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Similar Spectral Power Densities Within the Schumann Resonance and a Large Population of Quantitative Electroencephalographic Profiles: Supportive Evidence for Koenig and Pobachenko

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In 1954 and 1960 Koenig and his colleagues described the remarkable similarities of spectral power density profiles and patterns between the earth-ionosphere resonance and human brain activity which also share magnitudes for both electric field (mV/m) and magnetic field (pT) components. In 2006 Pobachenko and colleagues reported real time coherence between variations in the Schumann and brain activity spectra within the 6-16 Hz band for a small sample. We examined the ratios of the average potential differences (~3 μV) obtained by whole brain quantitative electroencephalography (QEEG) between rostral-caudal and left-right (hemispheric) comparisons of 238 measurements from 184 individuals over a 3.5 year period. Spectral densities for the rostral-caudal axis revealed a powerful peak at 10.25 Hz while the left-right peak was 1.95 Hz with beat-differences of ~7.5 to 8 Hz. When global cerebral measures were employed, the first (7-8 Hz), second (13-14 Hz) and third (19-20 Hz) harmonics of the Schumann resonances were discernable in averaged QEEG profiles in some but not all participants. The intensity of the endogenous Schumann resonance was related to the 'best-of-fitness' of the traditional 4-class microstate model. Additional measurements demonstrated real-time coherence for durations approximating microstates in spectral power density variations between Schumann frequencies measured in Sudbury, Canada and Cumiana, Italy with the QEEGs of local subjects. Our results confirm the measurements reported by earlier researchers that demonstrated unexpected similarities in the spectral patterns and strengths of electromagnetic fields generated by the human brain and the earth-ionospheric cavity.
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RESEARCH ARTICLE
Similar Spectral Power Densities Within the
Schumann Resonance and a Large
Population of Quantitative
Electroencephalographic Profiles: Supportive
Evidence for Koenig and Pobachenko
Kevin S. Saroka
1,2
, David E. Vares
1,2
, Michael A. Persinger
1,2,3
*
1Behavioural Neuroscience Laboratory, Laurentian University, Sudbury, Ontario, Canada P3E 2C6,
2Human Studies Program, Laurentian University, Sudbury, Ontario, Canada P3E 2C6, 3Biomolecular
Sciences Programs, Laurentian University, Sudbury, Ontario, Canada P3E 2C6
*mpersinger@laurentian.ca
Abstract
In 1954 and 1960 Koenig and his colleagues described the remarkable similarities of spec-
tral power density profiles and patterns between the earth-ionosphere resonance and
human brain activity which also share magnitudes for both electric field (mV/m) and mag-
netic field (pT) components. In 2006 Pobachenko and colleagues reported real time coher-
ence between variations in the Schumann and brain activity spectra within the 616 Hz
band for a small sample. We examined the ratios of the average potential differences
(~3 μV) obtained by whole brain quantitative electroencephalography (QEEG) between ros-
tral-caudal and left-right (hemispheric) comparisons of 238 measurements from 184 individ-
uals over a 3.5 year period. Spectral densities for the rostral-caudal axis revealed a
powerful peak at 10.25 Hz while the left-right peak was 1.95 Hz with beat-differences of
~7.5 to 8 Hz. When global cerebral measures were employed, the first (78 Hz), second
(1314 Hz) and third (1920 Hz) harmonics of the Schumann resonances were discernable
in averaged QEEG profiles in some but not all participants. The intensity of the endogenous
Schumann resonance was related to the best-of-fitnessof the traditional 4-class microstate
model. Additional measurements demonstrated real-time coherence for durations approxi-
mating microstates in spectral power density variations between Schumann frequencies
measured in Sudbury, Canada and Cumiana, Italy with the QEEGs of local subjects. Our
results confirm the measurements reported by earlier researchers that demonstrated unex-
pected similarities in the spectral patterns and strengths of electromagnetic fields generated
by the human brain and the earth-ionospheric cavity.
PLOS ONE | DOI:10.1371/journal.pone.0146595 January 19, 2016 1 / 22
OPEN ACCESS
Citation: Saroka KS, Vares DE, Persinger MA (2016)
Similar Spectral Power Densities Within the
Schumann Resonance and a Large Population of
Quantitative Electroencephalographic Profiles:
Supportive Evidence for Koenig and Pobachenko.
PLoS ONE 11(1): e0146595. doi:10.1371/journal.
pone.0146595
Editor: Lawrence M Ward, University of British
Columbia, CANADA
Received: May 12, 2015
Accepted: December 18, 2015
Published: January 19, 2016
Copyright: © 2016 Saroka et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any
medium, provided the original author and source are
credited.
Data Availability Statement: We have published all
the data necessary to recreate the results presented
in the manuscript on Figshare. Figs 1and 2:http://dx.
doi.org/10.6084/m9.figshare.1601012.Fig 3:http://dx.
doi.org/10.6084/m9.figshare.1601011. Figs 4,5,6:
http://dx.doi.org/10.6084/m9.figshare.1601010. Figs
7,8:http://dx.doi.org/10.6084/m9.figshare.1601014.
Funding: The authors have no support or funding to
report.
Introduction
In 1954 Von W. O. Schumann and H. Koenig [1] reported reliable and predictable peaks of fre-
quencies that were consistent with the model of an earth-ionospheric resonance. The possibil-
ity that the electrical components of the time-varying electrical potentials produced by the
brain may occasionally overlap and become synchronous with ultra-low frequency (ULF) elec-
tromagnetic activity occurring within this resonant cavity was originally observed and reiter-
ated by Koenig and his colleagues [2,3]. In their publication they noted qualitative
congruencies between the waveforms of electroencephalographic activity recorded from the
scalps of human subjects and patterns of naturally occurring electromagnetic activity (Type I
and II signals) that are generated by global lightning, particularly in tropical regions close to
the equator where lightning is observed year round. This observation is now supported by
additional quantifications showing that the space-time parameters of signals measured from
both the earth-ionosphere and brain electrical activity are complimentary. In particular the
Schumann resonances, which are traditionally defined by spectral peaks at approximately 8,
14, 20, 26, and 33 Hz [4], show remarkable consistency with electroencephalographic activity
in terms of frequency and intensity; both exhibit average magnetic field intensities of about 12
picoTeslas and when the average cortical thickness of about 3 mm is accommodated both
exhibit electric field intensities approaching .1 to 1 mV/m.
The apparent relationship between the Schumann resonance and brain activity has been
assessed theoretically. Nunez modeled the skull-brain cavity after the earth-ionospheric cavity
and predicted mathematically that the dominant resonant frequency of the brain would be
about 10 Hz [5]; this peak frequency decreased as a function of increasing skull size of the indi-
vidual [6]. Persinger, applying the concepts of scale-invariance, showed that the current densi-
ties of action potentials propagating along an axon were similar to those of lightning strikes
suggesting that a fractal relationship between processes occurring within the brain were reflec-
tive of processes occurring over the entire planet [7].
Many research groups have quantitatively assessed coupling of activities occurring globally
as geomagnetic perturbations within local regions electrically within the human brain. Repli-
cating observations made by Babyayev and Allahverdiyeva [8], Mulligan and colleagues [9]
described that theta (47 Hz) activity within the right prefrontal sensor was positively corre-
lated with terrestrial atmospheric power, an indicator of the strength of the steady-state mag-
netic field of the earth. Later, Saroka et al. [10] showed that both bi-temporal coherence and
parahippocampal activity was positively correlated with the strength of geomagnetic displace-
ment, the k-index. More detailed analyses indicated that the strength of the relationship
between posterior left-right temporal lobe coherence and geomagnetic activity was strongest
for coherences at 7.81 and approximately 20Hz, or stated alternatively the first and third har-
monic of the Schumann resonance.
To test direct synchrony between magnetic processes occurring in the earth-ionosphere cav-
ity and the human brain, Saroka and Persinger [11] measured simultaneously the Schumann
resonance and brain electrical activity of a single individual that was sitting quietly outside
with eyes-closed. Results of the analysis indicated the presence of transient periods of har-
monic synchronythat appeared when cross-channel coherence was computed between the
caudal root-mean-square signal derived from the brain and the extremely-low frequency (ELF)
magnetic activity occurring in the proximal environment. These periods of harmonic syn-
chrony lasted approximately 200300 msec and consisted of simultaneous coherence within
the 78, 1314 and 1920 Hz bands. The coherence magnitudes were similar in to those
reported earlier by Pobachenko and colleagues [12].
Schumann Frequencies from the Brain
PLOS ONE | DOI:10.1371/journal.pone.0146595 January 19, 2016 2 / 22
Competing Interests: The authors have declared no
competing interests exist.
