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Nonlinear Dynamics

, Volume 93, Issue 4, pp 2473–2485 | Cite as

Effects of the electromagnetic radiation on cognitive performance: a model study

  • Weijie Ye
  • Weidong Mai
  • Guiwu Hu
Original Paper
  • 130 Downloads

Abstract

We constructed a two-layer network model to study the effect of electromagnetic radiation on the cognitive functions. The network model was used to simulate two cognitive tasks under the electromagnetic radiation: the visual-guided saccade task and the memory-guided saccade task. The performance of these tasks showed that the electromagnetic radiation could induce faster ramping up activities, higher level of persistent activities and shorter reaction time, but the basic functions of the network such as working memory and motor output did not impair. We found that the electromagnetic radiation have both excitatory effect and inhibitory effect on the neuronal activities of the network model, but the excitatory effect played a major role. Finally, we concluded an excitatory mechanism to explain the effects of the electromagnetic radiation on the cognitive performance.

Keywords

Electromagnetic radiation Working memory Network model Saccade Cognitive function 

Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 11702064), and by the Science and Technology Program of Guangzhou, China (Grant No. 201707010227).

References

  1. 1.
    Cinel, C., Boldini, A., Fox, E., Russo, R.: Does the use of mobile phones affect human short-term memory or attention? Appl. Cogn. Psychol. 22(8), 1113–1125 (2008)CrossRefGoogle Scholar
  2. 2.
    Curcio, G., Ferrara, M., De Gennaro, L., Cristiani, R., D’Inzeo, G., Bertini, M.: Time-course of electromagnetic field effects on human performance and tympanic temperature. Neuroreport 15(1), 161–164 (2004)CrossRefGoogle Scholar
  3. 3.
    Jech, R., Sonka, K., Ruzicka, E., Nebuzelsky, A., Bohm, J., Juklikova, M., Nevsimalova, S.: Electromagnetic field of mobile phones affects visual event related potential in patients with narcolepsy. Bioelectromagnetics 22(7), 519–528 (2001)CrossRefGoogle Scholar
  4. 4.
    Koivisto, M., Revonsuo, A., Krause, C., Haarala, C., Sillanmaki, L., Laine, M., Hamalainen, H.: Effects of 902 MHz electromagnetic field emitted by cellular telephones on response times in humans. Neuroreport 11(2), 413–415 (2000)CrossRefGoogle Scholar
  5. 5.
    Lee, T.M.C., Lam, P.-K., Yee, L.T.S., Chan, C.C.H.: The effect of the duration of exposure to the electromagnetic field emitted by mobile phones on human attention. Neuroreport 14(10), 1361–1364 (2003)CrossRefGoogle Scholar
  6. 6.
    Okano, T., Terao, Y., Furubayashi, T., Yugeta, A., Hanajima, R., Ugawa, Y.: The effect of electromagnetic field emitted by a mobile phone on the inhibitory control of saccades. Clin. Neurophysiol. 121(4), 603–611 (2010)CrossRefGoogle Scholar
  7. 7.
    Eliyahu, I., Luria, R., Hareuveny, R., Margaliot, M., Meiran, N., Shani, G.: Effects of radiofrequency radiation emitted by cellular telephones on the cognitive functions of humans. Bioelectromagnetics 27(2), 119–126 (2006)CrossRefGoogle Scholar
  8. 8.
    Keetley, V., Wood, A.W., Spong, J., Stough, C.: Neuropsychological sequelae of digital mobile phone exposure in humans. Neuropsychologia 44(10), 1843–1848 (2006)CrossRefGoogle Scholar
  9. 9.
    Luria, R., Eliyahu, I., Hareuveny, R., Margaliot, M., Meiran, N.: Cognitive effects of radiation emitted by cellular phones: the influence of exposure side and time. Bioelectromagnetics 30(3), 198–204 (2009)CrossRefGoogle Scholar
  10. 10.
