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Chin. Phys. B, 2022, Vol. 31(2): 028901    DOI: 10.1088/1674-1056/ac0eeb
INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY Prev  

Collective behavior of cortico-thalamic circuits: Logic gates as the thalamus and a dynamical neuronal network as the cortex

Alireza Bahramian1, Sajjad Shaukat Jamal2, Fatemeh Parastesh1, Kartikeyan Rajagopal3, and Sajad Jafari1,4,†
1 Department of Biomedical Engineering, Amirkabir University of Technology(Tehran polytechnic), Iran;
2 Department of Mathematics, College of Science, King Khalid University, Abha, Saudi Arabia;
3 Centre for Nonlinear Systems, Chennai Institute of Technology, Chennai, India;
4 Health Technology Research Institute, Amirkabir University of Technology(Tehran polytechnic), Iran
Abstract  This paper introduces a two-layer network to investigate the effects of cortico-thalamic circuits on the cortex's collective behavior. In the brain, different parts of the cortex collaborate to process information. One of the main parts, which is the path of different cortex contacts, is the thalamus whose circuit is referred to as the "vertical" cortico-thalamic connectivity. Thalamus subnuclei can participate in the processing of the information that passes through them. It has been shown that they play the functional role of logic gates (AND, OR and XOR). To study how these thalamus circuits affect the cortical neuron behavior, a two-layer network is proposed wherein the cortex layer is composed of Hindmarsh-Rose models and the thalamus layer is constructed with logic gates. Results show that considering these logic gates can lead the network towards different synchronization, asynchronization, chimera and solitary patterns. It is revealed that for AND-gate and OR-gate, increasing the number of gates or their outputs can increase and decrease the network's coherency in excitatory and inhibitory cases, respectively. However, considering XOR-gates always results in the chimera state.
Keywords:  two-layer network      synchronization      chimera state      thalamus and cortex  
Received:  05 May 2021      Revised:  23 June 2021      Accepted manuscript online:  28 June 2021
PACS:  89.75.-k (Complex systems)  
  05.45.Xt (Synchronization; coupled oscillators)  
Fund: One of the authors Sajjad Shaukat Jamal extends his gratitude to the Deanship of Scientific Research at King Khalid University for funding this work through the research groups program (Grant No. R. G. P. 2/48/42).
Corresponding Authors:  Sajad Jafari     E-mail:  sajadjafari83@gmail.com

Cite this article: 

Alireza Bahramian, Sajjad Shaukat Jamal, Fatemeh Parastesh, Kartikeyan Rajagopal, and Sajad Jafari Collective behavior of cortico-thalamic circuits: Logic gates as the thalamus and a dynamical neuronal network as the cortex 2022 Chin. Phys. B 31 028901

[1] Boccaletti S, Latora V, Moreno Y, Chavez M and Hwang D U 2006 Phys. Rep. 424 175
[2] Lü L Y 2010 J. Univ. Electron. Sci. Technol. China 39 651
[3] Bera B K, Majhi S, Ghosh D and Perc M 2017 Europhys. Lett. 118 10001
[4] Ting C M, Samdin S B, Tang M and Ombao H 2020 IEEE Trans. Med. Imaging. 40 468
[5] Wei T H, Peng Y, Hai L M, Zhang P and Le T 2019 Acta Phys. Sin. 68 (in Chinese)
[6] Chrastil E R 2018 Behav. Neurosci. 132 317
[7] Bensaid S, Modolo J, Merlet I, Wendling F and Benquet P 2019 Front. Syst. Neurosci. 13 59
[8] Bordes S, Werner C, Mathkour M, et al. 2020 World Neurosurg. 137 310
[9] Sherman S M 2007 Curr. Opin. Neurobiol. 17 417
[10] Halassa M M and Sherman S M 2019 Neuron. 103 762
[11] Boutin A, Pinsard B, Boré A, Carrier J, Fogel S M and Doyon J 2018 NeuroImage. 169 419
[12] Ahissar E and Oram T 2015 Cereb. Cortex. 25 845
[13] Groh A, Bokor H, Mease R A, et al. 2014 Cereb. Cortex 24 3167
[14] Trageser J C, Burke K A, Masri R, Li Y, Sellers L and Keller A 2006 J. Neurophysiol. 96 1456
[15] Habas C, Manto M and Cabaraux P 2019 Cerebellum 18 635
[16] Vardi R, Guberman S, Goldental A and Kanter I 2013 Europhys. Lett. 103 66001
[17] Vogels T P and Abbott L F 2005 J. Neurosci. 25 10786
[18] Vogels T P and Abbott L 2009 Nat. Neurosci. 12 483
[19] Gisiger T and Boukadoum M 2011 Front. Comput. Neurosci. 5 1
[20] Nazari S and Faez K 2019 Inf. Sci. 474 221
[21] Goldental A, Guberman S, Vardi R and Kanter I 2014 Front. Comput. Neurosci. 8 52
[22] Cruikshank S J, Ahmed O J, Stevens T R, et al. 2012 J. Neurosci. 32 17813
[23] Pfeffer C K 2014 Curr. Biol. 24 R18
[24] Cruikshank S J, Lewis T J and Connors B W 2007 Nat. Neurosci. 10 462
[25] Hoerder Suabedissen A, Hayashi S, Upton L, et al. 2018 Cereb. Cortex 28 1882
[26] Steriade M 2005 Trends Neurosci. 28 317
[27] He S, Sun K, Wang H, Mei X and Sun Y 2018 Nonlinear Dyn. 92 85
[28] He S, Sun K and Wang H 2019 Commun. Nonlinear Sci. Numer. Simul. 73 146
[29] Wang S W and Tang L H 2019 Nature Commun. 10 1
[30] Al sawalha M M 2013 Chin. Phys. Lett. 30 070502
[31] Rui S, Wei C and Jing H X 2019 Acta Phys. Sin. 68 (in Chinese)
[32] Traub R D and Wong R 1982 Science 216 745
[33] Koeppen J A, Nahravani F, Kramer M, et al. 2019 Neuromodulation. 22 465
[34] Sauseng P and Klimesch W 2008 Neurosci. Biobehav. Rev. 32 1001
[35] Schülen L, Janzen D A, Medeiros E S and Zakharova A 2021 Chaos Solitons Fractals. 145 110670
[36] Parastesh F, Jafari S, Azarnoush H, et al. 2021 Phys. Rep. 898 1
[37] He S, Natiq H, Banerjee S and Sun K 2021 Symmetry. 13 341
[38] He S 2020 Front. Appl. Math. Stat. 6 24
[39] Majhi S, Bera B K, Ghosh D and Perc M 2019 Phys. Life Rev. 28 100
[40] Gooding D C, Luh K E and Tallent K A 2001 J. Schizophrenia Bulletin. 27 709
[41] Majhi S, Perc M and Ghosh D 2017 Chaos. 27 073109
[42] Majhi S, Perc M and Ghosh D 2016 Sci. Rep. 6 39033
[43] Ruzzene G, Omelchenko I, Sawicki J, Zakharova A, Schöll E and Andrzejak R G 2020 Phys. Rev. E 102 052216
[44] Izhikevich E M 2003 IEEE Trans. Neural Netw. 14 1569
[45] Ma J, Mi L, Zhou P, Xu Y and Hayat T 2017 Appl. Math. Comput. 307 321
[46] González Miranda J 2007 Int. J. Bifurcation Chaos 17 3071
[47] Gopal R, Chandrasekar V, Venkatesan A and Lakshmanan M 2014 Phys. Rev. E 89 052914
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