Abstract
Human exposure to the electromagnetic field emitted by wireless communication systems has raised public concerns. There were claims of the potential association of some neurophysiological disorders with the exposure, but the mechanism is yet to be established. The wireless networks, recently, experience a transition from the 4th generation (4G) to 5th generation (5G), while 4G long-term evolution (LTE) is still the frequently used signal in wireless communication. In the study, exposure experiments were conducted using the LTE signal. The subjects were divided into sham and real exposure groups. Before and after the exposure experiments, they underwent functional magnetic resonance imaging. Within-session and between-session comparisons have been executed for functional connectivity and network properties. Individual specific absorption rate (SAR) was also calculated. The results indicated that acute LTE exposure beneath the safety limits modulated both the functional connection and graph-based properties. To characterize the effect of functional activity, SAR averaged over a certain tissue mass was not an appropriate metric. The potential neurophysiological effect of 5G exposure has also been discussed in the study.
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References
Aalto S, Haarala C, Bruck A, Sipila H, Hamalainen H, Rinne JO (2006) Mobile phone affects cerebral blood flow in humans. J Cerebr Blood F Met 26:885–890. https://doi.org/10.1038/sj.jcbfm.9600279
Aguirre GK, Detre JA, Alsop DC, D’Esposito M (1996) The parahippocampus Ssubserves topographical learning in man. Cereb Cortex 6(6):823–829. https://doi.org/10.1093/cercor/6.6.823
Bassett S, Bullmore E, Verchinski BA, Mattay VS, Weinberger DR, Meyer-Lindenberg A (2008) Hierarchical organization of human cortical networks in health and schizophrenia. J Neurosci 28:9239–9248. https://doi.org/10.1523/JNEUROSCI.1929-08.2008
Beggs JM, Plenz D (2003) Neuronal avalanches in neocortical circuits. J Neurosci 23(35):11167–11177. https://doi.org/10.1523/JNEUROSCI.23-35-11167.2003
Burek M, Follmann R, Rosa E (2019) Temperature effects on neuronal firing rates and tonic-to-bursting transitions. Biosystems. 180:1–6. https://doi.org/10.1016/j.biosystems.2019.03.003
C95.1-2019 - IEEE standard for safety levels with respect to human exposure to electric, magnetic, and electromagnetic fields, 0 Hz to 300 GHz. 2019. SASB/SCC39 - SCC39 - International Committee on Electromagnetic Safety , pp.1-312
Catherine W, Patrick W, Virginia P, Robert Z, Todd P, Daniel A, Nina K (2009) Relating structure to function: Heschl’s gyrus and acoustic processing. J Hist Neurosci 29(1):61–69. https://doi.org/10.1523/JNEUROSCI.3489-08.2009
Croft R, Leung S, McKenzie R, Loughran S, Iskra S, Hamblin DL, Cooper NR (2010) Effects of 2G and 3G mobile phones on human alpha rhythms: resting EEG in adolescents, young adults, and the elderly. Bioelectromagnetics 31:434–444. https://doi.org/10.1002/bem.20583
Curcio G, Nardo D, Perrucci MG, Pasqualetti P, Chen TL, Del Gratta C, Romani G, Rossini PM (2012) Effects of mobile phone signals over BOLD response while performing a cognitive task. Clin Neurophysiol 123:129–136. https://doi.org/10.1016/j.clinph.2011.06.007
Engel SA, Glover GH, Wandell BA (1997) Retinotopic organization in human visual cortex and the spatial precision of functional MRI. Cereb Cortex 7:181–192. https://doi.org/10.1093/cercor/7.2.181
Haarala C, Aalto S, Hautzel H, Julkunen L, Rinne J, Laine M, Krause B, Hamalainen H (2003) Effects of a 902 MHz mobile phone on cerebral blood flow in humans: a PET study. Neuroreport 14:2019–2023. https://doi.org/10.1097/01.wnr.0000090954.15465.94
Hamblin DL, Croft RJ, Wood AW, Stough C, Spong J (2006) The sensitivity of human event-related potentials and reaction time to mobile phone emitted electromagnetic fields. Bioelectromagnetics 27:265–273. https://doi.org/10.1002/bem.20209
Hövel P, Viol A, Loske P, Merfort L, Vuksanović V (2018) Synchronization in functional networks of the human brain. J Nonlinear Sci. https://doi.org/10.1007/s00332-018-9505-7
International Commission on Non-Ionizing Radiation Protection (2020) Guidelines for limiting exposure to electromagnetic fields (100 kHz to 300 GHz). Health Physics 118:483–524
Kaiser M, Hilgetag CC (2006) Nonoptimal component placement, but short processing paths, due to long-distance projections in neural systems. Plos Comput Biol 2(7):805–816. https://doi.org/10.1371/journal.pcbi.0020095