Our approach is that the human cerebrum is a functional, dynamic dipole whose voltage, or
potential difference, is reflected as more or less steady-state potentials in the order of 10 to 30
mV [13] and extremely low frequency time-varying components whose average intensities are
about three orders of magnitudes less (μV range). Because the human cerebral volume is not a
sphere but more typical of an elliptoid there should be a slight difference in average μV inten-
sity that reflects this ratio. The relatively fixed volume and surface area of the cerebrum and
rostral-caudal bulk velocity of ~4.5 m!s
-1
should generate constant standing waves [6,14] with
parameters much like the fundamental Schumann resonance of ~7.5 to 8 Hz [3,15,16,17]
which is the resonance solution for the velocity of light (3!10
8
m!s
-1
) and the earths fixed cir-
cumference (4!10
7
m). The Schumann resonances were likely present during the origin of liv-
ing systems [18].
The purpose of the present study was to 1) to explore the potential manifestation of the
Schumann resonances within the electro-cortical activity of a large sample of individuals by
quantitative electroencephalographic assessments using various methodologies and 2) to repli-
cate the findings observed earlier showing an enhanced synchrony between human cortical
activity and the Schumann resonance when the later was measured locally in Sudbury, Canada
as well as distally in Cumiana, Italy.
Materials and Methods
Study 1-Intrinsic Schumann Resonance in Human Brain Activity
Subjects. The subjects in this study were 184 individuals, measured singly, who had partic-
ipated in various experiments within the laboratory between 2009 and 2013. Some subjects
were measured more than once so that the total numbers of records were 237. As part of the
laboratory protocol, eyes-closed measurements were collected at the beginning of each experi-
ment before testing. While exact indices of age of the participants were not available, the major-
ity of the individuals included in this study were university students between 19 and 25 years of
age. Some of the individuals had been referred to the third authors private practice for psycho-
metric and electroencephalographic assessment (N = 45). The proportion of men (N = 109)
and women (N = 128) were similar. Most measurements were completed within a commercial
acoustic (echoic) chamber under dim light conditions, otherwise measurements were obtained
in quiet rooms on the University campus from participants who volunteered for participation
in 4
th
-year thesis projects.
Equipment and Recordings. Brain electrical activity was monitored using a Mitsar 201
amplifier equipped with a 19-channel Electro-Cap International. Measurements from 19 sites
(Fp1, Fp2, F7, F3, Fz, F4, F8, T3, C3, Cz, C4, T4, T5, P3, Pz, P4, T6, O1, O2) consistent with the
International Standard of Electrode Placement were obtained. Impedance for all measurements
was maintained below 5 kOhms. The data recorded from the amplifier was delivered to a Dell
laptop equipped with WinEEG v.2.8 which produced a digital copy of the recorded voltages.
Sixteen-second epochs of eyes-closed data were extracted from each participant and exported
into MATLAB software for further filtering and processing.
While most data collected with the amplifier were obtained using a sampling rate of 250 Hz,
some measurements were collected with a sampling rate of 500 Hz. To insure homogeneity
across subjects, data that were collected using a sampling rate of 500 Hz was re-sampled to 250
Hz using the resample.mfunction within the MATLAB platform. The data for each subject was
then filtered between 1.5 and 40 Hz using the eegfiltfft.mfunction within the freely available
EEGLab toolbox [19]. The function uses an inverse FFT algorithm to band-pass filter raw mea-
surements within a specified frequency range. We have found qualitatively and quantitatively
that this filtering algorithm produced identical results independent of whether the segment
Schumann Frequencies from the Brain
PLOS ONE | DOI:10.1371/journal.pone.0146595 January 19, 2016 3 / 22
length was 16 seconds or 120 seconds in duration; the correlation between the raw voltage
recordings was 0.996. Once filtered, the data were submitted to spectral analysis, using the spec-
topo.mfunction, which computed spectral density within discrete frequencies for the Fp1 O2
T3 and T4 sensors using Welchs periodogram method employing a window size of 2048 (8.2
seconds) to maximize spectral resolution and a Hamming window with 50% overlap between
windows.
These data was then imported into SPSS for further analysis and for the computation of
mean absolute potential difference along the rostral-caudal (Fp1-O2) axis as well as between
the left-right temporal (T3 and T4) sensors. Absolute differences between rostral-caudal and
left and right temporal sensors were also obtained by subtracting the absolute raw voltages
(independent from spectral density) from the extracted EEG record for each 4-millisecond
point interval over 16 seconds.
Random Sample of 10 Brain Measurements. To appreciate the difference between a sub-
sample of the total population and the total population, 16 s of QEEG data (Fp1 02, T3 T4) for
10 subjects were randomly selected using a random number generator. Z-scores for
the μV
2
!Hz
-1
values for the rostral-caudal, left-right measures were obtained first in order to
minimize individual differences in absolute baseline values. Spectral analyses from SPSS 16 (a
different algorithm from the one applied in the previous section) were then applied to each of
the two measures for each of the 10 subjects. The frontal spectral density scores were then sub-
tracted from the occipital spectral density scores for each subject. The z-scores for each of these
new means were calculated so that there would be a standardized score for these differences to
compare directly across individuals. The average values for the two orthogonal measures were
calculated.
In order to examine the degree of individual differences of the spectral analyses each sub-
jects results were assessed visually for the peak spectral density within the 10 Hz range.
Because the Δf (increment of frequency) within this frequency range for 250 Hz samples is frac-
tional (less than an integer, i.e., about .01 Hz), the band width of the peak spectral density
could be inferred. This was discerned by direct inspection of the quantitative values where the
decline in z-scores on either side of the peak was conspicuous and greater than 2 standard devi-
ations for the interval.
Discerning the Schumann Resonance Signature in the Brain. After re-sampling and re-
filtering between 1.5 and 40 Hz for the 184 individuals by eegfiltfft.m, the anterior, middle, and
caudal root mean square signals were derived from integrating frontal (Fp1,Fp2,F7,F3,Fz,F4,
F8), middle (T3,C3,Cz,C4,T4) and caudal (T5,P3,Pz,P4,T6,O1,O2) sensors. These derived sig-
nals were spectral analyzed by spectropo.m with a window size equal to 2048 FFT points to
maximize spectral resolution employing the same spectral analysis parameters mentioned
above. Other researchers, e.g., Abeyuriya et al [20], have recently employed the same approach
to discern non-linear harmonics of sleep spindles in human electroencephalographic
recordings.
Because of a connection between activity within the parahippocampus and naturally-occur-
ring geomagnetic activity established in a previous publication [10] and its prominent role as
an integrator of experience before long-term memory processes within the hippocampus, infer-
ences of left and right parahippocampal current source density (μA!mm
-2
) were computed in
sLORETA [21] within the classical frequency bands used in more conventional electroenceph-
alographic studies [i.e. delta (1.54 Hz); theta (47 Hz); low-alpha (710 Hz); high-alpha (10
13 Hz); beta-1 (1320 Hz); beta-2 (2025 Hz); beta-3 (2530 Hz); gamma (>30 Hz)]. Corra-
dini and Persinger [22] have found that source localization performed with 19 sensors within a
clinical population was able to localize the source of infarctions and closed-head injuries and
was validated against accepted psychometric inferences of the functioning of these regions. We
Schumann Frequencies from the Brain
PLOS ONE | DOI:10.1371/journal.pone.0146595 January 19, 2016 4 / 22
employed the exact same methodology for computing the current source density for the para-
hippocampal regions as in a previously published paper [10]. Each of the 237 16-second
recordings were entered into sLORETA. First, the 19-channel series was translated into the fre-
quency-domain using the EEG to Cross-Spectrum function and computed cross-spectral densi-
ties in the defined frequency bands [i.e. delta (1.54 Hz); theta (47 Hz); low-alpha (710 Hz);
high-alpha (1013 Hz); beta-1 (1320 Hz); beta-2 (2025 Hz); beta-3 (2530 Hz); gamma
(>30 Hz)]. Next the Cross-Spectrum to sLORETA function was used to compute current source
density; the transformation matrix used here was defined by the 19-channel array produced
within the software. Finally inferences of left (MNI-co-ordinates: X = -28, Y = -40, Z = -12)
and right (X = 28, Y = -40, Z = -12) parahippocampal current source density for each of the fre-
quency bands (for each participant) were extracted by using the sLORETA to ROI function
using a customized ROI seed file.
The same epochs of electroencephalographic activity used in the sLORETA analyses were
also imported into MapWin software [23] for the computation of microstates and their related
parameters (i.e. duration of microstate, occurrence of microstate class, etc.). The strategies
involved in producing microstates involves clustering of topographic maps based upon voltage.
