Betreff: Research about eeg reactions to cellular phones
Von: Ellen Hellingwerf
Datum: Sun, 14 Aug 2005 02:55:41 -0700 (PDT)



Cellular Phone Electromagnetic Field Effects on Bioelectric Activity of Human Brain

N. N. Lebedeva, A. V. Sulimov, O. P. Sulimova, T. I. Kotrovskaya, and T. Gailus

Professor at the Institute of Higher Nervous Activity and Neurophysiogy, Russian Academy of Sciences (Moscow); 2Ph.D., senior researcher at the Institute of Higher Nervous Activity and Neurophysiogy, Russian Academy of Sciences (Moscow); 3Ph.D., researcher at the Institute of Higher Nervous Activity and Neurophysiogy, Russian Academy of Sciences (Moscow); 4Ph.D., researcher at the "Extremely High Frequency" Medical and Technical .Association (Moscow); 5Ph.D., senior researcher at Deutsche Telekom AG, Germany.




ABSTRACT:24 volunteers participated in the experiments. The investigation of EEG reactions to cellular phone (EMF frequency 902.4 MHz and intensity 0.06 mW/cm2) was conducted. Two experiments were performed with each subject ¾ cellular phone exposure and Placebo. Duration of the experiment was 60 min: 15 min ¾ background; 15 min ¾ EMF exposure or Placebo; 30 min ¾ afterexposure. EEG was recorded in 16 standard leads with "eyes open" and "eyes closed". Special software with non-linear dynamics was developed for EEG analyses. One parameter, multichannel (global) correlation dimension, was calculated. The changes of these parameters can be evidence of brain functional state changes. As a result of EEG record processing, a significant increase of global correlation dimension during the exposure and afterexposure period was discovered, more pronounced in the case of "eyes closed". That can be viewed as the manifestation of cortex activation under phone EMF exposure.




LITERATURE REVIEW

Technical progress has given birth to a variety of antropogenic factors, among which industrial electromagnetic fields (EMF) have a significant place. These EMFs contribute significantly to environment pollution and have a pronounced effect on living beings [1-3]. Recent research testifies that biological effects of EMFs are determined by their biotropic parameters: intensity, frequency, shape of signal, place of application, exposition and others [2, 4-11] as well as properties of the living being - initial functional state, age, sex and physic characteristics (dielectric permeability, electric conductivity and so on) [12-17].

A number of studies are devoted to the investigation of the responses of different systems to EMF acting on a whole organism [18-22]. Some authors report finding a relation among a number of diseases [23-28] and neurological syndromes (fatigue, acute and chronic headache, depression) [29-31] and levels of industrial EMF pollution. However, other researchers communicate a lack of pathology or only small deviations [2, 32, 33].

Direct measures of the degree of EMF penetration into different human organs and tissues in terms of specific absorption rate (SAR) were conducted. SAR was measured in the bodies, mainly in the central nervous system, of the users of wireless communication systems under exposure, essentially 900 MHz [4-37].

It was demonstrated that the central nervous system is most sensitive to EMF effects [2, 38-41]. Significant changes of biochemical activity of neurons were observed during direct and intermediate EMF application to neurons and glia, and only neurons with a high level of activity were sensitive to weak EMF [42-46]. Microelectrode investigation allows the recording responses of neurons of different brain areas to EMF [11, 47-49]. The sensitivity of neurons and glia to EMF was supported by histological studies [50-52].

A large body of data shows that EMF can produce a wide diversity of physiological and behavioral effects, such as movement activity changes, avoidance reactions and orienting responses to EMF [7, 33, 53, 54].

Investigations concerned with EMF effects on conditional responses demonstrated that EMF modified the period of elaboration of conditioned responses to EMF [55-57] and transformed the conditional response in itself [58, 59].

Investigation of a wide range of intensity (0.2…1000 mW/ñm2) of electromagnetic microwave effects on bioelectrical brain activity of animals revealed such phenomena as an increase of alpha spindles numbers, an increase of EEG synchronization, tens and hundred of milliseconds, prolonged desynchronization - a decrease of main rhythm amplitudes; short-term desyncronization at the onset of EMF application and, after that; an after-effect reaction that is similar to desyncronization but arises during the long period after the termination of EMF application; epileptic activity.

At decimeter and centimeter wave exposure on the lateral surface of rabbits bodies, it was revealed that, at higher thermal intensities, the stability of EEG reactions was lower and, at lower (non-thermal) intensities, this EEG index did not greatly depend on intensity and even has a tendency to increase while the latter decreased [60].

The response of the central nervous system (CNS) after 30 min, 3mW/cm2 exposure of rats to 2.45 GHz, 217 Hz was investigated by quantitative EEG and Visual Evoked Potential (VEP) analysis. The above-mentioned parameters were evaluated before and after (5 min and 20 min) exposure. It was shown that the delta band of the EEG power spectrum was increased definitely, the alpha and beta bands were decreased in the 5 min after the exposure. These alterations disappeared 20 min after exposure. No changes were observed in VEP [61].

The experiments recording cortex neuronal activity during microwave (40mV/cm2) exposure were carried out on rabbits with preliminarily implanted microelectrodes in the sensomotory cortex under barbital anesthesia. The EEG reactions to the microwave exposure manifested as the pronounced enhancement of slow waves. The changes of pulse activity of the cortex neurons' populations were observed during this reaction. The mean values of the interspike intervals increased, i.e., the enhancement of inhibitory processes took place. For these changes to occur, microwave exposure of less than 1 min was sufficient. After terminating of exposure, the changes arose again [62].

CNS responses to 60 min, 50 Hz, 100 mT and 500 mT magnetic field exposure of freely moving rats was observed by quantitative EEG. There were no significant changes in the EEG activity (the sum of EEG spectral bands) at 100 mT during and after exposure. In the case of 500 mT flux density, EEG activity increased significantly immediately (1st min) and in the 20th min of exposure and 20 min after exposure (p<0.05). Significant changes of spectral components were found at both flux densities. Mainly, the slow frequency components increased and the higher components decreased [63].

In a number of investigations of different ranges EMF effects on volunteers EEG spectral changes were discovered. In spite of great between-subject variability of effects the most characteristic feature was an increase of alpha, theta and, in some cases, delta power [12, 64-66]. Similar EEG spectral changes manifesting the dominance of inhibitor processes have been discovered by other authors [67,68].