    Regel, S.J., Tinguely, G., Schuderer, J., Adam, M., Kuster, N., Landolt, H.T.E.R., Achermann, P.: Pulsed radio-requency electromagnetic fields: dose-ependent effects on sleep, the sleep EEG and cognitive performance. J. Sleep Res. 16(3), 253–258 (2007)CrossRefGoogle Scholar
  11. 11.
    Regel, S.J., Gottselig, J.M., Schuderer, J., Tinguely, G., Retey, J.V., Kuster, N., Landolt, H.-P., Achermann, P.: Pulsed radio frequency radiation affects cognitive performance and the waking electroencephalogram. Neuroreport 18(8), 803–807 (2007)CrossRefGoogle Scholar
  12. 12.
    Smythe, J.W., Costall, B.: Mobile phone use facilitates memory in male, but not female, subjects. Neuroreport 14(2), 243–246 (2003)CrossRefGoogle Scholar
  13. 13.
    Krause, C.M., Haarala, C., Sillanmaki, L., Koivisto, M., Alanko, K., Revonsuo, A., Laine, M., Hamalainen, H.: Effects of electromagnetic field emitted by cellular phones on the EEG during an auditory memory task: a double blind replication study. Bioelectromagnetics 25(1), 33–40 (2004)CrossRefGoogle Scholar
  14. 14.
    Rodina, A., Lass, J., Riipulk, J., Bachmann, T., Hinrikus, H.: Study of effects of low level microwave field by method of face masking. Bioelectromagnetics 26(7), 571–577 (2005)CrossRefGoogle Scholar
  15. 15.
    Curcio, G., Nardo, D., Perrucci, M.G., Pasqualetti, P., Chen, T.L., Del Gratta, C., Romani, G.L., Rossini, P.M.: Effects of mobile phone signals over BOLD response while performing a cognitive task. Clin. Neurophysiol. 123(1), 129–136 (2012)CrossRefGoogle Scholar
  16. 16.
    De Vocht, F., Liket, L., De Vocht, A., Mistry, T., Glover, P., Gowland, P., Kromhout, H.: Exposure to alternating electromagnetic fields and effects on the visual and visuomotor systems. Br. J. Radiol. 80(958), 822–828 (2007)CrossRefGoogle Scholar
  17. 17.
    Hamblin, D.L., Croft, R.J., Wood, A.W., Stough, C., Spong, J.: The sensitivity of human event-related potentials and reaction time to mobile phone emitted electromagnetic fields. Bioelectromagnetics 27(4), 265–273 (2006)CrossRefGoogle Scholar
  18. 18.
    Krause, C.M., Pesonen, M., Haarala Bjornberg, C., Hamalainen, H.: Effects of pulsed and continuous wave 902 MHz mobile phone exposure on brain oscillatory activity during cognitive processing. Bioelectromagnetics 28(4), 296–308 (2007)CrossRefGoogle Scholar
  19. 19.
    Sauter, C., Dorn, H., Bahr, A., Hansen, M., Peter, A., Bajbouj, M., Danker-Hopfe, H.: Effects of exposure to electromagnetic fields emitted by GSM 900 and WCDMA mobile phones on cognitive function in young male subjects. Bioelectromagnetics 32(3), 179–190 (2011)CrossRefGoogle Scholar
  20. 20.
    Terao, Y., Okano, T., Furubayashi, T., Ugawa, Y.: Effects of thirty-minute mobile phone use on visuo-motor reaction time. Clin. Neurophysiol. 117(11), 2504–2511 (2006)CrossRefGoogle Scholar
  21. 21.
    Regel, S.J., Achermann, P.: Cognitive performance measures in bioelectromagnetic research-critical evaluation and recommendations. Environ. Health 10(1), 10–10 (2011)CrossRefGoogle Scholar
  22. 22.
    Hareuveny, R., Eliyahu, I., Luria, R., Meiran, N., Margaliot, M.: Cognitive effects of cellular phones: a possible role of non-radiofrequency radiation factors. Bioelectromagnetics 32(7), 585–588 (2011)CrossRefGoogle Scholar
  23. 23.
    Boardman, I., Bullock, D.: A neural network model of serial order recall from short-term memory. In: IJCNN-91-Seattle International Joint Conference on Neural Networks, vol. 2, pp. 879–884 (1991)Google Scholar
  24. 24.
    Lo, C.C., Boucher, L., Pare, M., Schall, J.D., Wang, X.J.: Proactive inhibitory control and attractor dynamics in countermanding action: a spiking neural circuit model. J. Neurosci. 29(28), 9059–9071 (2009)CrossRefGoogle Scholar