Because of the stochasticnature of EEG signals, only those maps that exceed a certain thresh-
old of signal to noiseare included [24]. The criterion for this threshold is defined by global
field potential (GFP); only those maps with elevated GFP peaks that are high are considered for
clustering. This equation is expressed as a spatial standard deviation and can be modeled math-
emtaically as [24]:
GFP ¼ð
PðvðtÞ%VðtÞ2=nÞ1=2ð1Þ
where v is the voltage at a given channel, t is the time point of interest, and V is the mean volt-
age across all channels. These maps are then entered into a k-means clustering algorithm
within the MapWin software itself and classes of microstate maps are produced irrespective of
polarity. Effectively the resultant classes, or clusters, are the mean centers for each channel
interpolated onto a 5x5 matrix with approximate locations of channels identied. The montage
in this case was:
Fp1Fp2
F7F3Fz F4F8
T3C3Cz C4T4
T5P3Pz P4T6
O1O2
The 16-second epochs for each of the 237 available records were segmented into 4x4 second
segments for later averaging. Then, microstate computations were computed separately for
each participant utilizing the following methods. First, each of the 4 segments were imported
into MapWin where a digital filter between 220 Hz was applied, in accordance for standard
procedures described by Koenig et al [25]. Next, microstate clusters were then produced using
the Compute Microstates function. Here we selected to produce only 4-clusters (maximum = 8)
with a convergence criterion set to 25 iterations. All maps produced here were polarity insensi-
tive and were only generated at GFP peaks. After this process was repeated for all 237 cases, the
resultant average microstate maps (N = 237) were entered into the Combine Microstates func-
tion which clustered all of the scalp maps of each individual to produce 4 mean microstate-
classes; the classes were almost identical to those reported by Koenig et al. [25] and explained
approximately 72% of the variance in scalp map classification.
Schumann Frequencies from the Brain
PLOS ONE | DOI:10.1371/journal.pone.0146595 January 19, 2016 5 / 22
Next, 4 microstate statistics (occurrence, coverage and duration) for each microstate class as
well as model percent variance (which effectively described how well the average model fit the
individual subjects) were computed within the software. To accomplish this all 4-second seg-
ments (of each participant) were re-imported into Mapwin software. The average 4-class
model computed above was then applied to each of these segments (N = 237x4) separately and
statistics were computed using the Microstate Statistics function which exported each statistic
for each epoch into a Microsoft Excel file. Averages of each of the statistics for each individual
were then computed.
Finally, the raw voltages, spectral densities, inferences of parahippocamapal activity, and
microstate parameters were exported into a singular SPSS dataset for further analyses.
Study 2-Real Time Correlations Between Schumann resonance
Measured Locally and Non-Locally and Brain Spectral Power
Densities
To replicate our previous findings [11] and those of Pobachenko et al [12] indicating a syn-
chrony between signals measured from the earth-ionospheric cavity and electroencephalo-
graphic activity two participants (2 male and 2 female) were recruited to participate. While the
relationship has since been replicated with a larger population involving synchronous correla-
tions between brain activity and the Schumann resonance measured in Italy, the effect sizes for
the relationship between Schumann and human brain coherences made locally were such that
we decided two randomly selected individuals should be demonstrative; in effect the correla-
tions observed within these two individuals should be comparable to that observed in a previ-
ous study [11].
Local Brain-Schumann Coherence
Two individuals (1 male and 1 female) were outfitted with a 19-channel QEEG cap (Electro-
Cap International) which was connected to a Mitsar-201 amplifier while laying in a supine
position outside the Laurentian University Arboretum, which was distant enough from sources
of electrical interference (i.e. power and telephone lines) to allow for relatively noise-free
recordings. All sensor impedances were maintained below 5 kOhms and were sampled at 500
Hz within WinEEG 2.8 software. A lead from a custom-constructed induction coil magnetom-
eter system was fed into the ECG input of the amplifier in order to allow simultaneous record-
ings of brain electrical activity and electromagnetic perturbations occurring within the local
earth-ionosphere.
The exact specifications and methodology of the experiment and equipment (including pic-
tures) were identical to a protocol previously described [11]. For brevity, the coil was composed
of 28 gauge copper wire (approximately 14 kg) wound around a 5-cm diameter PVC pipe and
was connected into a pre-amplifier with a gain of 40 dB. Calibration with the Mitsar box demon-
strated that the magnetometer was sensitive to changes on the order of a picoTesla and on clear
and cloudy days with minimal wind Schumann resonances were readily observable in the aver-
aged spectrum after 12 minutes of continuous sampling. This is similar to the time required by
other researchers [26] to clearly discriminate the Schumann power densities. In addition the vari-
ations in power within the Schumann signals from our station are strongly correlated with those
of the on-line data from an Italian station (Observatory IK1QFK; www.vlf.it).
For both participants, the caudal root-mean-square was calculated from the 7 posterior
channels (T5,P3,Pz,P4,T6,O1,O2) as already described for 60-second segments (N = 2) where
the Schumann resonance was readily observable from initial spectral screening. This signal as
well as the magnetic component of extremely-low frequency (ELF) activity collected
Schumann Frequencies from the Brain
PLOS ONE | DOI:10.1371/journal.pone.0146595 January 19, 2016 6 / 22
simultaneously were then merged together into a two-channel set and entered into EEGLab
[19] for channel cross-coherence for estimations of coherence magnitude and phase. This mea-
sure was computed in 10-second time bins using sinusoidal Hanning-tapered wavelets 3 cycles
in length 0.5 seconds long and a padding ratio of 1.
Non-Local Brain-Schumann Coherence
To discern whether the coherence observed between the Schumann resonance and brain elec-
trical activity was similar when atmospheric noisewas recorded non-locally, a stream of ultra-
low frequency electric field perturbations (http://78.46.38.217/vlf15.m3u), measured with a
Marconi T antenna, was directed into the Mistar ECG input using a custom-constructed
audio-to-ECG cable for 2 subjects (1 male and 1 female). The stream is made available from
Mr. Renato Romero who owns and operates an open-source website dedicated to the exchange
of techniques and real-time radio frequency data below 22 kHz for amateur radio hobbyists.
One-way ping times were measured from this site from our laboratory in Sudbury and the
results indicated that the maximum latency was 50 milliseconds. Data collection and analysis
was exactly the same as for the two participants whose ELF and EEG data were measured
locally; the only difference was that five minutes of eyes closed data was collected for 30 partici-
pants within a sound-proof acoustic chamber instead of outside.
Results
Differential Potential Differences
The means for the μV
2
/Hz for global frequencies between the rostral-caudal (RC) axis and the
left-right (LR) temporal lobe for the 237 records available for this study are shown in Fig 1. For
this particular analysis (N = 177), we only selected individuals whose z-score was within +/-
one standard deviation from the mean. The amount of shared variance (r
2
) was 67% (i.e.,
r = 0.82). After accommodating for bandwidths pertaining to the window size of the spectral
analysis, the square root of the two mean values was 3.89 μV and 3.05 μV, respectively, or a
major (RC)-to-minor (LR) axis ratio of 1.27. According to Blenkov and Glazer [27] the mean
rostral-caudal length of the cerebrum is 172.5 mm (155190 mm) while the RL length is 136
mm (131141). The ratio is 1.27. Consequently the average disparity of potential difference
between the two axes reflects the proportional distance between the sensors. The scattergram
displaying the correlation between the discrete quantitative values for the RC and LR measure-
ments is shown in Fig 2.
Results of Random Sample (n = 10) Analyses
The correlation of the voltage values between the RC and LR axes for the 10 subjects was
r = 0.88. Because the values were μV
2
!Hz
-1
, square root values were obtained for the FC value
(3.71±0.76 μV) and RL (2.88±0.47 μV). The ratio was 1.29, compared to the ratio of 1.27 for
the entire sample. The distributions of the spectral density profiles for the major and minor
axes of the human cerebra in our sample are shown in Fig 3. The classic peak around 10 Hz,
with the majority of the power within the area of the curve between ~7 Hz and 13 Hz, is evi-
dent. The mean for this population was 10.25 Hz. Although the later peak was evident for the
minor (LR) axis, most of the power density for the LR axis was around 2 Hz (1.95 Hz) with a
more leptokurtic boundary within the delta band. The primary beat (difference) frequency was
8.3 Hz.
More detailed examination of the power spectra for the 10 randomly sampled records
employed to verify RC-LR differences in voltage revealed potentially relevant individual
Schumann Frequencies from the Brain
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variability. Employing the peak z-range obtained from each of the increments of frequency
from the spectral analyses, the mean peak was 10.12 Hz for the RC and 2.44 Hz for the LR axis.