Experimental studies of peripheral exposure (30 min and 60 min) to low intensity MM waves (5mW/cm2) on volunteers revealed that, at a pronounced increase of alpha-rhythm power in occipital areas of the cortex and heightening of coherence by theta-rhythm in the frontal-central areas were observed in the EEG. Such a pattern of bioelectric activity testifies the development of a non-specific cortex activation reaction, i.e., the increase of cortical tone. It has also been revealed that long-term exposure of MM radiation with l= 7.1 mm produces a stabilizing effect on day-to-day variation of human cortical biopotentials (most easily observable with alpha power and the inter- and intrahemispheric mean coherence of delta, theta and alpha ranges) [9, 10, 69].

It has been described peculiar EEG-effect of ELF EMF ¾ increasing beta-activity in frontal and central areas and increasing alpha-power mainly at occipital areas [64, 70].

The possibility of correcting human conditions by electromagnetic exposure was investigated. EHF exposure brought the functional state of the nervous and cardiac systems to equlibrium in persons with high and middle plasticity of neurodynamic processes (determined by EEG parameters), but, in persons with low neurodynamic plasticity, EHF exposure was ineffective (functional reserves of the organism are low for a long time) [71].

Investigations of EMF perception have demonstrated that people can perceive EMF of low intensity. Human EMF-sensitivity, besides individual features, is determined by the frequency and signal form of the EM-signal and localization of its application. The modality of the resulting sensation testifies to the participation of a cutaneous analyzer in EMF reception. Latency of the reaction was 20-60 s. Sensory asymmetry of perception was revealed: subjects distinguish between the field and false trials much better with their non-leading hand (right-handed ¾ by the left hand, left-handed ¾ by the right one). The experimental data has shown the presence of a correlation between human sensitivity to EMF and pain thresholds - the lower these thresholds, the higher the sensitivity. There are some "critical" values of these thresholds when subjects manifest no sensitivity to EMF of any frequency ranges [9, 10, 72-74].

The correlation between human electromagnetic sensitivity and EEG properties was investigated [74]. Highly sensitive volunteers had an optimally pronounced alpha rhythm with prominent topographic differences. The low-sensitive volunteers have higher or lower level of alpha rhythm without topographical differences.

The purpose of this work was to study EEG reactions to cellular phone EMF exposure (intensity 0,06 mW/cm2, frequency 902,4 MHz).




METHODS




24 healthy male volunteers aged from 20 to 30 years participated in the experiments. Two experiments (mobile telephone exposure and placebo, the order of the experiments was randomized) were performed with each subject at the same time of day with a constant interval of 1 week between them. Duration of the experiment was 60 min.: 15 min. ¾background, 15 min. ¾ EMF exposure or placebo, 15 min ¾ afterexposure I and 15 min afterexposure II (Fig. 1). To exclude sleepness of the subject, the closed-eyes periods of EEG recording alternate with opened-eyes periods every 5 minutes. EEG was recorded in 16 electrodes according to the international 10-20 system (Fz, F3, C3, P3, Pz, P4, C4, F4, F7, T3, T5, O1, O2, T6, T4, F8) against Cz as the reference. The EMF was directed to the back of head by a special antenna. The subject and the EEG machine were shielded from the devices used. EEG data were stored on magneto-optical disks for further processing.

To estimate EEG changes, we use the global dimensional complexity (a measure derived from nonlinear dynamics) of EEG. Calculation of dimensional complexity was performed for each 8-s artifact-free EEG segment [75]. Then these values were averaged across 10 segments.

Statistical comparisons were performed by analysis of variance (ANOVA).




RESULTS




The dynamics of mean multichannel (global) correlation dimension values D2 in experiment time is shown in Fig. 2.




FIGURE 1. Protocol of experiments.




FIGURE 2. Multichannel correlation dimension values of baseline (1-12 epochs), exposure (13-24 epochs), afterexposure I (25-36 epochs), afterexposure II (37-48 epochs) for the group.




The dynamics of D2 under cellular phone EMF is as follows. After starting EMF, parameter D2 increases immediately; in 2 min, D2 decreases but stays higher than Placebo for 6-7 min; for the rest time of EMF exposure, the difference between Placebo and EMF experiments disappears. During the afterexposure period (30-45th min), D2 in EMF experiments again exceeds that in Placebo.

The difference between D2 under cellular phone and Placebo is significant in the periods of exposure, afterexposure 1 and afterexposure 2 (Tabl. 1).




Table 1. The mean values of correlation dimension D2 in baseline (1), exposure (2), afterexposure I (3) and afterexposure II (4) for the group.


Telephone

MEGA-WAVE

Placebo

baseline

6,866372

6,855634

6,789336

under exposure

6,86607*

6,78914*

6,528643

after- exposure I

6,64857*

6,67518*

6,434974

after- exposure II

6,96569*

6,83421*

6,204254




The mean values of each period (baseline, exposure, afterexposure 1 and afterexposure 2) are demonstrated on Fig. 3.



FIGURE 3. The mean values of correlation dimension D2 in baseline (1), exposure (2), afterexposure I (3) and afterexposure II (4) for the group.




In Fig. 2, one can see sawtooth (5 min) oscillations of D2. These oscillations are related to distinct neocortex functional states ¾ "open eyes" and "closed eyes" (Fig. 1). Separate EEG analysis of these two functional states has revealed that the mean values of D2 (both of EMF experiments and Placebo) are greater in "open eyes" (OE) state in comparison with the "close eyes" (CE) state ¾ Fig. 4, Tabl. 2.

Table 2. The mean values of correlation dimension D2 in baseline (1), exposure (2), afterexposure I (3) and afterexposure II (4) with open and closed eyes


CLOSED EYES

OPENED EYES

Telephone

Placebo

Telephone

Placebo

baseline

6,936

6,881

7,128

6,826

under exposure

6,624*

6,061

6,743

6,580

after-exposure I

6,466*

6,174

6,868

6,564

after-exposureII

6,754*

6,049

6,880*

6,264





A




B




FIGURE 4. The mean values of correlation dimension D2 in baseline (1), exposure (2), afterexposure I (3) and afterexposure II (4); A - closed eyes, B - open eyes.