  25. 25.
    Lo, C.C., Wang, X.J.: Conflict resolution as near-threshold decision-making: a spiking neural circuit model with two-stage competition for antisaccadic task. PLoS Comput. Biol. 12(8), e1005081–e1005081 (2016)CrossRefGoogle Scholar
  26. 26.
    Wiecki, T.V., Frank, M.J.: A computational model of inhibitory control in frontal cortex and basal ganglia. Psychol. Rev. 120(2), 329–355 (2013)CrossRefGoogle Scholar
  27. 27.
    Heinzle, J., Hepp, K., Martin, K.A.: A microcircuit model of the frontal eye fields. J. Neurosci. 27(35), 9341–9353 (2007)CrossRefGoogle Scholar
  28. 28.
    Tajima, S., Koida, K., Tajima, C.I., Suzuki, H., Aihara, K., Komatsu, H.: Task-dependent recurrent dynamics in visual cortex. eLife 6, e26868 (2017)CrossRefGoogle Scholar
  29. 29.
    Silver, M.R., Grossberg, S., Bullock, D., Histed, M.H., Miller, E.K.: A neural model of sequential movement planning and control of eye movements: item-order-rank working memory and saccade selection by the supplementary eye fields. Neural Netw. 26, 29–58 (2012)CrossRefGoogle Scholar
  30. 30.
    Miller, P.: A recurrent network model of somatosensory parametric working memory in the prefrontal cortex. Cereb. Cortex 13(11), 1208–1218 (2003)CrossRefGoogle Scholar
  31. 31.
    Ye, W., Liu, S., Liu, X., Yu, Y.: A neural model of the frontal eye fields with reward-based learning. Neural Netw. 81, 39–51 (2016)CrossRefGoogle Scholar
  32. 32.
    Ardid, S., Wang, X.J.: A tweaking principle for executive control: neuronal circuit mechanism for rule-based task switching and conflict resolution. J. Neurosci. 33(50), 19504–19517 (2013)CrossRefGoogle Scholar
  33. 33.
    Fusi, S., Asaad, W.F., Miller, E.K., Wang, X.J.: A neural circuit model of flexible sensorimotor mapping: learning and forgetting on multiple timescales. Neuron 54(2), 319–333 (2007)CrossRefGoogle Scholar
  34. 34.
    Cain, C.A.: A theoretical basis for microwave and RF field effects on excitable cellular membranes. IEEE Trans. Microw. Theory Technol. 28(2), 142–147 (1980)CrossRefGoogle Scholar
  35. 35.
    Bao, B.C., Liu, Z., Xu, J.P.: Steady periodic memristor oscillator with transient chaotic behaviours. Electron. Lett. 46(3), 237–238 (2010)CrossRefGoogle Scholar
  36. 36.
    Muthuswamy, B.: Implementing memristor based chaotic circuits. Int. J. Bifurcat. Chaos 20(05), 1335–1350 (2010)CrossRefzbMATHGoogle Scholar
  37. 37.
    Strukov, D.B., Snider, G.S., Stewart, D.R., Williams, R.S.: The missing memristor found. Nature 453(7191), 80–83 (2008)CrossRefGoogle Scholar
  38. 38.
    Lv, M., Ma, J.: Multiple modes of electrical activities in a new neuron model under electromagnetic radiation. Neurocomputing 205, 375–381 (2016)CrossRefGoogle Scholar
  39. 39.
    Lv, M., Wang, C., Ren, G., Ma, J., Song, X.: Model of electrical activity in a neuron under magnetic flow effect. Nonlinear Dyn. 85(3), 1479–1490 (2016)CrossRefGoogle Scholar
  40. 40.
    Ma, J., Wu, F., Wang, C.: Synchronization behaviors of coupled neurons under electromagnetic radiation. Int. J. Mod. Phys. B 31(2), 1650251–1650251 (2017)MathSciNetCrossRefGoogle Scholar
  41. 41.
    Fan, D., Wang, Q.: Synchronization and bursting transition of the coupled Hindmarsh-Rose systems with asymmetrical time-delays. Sci. China Technol. Sci. 60(7), 1019–1031 (2017)CrossRefGoogle Scholar
  42. 42.
    Zhang, L., Wang, Y., Wang, Q.: Synchronization for time-varying complex dynamical networks with different-dimensional nodes and non-dissipative coupling. Commun. Nonlinear Sci. Numer. Simul. 24(1), 64–74 (2015)MathSciNetCrossRefGoogle Scholar