The primary beat (difference) was 7.7 Hz. The results of analyzing the widthof the peak in
spectral power densities are shown in Table 1 for each of the 10 subjects. The mean frequency
of the peak band widthwas 0.39 Hz.
Fig 1. Rostral-Caudal Difference. Absolute potential difference (ΔμV
2!
Hz
-1
) plotted as a function of frequency for the rostral-caudal and left-right
measurements during QEEG for 177 subjects measured over a three year period.
doi:10.1371/journal.pone.0146595.g001
Schumann Frequencies from the Brain
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The Schumann Resonance Signature
A spectral distribution comparable to the Schumann resonances recorded from the earth was
observed with peak frequencies centering at approximately 7.5 Hz, 13.5 Hz and 20 Hz within
the global QEEG power for 237 records. One outlier (with a z>10) was removed. A 3-D plot
showing the distribution of each individual's spectral profile for the caudal aspect is displayed
in Fig 4.
We reasoned that if this resonance pattern within the human brain was normally distrib-
uted, certain individuals should show elevations in the spectral density of the Schumann reso-
nance. Thus, we computed a measure of Schumann intensity by multiplying the spectral
density of the mean of 78 Hz, 1314 Hz and 1920 Hz spectral densities for each of the ros-
tral, middle, and caudal RMS values described above. This computation provided an overall
Fig 2. Rostral-Caudal Correlation. Scattergram of the correlation (r = 0.82) between the discrete potential difference values for the caudal-rostral vs left-
right potential differences.
doi:10.1371/journal.pone.0146595.g002
Schumann Frequencies from the Brain
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measure of the strength of the Schumann resonance signature found within the cerebrums of
all 237 records along the rostral, middle, and caudal regions of the brain. These values were
then cube-rooted for each signal (i.e. rostral, middle and caudal) separately. Hence the equation
characterizing the computations for each of the 3 signals could be described by:
MeanðxÞ¼½xð7%8Hz DensityÞ'xð13 %14 Hz DensityÞ'xð19 %20 Hz DensityÞ(1=3
Where x corresponds to the selected region of computation (i.e. rostral, middle or caudal).
We then computed a global measure of the Schumann resonance by averaging all 3 (rostral,
middle and caudal) of these newly computed measures. Individuals were then categorized into
Fig 3. Rostral-Caudal and Left-Right Individual Differences. Means of the z-scores of the spectral density (μV
2
!Hz
-1
) of the measurements as a function
of frequency for the rostral-caudal and left-right measurements.
doi:10.1371/journal.pone.0146595.g003
Schumann Frequencies from the Brain
PLOS ONE | DOI:10.1371/journal.pone.0146595 January 19, 2016 10 / 22
one of the 3 groups based upon the z-scores of this global average. The groups were low
(z<-.5), medium (-.5<z<.5) and high (z>.5). This classification resulted in 19 individuals
(M = 11, F = 8) within the low group and 34 individuals (M = 9, F = 25) within the high group;
the rest of the individuals were within the medium group (M = 89, F = 95).
When the discrete spectral scores for each group were averaged across individuals within a
given intensity group (high versus low) and graphed, there were qualitative differences in the
definition of the spectral profiles (which were smoothed with a moving average with a
period = 40 FFT points, or approximately 1 Hz). Fig 5 depicts the spectral profiles within the
rostral, middle and caudal regions as a function of intensity group (low Schumann intensity
Table 1. Peak Frequency Individual Differences. Range of the standardized (z-score) for the raw spectral
density values for the peak band (in Hz) for the 10 randomly selected subjects. The band widthfor the peak
band range is also shown.
Subject Z-Range Peak band (Hz) Bandwidth (Hz)
1 1214 11.4311.68 0.25
2 1014 10.1810.75 0.57
3814 10.3110.50 0.19
4 1011 12.1812.43 0.25
536 10.5111.31 0.8
6919 10.3110.68 0.37
7 1518 10.4310.68 0.25
824 11.0011.37, 11.7512.50 0.37, 0.75
9619 9.7510.18 0.43
10 915 11.9312.31 0.38
doi:10.1371/journal.pone.0146595.t001
Fig 4. Individual Electroencephalographic Schumann Resonance Profiles. Log of spectral density of various frequencies reflecting the Schumann
resonance for all 237 records.
doi:10.1371/journal.pone.0146595.g004
Schumann Frequencies from the Brain
PLOS ONE | DOI:10.1371/journal.pone.0146595 January 19, 2016 11 / 22
versus high Schumann intensity). The first observation was that the Schumann resonance was
more defined for individuals who displayed stronger Schumann resonances intensities, defined
by their z-score. Whereas the low group could be described as "flat", the high group showed
peaks and valleys more characteristic of standing waves of 7.18 Hz, 13.52 Hz and 20.29 Hz.
The transformed difference for the high and low group was ~1 μV and 0.3 μV per Hz, respec-
tively. The peak to trough difference at the 20 Hz peak for the high spectral density group
would be about 2 μV
2
!Hz
-1
. The second observation was that, regardless of group (high versus
low intensity), the Schumann resonance was more pronounced within the caudal regions of
the brain.
Selected Associations Between the Schumann Resonance Signature
with Other Measures of Brain Activity
Given the remarkable rhythmic character of the subthreshold oscillation of ~8 Hz for stellate
cells in Layer II of the entorhinal cortices [28] and the importance of this region for receiving
convergent inputs from the entire cortical manifold before their distribution to the hippocam-
pal formation and amygdala, we specifically investigated the parahippocampal region by
Fig 5. Averaged Schumann Resonance Profiles. Mean Log value of the spectral density for high and low intensity subjects as a function of frequency for
the rostral, middle, and caudal regions of the cerebrums. Note the peaks at the fundamental Schumann resonance (first harmonic) as well as the second
(about 14 Hz) and third (about 20 Hz) harmonics.
doi:10.1371/journal.pone.0146595.g005
Schumann Frequencies from the Brain
PLOS ONE | DOI:10.1371/journal.pone.0146595 January 19, 2016 12 / 22
sLORETA using the three computed Schumann intensity groups. Separate one-way analyses of
variance for the left and right parahippocampal current source densities within the pre-defined
frequency bands with Schumann intensity (low, medium, high) as a between-subject factor
indicated that there was significantly (p <.001) more current source density within the bilat-
eral parahippocampus across most frequency bands for individuals who displayed high Schu-
mann resonance intensities. The strongest effects, as inferred by effect size, were observed
within the theta and gamma frequency ranges within the left hemisphere. The relationship
appeared linear which suggested that as the endogenous Schumann Resonance intensity
increased the activity in the left parahippocampus increased. These results are shown in
Table 2.
We also decided to explore this categorization of Schumann intensities within the context of
microstate topographies, which may be considered as geometric shapes of the electric field
(and by association magnetic field) produced by constructive and destructive interference pro-
cesses. A one-way analysis of variance indicated that the model percent variance of the
four microstate clusters explained significantly more variance (F
2,234
= 22.89, p <.001,
2
estimate = .16) in brain topographical patterns within individuals who displayed strong
Schumann resonances. These results are shown in Fig 6 and indicated that the classic 4-class
model, used to describe normal resting-state EEG topographies, was highly influenced by the
presence of the Schumann resonance within human brain cortical activity.
Real Time Coherence Between Directly Measured Schumann
Resonance Power Densities and QEEG Profiles
The coherence profiles for two subjects (1 male and 1 female) whose QEEG were measured
and spectral analyzed at the same time as direct measurements were taken for the Schumann
Resonance locally and within 1 meter of the person are shown in Fig 7. For the first person the
major coherence, as indicated by the red color that reflects the highest correlation occurred for
intervals of about 300 ms for the frequencies 8 Hz, 13 Hz, and 20 Hz. The greatest phase shift
was at 7.8 Hz and was equivalent to about 38.1 ms. For the second person the congruence
between the persons spectral power density for brain activity and the simultaneous Schumann
measurements were strongest within the same three frequency bands. The phase shift at 7.8 Hz
for that person on that day was 57 ms. The results for these two people are very similar to the
pattern we observed for a third person [11]. They are also consistent with the data reported by
Pobachenko et al [12] whose measurements were completed in Russia and with the general
properties of phase-modulation [26].
Table 2. Means and Standard Errors of the Means (in parentheses) for current source density (μA!mm
-2
) of the parahippocampal gyrus within the
classical frequency bands.