In "closed eyes" state, the cellular phone EMF effect (D2 increase in compare with Placebo) is more pronounced (the difference is significant for exposure and afterexposure). The "open eyes" increase of D2 is significant only during the afterexposure 2 period.

So the data obtained indicate that bioelectric human brain activity (as can be observed with D2) is modified under EMF cellular phone exposure.




DISCUSSION




There is wide experience using spectral analysis of the bioelectric activity of the brain cortex to evaluate its functional state [76-78]. The dynamics of two main measures is most commonly investigated: spectral power of each EEG range (delta, theta, alpha and beta) and coherence for each pair of EEG. For multichannel EEG records, these measures give the possibility to estimate changes of spatio-temporal patterns of brain cortex biopotentials due to external factors - to determine the power of separate EEG frequency components of different cortex areas and coherence (i.e. statistical dependence) of the electrical processes of both hemispheres - inter- and intra-hemisphere connections. Employing these methods of EEG analysis, the researcher obtains knowledge of the functioning of brain cortex areas that allows some conclusions about neurophysiological mechanisms of CNS response to affective factors and an evaluation of changes arising in the cortex functional state.

However, to state definitely that the brain functional state has been changed, the researcher needs to account for a variety of parameters and interdepencies among them, and identification of the functional state is highly subjective. In addition, sometimes this method is not sufficiently responsive, especially for evaluating the bioeffects of weak nonspecific stimuli. This method implies the linear stochastic nature of EEG. Chaotic dynamics propose an alternative model of EEG as nonlinear deterministic processes [79-82].

It was shown that the use of nonlinear techniques of EEG analysis presents a way to determine some pathological states and some functional states of healthy subjects [83].

A number of authors suggest that chaotic EEG components are related to CNS information processes and reflect the spatial-temporal organization of underlying brain processes. These methods extract information that cannot be obtained from spectral analysis [84-87].

Processing of EEG records by methods of nonlinear dynamics with the calculation of the multichannel (global) correlation dimension allows the evaluation of changes of the functional state of the brain at whole. The measure obtained as a result of such processing is highly sensitive to the effects of low-intensity EMF produced by cellular phone. The significant increase of global correlation dimension obtained during and after exposition (in comparison with Placebo) suggests a change of functional state of the human brain. This can be a result of brain cortex activation that begins with EMF onset and continues after termination of EMF exposure. On the other hand, some brain activation can be viewed as a positive factor that helps intellectual performance. However, taking into consideration the fact that this activation was produced by short-term (15-min) exposure to cellular phone EMF, the data obtained cannot be treated unambiguously. There is a neurophysiological phenomenon known to
occur when repeated application of the weak stimulus produce stable focus of excitation that has a number of properties [88-90], for example:
   stability for some period of time;
   capacity to produce extinction of nearby areas of the cortex;
   capacity to use other stimuli to enhance its own activity.

On long standing, such a dominant focus violates balanced relations between different regions of the brain and disturbs normal brain functioning, producing different CNS diseases. So, if the cellular phone is used repeatedly in the course of the day, it can be such a weak stimulus that will produce dominant focus. To draw inferences about the usefulness or damage of cellular phone EMF for humans, it is necessary to conduct more extensive research on the responses of CNS and other systems, but it is apparent that much attention must be given to this problem.




