Effect of proximity to high-voltage fields: results of the neural network model and experimental model with macaques

  • H. Aliyari
  • S. H. Hosseinian
  • H. Sahraei
  • M. B. MenhajEmail author
Original Paper


An important biological hazard that is caused by the placement of power transmission lines in the vicinity of cities and villages is the computation of the magnetic and electric fields around these lines. Therefore, the present research objective was to study the effect of high-voltage fields on the effect of the neural network model on the brain and to compare the results of this model with the results of behavioral and biological analyses of primates. In this research, two adult male macaques were selected for the experiments. Prior to inclusion in the research, the primates were exposed to behavioral tests, hormonal assays (melatonin and cortisol), and MRI-assisted brain anatomy analyses using special kits. The monkey in the experimental group was exposed to a 3 kV/m high-voltage field for 4 h a day for a month, after applying electric field simulations. In addition, the behavioral elements of the primates in the experimental and control groups were analyzed during the treatment. Computation models were used in this research, and the results were compared to experimental data. Behavioral elements manifested in the form of changes such as reduced activity, isolation, reduced appetite, and sleep disorders during applying electric field simulations of the monkey that was exposed to the high-voltage field. Based on the results of the simulation model and the variations of the behavioral, hormonal, and anatomical elements, the decrease in the activity of the brain cortex, sleep disorders, and isolation were indicative of depression in the monkey exposed to the high-voltage field.


High-voltage field Depression Melatonin MRI Cortisol Spiking neural network model Monkey 



This research was conducted by financial support of Neuroscience Research Center, Baqiyatallah, Electrical Engineering Department of Amirkabir University of Technology (Tehran Polytechnic), and Qazvin Branch, Islamic Azad University (Intelligent Systems and Cognitive Science Research Lab).

Compliance with ethical standards

Conflict of interest

The authors have no potential conflict of interests pertaining to this journal submission.


