5_4

A Physiologically-Grounded, Computationally-Efficient Model of the Human Hippocampus

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