REFERENCES

1. Presman, A.S., Electromagnetic signalization in living nature. Moscow, Sovetskoe radio, 1974 (in Russian).
2. Plekhanov, G.F., Basic laws of electromagnetobiolody. Tomsk. T.G.U. (The Tomsk State University), 1990, 187 p. (in Russian).
3. Tenforde, T,. Interaction of ELF magnetic fields with living matter. Handbook of biological effects of electromagnetic fields. /Ed.C.Polk, E Postow.Boca Raton; CRS press Inc., 1986; pp.197-225.
4. Adey, W.R., Frequency and power window in tissue interactions with weak electromagnetic fields, Proc. IEEE. 1980, 68 (1): 119.
5. Temuryants, N.A., Nervous and humoral mechanisms of adaptation to action of non-ionizing radiation, Moscow: D.Sc. thesis, 1989 (in Russian).
6. Sidyakin, V.G., Effect of global ecological factors on nervous system, Kiev: Naukova Dumka, 1986 (in Russian).
7. Temuryants, N.A., Vladimirsky, B.M., Tishkin, O.G., Extremely low frequency signals in biological world, Kiev: Naukova Dumka, 1992, 188 p. (in Russian).
8. Lebedeva, N.N., Reaction of human CNS on electromagnetic fields with various biotropic parameters, Moscow: D.Sc. thesis, 1992 (in Russian).
9. Lebedeva, N.N., Sensory and subsensory reactions of a healthy man on peripheral effects of low intensity MM-waves, Zh. Millimetrovye volny v biologii i meditsine (J. Millimeter Waves in Medicine and Biology), 1993, no. 2, pp. 5-23 (in Russian).
10. Kolomytkin, O.V., et al., High sensetivity of brain receptor system to low intensity microwaves. 2-nd International Scientific Meeting "Microwaves in medicine 1993", Rome, 1993.
11. Pakhomov, A.G., Prol, H.K., Mathur, S.P., et al., Frequency and intensity dependence of the Millimeter-wawe radiation effect on isolated nerve function. BEMS. Abstract Book. Eighteenth Annual Meeting, Canada, June 9-14, 1996.
12. Kholodov, Yu.A., Lebedeva, N.N., Nervous systems reactions to electromagnetic fields, Moscow: Nauka, 1992; 135 p. (in Russian).
13. Demetskiy, A.M., Zukov, B.N., and Tsetsocko, A.V., Electromagnetic fields in medicine. Samara, 1991; 157 p. (in Russian).
14. Devyatkov, N.D., Golant, M.B., and Betskii, O.V., Millimeter waves and their role in life-giving processes, Moscow: Radio i Svyaz, 1991 (in Russian).
15. Golovacheva, T.V., Chronobiological Aspects of EHF-therapy of the Ischemic Heart Disease, XI Ross.simp. (with participation of foreign scientists), "Millimeter Waves in Medicine and Biology", Moscow, 1997 (in Russian).
16. Gordon, D.S., Merkulova, L.M., et al., Hystochemistry of thymus monoamins in local EHF action, Magnitologiya (Magnetology), 1994, no. 1 (in Russian).
17. Gordon, B.M., Merkulova, L.M., et al., Status of bioamins in rat thymus cells after acute pain stress and MM-therapy, X Russian Symposium (with participation of foreign scientists) "Millimeter Waves in Medicine and Biology", Moscow, 1995 (in Russian).
18. Kholodov, Yu.A., Nociception system and living being reactions to EMF. Magnitologya (Magnetology), 1991, no. 2 (in Russian).
19. Jacobson, J.I., Electromagnetism in medicine, Indian.J.Med.Sci., 1992; no. 6(11), pp. 321-327.
20. Lambroso, J., Champs electromagnetiques et sante. Un conte de fies? Energ.sante/ serv. atud/ med., 1994, pp. 5-115.
21. Lebedeva, N.N. and Sulimova, O.P., MM-waves modifying effect on human central nervous system functional state under stress, Zh. Millimetrovye volny v biologii i meditsine (J. Millimeter waves in biology and medicine), 1994, no. 3, pp. 16-21 (in Russian).
22. Sulimova, O.P., Low intensity EHF EMF peripheral exposure on heart rate dynamics. Problemy electromagnitnoy bezopasnosti cheloveka, (The problem of human electromagnetic safety), The 1-st Russian conference with international participation. 28-29 November 1996, Moscow (in Russian).
23. Ahlbom, A., A review of the epidemiology literature on magnetic fields and cancer, Scand.J.Work Environ.Health, 1988, vol. 14, pp. 337-343.
24. Calle, E. and Savitz, D.A., Leukemia in occupational groups with exposure to electrical and magnetic fields, New Engl.J.Med, 1985, vol. 23, pp. 1476-1477.
25. Juutilainen, J., Bjork, E., and Saali, K., Epilepsy and electromagnetic fields: effects of stimulated atmospherics and 100 Hz. Int.J., Biometeorology, 1988, vol. 32, pp. 17-22.
26. Feychting, M. and Ahlbohm, A., Magnetic fields and cancer in children residing near Swedish high-voltage power lines, Am.J.Epidimiol, 1993, vol. 138, pp. 467-481.
27. London, S.J., Thomas, D.S., Bowman, J.D., et al., Exposure to residential electric and magnetic fields and risk of childhood leukemia, Am.J.Epidemiol, 1991, vol. 134, pp. 923-937.
28. Michaelis, J., Schuz, J., Meinert, R., et al., A population-based case-control study on electromagnetic fields and childhood leukemia, BEMS. Abstract Book. Eiteenth Annual Meeting, Canada, June 9-14, 1996.
29. Polk, C., Biological effects of low-level low-frequency electric and magnetic fields, IEEE Transact Edue, 1991, vol. 34, pp. 243-249.
30. Poole, Ch., Kavet, R., Funch, D.P., et al., Depressive symptoms and headaches in proximity of residence to an alternating-current transmission line right-of-way, Am.J. of Epidemiology, 1991, vol. 137, pp. 318-330.
31. Cobb, B.L., Mason, P.A., Miller, S.A., et al., A teratologic study of ultrawideband electromagnetic field exposure, BEMS. Abstract Book. Eighteenth Annual Meeting, Canada, June 9-14, 1996.
32. Davis, C.C., Katona, G.A., Taylor, L.S., et al., Dielectric measurement of tissues in the mammalian head at cellular telephone frequencies, BEMS. Abstract Book. Eighteenth Annual Meeting, Canada, June 9-14, 1996.
33. Douglas, M.G., Okoniewski, M., and Stuchly, S.S., Antennas for cellular telephones with reduced power deposition in the body of the user, BEMS. Abstract Book. Eighteenth Annual Meeting, Canada, June 9-14, 1996.
34. Bao, J.-Z., Lu, S.-T., Hurt, W.D., et al., Dielectric measurements of brain tissues in the frequency range between 45 MHz and 26.5 GHz, BEMS. Abstract Book. Eighteenth Annual Meeting, Canada, June 9-14, 1996.
35. Burkhardt, M., Spinelli, Y., and Kuster, N., Exposure setup totest the effects on the CNS of wireless communications systems, BEMS. Abstract Book. Eighteenth Annual Meeting, Canada, June 9-14, 1996.
36. Kholodov, Yu.A., Nervous systems reactions to electromagnetic fields. Moscow: Nauka, 1975, 207 p. (in Russian).
37. Kholodov, Yu.A., The brain in electromagnetic fields, Moscow: Nauka, 1982; 123 p. (in Russian).
38. Kholodov, Yu.A., MM-radiation in neurobiology, X Ross.simp. (with participation of foreign scientists) "Millimeter Waves in Medicine and Biology", Moscow, 1995, pp. 115-117 (in Russian).
39. Graham, C., Cook, M.R., Cohen, H.D., et al., Dose responce study of human exposure to 60 Hz electric and magnetic fields, Bioelectromagnetics, 1994, vol. 15, pp. 447-463.
40. Kaznacheev, V.P. and Michailova, L.P., Extremely weak radiations in intercellular interactions, Novosibirsk: Nauka, 1981, 144 p. (in Russian).
41. Bravarenko, N.I., Balaban, P.M., Kuznetsov, A.N., et al., Glia role in reactions of snail neurons to constant magnetic field, Problemy electromag. neurobiol (The electromagnetic neurobiology problems), Moscow: Nauka, 1988; pp. 64-73 (in Russian).
42. Chizhenkova, R.A., Low intensity EHF radiation and pulse trains of cortex neurons, Problemy electromag. Neurobiol, (The electromagnetic neurobiology problems), Moscow: Nauka, 1988 (in Russian).
43. Blackman, C.F., Benane, S.G., and Elliot, D.J., Importance of alignment between local DC magnetic and an oscillating magnetic field in responses of brain tissue in vitro and in vivo, Bioelectromagnetics, 1990; vol. 11, pp. 159-167.
44. Sheppard, A.R., Effects of 60 Hz magnetic field on a spontaneously active neuronal system, Proceedings of the 9th Annual conference of the IEEE engineering in medicine and biology society, Boston, 1987, pp. 79-82.
45. Khitrova-Orlova, T.V., Pavlenko, V.B., Ilyicheva, T.V., et al., EHF effects on background and evoked activity of cortex neurons of cat brain, Magnitobiologiya i magnitotherapiya, (Magnetobiology and magnetotherapy), 1991 (in Russian).
46. Burkhardt, M., Spinelli, Y., and Kuster, N., Exposure setup totest the effects on the CNS of wireless communications systems, BEMS. Abstract Book. Eighteenth Annual Meeting, Canada, June 9-14, 1996.
47. Pavlenko, V.B., Khitrova-Orlova, T.V., Kopilov, A.N., et al., Alternating EHF fields effects on neuron activity of cat brain, Magnitobiologiya i magnitotherapiya (Magnitobiology and magnetotherapy), 1991 (in Russian).
