Abstract We investigate the relationship between the synchronous transition and the power law behavior in spiking networks which are composed of inhibitory neurons and balanced by dc current. In the region of the synchronous transition, the avalanche size and duration distribution obey a power law distribution. We demonstrate the robustness of the power law for event sizes at different parameters and multiple time scales. Importantly, the exponent of the event size and duration distribution can satisfy the critical scaling relation. By changing the network structure parameters in the parameter region of transition, quasicriticality is observed, that is, critical exponents depart away from the criticality while still hold approximately to a dynamical scaling relation. The results suggest that power law statistics can emerge in networks composed of inhibitory neurons when the networks are balanced by external driving signal.
Fund: Project supported by the National Natural Science Foundation of China (Grant No. 11675096) and the Fund for the Academic Leaders and Academic Backbones, Shaanxi Normal University, China (Grant No. 16QNGG007).
Corresponding Authors:
Sheng-Jun Wang
E-mail: wangshjun@snnu.edu.cn
Cite this article:
Lei Tao(陶蕾) and Sheng-Jun Wang(王圣军) Power-law statistics of synchronous transition in inhibitory neuronal networks 2022 Chin. Phys. B 31 080505
[1] Newman M 2005 Contemp. Phys.46 323 [2] Zeng H L, Zhu C P, Wang S X, Guo Y D, Gu Z M and Hu C K 2005 Physica A540 123191 [3] Touboul J and Destexhe A 2017 Phys. Rev. E95 012413 [4] Lin M, Wang G and Chen T L 2006 Commun. Theor. Phys.46 1011 [5] Pan B C, Shi Q F and Sun G 2013 Chin. Phys. Lett.30 124701 [6] Dong Y Q, Wang F, Wang S J and Huang Z G 2019 Chin. Phys. B28 128701 [7] Wang F and Wang S J 2019 Chin. Phys. B71 746 [8] Gutenberg B and Richter C F 1944 Bull. Seismol. Soc. Am.34 185 [9] Li B Q, Wu Z X and Wang S J 2019 Chin. Phys. B28 090503 [10] Sun B A, Wang L F and Shao J H 2017 Acta Phys. Sin.66 178103 (in Chinese) [11] Malamud B D, Morein G and Turcotte D L 1998 Science281 1840 [12] Willis J C and Yule G U 1922 Nature109 177 [13] de Solla Price D J 1965 Science149 510 [14] Adamic L and Huberman B A 2000 SSRN Electron. J.1 1 [15] Wang S J, Hilgetag C C and Zhou C S 2011 Front. Comptut. Neurosci.5 30 [16] Bédard C, Kröger H and Destexhe A. 2006 Phys. Rev. Lett.97 118102 [17] Zhang G Q, Yang Q Y and Zhang A Z 2014 Appl. Math. Comput.242 346 [18] Pan G J, Zhang D M, Yin Y P and He M H 2006 Chin. Phys. Lett.23 2811 [19] Zhou T and Wang B H 2005 Chin. Phys. Lett.22 1072 [20] Beggs J M and Plenz D 2003 J. Neurosci.23 11167 [21] Villegas P, Santo S di, Burioni R and Muñoz M A 2019 Phys. Rev. E100 012133 [22] Beggs J M and Plenz D 2004 J. Neurosci.24 5216 [23] Ribeiro T L, Copelli M, Caixeta F, Belchior H, Chialvo D R, Nicolelis M A L and Ribeiro S 2010 PLoS ONE5 e14129 [24] Palva J M, Zhigalov A, Hirvonen J, Korhonen O, Linkenkaer-Hansen K and Palva S 2013 Proc. Natl. Acad. Sci. USA110 3585 [25] Shew W L, Clawson W P, Pobst J, Karimipanah Y, Wright N C and Wessel R 2015 Nat. Phys.11 659 [26] Zhigalov A, Arnulfo G, Nobili L, Palva S and Palva J M 2015 J. Neurosci.35 5385 [27] Scott G, Fagerholm E D, Mutoh H, Leech R, Sharp D J, Shew W L and Knöpfel T 2014 J. Neurosci.34 16611 [28] Bellay T, Klaus A, Seshadri S and Plenz D 2015 eLife4 e07224 [29] Beggs J M and Timme N 2012 Front. Physiol.3 163 [30] Mitzenmacher M 2004 Internet Math.1 226 [31] Zapperi S, Lauritsen K B and Stanley H E 1995 Phys. Rev. Lett.75 4071 [32] Haldeman C and Beggs J M 2005 Phys. Rev. Lett.94 058101 [33] Plenz D and Thiagarajan T C 2007 Trends Neurosci.30 101 [34] Alstrom P 1988 Phys. Rev. A38 4905 [35] Arenas A, Díza-Guilera A, Kurths J, Moreno Y and Zhou C 2008 Phys. Rep.469 93 [36] Kurrer C and Schulten K 1995 Phys. Rev. E51 6213 [37] Bertolotti E, Burioni R, Volo M D and Vezzani A 2017 Phys. Rev. E95 012308 [38] Qian Y, Gao H Y, Yao C G, Cui X H and Ma J 2018 Chin. Phys. B27 108902 [39] Feng C F, Xu J X, Wu Z X and Wang Y H 2008 Chin. Phys. B17 1951 [40] Zhang J Q, Huang S F, Pang S T, Wang M S and Gao S 2015 Chin. Phys. Lett.32 120502 [41] Varela F, Lachaux J P, Rodriguez E and Martinerie J 2001 Nat. Rev. Neurosci.2 229 [42] Shusterman V and Troy W C 2008 Phys. Rev. E77 061911 [43] McAuley J H and Marsden C D 2000 Brain123 1545 [44] Fontenele A J, Vasconcelos N A P de, Feliciano T, Aguiar L A A, Soares-Cunha C, Coimbra B, Porta L D, Ribeiro S, Rodrigues A J, Sousa N, Carelli P V and Copelli M 2019 Phys. Rev. Lett.122 208101 [45] Santo S di, Villegas P, Burioni R and Muñoz M A 2018 Proc. Natl. Acad. Sci. USA115 E1356 [46] Yang H, Shew W L, Roy R and Plenz D 2012 J. Neurosci.32 1061 [47] Ma Z, Turrigiano G G, Wessel R and Hengen K B 2019 Neuron104 655 [48] Volo M di and Torcini A 2018 Phys. Rev. Lett.121 128301 [49] Mejias J F and Longtin A 2012 Phys. Rev. Lett.108 228102 [50] Priesemann V, Munk M H and Wibral M 2009 BMC Neurosci.10 40 [51] Carvalho T T A, Fontenele A J, Girardi-Schappo M, Feliciano T, Aguiar L A A, Silva T P L, Vasconcelos N A P de, Carelli P V and Copelli M 2021 BMC Neurosci.14 83 [52] Kanders K, Lorimer T and Stoop R 2017 Chaos27 047408 [53] Klaus A, Yu S and Plenz D 2011 PLoS ONE6 e19779 [54] Raimo D, Sarracino A and Arcangelis L de 2020 Physica A565 125555 [55] Fosque L J, Williams-García R V, Beggs J M and Ortiz G 2021 Phys. Rev. Lett.126 098101
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