Anti-interference ability of spiking neuron-astrocyte networks in working memory

doi:10.1088/1674-1056/ae4e8c

Abstract Working memory is a fundamental aspect of brain cognitive function. Its anti-interference ability relies on the network structure and the balance between excitatory and inhibitory neurons in neural systems. Here, we discuss the resistance of the spiking neuron-astrocyte network (SNAN) to noise interference of the input signal during working memory tasks, and we underscore that astrocytes play an essential regulatory role in synaptic plasticity. These results indicate that, compared to the SNAN and spiking neuron network (SNN), the improved SNAN incorporated 2-Arachidonoylglycerol (2-AG) modulation displays notable resistance to high noise interference. The improved SNAN shows optimal working memory performance, demonstrating a greater correlation between recalled patterns and input patterns. This may be due to the reduced connection sparsity of the neural network and decreased neural firing frequency caused by 2-AG, as well as its simultaneous impact on the secretion of glutamate. At the same time, astrocytes affecting memory maintenance generate overlapping calcium signals in multi-task working memory. In addition, astrocytes can significantly enhance working memory performance by modulating synaptic coupling under high noise interference. This study may provide insights into understanding the role of astrocytes in the neural mechanisms of working memory and information processing.

Keywords: working memory astrocytes anti-interference ability spiking neuron-astrocyte network synaptic plasticity

Received: 16 January 2026
Revised: 05 March 2026
Accepted manuscript online: 07 March 2026

PACS:	87.19.L-	(Neuroscience)
	05.45.-a	(Nonlinear dynamics and chaos)
	87.19.ll	(Models of single neurons and networks)
	87.19.lw	(Plasticity)

Fund: This study was supported by the National Natural Science Foundation of China (Grant Nos. 12305054 and 12572032), the Guangdong Provincial Key Laboratory of Mathematical and Neural Dynamical Systems (Grant No. 2024B1212010004), and the Fundamental Research Funds for Central Universities, China University of Geosciences (Wuhan) (Grant No. CUGQT2023001).

Corresponding Authors: Lulu Lu
E-mail: lululu@cug.edu.cn

Cite this article:

Lin Li(李琳), Bingyi Mo(莫冰毅), Shanshan Cheng(程姗姗), Zhouchao Wei(魏周超), Ming Yi(易鸣), and Lulu Lu(鹿露露) Anti-interference ability of spiking neuron-astrocyte networks in working memory 2026 Chin. Phys. B 35 068703