48. Alekseev, S.I., Kochetkova, N.V., Bolshakova,M.A., et al., Influence of EMF EHF on neuron membrans, IX Ross.simp. (with participation of foreign scientists), "Millimeter Waves in Medicine and Biology", Moscow, 1991 (in Russian).
49. Semm, P., Marhold, S., Dombek, K.-P., et al., Neuronal responses to low-intencity electromagnetic fields at 900 MHz, BEMS. Abstract Book. Eighteenth Annual Meeting, Canada, June 9-14, 1996.
50. Sigalevi, L.A., Balaban, P.M, Dementev, V.A., et al., CMF influence on identific neurons and interglianeuronal interactions in isolated neural system of grapes snail. //Inf. of USSR Academy of Science, 1983, no. 4 (in Russian).
51. Artyukhina, N.I., The reactions of structure elements of the rat brain on magnetic fields exposure. Problemy electromag. neurobiol. (The electromagnetic neurobiology problems), Moscow: Nauka, 1988, pp. 42-47 (in Russian).
52. Hansson, H.A., Effects on the nervous system by exposure to electromagnetic fields: experimental and clinical studies, Prog. Clin. Biol. Res., 1988, vol. 257, pp. 119-134.
53. Hansson, H.A., Effects on nervous tissue of exposure to electromagnetic fields. In Adey W.R., Leurence A.F.(eds): "Nonlinear electrodynamics in biological systems", New York: Plenum Press, 1994, pp. 65-87.
54. Khromova, S.V., Modification of rat behavior by millimeter radiation, Thesis. Ph. D., Moscow, 1990 (in Russian).
55. Sienkiewicz, Z.J., Haylock, R.G., and Saunders, R.D., Prior exposure to A 0.75 mT, 50 Hz Magnetic fields impairs spatial learning in adult male mice, BEMS. Abstract Book. Eighteenth Annual Meeting, Canada, June 9-14, 1996.
56. Michailovsky, V.N., Voychishin, K.S., and Grabar', L.I., About human perception of MF ELF oscillation and protection means, Biological system reactions on weak MF. Moscow: Nauka, 1991 (in Russian).
57. Lukyanova, S.N., Rinskov, V.V., and Makarov, V.P., Analysis of CNS reactions to low intensity short-term microwave radiation, Problemy electromagnitnoy bezopasnosti cheloveka, The 1-st Russian conference with international participation, 28-29 november, Moscow, 1996 (in Russian).
58. Ziriax, J.M., MacCullum, M., and Hurt, W., Detection of 94,5 GHz radio frequency fields by Rhesus Monkeys, BEMS. Abstract Book. Eighteenth Annual Meeting, Canada, June 9-14, 1996.
59. Norekyan, T.P. and Matukhina, I.A., Alternating magnetic field and conditional reflex. Problemy electromag. neurobiol (The electromagnetic neurobiology problems), Moscow: Nauka, 1988; pp. 5-11 (in Russian).
60. Sidyakin, V.G. and Yanova, N.P., Modifying effect of extremely low frequency alternating magnetic field on animal conditioned reflex activity, Problemy electromag. Neurobiol. (The electromagnetic neurobiology problems), Moscow: Nauke, 1988 (in Russian).
61. Kholodov, Yu.A., Influence of EMF and MF on CNS, Moscow: Nauka, 1966 (in Russian).
62. Thuroczy, G., Kubinyi, G., Nagy, N., and Szabo, L.D., Measurements of visual evoked potentials (VEP) and brain electrical activity (EEG) on freely moving rats exposed to 50 Hz, 100 *Ò and 500 *T magnetic fields, BEMS, Abstract Book. Seventeenth Annual Meeting, USA, June 18-22, 1995.
63. Chizhenkova, R.A. and Safroshkina, A.A., Cortex neuronal activity during EEG reaction to microwave irradiation, BEMS. Abstract Book. Seventeenth Annual Meeting, USA, June 18-22, 1995.
64. Thuroczy, G., Kubinyi, G., Nagy, N., and Szabo,. L.D., Acute changes in brain electrical activity (EEG) after GSM modulated microwave exposure on rats, BEMS. Abstract Book. Sixteennth Annual Meeting, Denmark, June 12-17, 1994.
65. Bell, G.B., Marino, A.A., and Chesson, A.L., Alterations in brain electrical activity caused by magnetic fields: Detecting the detection process, Electroencephalogr. Clin. Neurophysiol., 1992; vol. 83, pp. 389-397.
66. Bell, G.B., Marino, A.A., Chesson, A.L., and Struve F.A., Human sensitivity to weak magnetic fields, Lancet. 1991, vol. 338, pp. 1521-1522.
67. Selitskiy, G.V., Karlov, V.A., and Sorokina, N.D., Mechanisms of human magnetic field perception, Fisiologiya cheloveka (Human physiology), 1996; vol. 22(7), pp. 66-72 (in Russian).
68. Levillain, D. and Picat, J., Interet de l'analyse spectrale dans l'evaluation des effects sur le rythme alpha des champs magnepulses, Ann. Med.Psychol., 1985, vol. 143, pp. 235-254.
69. Lyskov, E., ELF magnetic fields alter the sentral nervous system activity. Neurophusiological evidens, Abstracts till 3:e Nordiska Arbetsmotet. Biologiska effekter av lagfrkventa elektromagnetiska falt, Umeo, March, 13-14. 1994, p.16.
70. Sulimova, O.P., Electro and psychophysiological human reactions to EHF electromagnetic fields, Ph.D.thesis, Simferopol, 1992 (in Russian).
71. Lyskov, E., The change of human CNS functional state in complex action of constant and ultralowfrequency magnetic field of low power density, Moscow: D. Sc. Thesis, 1996 (in Russian).
72. Vassilevsky, N.N. and Suvorov, N.B., Electromagnetic correction of human state, BEMS, Abstract Book. Seventeenth Annual Meeting, USA, June 18-22, 1995.
73. Lebedeva, N.N., Vekhov, A.V., and Bazhenova, S.I., On human electromagnetic perception. Problemy electromag. neurobiol (The electromagnetic neurobiology problems), Moscow: Nauka, 1988, pp.85-93 (in Russian).
74. Lebedeva, N.N., Neurophysiological mechanisms of biological effects on peripherical action of non-ionizing electromagnetic fields, X Russian Symposium (with participation of foreign scientists) "Millimeter Waves in Medicine and Biology", Moscow. 1995 (in Russian).
75. Kotrovskaya, T.I., Human electromagnetic perception and its relation with individual properties, Moscow: Ph.D.thesis, 1996 (in Russian).
76. Stam, K.J., Tavy, D.L.J., Jettes, B., et al., Non-linear dynamical analysis of multichannel EEG: clinical applications in Dementia and Parkinson's disease, Brain Topography, 1994, vol. 7(2), pp. 141-150.
77. Boldyreva, G.N. and Zhavoronkova, L.A., EEG inter-hemispheric relationship for estimation of Human brain functional state, Jh.Vyssh.Nerv.Deyat. im I.P.Pavlova (Journal of the higher nervous activity named by I.P.Pavlov), 1989, vol. 39-2 (in Russian).
78. Rusinov, V.S., Grindel, O.M., Boldyreva, G.N., el al., Human brain biopotentials, Moscow: Meditsina (Medicine), 1987 (in Russian).
79. Sviderskaya, N.E., Synchronous electric activity of brain and psychical processes, Moscow: Nauka, 1987, pp. 61-81 (in Russian).
80. Grassberger, P. and Procaccia, I., Measuring the strangeness of strange attractors, Physica D., 1983, vol. 9(1-2).
81. Aranson, I.S., Reyman, À.N., and Shechov, V.G., The methods of measuring of correlation dimension in the experiment, Nelineynyye volny, Dinamika i evolutsiya (Nonlinear waves. Dynamics and evolutia.), Moscow: Nauka, 1989 (in Russian).
82. Osovets, S.M., Ginsburg, D.A., Gurfinkel, V.S., et al., Electric activity of brain, Uspekhi fis.nauk (The evidences of fisical science), 1983, vol. 141(1) (in Russian)
83. Rapp, P.E., Zimmerman, I.D., Albano, A.M., et al., Dynamics of spontaneous neural activity in the simian motor cortex: the dimension of chaotic neurons, Phys. Lett. A., 1985, vol. 110(6).
84. Belskii, U.A., Vedenin, A.B., and Dmitriev, A.S., Diagnostics of brain pathology by the method of non-linear dynamics, Radiotekhnika i Electronika (Radio engeneering and Electronics), 1993, vol. 38(9) (in Russian).
85. Skarda, Ch.A. and Freeman, W.J., How brains make chaos in order to make sense of the world Behav, Brain. Sci., 1987; 10.
86. Efremova, T.M., Kulikov, M.A., and Rezvova, I.R., The participation of non-linear dynamical processes in forming of the high frequency rabbit EEG component, Zh. Vyssh. Nerv. Deyat. im I.P.Pavlova (Journal of the higher nervous activity named by I.P.Pavlov), 1991; 41(5) (in Russian).
87. Mann, K. and Roschke, J., REM-suppression induced by digital mobile radio telephone, Wien-Med-Wochenschr.,1996, vol. 146, pp. 13-14.
88. Ulbikas, Yu.K., Davydov, V.I., and Levedeva, N.N., Application of the methods of chaotic dynamics to investigate EHF exposure effects on human bioelectric brain activity, Millimetrovye volni v Meditsine (Millimeter Waves in Medicine), vol. 2, Moscow, 1991 (in Russian).
89. Dominanta: electrophysiological study, Moscow: Medicine, 1969 (in Russian).
90. Pavligina, R.A., Dominanta and its role in animal behaviour, Uspekhi physiol.nauk (The evidence of fisiological science), 1982, vol. 13 (in Russian).
91. Pavligina, R.A., Lebedeva, N.N., Davidov, V.I., Study of human locomotory dominanta, Zh. Vyssh. Nerv. Deyat. im I.P.Pavlova (Journal of the higher nervous activity named by I.P.Pavlov), 1998, no. 6 (in Russian).