  43. 43.
    Zheng, Y., Lu, Q., Wang, Q.: Spatio-temporal coherence resonance and firing synchronization in a neural network: noise and coupling effects. Int. J. Mod. Phys. C 20(03), 469–478 (2009)MathSciNetCrossRefzbMATHGoogle Scholar
  44. 44.
    Mvogo, A., Takembo, C.N., Ekobena Fouda, H.P., Kofane, T.C.: Pattern formation in diffusive excitable systems under magnetic flow effects. Phys. Lett. A 381(28), 2264–2271 (2017)MathSciNetCrossRefGoogle Scholar
  45. 45.
    Pariz, A., Esfahani, Z.G., Parsi, S.S., Valizadeh, A., Canals, S., Mirasso, C.R.: High frequency neurons determine effective connectivity in neuronal networks. NeuroImage 166, 349–359 (2018)CrossRefGoogle Scholar
  46. 46.
    Bayati, M., Valizadeh, A., Abbassian, A., Cheng, S.: Self-organization of synchronous activity propagation in neuronal networks driven by local excitation. Front. Comput. Neurosci. 9, 69 (2015)CrossRefGoogle Scholar
  47. 47.
    Wang, X.J.: Synaptic basis of cortical persistent activity: the importance of NMDA receptors to working memory. J. Neurosci. 19(21), 9587–9603 (1999)CrossRefGoogle Scholar
  48. 48.
    Compte, A., Brunel, N., Goldman-Rakic, P.S., Wang, X.J.: Synaptic mechanisms and network dynamics underlying spatial working memory in a cortical network model. Cereb. Cortex 10(9), 910–923 (2000)CrossRefGoogle Scholar
  49. 49.
    Wu, F., Wang, C., Jin, W., Ma, J.: Dynamical responses in a new neuron model subjected to electromagnetic induction and phase noise. Physica A 469, 81–88 (2017)MathSciNetCrossRefGoogle Scholar
  50. 50.
    Ma, J., Wang, Y., Wang, C., Xu, Y., Ren, G.: Mode selection in electrical activities of myocardial cell exposed to electromagnetic radiation. Chaos Solitons Fractals 99, 219–225 (2017)CrossRefGoogle Scholar
  51. 51.
    Wu, F., Wang, C., Xu, Y., Ma, J.: Model of electrical activity in cardiac tissue under electromagnetic induction. Sci. Rep. 6(1), 28–40 (2016)CrossRefGoogle Scholar
  52. 52.
    Itoh, M., Chua, L.O.: Memristor oscillators. Int. J. Bifurcat. Chaos 18(11), 3183–3206 (2008)MathSciNetCrossRefzbMATHGoogle Scholar
  53. 53.
    Wu, J., Xu, Y., Ma, J.: Levy noise improves the electrical activity in a neuron under electromagnetic radiation. PLoS One 12(3), e0174330–e0174330 (2017)CrossRefGoogle Scholar
  54. 54.
    Wang, Y., Ma, J., Xu, Y., Wu, F., Zhou, P.: The electrical activity of neurons subject to electromagnetic induction and Gaussian white noise. Int. J. Bifurcat. Chaos 27(02), 1750030–1750030 (2017)MathSciNetCrossRefzbMATHGoogle Scholar
  55. 55.
    Brunel, N., Wang, X.J.: Effects of neuromodulation in a cortical network model of object working memory dominated by recurrent inhibition. J. Comput. Neurosci. 11(1), 63–85 (2001)CrossRefGoogle Scholar
  56. 56.
    Everling, S., Fischer, B.: The antisaccade: a review of basic research and clinical studies. Neuropsychologia 36(9), 885–899 (1998)CrossRefGoogle Scholar
  57. 57.
    Johnston, K., Everling, S.: Monkey dorsolateral prefrontal cortex sends task-selective signals directly to the superior colliculus. J. Neurosci. 26(48), 12471–12478 (2006)CrossRefGoogle Scholar
  58. 58.
    Terao, Y., Okano, T., Furubayashi, T., Yugeta, A., Inomata-Terada, S., Ugawa, Y.: Effects of thirty-minute mobile phone exposure on saccades. Clin. Neurophysiol. 118(7), 1545–1556 (2007)CrossRefGoogle Scholar

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© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Statistics and MathematicsGuangdong University of Finance and EconomicsGuangzhouChina

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