| SPECIAL TOPIC — Biophysical circuits: Modeling & applications in neuroscience |
Prev
Next
|
|
|
Memristive effect on a Hindmarsh-Rose neuron |
| Fei Gao(高飞)1, Xiangcheng Yu(于相成)2, Yue Deng(邓玥)2, Fang Yuan(袁方)2, Guangyi Wang(王光义)1, and Tengfei Lei(雷腾飞)1,† |
1 Jinan Key Laboratory of Memristive Computing and Applications (JKLMCA), Qilu Institute of Technology, Jinan 250200, China; 2 College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao 266590, China |
|
|
|
|
Abstract Considering the impact of electromagnetic induction on neurons, this paper presents a three-dimensional (3D) memristor Hindmarsh-Rose (HR) neuron model. This model exhibits diverse hidden chaotic dynamics due to the absence of equilibrium points, including bifurcation phenomena, coexisting attractors, transient chaos, state transitions, and offset-boosting control. Since equilibrium points are absent in this model, all observed dynamics are classified as hidden behaviors. The complex dynamics of this neuron model are illustrated through bifurcation diagrams, Lyapunov diagrams, time series plots, and phase portraits. Furthermore, an equivalent circuit for the memristor HR neuron is constructed, and the accuracy of numerical simulations is confirmed via circuit simulation results.
|
Received: 03 August 2025
Revised: 04 September 2025
Accepted manuscript online: 25 September 2025
|
|
PACS:
|
05.45.-a
|
(Nonlinear dynamics and chaos)
|
| |
87.19.ll
|
(Models of single neurons and networks)
|
| |
84.35.+i
|
(Neural networks)
|
|
| Fund: This work was supported by the Natural Science Foundation of Shandong Province (Grant No. ZR2024MF106), the National Natural Science Foundation of China (Grant Nos. 62371274 and 62401346), the China Postdoctoral Science Foundation (Grant No. 2023M742138), the Natural Science Foundation of Shandong Province (Grant Nos. ZR2023MF004 and ZR2022MA073), the Postdoctoral Innovation Project of Shandong Province (Grant No. SDCX-ZG-202400311), the Natural Science Foundation of Qingdao Municipality (Grant No. 23-2-1-151-zyydjch), the Qingdao Postdoctoral Innovation Project (Grant No. QDBSH20230202012), and in part by the Elite Project of Shandong University of Science and Technology. |
Corresponding Authors:
Tengfei Lei
E-mail: leitengfeicanhe@126.com
|
Cite this article:
Fei Gao(高飞), Xiangcheng Yu(于相成), Yue Deng(邓玥), Fang Yuan(袁方), Guangyi Wang(王光义), and Tengfei Lei(雷腾飞) Memristive effect on a Hindmarsh-Rose neuron 2025 Chin. Phys. B 34 120504
|
[1] Du Z, Li Z, Wang P, Zhuang Z and Liu Z 2022 Int. J. Solids Struct. 242 111554 [2] Ma J 2025 Nonlinear Dyn. (in press) [3] Singh A, Verma U, Mishra A, Yadav K, Sharma A and Varshney V 2024 Chaos Solitons Fractals 182 114864 [4] Beyhan S 2024 Chaos Solitons Fractals 180 114578 [5] Ding D, Chen S, Zhang H, Yang Z, Jin F and Liu X 2024 Nonlinear Dyn. 112 10529 [6] Yang Y and Liao X 2019 IEEE Trans. Neural Netw. Learn. Syst. 30 306 [7] Huang L, Wang S, Lei T, Huang K and Li C 2024 Int. J. Bifurc. Chaos 34 2450022 [8] Chen D, Li J, Zeng W and He J 2023 Cogn. Neurodyn. 17 203 [9] Slepukhina E, Bashkirtseva I, Kgler P and Ryashko L 2023 Chaos 33 033106 [10] Moujahid A and Vadillo F 2022 Chaos Solitons Fractals 158 112071 [11] Tezoh F, Adamou D and Fouda H 2023 Phys. Scr. 98 115233 [12] Wu K, Zheng H and Li T 2022 Discrete Dyn. Nat. Soc. 2022 8384444 [13] Afuwape O, Olafasakin O and Jiles D 2022 IEEE Trans. Magn. 58 5800205 [14] Yan X, Li Z J and Li C L 2024 Chin. Phys. B 33 028705 [15] Nefzi A, Orlacchio R, Carr L, Lemercier C, El Khoueiry C, Lewis N et al 2022 IEEE Trans. Microw. Theory Techn. 70 1871 [16] Wan J Y, Wu F Q, Ma J and Wang W S 2024 Chin. Phys. B 33 050504 [17] Lin H, Wang C and Tan Y 2020 Nonlinear Dyn. 99 2369 [18] Njitacke Z, Tsafack N, Ramakrishnan B, Rajagopal K, Kengne J and Awrejcewicz J 2021 Chaos Solitons Fractals 153 111577 [19] Zhang F, Shi H, Jié M, Wang L and Duan S 2022 Int. J. Bifurc. Chaos 32 2250165 [20] Li Z, Zhou C and Wang M 2019 AEU-Int. J. Electron. Commun. 100 127 [21] Lv M and Ma J 2016 Neurocomputing 205 375 [22] Bao H, Hu A, LiuWand Bao B 2020 IEEE Trans. Neural Netw. Learn. Syst. 31 502 [23] Zhang S, Zheng J, Wang X and Zeng Z 2021 Chaos Solitons Fractals 145 110761 [24] Parastesh F, Rajagopal K, Jafari S and Perc M 2025 Fractal Fract. 9 276 [25] Lin H, Wang C, Sun Y and Yao W 2020 Nonlinear Dyn. 100 3667 [26] Yuan F, Li S, Deng Y, Li Y and Chen G 2023 IEEE Trans. Ind. Electron. 70 4120 [27] Kaslik E 2017 Fract. Calc. Appl. Anal. 20 623 [28] Yang F, Xu Y and Ma J 2023 Chaos 33 023110 [29] Stenzinger R V and Tragtenberg M H R 2025 Chaos 35 013132 |
| No Suggested Reading articles found! |
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
Altmetric
|
|
blogs
Facebook pages
Wikipedia page
Google+ users
|
Online attention
Altmetric calculates a score based on the online attention an article receives. Each coloured thread in the circle represents a different type of online attention. The number in the centre is the Altmetric score. Social media and mainstream news media are the main sources that calculate the score. Reference managers such as Mendeley are also tracked but do not contribute to the score. Older articles often score higher because they have had more time to get noticed. To account for this, Altmetric has included the context data for other articles of a similar age.
View more on Altmetrics
|
|
|