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Investigation of Brain Potentials in Sleeping Humans Exposed to the Electromagnetic Field of Mobile Phones




Doctor of Biological Sciences, Principal Scientist at the Institute of Higher Nerve Activity and Neurophysiology, Russian Academy of Sciences. E-mail: N.Leb@relcom.ru; 2Candidate of Medical Science, Senior Researcher at the Institute of Higher Nerve Activity and Neurophysiology, Russian Academy of Sciences.; 3Researcher at the Institute of Higher Nerve Activity and Neurophysiology, Russian Academy of Sciences; 4Deputy Director of the "Extremely High Frequency" Medical and Technical Association; 5Biological Department Head at the Deutsche Telekom AG (Germany).




ABSTRACT: An investigation was made of 8-hour EEG tracings of sleeping humans exposed to the electromagnetic field of a GSM-standard mobile phone. To analyze the EEG-patterns, manual scoring, nonlinear dynamics, and spectral analysis were employed. It was found that, when human beings were exposed to the electromagnetic field of a cellular phone, their cerebral cortex biopotentials revealed an increase in the a-range power density as compared to the placebo experiment. It was also found that the dimension of EEG correlation dynamics and the relation of sleep stages changed under the influence of the electromagnetic field of a mobile phone.




LITERATURE REVIEW




Normal sleep is made up of cyclic variations in the functional state of the brain. The most salient and invariable feature of sleep consists in that the brain shows a decrease in the cerebral cortex activity on the scale "sleep-wakefulness". The functional state of the brain is usually studied by means of an electroencephalogram (EEG). An analysis of electroencephalograms made earlier demonstrated that sleep is an inhomogeneous process. It has a complex structure and a certain sequence of alternating patterns. There are many classifications of sleep due to numerous approaches to the description of EEG patterns. One of the first classifications made it possible to analyze EEG patterns in sleeping subjects [1]. However, the application of this classification can only show how deep is the subject's sleep. In other words, this classification is capable of revealing only two stages of sleep, such as drowsiness and deep (slow-wave) sleep. The discovery of the rapid-eye-movement (REM) stage
of sleep allowed the development of a new classification [2]. According to this classification, sleep was divided into orthodox sleep, which does not involve rapid eye movements, and into paradoxical, or REM, sleep.