  1. Adolphs R (2009) The social brain: neural basis of social knowledge. Annu Rev Psychol 60:693–716CrossRefGoogle Scholar
  2. Aliyari H et al (2018) The beneficial or harmful effects of computer game stress on cognitive functions of players. Basic Clin Neurosci 9(3):177–186CrossRefGoogle Scholar
  3. Beale I et al (1997) Psychological effects of chronic exposure to 50 Hz magnetic fields in humans living near extra-high-voltage transmission lines. Bioelectromagnetics 18(8):584–594CrossRefGoogle Scholar
  4. Blask DE (2009) Melatonin, sleep disturbance and cancer risk. Sleep Med Rev 13(4):257–264CrossRefGoogle Scholar
  5. Brady TF, Konkle T, Alvarez GA (2011) A review of visual memory capacity: beyond individual items and toward structured representations. J Vis 11(5):4–4CrossRefGoogle Scholar
  6. Bullmore E, Sporns O (2009) Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci 10(3):186CrossRefGoogle Scholar
  7. Burke HM et al (2005) Depression and cortisol responses to psychological stress: a meta-analysis. Psychoneuroendocrinology 30(9):846–856CrossRefGoogle Scholar
  8. Carpenter DO (2013) Human disease resulting from exposure to electromagnetic fields. Rev Environ Health 28(4):159–172CrossRefGoogle Scholar
  9. Chaddock L et al (2010) A neuroimaging investigation of the association between aerobic fitness, hippocampal volume, and memory performance in preadolescent children. Brain Res 1358:172–183CrossRefGoogle Scholar
  10. Chen J et al (2004) Functional analysis of genetic variation in catechol-O-methyltransferase (COMT): effects on mRNA, protein, and enzyme activity in postmortem human brain. Am J Hum Genet 75(5):807–821CrossRefGoogle Scholar
  11. Chudler EH, Bergsman KC (2016) Brains–computers–machines: neural engineering in science classrooms. CBE-Life Sci Edu 15(1):fe1CrossRefGoogle Scholar
  12. Churchland PS, Sejnowski TJ (2016) The computational brain. MIT press, CambridgeGoogle Scholar
  13. Constantinidis C, Procyk E (2004) The primate working memory networks. Cognit Affect Behav Neurosci 4(4):444–465CrossRefGoogle Scholar
  14. Cook C, Thomas A, Prato F (2002) Human electrophysiological and cognitive effects of exposure to ELF magnetic and ELF modulated RF and microwave fields: a review of recent studies. Bioelectromagnetics 23(2):144–157CrossRefGoogle Scholar
  15. Crasson M (2003) 50-60 Hz electric and magnetic field effects on cognitive function in humans: a review. Radiat Prot Dosimetry 106(4):333–340CrossRefGoogle Scholar
  16. Dedovic K et al (2009) The brain and the stress axis: the neural correlates of cortisol regulation in response to stress. Neuroimage 47(3):864–871CrossRefGoogle Scholar
  17. Demuth HB et al (2014) Neural network design. Martin Hagan, BostonGoogle Scholar
  18. Frodl T et al (2006) Reduced hippocampal volume correlates with executive dysfunctioning in major depression. J Psychiatry Neurosci 31(5):316Google Scholar
  19. Goodwin FK, Jamison KR (2007) Manic-depressive illness: bipolar disorders and recurrent depression, vol 1. Oxford University Press, OxfordGoogle Scholar
  20. Gruber R, Sadeh A, Raviv A (2000) Instability of sleep patterns in children with attention-deficit/hyperactivity disorder. J Am Acad Child Adolesc Psychiatry 39(4):495–501CrossRefGoogle Scholar
  21. Guo D, Wang Q, Perc M (2012) Complex synchronous behavior in interneuronal networks with delayed inhibitory and fast electrical synapses. Phys Rev E 85(6):061905CrossRefGoogle Scholar
  22. Hare TA, Hakimi S, Rangel A (2014) Activity in dlPFC and its effective connectivity to vmPFC are associated with temporal discounting. Front Neurosci 8:50CrossRefGoogle Scholar
  23. Hickie IB, Rogers NL (2011) Novel melatonin-based therapies: potential advances in the treatment of major depression. The Lancet 378(9791):621–631CrossRefGoogle Scholar
  24. Izhikevich EM (2003) Simple model of spiking neurons. IEEE Trans Neural Netw 14(6):1569–1572CrossRefGoogle Scholar
  25. Izhikevich EM (2007) Dynamical systems in neuroscience. MIT Press, CambridgeGoogle Scholar
  26. Kazemi M et al (2018) Effects of the extremely low frequency electromagnetic fields on NMDA-receptor gene expression and visual working memory in male rhesus macaques. Basic Clin Neurosci 9(3):167–176CrossRefGoogle Scholar
  27. Laakso M et al (1995) Volumes of hippocampus, amygdala and frontal lobes in the MRI-based diagnosis of early Alzheimer’s disease: correlation with memory functions. J Neural Trans-Parkinson’s Dis Dement Sect 9(1):73–86CrossRefGoogle Scholar
  28. LaBar KS, Cabeza R (2006) Cognitive neuroscience of emotional memory. Nat Rev Neurosci 7(1):54CrossRefGoogle Scholar
  29. Lai H, Singh NP (1997) Acute exposure to a 60 Hz magnetic field increases DNA strand breaks in rat brain cells. Bioelectromagnetics 18(2):156–165CrossRefGoogle Scholar
  30. Lau CG, Zukin RS (2007) NMDA receptor trafficking in synaptic plasticity and neuropsychiatric disorders. Nat Rev Neurosci 8(6):413CrossRefGoogle Scholar