Left Right
Low Medium High Effect Size Low Medium High Effect Size
Delta 737 (67) 1412 (81) 1999 (257) 0.06 678 (64) 1563 (112) 1856 (230) 0.04
Theta 122 (11) 341 (22) 866 (147) 0.19 115 (9) 408 (35) 897 (150) 0.12
Low Alpha 188 (38) 1005 (90) 2710 (642) 0.12 149 (26) 1277(116) 2888 (495) 0.13
High Alpha 238 (54) 847 (71) 1435 (158) 0.09 279 (77) 951 (82) 1988 (272) 0.12
Beta-1 352 (50) 619 (40) 1134 (117) 0.12 345 (50) 667 (44) 1206 (142) 0.11
Beta-2 189 (49) 248 (26) 452 (62) 0.05 166 (32) 285 (37) 429 (45) 0.02
Beta-3 589 (224) 512 (93) 1188(421) 0.03 471 (174) 499 (74) 918 (206) 0.02
Gamma 2649 (319) 5783 (280) 11356 (1088) 0.23 2419 (239) 6608 (350) 12004 (893) 0.2
doi:10.1371/journal.pone.0146595.t002
Schumann Frequencies from the Brain
PLOS ONE | DOI:10.1371/journal.pone.0146595 January 19, 2016 13 / 22
Similarly, the results of the same cross-channel coherence analysis indicated periods of har-
monic synchrony between the cRMS and ELF recorded in Italy. Maximal synchronization was
commonly observed simultaneously within the 78 Hz, 1314Hz and 1920Hz frequency
bands, although scattering of coherence amongst other frequencies was common. Fig 8 displays
exemplary cases of harmonic synchrony for a different male and female. As in the cases where
the Schumann resonance was monitored locally, harmonic synchronous events were approxi-
mately 300 milliseconds in duration and typically occurred about 12 times per minute.
Discussion
Our results confirm and extend the results from other researchers that the QEEG properties of
the human brain reflect the subtle differences in volume and three-dimensionality [5], the
peaks of spectral power of the earths Schumann resonances in many (but not all) individuals
[3] and the real time coherence between the spectral power densities [12]. For the brain param-
eters, the absence of statistically significant differences between the strengths of the correlations
of power between the rostral-caudal and left-right comparisons and their ratios of power for
the total sample and the random sub-sample of 10 subjects indicates the robust nature of these
relationships. The precision of the ratio of the physical differences in RC and LR distances of a
population of adult cerebrums and the differences in the power densities of electrical activity
support our disciplines assumption that the amplitude of QEEG activity is a physical reflection
of potential difference (voltage).
Fig 6. Variance explained of all classic microstates as a function of the intensity of the Schumann resonance (first three harmonics) within the
EEG. N indicates numbers of records per post hoc group.
doi:10.1371/journal.pone.0146595.g006
Schumann Frequencies from the Brain
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Fig 7. Local Harmonic Synchrony. Cross-channel coherence between the caudal root-mean-square derivation and extremely low-frequency
electromagnetic activity recorded simultaneously in Sudbury, Canada for one male and one female measured on separate days. Evident in this time-
frequency analysis is harmonic synchrony occurring between brain electrical activity and atmospheric noiseat approximately 8, 13 and 20 Hz which define
the first three harmonics of the Schumann resonance.
doi:10.1371/journal.pone.0146595.g007
Schumann Frequencies from the Brain
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Fig 8. Non-local Harmonic Synchrony. Similar harmonic synchrony between extremely low-frequency atmospheric noise measured in Cumiana, Italy and
brain electrical activity measured in Sudbury, Canada at 8, 13, and 20 Hz for two subjects (1 male and 1 female) measured on a different day.
doi:10.1371/journal.pone.0146595.g008
Schumann Frequencies from the Brain
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Quantitative Inference of Cerebral Magnetic Field Strength
We reasoned that if the cerebral and earth-ionospheric resonances shared some characteristic
that could allow potential interaction, some variant of diffusivityshould be involved. Mag-
netic diffusivity, ή=(μ
o
σ)
-1
, where μ
o
is magnetic susceptibility (4π!10
7
N!A
-2
) and σ= elec-
trical conductivity, is a concept relevant to geophysical [29] and neurophysical phenomena.
Assuming the average resistivity of 2 O!m(σ~ 0.5 S!m
-1
) for extracellular fluid, and the average
potential difference of 3 μV in the rostral-caudal axis observed here, the resulting estimate for
the magnetic field strength is (3!10
6
kg!m
2
!A
-1
!s
-3
) divided by 1.58!10
6
m
2
!s
-1
or ~1.9!10
12
T,
that is about 2 picoTeslas (pT). This is well within the range based upon direct measurement
from of action potentials from isolated frog sciatic nerves at distance of 1 mm [30]. The spatial
domain is sufficiently large to have major influence upon the integrated cerebral field. This
magnitude is within a factor of 10 of the transient magnetic oscillatory response [31] evoked in
the human cerebrum, with a peak near 10 Hz and 3040 Hz, when the measured values in 20
fT!Hz
-1/2
are applied over the full frequency range of 100 Hz.
Although these intensities appear small, experimental application of pT, spatial and tempo-
rally-patterned magnetic fields have been reported to produce discernable improvement in
some clinical disorders, such as Tourettes and multiple sclerosis [32,33] as well as some electri-
cal foci associated with partial seizures [34]. Correlative responses associated with subjects
experiences have been associated with geomagnetic changes in the order of pT!s
-1
[35]. The lat-
ter occurred when ambient geomagnetic changes displayed progressive increases at this rate
over an approximately 15 min interval.
Comparisons with the Fundamental Schumann Resonance and
Interhemispheric Beats
It may be relevant that the recondite beat(the difference between the frequencies) between
the rostral-caudal and left-right power peaks was between 7 Hz and 8 Hz, the range of the fun-
damental (first harmonic) of the Schumann resonance. This compliments the more global
QEEG emergence of the first, second and third harmonics when a different method of analysis
was employed. The intrinsic resonance frequencymediated through the external shellof
the cerebral cortices [14] is also within this interval. Precise frequencies in this range can be
important. For example Harmony [36] found that 7.8 Hz power within the frontal lobes
decreased in adults but increased in children during a task that emphasized short-term
memory.
Resonances often arise in a cavity with sharp, homogeneous, and isotropic boundaries. The
Schumann resonances, with a fundamental frequency around 7.8 Hz and harmonics around
14.1, 20.3, 26.4, and 32.5 Hz [16], are generated within the approximately 100 km earth-ion-
ospheric cavity. The higher modes (harmonics) are separated by ~6 Hz according to the general
formula f
n
=f
1
[(n(n+1)]
1/2
although some authors include geometric coefficients. Primary ori-
gins of the energy are attributed to global lightning activity [7]. The typical median value for
the electric field is ~1 mV m
-1
while the magnetic field strengths are in the order of 1 pT. At
the lowest mode, around 8 Hz, the attenuation is ~1 db per 2000 km [16]. The significance of
these weak amplitudesbecome salient to neuroscience when one realizes that the potential
differences involved with reconnection of flux lines within the geomagnetic field when solar
wind energy is transferred into the magnetosphere is actually about 4 μV!cm
-1
[37] which is
within cerebral parameters.
Although popular authors emphasize the exactness of the fundamental (first harmonic) fre-
quency, empirical measurements indicate a range that would be significant from a QEEG per-
spective. For example injections of energies from protons (solar proton events) into the upper
Schumann Frequencies from the Brain
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atmosphere are followed by systematic increases of between 0.04 to 0.14 Hz above the funda-
mental (7.5 Hz) and amplitude enhancements of between 0.11 and 0.42 pT relative to the 1 pT
background [17]. In addition, splitting of Schumann resonances have been measured intermit-
tently for decades [38]. While pursuing the theoretical predictions of Madden et al [39], Tana-
hashi [40] noted doublet and triplet splitpeaks at 7.1, 7.85 and 8.5 Hz for the first mode and
12.4, 13.3, 14.0 and 14.8 Hz in the second mode. Fraser-Smith and Buxton [38] showed that
doublets (8 and 10 Hz) occurred for several tens of minutes. The amplitudes of these discrete
peaks were in the order of 1 or 2 pT!Hz
-1/2
.
Analyses of global power of 16-second samples of QEEG data from almost 200 subjects over
a five-year period indicated that spectral densities exhibited relatively wide-band peaks within
the first three harmonics of the Schumann resonance. The origins of these fundamental and
harmonic enhancements with the QEEG data cannot be identified at this time. One possibility
is that the Schumann peaks may reflect some intrinsic feature of the cerebral space due to the
average circumference and bulk velocity [6,14] or even a coupling between cerebral and ion-
ospheric frequencies through mechanisms yet to be identified. If the latter condition is valid
then intrinsic interactions, most likely intermittent, might occur and could be potentially quan-
tified by near-future QEEG and source-location technology. Transience may define these phe-
nomena within QEEG profiles. In our studies the harmonics were not obvious within single
16-s samples but were clear when aggregates from many subjects were averaged. Interestingly
this process is also required to obtain spectral profiles (such as in Fig 5 for brain activity) even
with direct environmental measurement of Schumann resonances [26]. It is also noteworthy
that optimal filtering between 1.540 Hz was required in order to observe Schumann frequency
peaks. When the low-cut frequency was set to below 1.5 Hz or above 3 Hz, the characteristic
peaks were not observed. This may indicate that energies represented within the 1.53Hz fre-
quency band are crucial in discerning the Schumann resonance within the brain.