The most complete classification of polysomnographic sleep records is given in [3]. It uses electroencephalograms, electromyograms, electrooculograms, and some other techniques. This approach made it possible to recognize five alternating stages of sleep with certain EEG correlates for every stage.

The first stage is marked by a relatively low amplitude and mixed frequencies with a pronounced activity at 2 to 7 Hz. The duration of this stage is relatively short and it ranges from 1 to 7 min. This stage occurs mostly when a person starts to fall asleep or between other stages of sleep. The second stage is recognized by a relatively low amplitude, "sleep spindles", and K-complexes arising either due to responses to unexpected stimuli or in the absence of any differentiable stimuli. This stage constitutes approximately a half of the total sleeping time. The third stage is characterized by slow high-amplitude waves, which account for 20 to 50% of the whole analyzed period. The fourth stage shows high-amplitude waves with a frequency of 2 Hz. These waves make up more than 50% of the whole analyzed period. The fifth stage (or REM-stage) is distinguished by a relatively low amplitude and by mixed EEG frequencies periodically interrupted by episodes of REM sleep.

Presently, researchers make use of all the enumerated classifications of sleep stages depending on the solved problem.

In healthy adults, night sleep is made up of 4 to 6 sleep cycles that include all five stages. Each cycle begins with a period of slow-wave sleep. On the average, each cycle lasts for 90 min. However, the first cycle lasts longer than the final ones.

However, night sleep of healthy people can be affected by many kinds of things in the environment. For example, sleep is dependent on personality and it was found to be different in morning types and evening types [4-7]. Apart from that, sleep depends on the time when a person goes to bed and on the time during which he or she stayed awake before going to bed [8, 9]. In addition, sleep depends on the surroundings [10], age [11], subject's geomagnetic orientation [12, 13], and other conditions.
   In view of a constantly aggravating electromagnetic pollution of the environment, it seems essential to study the effect of various electromagnetic devices and equipment on the activity of the central nervous system of human beings [14], for example, during their sleep [15].




METHODS




Our investigation was conducted on 20 volunteers (20 men aged from 20 to 28). We made two runs of experiments, in which the volunteers were exposed to simulated (sham) and actual electromagnetic fields of a mobile phone in random order. Two-channel EEG tracings were recorded during an 8-hour laboratory sleep. The EEG tracings were recorded in the CZ and PZ leads, with the reference electrode being placed in the FZ lead.

As soon as electroencephalograms were recorded, sleep stages were scored manually and then their duration and alternation were analyzed. After that, nonlinear dynamics methods were employed to calculate correlation dimension and then FFT-based spectral analysis was used. We left out of account periods affected by muscular motion or winking artifacts. For normal EEG periods, we calculated the absolute spectral power in the d-, q-, a-, and b-ranges and the correlation dimension D2 for each lead. The secondary statistical treatment was carried out with the aid of variance analysis (ANOVA).




RESULTS




The spectral analysis of EEG patterns obtained from sleeping humans demonstrated that reliable variations in the spectral power indices were observed only in the a-range for the PZ lead (Figure 1, Table 1). An increased spectral power in the a-range can be explained by the fact that this range is most reactive to the influence of electromagnetic fields [16, 17]. A similar tendency of changes was also observed in the d- and q-ranges. However, the b-range did not exhibit significant variations or tendencies. It was also found that volunteers exposed to the actual electromagnetic field of a mobile phone showed a significant decrease (p < 0.05) in the two-channel correlation dimension D2 during an 8-hour sleep as compared to the placebo experiment with a simulated electromagnetic field (Figure 2).

The mean values of correlation dimension indices D2 for EEG tracings recorded during an 8-hour sleep from the CZ and PZ leads are presented in Figure 3 and in Table 2. Although the decrease in D2 was significant (p < 0.05) for both leads, it was more pronounced for the CZ lead.

Table 1. Mean values of the spectral power indices in the a-range for simulated and actual electromagnetic fields of a mobile phone.


Lead

Simulated
Electromagnetic Field

Actual
Electromagnetic Field

CZ

PZ

3.47840

3.346288

3.4813

3.574357






FIGURE 1. Mean values of the EEG spectral power density in the a-range obtained from the CZ and PZ leads during an 8-hour sleep for simulated and actual electromagnetic fields of a mobile phone (pPz < 0.05).





FIGURE 2. Mean values of the two-channel correlation dimension D2 during an 8-hour sleep.





FIGURE 3. Mean values of the correlation dimension indices D2 obtained from the CZ and PZ leads during an 8-hour sleep.




Table 2. Mean values of the correlation dimension indices D2 for simulated and actual electromagnetic fields of a mobile phone.


Lead

Simulated
Electromagnetic Field

Actual
Electromagnetic Field

CZ

PZ

12.70191

12.73272

12.36518

12.51446



The dynamics of the correlation dimension indices D2 during an 8-hour sleep for simulated and actual electromagnetic fields of a mobile phone is shown in Figure 4. Similar patterns were observed for every lead.
   Manual scoring demonstrated that, when volunteers were exposed to simulated and actual electromagnetic fields of a mobile phone, they exhibited insignificant differences in sleep stages. However, one can see that the percentage of slow-wave sleep during the whole 8-hour sleep revealed a tendency to decrease in volunteers exposed to the actual electromagnetic field (Figure 5, Table 3).

Table 3. Percentage of the slow-wave sleep for simulated and actual electromagnetic fields of a mobile phone.


Lead

Simulated
Electromagnetic Field

Actual
Electromagnetic Field

CZ

PZ

32.5754

32.0531

29.5682

29.8533




FIGURE 4. Dynamics of the mean correlation dimension indices D2 obtained from the CZ and PZ leads during an 8-hour sleep for simulated and actual electromagnetic fields of a mobile phone (p < 0.05).




DISCUSSION




It is known that the structure of night sleep includes deep synchronized slow-wave sleep (SSWS), which takes a large part of the first half of a sleep cycle. SSWS percentage then decreases and EEG tracings reveal desynchronization processes. These processes are typical of nonsynchronized slow-wave sleep (NSSWS), which includes the first, the second, and the fifth (or REM) stages [3].