  31. Liang P et al (2011) Functional disconnection and compensation in mild cognitive impairment: evidence from DLPFC connectivity using resting-state fMRI. PLoS ONE 6(7):e22153CrossRefGoogle Scholar
  32. Loh M, Rolls ET, Deco G (2007) A dynamical systems hypothesis of schizophrenia. PLoS Comput Biol 3(11):e228CrossRefGoogle Scholar
  33. Maass W (1997) Networks of spiking neurons: the third generation of neural network models. Neural Netw 10(9):1659–1671CrossRefGoogle Scholar
  34. Markram H (2012) The human brain project. Sci Am 306(6):50–55CrossRefGoogle Scholar
  35. Markram H et al (2011) Introducing the human brain project. Procedia Comput Sci 7:39–42CrossRefGoogle Scholar
  36. Mitchell TM et al (2008) Predicting human brain activity associated with the meanings of nouns. Science 320(5880):1191–1195CrossRefGoogle Scholar
  37. Monyer H et al (1994) Developmental and regional expression in the rat brain and functional properties of four NMDA receptors. Neuron 12(3):529–540CrossRefGoogle Scholar
  38. Nadeem M et al (2003) Computation of electric and magnetic stimulation in human head using the 3-D impedance method. IEEE Trans Biomed Eng 50(7):900–907CrossRefGoogle Scholar
  39. Orban GA et al (2003) Similarities and differences in motion processing between the human and macaque brain: evidence from fMRI. Neuropsychologia 41(13):1757–1768CrossRefGoogle Scholar
  40. Rao RP, Olshausen BA, Lewicki MS (2002) Probabilistic models of the brain: perception and neural function. MIT press, CambridgeGoogle Scholar
  41. Reiter RJ (1993) Static and extremely low frequency electromagnetic field exposure: reported effects on the circadian production of melatonin. J Cell Biochem 51(4):394–403CrossRefGoogle Scholar
  42. Sala C et al (2015) Shank synaptic scaffold proteins: keys to understanding the pathogenesis of autism and other synaptic disorders. J Neurochem 135(5):849–858CrossRefGoogle Scholar
  43. Salunke BP, Umathe SN, Chavan JG (2014) Involvement of NMDA receptor in low-frequency magnetic field-induced anxiety in mice. Electromagn Biol Med 33(4):312–326CrossRefGoogle Scholar
  44. Salzman CD, Fusi S (2010) Emotion, cognition, and mental state representation in amygdala and prefrontal cortex. Annu Rev Neurosci 33:173–202CrossRefGoogle Scholar
  45. Sapolsky RM (2001) Depression, antidepressants, and the shrinking hippocampus. Proc Natl Acad Sci 98(22):12320–12322CrossRefGoogle Scholar
  46. Seung HS (2003) Learning in spiking neural networks by reinforcement of stochastic synaptic transmission. Neuron 40(6):1063–1073CrossRefGoogle Scholar
  47. Soininen HS et al (1994) Volumetric MRI analysis of the amygdala and the hippocampus in subjects with age-associated memory impairment correlation to visual and verbal memory. Neurology 44(9):1660–1660CrossRefGoogle Scholar
  48. Squire LR (1992) Memory and the hippocampus: a synthesis from findings with rats, monkeys, and humans. Psychol Rev 99(2):195CrossRefGoogle Scholar
  49. Stevens JC et al (1993) Comparison of human and rhesus monkey in vitro phase I and phase II hepatic drug metabolism activities. Drug Metab Dispos 21(5):753–760Google Scholar
  50. Tekieh E et al (2017) Role of basal stress hormones and amygdala dimensions in stress coping strategies of male rhesus monkeys in response to a hazard-reward conflict. Iranian J. Basic Med. Sci. 20(8):951–957Google Scholar
  51. Tsodyks M, Pawelzik K, Markram H (2006) Neural networks with dynamic synapses. Neural Netw 10(4):821–835Google Scholar
  52. Van Ooijen P et al (2005) DICOM storage into PACS of out-hospital CD-ROMs—a half year experience report. In: International congress series, ElsevierGoogle Scholar
  53. Van Petten C (2004) Relationship between hippocampal volume and memory ability in healthy individuals across the lifespan: review and meta-analysis. Neuropsychologia 42(10):1394–1413CrossRefGoogle Scholar
  54. Videbech P, Ravnkilde B (2004) Hippocampal volume and depression: a meta-analysis of MRI studies. Am J Psychiatry 161(11):1957–1966CrossRefGoogle Scholar
  55. Wang DD, Kriegstein AR (2008) GABA regulates excitatory synapse formation in the neocortex via NMDA receptor activation. J Neurosci 28(21):5547–5558CrossRefGoogle Scholar
  56. Wilson BW (1988) Chronic exposure to ELF fields may induce depression. Bioelectromagnetics 9(2):195–205CrossRefGoogle Scholar

Copyright information

© Islamic Azad University (IAU) 2018

Authors and Affiliations

  • H. Aliyari
    • 1
  • S. H. Hosseinian
    • 1
    • 2
  • H. Sahraei
    • 3
  • M. B. Menhaj
    • 1
    • 2
    Email author
  1. 1.Faculty of Electrical, Biomedical and Mechatronics Engineering, Qazvin BranchIslamic Azad UniversityQazvinIran
  2. 2.Department of Electrical EngineeringAmirkabir University of TechnologyTehranIran
  3. 3.Neuroscience Research CenterBaqiyatallah University of Medical SciencesTehranIran

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