Individual Differences
Although the statement that individual differences is the largest source of variance is well
known to any first year psychology student, the relevance to electrophysiological measure-
ments was obscured until QEEG became the general tool. If there is intercalation between
exogenous sources of Schumann resonances and comparable global cerebral frequencies then
quantifying and classifying these features may help explain sensitive populations. The individ-
ual differences were remarkable. In Table 1 the z-score for the peak band in the spectral densi-
ties for each person are shown. A representation of the 7.5 Hz Schumann line in brain activity
would occur in only two of the 10 subjects. Line splitting of the Schumann resonance displays
peaks with frequency spacing between ~ 0.2 to ~0.6 Hz. This overlaps with the bandwidth of
the peak power frequency. That only about 10% to 13% of all brains showed enhancements in
the intensity of the Schumann resonance may be useful for defining the characteristics of this
subpopulation.
There were also individual differences (or more accurately group differences) for the
amount of variance in the four classic microstates as a function of the intrinsic power of the
first three harmonics of the Schumann frequencies within the cerebral volume. As the power
for these bands increased the percentage of variance explaining the four microstates increased
from about 48% to 68%. Or stated alternatively, less of the total variance for the classic micro-
states was explained for those brains that displayed the lowest Schumann spectral density. This
could be interpreted as Schumann power functions like a homogenizerby removing ran-
domor uniquesources of variation and enhancing the prevalence of the four basic micro-
states. Considering its global nature, a direct contribution of Schumann resonance-induced
Schumann Frequencies from the Brain
PLOS ONE | DOI:10.1371/journal.pone.0146595 January 19, 2016 18 / 22
power to the proportional predominance of the four major microstates if they are the building
blocks of thought [41], could potentially affect large numbers of the human species for tran-
sient periods.
Potential Interactions Between Human Brain and Schumann Dynamics
Whether or not information from the cerebral volume could be represented within the Schu-
mann volume (or visa versa) has significant philosophical and social implications that QEEG
and neuroimaging could soon address. Even relatively complex mathematical solutions suggest
that gravity waves would interface with the earths second harmonic (14 Hz) Schumann reso-
nance [42]. The energy associated with the loss or gain of a bit of information according to the
Landauer Limit (ln 2 kT where k is the Boltzmann constant and T is temperature) is equivalent
to about 2.97!10
21
J, at brain temperature. In comparison, the energy upon a unit charge from
the ~2.6 (±0.5) mV of stellate cells that occurs within the upper (Layer II) cortical neurons
within the entorhinal cortices or parahippocampal region [28], which is 4.16!10
22
J would be
precisely within this range because this energy is generated about 8 times per second (~8 Hz)
by the persistent subthreshold oscillations. The stellate cells in the medial entorhinal cortices
are involved with convergences of information from the entire cortices and are a primary ori-
gin of the perforant path fibers to the dentate gyrus of the hippocampal formation.
Our results indicated that the average current source density within the parahippocampal
regions was greatest within the theta and gamma bands for individuals who displayed elevated
amplitudes for the three first harmonics of the Schumann resonance. This may be relevant not
only because the gammaor 40 Hzripples are superimposed upon hippocampal theta oscil-
lations [43]. The interconnectedness between hippocampal theta and cerebral cortical gamma
activity has been considered an important electrophysiological correlate for the intercalation
between neurocognitive processes such as consciousness and memory [44]. Theta phase can
modify the synchrony or coherence between gamma oscillations originating in multiple
regions. It may also be relevant that the hippocampal formation and the parahippocampal
regions, particularly within the right hemisphere appear, to be particularly responsive to small
changes in geomagnetic activity and experimentally applied fields within the pT range
[9,32,33,35].
Clearly the most compelling evidence that the similarities between the intensities of the
magnetic field and electric field strengths generated within the earth-ionosphere cavity, mea-
sured locally in Canada and non-locally in Italy, and those measured by EEG from the human
brain as well as the appearance of Schumann resonances within the EEG profiles of a large pop-
ulation of subjects that we have measured was the real-time coherence. Pobachenko et al [12]
had measured such coherence, employing different methods, in a different area of the world.
The enhanced coherence of power spectral between the simultaneous Schumann powers within
the first three harmonics and these frequencies within the EEG of the subjects is consistent
with a direct relation between the two. The coherence is not continuous but occurs in quasi-
discrete durations in the range of 300400 ms and approximate that of the single microstate.
Even the phase-modulations of between 40 to 60 ms reflects the band width ratios. For example
(Table 1) the ~0.4 Hz width divided by the primary beat frequency (7.7 Hz) would be equiva-
lent to a proportion that is about 50 ms.
Although Koenig et al [2,3] may have argued that the Schumann patterns are the zeitgebers
for this real-time correlation, there may be third factors that affect both. Pobachenko et al [12]
noted that both the Schumann and EEG profiles varied with changes in geomagnetic activity.
Saroka et al [10] measured greater EEG coherence between left and right temporal lobe struc-
tures during increased geomagnetic activity. The effect sizes for the coherences exhibited
Schumann Frequencies from the Brain
PLOS ONE | DOI:10.1371/journal.pone.0146595 January 19, 2016 19 / 22
maxima for the fundamental and first harmonic of the Schumann Resonance. That geomag-
netic activity affects QEEG profiles has been shown by correlation [9] and experimental [45]
analyses.
One of the basic assumptions of modern Neuroscience is that ultimately all of the qualitative
features of the ephemeral cognitive processes such as thinking and consciousness will be inter-
pretable as quantitative configurations [46] of the complex temporal patterns of electromag-
netic values that can be measured from the surface of the human cerebrum. The similarity of
average duration of microstates and the duration of the human percept is an example of such
transformation of perspective. The clever consideration [47,41] that four microstates [25]
could reflect functional cognitive units or atoms of thoughtthat are the information within
the stream of dynamic process within cerebral space, analogous to base nucleotide pairs for
genetic information within DNA sequences, exemplifies the significance of this approach. The
shift towards biophysical analyses [6,14,48,49,50] of complex cerebral functions once relegated
to the domain of the philosopher and psychologist requires a verification of the physical
parameters for these operations. Here we reiterate and report validation of quantitative phe-
nomena that define the electric and potentially magnetic features of our primary inferential
measurement: quantitative electroencephalography (QEEG) and how their characteristics are
shared by a unique pervasive property of the earth-ionosphere cavity.
Author Contributions
Conceived and designed the experiments: MAP KSS DEV. Performed the experiments: KSS
DEV MAP. Analyzed the data: KSS DEV MAP. Contributed reagents/materials/analysis tools:
MAP KSS. Wrote the paper: MAP KSS.
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Schumann Frequencies from the Brain
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... Честотата на алфа-ритъмът на мозъчната дейност на човек е в диапазона между честотите на първия и втория хармоник на резонанса на Шуман [2,6]. Съгласно [5] демонстрирано е подобие в спектралните модели и генерираните електромагнитни полета от човешкия мозък и земнойоносферното пространство. ...
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This article presents the origin of Schumann frequencies, their measurement and monitoring. The results of their measurements are presented and their diurnal and seasonal variations are analyzed. Application areas of Schumann frequencies are discussed.
... Specifically, brain oscillations within the theta (4-7 Hz) and alpha (8)(9)(10)(11)(12)(13) Hz) EEG bands can become synchronized with the Earth's EM field [137]. Saroka and colleagues [138] were the first to demonstrate real-time coherence between Schumann resonance and the frequency spectra of EEG rhythms across hundreds of independent human brains. Confirming the EM-brain interaction, Kirschvink's team recently described a series of experiments that demonstrate a significant, orientation-dependent desynchronization of alpha-band rhythms (8)(9)(10)(11)(12)(13) Hz) associated with the static magnetic field of the Earth [137]. ...