It is also known [18] that EEG correlation dimension indices D2 of SSWS are significantly lower than those of NSSWS. This is associated with the fact that processes occurring in the brain at the third and fourth stages take a simplified course. During the second half of night sleep, NSSWS becomes dominating and the cerebral cortex's bioelectrical processes get more complicated. This gives rise to increased values of D2. It is this dynamics of D2 that was seen during sleep in human beings exposed to a simulated electromagnetic field (Figure 4).




FIGURE 5. Percentage of the slow-wave sleep (the third and the fourth stages) with respect to the whole 8-hour sleep structure for simulated and actual electromagnetic fields of a mobile phone.




However, when volunteers were exposed to the actual electromagnetic field of a mobile phone, they exhibited a different EEG pattern. Although during the first half of their sleep the dynamics of D2 was virtually identical to that of the control group, it did not show the expected increase in D2 during the second half of their sleep. Moreover, it remained invariable to the end of our experiment. Thus, the dynamics of D2 provided evidence for a changed sleep structure, which was related to the NSSWS depression. Similar results were reported in [15], in which healthy people were exposed to the electromagnetic field of a cellular phone and they also revealed a suppressed REM-stage (which is one of NSSWS stages). Apart from that, one can see from Figure 5 that the slow-wave sleep cycle (the third and fourth stages) revealed a tendency to decrease under the influence of the actual electromagnetic field, although this effect was not significant.

Thus, taking into account the results obtained in [18] and results presented in Figures 4 and 5, one can postulate that a prolonged exposure to the electromagnetic field of a mobile phone brings about a pronounced sleep structure transformation. In this case, sleep is largely made up of the first and second sleep stages, which involve no dreaming. Bearing in mind that the first stage is rather short and that it mainly accompanies the REM-stage, one can conclude that, when human beings were exposed to the actual electromagnetic field of a mobile phone, a great part of their sleep consisted of the second sleep stage, which is typical of aged people [3].

It is known that the fundamental biological role of sleep in live organisms is directed to providing adaptive regulation. On the one hand, sleep reduces functional loads on various bodily systems, such as the nervous system, the cardiovascular system, and the muscular system, with this reduction taking place during the third and the fourth sleep stages. On the other hand, the adaptive role of dreaming, which occurs during the REM-stage, is also of great importance because dreaming helps people to process stored information and to reduce psychological tension.

Hence, the electromagnetic field of a mobile phone affects the sleep structure and reduces slow-wave and REM-stage sleep percentage, which is able to decrease the adaptive reactions of human beings and to impair their state of health as a result of this.




REFERENCES

1. Loomis, A. L., Harvey, E. N., and Hobart, G. A., Cerebral states during sleep as studied by human brain potentials. J. Exper. Phychol., 1937.
2. Dement, W. and Kleitman, N., Cyclic variations in EEG during sleep and their relation to eye movements, body motility, and dreaming. Electroencephal. Clin. Neurophysiol., No. 9, 1957.
3. Rechtshaffen, A. and Kales, A., A manual of Standardized Terminology Techniques and Scoring System for Sleep Stages of Human Subjects. National Institutes of Health. Publication No. 204, Washington, 1968.
4. Akerstedt, T., Kecklund, G., and Knutsson, A., Manifest sleepiness and spectral content of the EEG during shift work. Sleep, Vol. 14, No. 3, pp. 221-225, 1991.
5. Lancel, M. and Kerkhof, G. A., Sleep structure and EEG power density in morning types and evening types during a simulated day and night shift. Physiol. Behav., Vol. 49, No. 6, 1991.
6. Kerkhof, G. A., Differences between morning types and evening types in the dynamics of EEG slow-wave activity during night sleep. Electroencephal. Clin. Neurophysiol. Vol. 78, No. 3, 1991.
7. Armitage, R. and Roffwarg, H. P., Distribution of period-analyzed delta activity during sleep. Sleep, Vol. 15, No. 6, 1992.
8. Aeschbach, D., Dijk, D. J., and Borbely, A. A., Dynamics of EEG spindle frequency activity during extended sleep in humans: relationship to slow-wave activity and time of day. Brain-Res., Vol. 14, 1997.
9. Gillberg M., and Akerstedt, T., The dynamics of the first sleep cycle. Sleep, Vol. 14, 1991.
10. McCall, W. V., Erwin, C. W., Edinger J. D., et al., Ambulatory polysomnography: technical aspects and normative values. J. Clin. Neurophysiol., Vol. 9, No. 1, 1992.
11. Dijk, D. J., Beersma, D. G. and van den Hoofdakker ,R. H., All night spectral analysis of EEG sleep in young adult and middle-aged male subjects. Neurobiol. Aging. Vol. 10, No. 6, 1989.
12. Ruhenstroth-Bauer, G., Ruther, E., and Reinertshofer, T., Dependence of a sleeping parameter from the N-S or E-W sleep direction. Z. Naturforsh [C], Vol. 42, No. 9-10, 1987.
13. Ruhenstroth-Bauer, G., Gunther, W., Hantschk, I., et al., Influence of the Earth’s magnetic field on resting and activated EEG mapping in normal subjects. Int. J. Neurosci., Vol. 73, No. 3-4, 1993.
14. Lebedeva, N. N., Reactions of the central nervous system to electromagnetic fields with various biotropic parameters. Biomeditsinskaya Radioelektronika, No. 1, 1998 (in Russian).
15. Mann, K. and Roschke, J., REM suppression induced by digital mobile radio telephones. Wein. Med. Wochenschr., Vol. 146, No. 13-14, 1996.
16. Lebedeva, N. N., Sulimov, A. V., Sulimova, O. V., and Kotrovskaya, T. I., Effect of the electromagnetic field of a mobile phone on the bioelectrical activity of the human brain. Biomeditsinskaya Radioelektronika, No. 4, 1998 (in Russian).
17. Sulimova, O. P., Electrical and Psychophysiological Reactions of the Human Being on the Peripheral Influence of Low-intensity EHF Electromagnetic Radiation. Abstract of Thesis for the Candidate of Biological Science. Simferopol State University, 1992 (in Russian).
18. Fell, J. and Roschke, J., Nonlinear dynamical aspects of human sleep EEG. Int. J. Neurosci., Vol. 76, No. 1-2, 1994.



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