arXiv:2407.20055
Phase transformation and synchrony for a network of coupled Izhikevich neurons
원문 초록
A number of recent articles have employed the Lorentz ansatz to reduce a network of Izhikevich neurons to a tractable mean-field description. In this letter, we construct an equivalent phase model for the Izhikevich model and apply the Ott-Antonsen ansatz, to derive the mean field dynamics in terms of the Kuramoto order parameter. In addition, we show that by defining an appropriate order parameter in the voltage-firing rate framework, the conformal mapping of Montbri\'o et al., which relates the two mean-field descriptions, remains valid.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Identifying economic narratives in large text corpora -- An integrated approach using Large Language Models
AI Wizards at CheckThat! 2025: Enhancing Transformer-Based Embeddings with Sentiment for Subjectivity Detection in News Articles
Remember Past, Anticipate Future: Learning Continual Multimodal Misinformation Detectors
Narrative Shift Detection: A Hybrid Approach of Dynamic Topic Models and Large Language Models
The kernel of graph indices for vector search
Model-Based Real-Time Pose and Sag Estimation of Overhead Power Lines Using LiDAR for Drone Inspection
토론
이 논문과 연결된 포럼 글이 아직 없습니다.