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Identifying a complete, accurate model of brain function would allow neuroscientists and clinicians to make powerful neuropsychological predictions and diagnoses as well as develop more effective treatments to mitigate or reverse neuropathology. The productive model of brain function, which has been dominant in the field for centuries, cannot easily accommodate some higher-order neural processes associated with consciousness and other neuropsychological phenomena. However, in recent years, it has become increasingly evident that the brain is highly receptive to and readily emits electromagnetic (EM) fields and light. Indeed, brain tissues can generate endogenous, complex EM fields and ultraweak photon emissions (UPEs) within the visible and near-visible EM spectra. EM-based neural mechanisms, such as ephaptic coupling and non-visual optical brain signaling, expand canonical neural signaling modalities and are beginning to disrupt conventional models of brain function. Here, we present an evidence-based argument for the existence of brain processes that are caused by the transmission of extracerebral, EM signals and recommend experimental strategies with which to test the hypothesis. We argue for a synthesis of productive and transmissive models of brain function and discuss implications for the study of consciousness, brain health, and disease.
... It was found that synchronization exists between EEG and SR spectrum power and increases with overall increased GMA level. Later, these results were confirmed in [138]. ...
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A systematic review of heliobiological studies of the last 25 years devoted to the study of the potential influence of space weather factors on human health and well-being was carried out. We proposed three criteria (coordinates), according to which the work on solar–biospheric relations was systematized: the time scale of data sampling (years, days, hours, minutes); the level of organization of the biological system under study (population, group, individual, body system); and the degree of system response (norm, adaptation, failure of adaptation (illness), disaster (death)). This systematic review demonstrates that three parameters mentioned above are closely related in the existing heliobiological studies: the larger the selected time scale, the higher the level of estimated biological system organization and the stronger the potential response degree is. The long-term studies are devoted to the possible influence of solar activity on population disasters, i.e., significant increases in morbidity and mortality. On a daily scale, a probable effect of geomagnetic storms and other space weather events on short-term local outbreaks of morbidity is shown as well as on cases of deterioration in people functional state. On an intraday scale, in the regular functioning mode, the heart and brain rhythms of healthy people turn to be synchronized with geomagnetic field variations in some frequency ranges, which apparently is the necessary organism’s existence element. The applicability of different space weather indices at different data sampling rates, the need to take into account the contribution of meteorological factors, and the prospects for an individual approach in heliobiology are discussed. The modern important results of experiments on modeling the action of magnetic storms in laboratory conditions and the substantiation of possible theoreical mechanisms are described. These results provide an experimental and theoretical basis for studies of possible connections of space weather and human health.
... Частоты естественных ЭМП СНЧ (0,5-26 ГЦ) представляют особый интерес тем, что они попадают в диапазон собственных колебаний спонтанной биоэлектрической активности мозга, в частности, с частотами, характерными для начальных и глубоких стадий сна: альфа-ритма (8-12 Гц), тета-ритма, дельта-ритма (0,5-4 Гц), и сонных веретен (12-15 Гц), и поэтому могут быть биологически значимыми. ЭМП с частотой 1Гц совпадают с частотным диапазоном дельта-ритма, характерным для глубоких стадий сна [9,10]. В электромагнитной биологии слабыми обычно называют такие ЭМП СНЧ, величина которых сравнима со значениями геомагнитных вариаций, что существенно ниже установленного в России предельно допустимого уровня 100 мкТл для жилых и офисных помещений. ...
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Objective: To test the hypothesis that weak electromagnetic fields of low frequencies (0.5-26 Hz) could affect daytime sleep features and structure. Material and methods: Parameters of daytime sleep continuity were compared in the study with counterbalanced control/exposition (40 min exposure to electromagnetic field at 1 Hz/0.004 μT) scheme in 22 healthy volunteers. Nonlinear regression model was used to assess daytime sleep continuity. Results: Exposure to a weak electromagnetic field of ultra-low frequency significantly improved the quality of sleep, assessed by the indicator of sleep continuity, namely, there were fewer transitions from the second and deeper stages of sleep to the first stage and to the state of wakefulness (p<0.0001). Conclusion: The results can be used to develop non-pharmacological methods of sleep correction, as well as to improve the quality of short-term sleep and its positive effect on well-being, cognitive function and working capacity.
... In particular, drawing conclusions regarding the effectiveness of SRF should be subjected to assessment and discussion of the dependence of effects on the field amplitude. Coinciding with studies pointing out the importance of SRF as endogenous biological rhythms [Saroka et al., 2016;Price et al., 2020], our findings indicate that further research on this direction is worth undertaking, and provide a new confirmation of the usefulness of the utilized system of coils to evaluate several field intensities simultaneously in a single experiment. ...
... This tremor is also supposed to play a role in the temperature regulation of endotherm animals. There is a huge debate about the influence of artificial stimulation with this rhythm on the brain and thereby on human consciousness but also on other body functions such as the heart rate [3,4]. Despite there is some evidence for synchronization effects, this connection could ...
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Objectives: There is quite a debate about frequencies around 8 Hz playing a role in the human brain but also in micro-vibrations in muscles of the body. There are also claims about a positive bodily and mental influence of various kinds of vibrating whole-body stimulations. We have studied the effects of such a rhythmic whole-body stimulation on a subjective level. Study Design: We tested the effects of 20 minutes mechanical whole-body stimulation at about 8 Hz on physical and mental wellbeing on 20 healthy participants. An additional control group of 20 participants kept the same body postures in a relaxation session. Outcome Measures. Changes in bodily sensations, emotions and mental experiences as well as the phenomenology of consciousness were assessed by questionnaires. Results: Compared to a control group, vibrational stimulation resulted in a significant more intense and wider body feeling and changes of the body image summarized in a factor called Integration (z=1.94, p<.05). It also provided slightly more experiences of bliss (z=2.1, p<.05). Effect sizes were moderate. Conclusions: Despite rhythmic whole-body stimulation has an overall positive effect on body, mind and wellbeing, when compared to a relaxation exercise, it only offered a slightly more extended body awareness and stronger experiences of bliss.
... The alpha waves during human brain activity (8-13 Hz) lie in the same frequency range as the first two modes of SR. In some individuals, the first, second, and the third harmonic of the SR were discernable in the encephalogram (Saroka et al. 2016). The studies linked to experiments in vitro during the recent years showed that the SR frequency of 7.83 Hz can inhibit the growth of cancer cells (Tang et al. 2019) and induced a reduction in creatine kinase release in rat cardiac cell cultures (Elhalel et al. 2019). ...
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An increase in the daily rate of acute myocardial infarction (AMI) has been observed during days of geomagnetic storm (GS). However, the analysis of associations between the daily number of AMI and geomagnetic activity (GMA) over longer periods sometimes yields controversial results. The study aimed to detect the complex association between the daily numbers of AMI and weather, the Quasi-biennial Oscillation (QBO) phase, GMA, and solar wind variables. We used data of Kaunas population-based Ischemic Heart Disease Register of residents of Kaunas city (Lithuania) for 2000–2012. The associations between weather and space weather variables and the daily number of AMI were evaluated by applying the multivariate Poisson regression. A higher risk of AMI was positively associated with active-stormy local GMA (rate ratio (RR) = 1.06 (95% CI 1.01–1.10)), solar wind dynamic pressure with a lag of 4 days (RR = 1.02 (1.01–1.04) per 1 nPa increase), and solar wind speed with a lag of 3–7 days (RR = 1.03 (1.01–1.05) per 100 km/s increase). A positive association was found between the west QBO phase and the risk of AMI during winter (RR = 1.08 (1.01–1.16)), and a negative association was observed between them during March–November (RR = 0.93 (0.90–0.97)). The risk of AMI positively associated with the GS due to stream interaction regions with a lag of 0–2 days during the east QBO phase (RR = 1.10, p = 0.046) and was negatively associated with them during the west QBO phase (RR = 0.82, p = 0.024). These results may help understand the population’s sensitivity under different weather and space weather conditions. The QBO phase may modify the effect of GS.
... For example, the application of a magnetic field with the same intensity as the Earth's was used to classically condition sharks [1]. The potential interaction between environmental electromagnetic fields has already been demonstrated in the human brain, where the pattern of its electrical activity showed transient periods of coherence with the Earth's magnetic field [10,11]. ...
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Some species of fish show highly evolved mechanisms by which they can detect exogenous electric and magnetic fields. The detection of electromagnetic fields has been hypothesized to exist in humans, despite the lack of specialized sensors. In this experiment, planaria were tested in a t-maze with weak electric current pulsed in one arm to determine if the planaria showed any indication of being able to detect it. It was found that a small proportion of the population seemed to be attracted to this current. Additionally, if the experiment was preceded by a geomagnetic storm, the planaria showed a linear correlation increase in the variability of their movement in response to the presence of the weak electric field. Both of these results indicate that a subpopulation of planaria show some ability to respond to electromagnetic fields.