Li CS, Wu TN (2015) Dosimetry of infant exposure to power-frequency magnetic fields: Variation of 99th percentile induced electric field value by posture and skin-to-skin contact. Bioelectromagnetics 36(3):204–218. https://doi.org/10.1002/bem.21899
Li CS, Chen Z, Yang L, Lv B, Liu J, Varsier N, Hadjem A, Wiart J, Xie Y, Ma L, Wu T (2015) Generation of infant anatomical models for evaluating electromagnetic field exposures. Bioelectromagnetics 36:10–26. https://doi.org/10.1002/bem.21868
Lustenberger C, Murbach M, Durr R, Schmid MR, Kuster N, Achermann P, Huber R (2013) Stimulation of the brain with radiofrequency electromagnetic field pulses affects sleepdependent performance improvement. Brain Stimul 6:805–811. https://doi.org/10.1016/j.brs.2013.01.017
Lv B, Chen ZY, Wu TN, Shao Q, Yan Y, Ma L, Lu K, Xie Y (2014a) The alteration of spontaneous low frequency oscillations caused by acute electromagnetic fields exposure. Clin Neurophysiol 125:277–286. https://doi.org/10.1016/j.clinph.2013.07.018
Lv B, Su C, Yang L, Xie Yi, Wu TN (2014b) Whole brain EEG synchronization likelihood modulated by long term evolution electromagnetic fields exposure. 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. https://doi.org/10.1109/embc.2014.6943758
Maguire EA, Frackowiak RSJ, Frith CD (1996) Learning to find your way: a role for the human hippocampal region. Philos T R Soc B 263:1745–1750. https://doi.org/10.1098/rspb.1996.0255
McCarty DE, Carrubba S, Chesson AL, Jr Frilot C, Gonzalez-Toledo E, Marino AA (2011) Electromagnetic hypersensitivity: evidence for a novel neurological syndrome. Int J Neurosci 121:670–676. https://doi.org/10.3109/00207454.2011.608139
Menon V, Uddin LQ (2010) Saliency, switching, attention and control: a network model of insula function. Brain Struct Funct 214(5-6):655–667. https://doi.org/10.1007/s00429-010-0262-0
Nakatani-Enomoto S, Yamazaki M, Nishiura K, Enomoto H, Ugawa Y (2020) Effects of electromagnetic fields from long-term evolution on awake electroencephalogram in healthy humans. J Neurosci Res 156:102–107. https://doi.org/10.1016/j.neures.2020.01.010
Penny W, Friston K, Ashburner J, Kiebel S, Nichols T (2011) Statistical parametric mapping: the analysis of functional brain images. Elsevier, Amsterdam
Price CJ (2012) A review and synthesis of the first 20 years of PET and fMRI studies of heard speech, spoken language and reading. NeuroImage 62(2):816–847. https://doi.org/10.1016/j.neuroimage.2012.04.062
Repacholi MH (1999) WHO’s international EMF project. Radiation protection dosimetry. Radiat Prot Dosim 83(1-2):1–4. https://doi.org/10.1093/oxfordjournals.rpd.a032642
Robertson JA, Theberge J, Weller J, Drost DJ, Prato FS, Thomas AW (2009) Low-frequency pulsed electromagnetic field exposure can alter neuroprocessing in humans. J R Soc Interface 7(44):467–473. https://doi.org/10.1098/rsif.2009.0205
Roggeveen S, van Os J, Lousberg R (2015a) Does the brain detect 3G mobile phone radiation peaks? An explorative in-depth analysis of an experimental study. PLoS ONE 10(5):e0125390 org/10.1371/journal.pone.0125390
Roggeveen S, van Os J, Viechtbauer W, Lousberg R (2015b) EEG changes due to experimentally induced 3G mobile phone radiation. PLoS ONE 10(6):e0129496. https://doi.org/10.1371/journal.pone.0129496
Rowland JA, Stapleton-Kotloski JR, Dobbins DL, Rogers E, Godwin DW, Taber KH (2018) Increased small-world network topology following deployment-acquired traumatic brain injury associated with the development of post-traumatic stress disorder. Brain Connect 8(4):205–211. https://doi.org/10.1089/brain.2017.0556
Rubinov M, Sporns O (2010) Complex network measures of brain connectivity: uses and interpretations. Neuroimage 52:1059–1069. https://doi.org/10.1016/j.neuroimage.2009.10.003
Simard D, Nadeau L, Kroger H (2005) Fastest learning in small-world neural networks. Phys Lett A 336(1):8–15. https://doi.org/10.1016/j.physleta.2004.12.078
Squire L, Zola-Morgan S (1991) The medial temporal lobe memory system. Science 253:1380–1386. https://doi.org/10.1126/science.1896849
Tombini M, Pellegrino G, Pasqualetti P, Assenza G, Benvenga A, Fabrizio E, Rossini PM (2013) Mobile phone emissions modulate brain excitability in patients with focal epilepsy. Brain Stimul 6:448–454. https://doi.org/10.1016/j.brs.2012.07.006
Tzourio-Mazoyera N, Landeaub B, Papathanassioua D, Crivelloa F, Etarda O, Delcroixa N, Mazoyerc B, Joliota M (2002) Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. NeuroImage 15(1):273–289. https://doi.org/10.1006/nimg.2001.0978