[1] Alexander R, Aragon O R, Bookwala J, et al. 2021 Neuroscience & Biobehavioral Reviews 121 220
[2] Miyake A, Friedman N P, Emerson M J, et al. 2000 Cognitive Psychology 41 49
[3] Baddeley A D 2001 American Psychologist 56 851
[4] Kolk S M, Rakic P 2022 Neuropsychopharmacology 47 41
[5] Li H, Yan G, Luo W, et al. 2021 Brain Structure and Function 226 1961
[6] Zhu J, Cheng Q, Chen Y, et al. 2020 Neuron 105 934
[7] Spiegel I, Mardinly A R, Gabel H W, et al. 2014 Cell 157 1216
[8] Zeltser L M, Seeley R J, Matthias H 2012 Nature Neuroscience 15 1336
[9] Farhy-Tselnicker I, Allen N J 2018 Neural Development 13 7
[10] Perea G, Navarrete M, Araque A 2009 Trends in Neurosciences 32 421
[11] Scanziani M, Salin P A, Vogt K E, et al. 1997 Nature 385 630
[12] Navarrete M, Araque A 2010 Neuron 68 113
[13] Kang J, Jiang L I, Goldman S A, et al. 1998 Nature Neuroscience 1 683
[14] Fiacco T A, Agulhon C, Taves S R, et al. 2007 Neuron 54 611
[15] Binan L, Jiang A, Danquah S A, et al. 2025 Cell 188 2141
[16] Simpson E H, Akam T, Patriarchi T, et al. 2024 Neuron 112 718
[17] Saults J S, Cowan N 2007 Journal of Experimental Psychology: General 136 663
[18] Jiang S, Song Y, Kang H, et al. 2021 ACS Applied Materials & Interfaces 14 3385
[19] Guerrieri A, Lattanzio V, Palmisano F, et al. 2006 Biosensors & Bioelectronics 21 1710
[20] Song Y, Guo L, Man M, et al. 2024 Pattern Recognition 155 110672
[21] Iglesias J, Eriksson J, Grize F, et al. 2005 Biosystems 79 11
[22] Eshraghian J K, Ward M, Neftci E O, et al. 2023 Proceedings of the IEEE 111 1016
[23] Wang J, Zhao D, Du C, et al. 2024 iScience 28 112660
[24] Gordleeva S, Tsybina Y, Krivonosov M, et al. 2023 IEEE Transactions on Neural Networks and Learning Systems 36 881
[25] Zhuoheng G, Liqing W, Xin Z, et al. 2024 Cognitive Neurodynamics 18 503
[26] Naghieh P, Delavar A, Amiri M, et al. 2023 iScience 26 108241
[27] Palaba T, Ylmaz E 2025 Nonlinear Dynamics 113 8991
[28] Lu L, Gao Z, Wei Z, et al. 2023 Chaos 33 013127
[29] Keith J M, Apodaca R, Xiao W, et al. 2008 Bioorganic & medicinal chemistry letters 18 4838
[30] Mahmoud S, Gharagozloo M, Simard C, et al. 2019 Cells 8 184
[31] Gordleeva S, Tsybina Y, Krivonosov M, et al. 2021 Frontiers in Cellular Neuroscience 15 631485
[32] Santello M, Volterra A 2009 Neuroscience 158 253
[33] Rodríguez-Arellano J J, Parpura V, Zorec R, et al. 2016 Neuroscience 323 170
[34] Izhikevich E M 2003 IEEE Transactions on Neural Networks 14 1569
[35] Liu C, Wang J, Yu H, et al. 2015 Communications in Nonlinear Science and Numerical Simulation 28 10
[36] Lu L, Yi M and Liu L 2022 Science China Technological Sciences 65 1661
[37] Kampakis S 2012 Soft Computing 16 943
[38] Kanakov O, Gordleeva S, Ermolaeva A, et al. 2019 Phys. Rev. E 99 012418
[39] Esir P M, Gordleeva S Y, Simonov A Y, et al. 2018 Phys. Rev. E 98 052401
[40] Caporale N and Dan Y 2008 Annual Review of Neuroscience 31 25
[41] Feldman D E 2012 Neuron 75 556
[42] Pfister J P, Gerstner W 2006 The Journal of neuroscience 26 9673
[43] Ullah G, Jung P, Cornell-Bell A H 2006 Cell Calcium 39 197
[44] Kazantsev V B, Asatryan S Y 2011 Phys. Rev. E 84 031913
[45] Aghazadeh R, Salimi-Nezhad N, Arezoomand F, et al. 2025 Neural Networks 182 106934
[46] Zhou T, Yan G, Wang B H 2005 Phys. Rev. E 71 046141
[47] Tsybina Y, Kastalskiy I, Krivonosov M, et al. 2022 Neural Computing and Applications 34 9147
[48] Ghavasieh A, De Domenico M 2024 Nature Physics 20 512
[49] Hens C, Harush U, Haber S, et al. 2019 Nature Physics 15 403
[50] Zachariah M K, Coleman G T, Mahns D A, et al. 2001 Journal of Neurophysiology 86 900
[51] Amiri M, Hosseinmardi N, Bahrami F, et al. 2013 Journal of Computational Neuroscience 34 489
[52] Squadrani L, Wert-Carvajal C, Muller-Komorowska D, et al. 2024 Communications biology 7 852
[53] Yamamoto M and Takano T 2025 Cells 14 1936
[54] Lv G, Xu T, Chen F, et al. 2024 Chin. Phys. B 33 028704
[55] Li Z J, Zhang J 2024 Chin. Phys. B 33 128701
[56] Oberheim N A, Wang X, Goldman S, et al. 2006 Trends in Neurosciences 29 547
[57] Oberheim N A, Takano T, Han X, et al. 2009 Journal of Neuroscience 29 3276
[58] Halassa M M, Fellin T, Takano H, et al. 2007 Journal of Neuroscience 27 6473

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Anti-interference ability of spiking neuron-astrocyte networks in working memory

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