Effect of applied electric fields on supralinear dendritic integration of interneuron
Ya-Qin Fan(樊亚琴)1, Xi-Le Wei(魏熙乐)1, Mei-Li Lu(卢梅丽)2, and Guo-Sheng Yi(伊国胜)1,†
1 Tianjin Key Laboratory of Process Measurement and Control, School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China; 2 School of Information Technology Engineering, Tianjin University of Technology and Education, Tianjin 300222, China
Abstract Evidences show that electric fields (EFs) induced by the magnetic stimulation could modulates brain activities by regulating the excitability of GABAergic interneuron. However, it is still unclear how and why the EF-induced polarization affects the interneuron response as the interneuron receives NMDA synaptic inputs. Considering the key role of NMDA receptor-mediated supralinear dendritic integration in neuronal computations, we suppose that the applied EFs could functionally modulate interneurons' response via regulating dendritic integration. At first, we build a simplified multi-dendritic circuit model with inhomogeneous extracellular potentials, which characterizes the relationship among EF-induced spatial polarizations, dendritic integration, and somatic output. By performing model-based singular perturbation analysis, it is found that the equilibrium point of fast subsystem can be used to asymptotically depict the subthreshold input-output (sI/O) relationship of dendritic integration. It predicted that EF-induced strong depolarizations on the distal dendrites reduce the dendritic saturation output by reducing driving force of synaptic input, and it shifts the steep change of sI/O curve left by reducing stimulation threshold of triggering NMDA spike. Also, the EF modulation prefers the global dendritic integration with asymmetric scatter distribution of NMDA synapses. Furthermore, we identify the respective contribution of EF-regulated dendritic integration and EF-induced somatic polarization to an action potential generation and find that they have an antagonistic effect on AP generation due to the varied NMDA spike threshold under EF stimulation.
Fund: Project supported by the National Natural Science Foundation of China (Grant No. 62171312) and the Tianjin Municipal Education Commission Scientific Research Project, China (Grant No. 2020KJ114).
Corresponding Authors:
Guo-Sheng Yi
E-mail: guoshengyi@tju.edu.cn
Cite this article:
Ya-Qin Fan(樊亚琴), Xi-Le Wei(魏熙乐), Mei-Li Lu(卢梅丽), and Guo-Sheng Yi(伊国胜) Effect of applied electric fields on supralinear dendritic integration of interneuron 2024 Chin. Phys. B 33 020202
[1] Isaacson J S and Scanziani M 2011 Neuron72 231 [2] Shetty A K and Bates A 2016 Brain Research1638 74 [3] Kwakowsky A, Guzman B C F, Pandya M, Turner C, Waldvogel H J and Faull R L 2018 Journal of Neurochemistry145 374 [4] Tyson J A and Anderson S A 2014 Trends Neurosciences37 169 [5] Southwell D G, Nicholas C R, Basbaum A I, Stryker M P, Kriegstein A R, Rubenstein J L and Alvarez-Buylla A 2014 Science344 167 [6] Amatniek J C and Hauser W A 2006 Epilepsia47 867 [7] Guzman B C F, Vinnakota C, Govindpani K, Waldvogel H J, Faull R L M and Kwakowsky A 2018 Journal of Neurochemistry146 649 [8] Xu M Y and Wong A H C 2018 Acta Pharmacologica Sinica39 733 [9] Huang Y, Liu A A, Lafon B, Friedman D, Dayan M, Wang X Y, Bikson M, Doyle W K, Devinsky O and Parra L C 2017 ELife6 e18834 [10] Sathappan A V, Luber B M and Lisanby S H 2019 Progress in Neuro-Psychopharmacology & Biological Psychiatry89 347 [11] Ladenbauer J, Ladenbauer J, Kulzow N, de Boor R, Avramova E, Grittner U and Floel A 2017 The Journal of Neuroscience37 7111 [12] Deng Z D, Lisanby S H and Peterchev A V 2013 Brain Stimulation6 1 [13] Bikson M, Inoue M, Akiyama H, Deans J K, Fox J E, Miyakawa H and Jefferys J G R 2004 Journal of Physiology-London557 175 [14] Radman T, Su Y Z, An J H, Parra L C and Bikson M 2007 Journal of Neuroscience27 3030 [15] Reato D, Rahman A, Bikson M and Parra L C 2010 Journal of Neuroscience30 15067 [16] Radman T, Ramos R L, Brumberg J C and Bikson M 2009 Brain Stimulation2 215 [17] Jackson M P, Rahman A, Lafon B, Kronberg G, Ling D, Parra L C and Bikson M 2016 Clinical Neurophysiology127 3425 [18] Murphy S C, Palmer L M, Nyffeler T, Muri R M and Larkum M E 2016 Elife5 e13598 [19] Xue J G, Masuoka T, Gong X D, Chen K S, Yanagawa Y, Law S K A and Konishi S 2011 Journal of Neurophysiology105 2897 [20] Poleg-Polsky A 2015 Plos One10 e0140254 [21] Lavzin M, Rapoport S, Polsky A, Garion L and Schiller J 2012 Nature490 397 [22] Tran-Van-Minh A, Caze R D, Abrahamsson T, Cathala L, Gutkin B S and DiGregorio D A 2015 Frontiers in Cellular Neuroscience9 67 [23] Augusto E and Gambino F 2019 Frontiers in Molecular Neuroscience12 238 [24] Fan Y Q, Wei X L, Yi G S, Lu M L, Wang J and Deng B 2021 Neural Computation33 3102 [25] Fan Y Q, Wei X L, Lu M L, Wang J and Yi G S 2023 Cognitive Nuerodynamic [26] Peterchev A V, Wagner T A, Miranda P C, Nitsche M A, Paulus W, Lisanby S H, Pascual-Leone A and Bikson M 2012 Brain Stimulation5 435 [27] Laakso I, Murakami T, Hirata A and Ugawa Y 2018 Brain Stimulation11 166 [28] Saraga F, Wu C P, Zhang L, Skinner F K 2003 Journal of Physiology-London552 673 [29] Berzhanskaya J, Chernyy N, Gluckman B J, Schiff S J and Ascoli G A 2013 Journal of Computational Neuroscience34 369 [30] Hines M L and Carnevale N T 1997 Neural Computation9 1179
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