English
 
Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
 
 
DownloadE-Mail
  Emergence of Shilnikov homoclinic bifurcation and orbit-induced mixed-mode oscillations in a neuronal dynamical system

Liu, Y., Xia, Y., Kurths, J. (2025): Emergence of Shilnikov homoclinic bifurcation and orbit-induced mixed-mode oscillations in a neuronal dynamical system. - Chaos, Solitons and Fractals, 200, Part 2, 116893.
https://doi.org/10.1016/j.chaos.2025.116893

Item is

Files

show Files
hide Files
:
Liu_2025_1-s2.0-S0960077925009063-main.pdf (Publisher version), 3MB
 
File Permalink:
-
Name:
Liu_2025_1-s2.0-S0960077925009063-main.pdf
Description:
-
OA-Status:
Visibility:
Private
MIME-Type / Checksum:
application/pdf
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show

Creators

show
hide
 Creators:
Liu, Yaru1, Author
Xia, Yibo1, Author
Kurths, Jürgen2, Author           
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

Content

show
hide
Free keywords: -
 Abstract: Our paper investigates the dynamic relationship between homoclinic bifurcations and mixed-mode oscillations (MMOs) in a reduced three-dimensional singularly perturbed Hodgkin–Huxley (HH) liked model, developed to characterize complex neurodynamic oscillations in neural systems. Through invariant manifold tracking, we establish the coexistence of elusive homoclinic bifurcations and MMOs. Our manifold analysis reveals critical conditions for the emergence of Shilnikov homoclinic bifurcation and oscillatory stability parameter thresholds. Employing Fenichel’s theorem and Bogdanov–Takens (BT) bifurcation theory within a nonlinear multiscale framework, we construct a locally topologically equivalent system for singular dynamics. This system exhibits three canonical bifurcation curves that elucidate the mechanistic origins of MMOs induced by singular BT bifurcations. The proof strategy for Shilnikov homoclinic bifurcations relies on a systematic examination of invariant manifold intersections in multiscale systems. Application to neuronal models demonstrates rich dynamic phenomena including pseudo-plateau bursting, MMOs, and chaotic-MMOs. Numerical simulations validate theoretical predictions with remarkable consistency, particularly in the bifurcation parameter regions.

Details

show
hide
Language(s): eng - English
 Dates: 2025-08-192025-11-01
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.chaos.2025.116893
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Complex Networks
Research topic keyword: Nonlinear Dynamics
Model / method: Machine Learning
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Chaos, Solitons and Fractals
Source Genre: Journal, SCI, Scopus, p3
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 200 (Part 2) Sequence Number: 116893 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/190702
Publisher: Elsevier