Vecchio F, Babiloni C, Ferreri F, Curcio G, Fini R, Del Percio C, Rossini PM (2007) Mobile phone emission modulates interhemispheric functional coupling of EEG alpha rhythms. J Neurosci 25:1908–1913. https://doi.org/10.1111/j.1460-9568.2007.05405.x
Vecchio F, Tombini M, Buffo P, Assenza G, Pellegrino G, Benvenga A, Babiloni C, Rossini PM (2012) Mobile phone emission increases inter-hemispheric functional coupling of electroencephalographic alpha rhythms in epileptic patients. Int J Psychophysiol 84:164–171. https://doi.org/10.1016/j.ijpsycho.2012.02.002
Volkow ND, Tomasi D, Wang GJ, Vaska P, Fowler JS, Telang F, Alexoff D, Logan J, Wong C (2011) Effects of cell phone radiofrequency signal exposure on brain glucose metabolism. JAMA. 305:808–813. https://doi.org/10.1001/jama.2011.186
Wang JH, Zuo XN, Gohel S, Milham MP, Biswal BB, He Y (2011) Graph heoretical analysis of functional brain networks: test-retest evaluation on short-and long-term resting-state functional MRI data. PLoS One 6:e21976. https://doi.org/10.1371/journal.pone.0021976
Wang J, Wang X, Xia M, Liao X, Evans A, He Y (2015) GRETNA: a graph theoretical network analysis toolbox for imaging connectomics. Front Hum Neurosci 9(386):1–16. https://doi.org/10.3389/fnhum.2015.00386
Watts DJ, Strogatz SH (1998) Collective dynamics of’ small-world networks. Nature 393:440–442. https://doi.org/10.1038/30918
Wei YW, Yang JY, Chen ZY, Wu TN, Lv B (2019) Modulation of resting-state brain functional connectivity by exposure to acute fourth-generation long-term evolution electromagnetic field: an fMRI Study. Bioelectromagnetics 40:42–51. https://doi.org/10.1002/bem.22165
Wu TN, Lv B, Chen ZY (2012) Dosimetric studies involving in the experiments for the evaluation of the brain activation by LTE exposure. In: Proceedings of international symposium on electromagnetic compatibility (EMC EUROPE), Rome, Italy: IEEE. IEEEXplore. https://doi.org/10.1109/EMCEurope.2012.6396795
Wu T, Shao Q, Yang L (2013) Simplified segmented human models for whole body and localised SAR evaluation of 20 MHz to 6 GHz electromagnetic field exposures. Radiat Prot Dosim 153(3):266–272. https://doi.org/10.1093/rpd/ncs105
Yan CG, Zang YF (2010) DPARSF: a MATLAB tool box for “pipeline” data analysis of resting state fMRI. Front Syst Neurosci 4(13):1–7. https://doi.org/10.3389/fnsys.2010.00013
Yang L, Chen QH, Lv B, Wu TN (2016) Long-term evolution electromagnetic fields exposure modulates the resting state EEG on alpha and beta bands. Clin Eeg Neurosci 48:168–175. https://doi.org/10.1177/1550059416644887
Zang YF, Jiang TZ, Lu YL, He Y, Tian L (2004) Regional homogeneity approach to fMRI data analysis. Neuroimage 22:394–400. https://doi.org/10.1016/j.neuroimage.2003.12.030
Zang YF, He Y, Zhu CZ, Cao QJ, Sui MQ, Liang M, Tian LX, Jiang TZ, Wang YF (2007) Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI. Brain Dev Jpn 29:83–91. https://doi.org/10.1016/j.braindev.2006.07.002
Zhang J, Sumich A, Wang GY (2017) Acute effects of radiofrequency electromagnetic field emitted by mobile phone on brain function. Bioelectromagnetics 38(5):329–338. https://doi.org/10.1002/bem.bioelectromagnetics
Zubko O, Gould RL, Gay HC, Cox HJ, Coulson MC, Howard RJ (2017) Effects of electromagnetic fields emitted by GSM phones on working memory: a meta-analysis. Int J Geriatr Psych. 32:125–135. https://doi.org/10.1002/gps.4581
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The datasets generated and analyzed during the current study are not publicly available due (data involves the subject’s privacy) but are available from the corresponding author on reasonable request.
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This work was supported by grants from National Natural Science Foundation Project (Grant No. 61971445)
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Lei Yang and Tongning Wu conceived and designed the study; Lei Yang performed the experiments; Tongning Wu wrote the paper; Chen Zhang reviewed and edited the manuscript; Congsheng Li and Zhiye Chen collection of the data; all authors read and approved the manuscript.
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Yang, L., Zhang, C., Chen, Z. et al. Functional and network analyses of human exposure to long-term evolution signal. Environ Sci Pollut Res 28, 5755–5773 (2021). https://doi.org/10.1007/s11356-020-10728-w
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DOI: https://doi.org/10.1007/s11356-020-10728-w