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Objective. To study the effects of exposure to weak ultra low frequency electromagnetic fields on the structure of daytime sleep. Materials and methods. A total of 22 healthy volunteers were compared in a counterbalanced scheme in terms of daytime sleep continuity (consolidatedness) using 40-min exposure to an electromagnetic field (1 Hz/0.004 μT) and without exposure (control condition). Sleep continuity was evaluated using a nonlinear regression model. Results and conclusions. Exposure to a weak ultra low frequency electromagnetic field significantly improved sleep quality assessed in terms of sleep continuity: fewer transitions from stage 2 and deeper sleep stages to stage 1 and the waking state were seen (p < 0.0001). These results may be of value for developing pharmacological methods for correcting sleep and for increasing the quality of short periods of sleep and its positive effects on wellbeing, cognitive functions, and the ability to work.
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Schumann resonance has been studied for more than half a century. The field became popular among researchers of the terrestrial environment using natural sources of electromagnetic radiation-lightning strokes, primarily-and now many Schumann observatories have been established around the world. A huge number of publications can be found in the literature, the most recent collection of which was presented in a special Schumann resonance section of the journal Radio Science in 2007. The massive publications, however, impede finding information about how to organize measurements and start observations of global electromagnetic resonance. Relevant information is scattered throughout many publications, which are not always available. The goal of this book is to collect all necessary data in a single edition in order to describe the demands of the necessary equipment and the field-site as well as the impact of industrial and natural interference, and to demonstrate typical results and obstacles often met in measurements. The authors not only provide representative results but also describe unusual radio signals in the extremely low-frequency (ELF) band and discuss signals in the adjacent frequency ranges.
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The concept of the ∑n (the sum of n) = n can be considered a description of the holographic condition. We present systematic calculations of the quantitative convergence between the electromagnetic and related physical properties of the plasma cell membrane and its ion channels with those of the entire cerebral volume. The thickness and fundamental frequencies of the cerebral cortices reflect both space and time constants of the unit neuron and are congruent with the traditionally postulated re-entrant processes coupled to consciousness. The essential wavelengths and densities of the whole cerebrum can be viewed as identities with those of single action potentials and photon fields. The energy generated by consciousness-associated neuronal electromagnetic activity can be matched by applying weak transcerebral magnetic fields. Matrices of 'punctuated' fields whose configurations approach the width of synapses and whose angular rotations move with tensor-like patterns around cerebral space might be employed to experimentally manipulate the holographic condition by direct field-to-field interactions.
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The multiple quantitative similarities of basic frequencies, harmonics, magnetic field intensities, voltages, band widths, and energetic solutions that define the Schumann resonances within the separation between the earth and ionosphere and the activity within the human cerebral cortices suggest the capacity for direct interaction. The recent experimental demonstration of the representations of the Schumann resonances within the spectral densities of normal human quantitative electroencephalographic (QEEG) activity suggests a casual interaction. Calculations supported by correlations between amplitudes of the global Schumann resonances measured several thousands of km away (which were nearly identical to our local measurements) and the coherence and current densities or these frequency bands between cerebral hemispheres for a large population of human QEEG measures indicate that such interaction occurs. The energies are within the range that would allow information to be exchanged between cerebral and Schumann sources. The near-identical solution for current density from the increasing human population and background vertical electric fields suggests that changes in the former might determine the degree of coherence between the Schumann resonances. Direct comparisons of local Schumann measurements and brain activity exhibited powerful intermittent coherence within the first three harmonics. Implications of the contributions of solar transients, surface temperature, and rapidly developing technologies to modify the ionosphere’s Schumann properties are considered.
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Electroencephalographic (EEG) microstate analysis is a method of identifying quasi-stable functional brain states ("microstates") that are altered in a number of neuropsychiatric disorders, suggesting their potential use as biomarkers of neurophysiological health and disease. However, use of EEG microstates as neurophysiological biomarkers requires assessment of the test-retest reliability of microstate analysis. We analyzed resting-state, eyes-closed, 30-channel EEG from 10 healthy subjects over 3 sessions spaced approximately 48 hours apart. We identified four microstate classes and calculated the average duration, frequency, and coverage fraction of these microstates. Using Cronbach's α and the standard error of measurement (SEM) as indicators of reliability, we examined: (1) the test-retest reliability of microstate features using a variety of different approaches; (2) the consistency between TAAHC and k-means clustering algorithms; and (3) whether microstate analysis can be reliably conducted with 19 and 8 electrodes. The approach of identifying a single set of "global" microstate maps showed the highest reliability (mean Cronbach's α>0.8, SEM ≈10% of mean values) compared to microstates derived by each session or each recording. There was notably low reliability in features calculated from maps extracted individually for each recording, suggesting that the analysis is most reliable when maps are held constant. Features were highly consistent across clustering methods (Cronbach's α>0.9). All features had high test-retest reliability with 19 and 8 electrodes. High test-retest reliability and cross-method consistency of microstate features suggests their potential as biomarkers for assessment of the brain's neurophysiological health.
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Primary objective: To explore the quantitative relationship between neuropsychological impairment and spectral QEEG power, source localization (s-LORETA) and microstate duration in patients who 'fail to adapt' years after mild closed head injury. Methods and procedures: Differences in classic psychometric measures, QEEG measures, s-LORETA indicators and microstate durations were compared for three levels of neuropsychological impairment ∼(average) 6 years after injury. Results: Patients who displayed the moderate-to-severe neuropsychological impairments typical of mild TBIs exhibited shorter microstates, less power within the alpha band and lower power within the theta and delta bands within caudal regions. There were conspicuous differences in the configurations of microstates, their source localizations and frequency bands. Conclusions: The systematic relationship between neuropsychological impairment as inferred by classic psychometric measures that can require tens of hours to collect and modern configurational analyses of brain activity that require ∼30 minutes suggests that the latter might be useful in discerning the area of dysfunction and potential focus of treatment for patients with closed head injury years after the event.
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Ample evidence suggests that electroencephalographic (EEG) oscillatory activity is linked to a broad variety of perceptual, sensorimotor, and cognitive operations. However, few studies have investigated the delta band (0.5-3.5 Hz) during different cognitive processes. The aim of this review is to present data and propose the hypothesis that sustained delta oscillations inhibit interferences that may affect the performance of mental tasks, possibly by modulating the activity of those networks that should be inactive to accomplish the task. It is clear that two functionally distinct and potentially competing brain networks can be broadly distinguished by their contrasting roles in attention to the external world vs. the internally directed mentation or concentration. During concentration, EEG delta (1-3.5 Hz) activity increases mainly in frontal leads in different tasks: mental calculation, semantic tasks, and the Sternberg paradigm. This last task is considered a working memory task, but in neural, as well as phenomenological, terms, working memory can be best understood as attention focused on an internal representation. In the Sternberg task, increases in power in the frequencies from 1 to 3.90 Hz in frontal regions are reported. In a Go/No-Go task, power increases at 1 Hz in both conditions were observed during 100-300 ms in central, parietal and temporal regions. However, in the No-Go condition, power increases were also observed in frontal regions, suggesting its participation in the inhibition of the motor response. Increases in delta power were also reported during semantic tasks in children. In conclusion, the results suggest that power increases of delta frequencies during mental tasks are associated with functional cortical deafferentation, or inhibition of the sensory afferences that interfere with internal concentration. These inhibitory oscillations would modulate the activity of those networks that should be inactive to accomplish the task.
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Objective We compared the temporal dynamics of sensory-motor network during the preparation of actual and imagined reaching and tried to separate ideational-to-motor from pure ideational part of motor program. Methods Ten volunteers reached or imagined reaching with right arm. EEG and reaction time were recorded. Event related potentials were analysed with sLORETA (http://www.uzh.ch/keyinst/loreta), comparing preparation of both tasks with respect to their baseline and between them. Results Reaction time for actual reaching was 360 ± 59 ms. There were three key differences between tasks with stronger activity during actual reaching. The first was from 160 ms to 220 ms after target presentation in frontal and parietal regions, the second from 220 ms to 320 ms, in premotor cortex and the third from 320 ms to the reaching onset, mainly in the peri-rolandic region. These brain regions can be crucial for real reaching; processing arm-target integration and muscle activation. Anterior and posterior cingulate cortex were also involved most likely in awareness and controlling of the process. Conclusions and key message Our results suggest the existence of two systems: cortical/integrational and subcortical/controlling system. Observed differences in the first system may be important in separating the ideational from the motor part of the program.
Book
Elf and VLF Signal Properties: Physical Characteristics.- Electric and Magnetic Field Strengths in the open and in Shielded Rooms in the ULF- to LF-Zone.- Behavioural Changes in Human Subjects Associated With ELF Electric Fields.- ELF-Effects on Human Circadian Rhythms.- Operant Methods Assessing the Effects of ELF Electromagnetic Fields.- Behavioural, Physiological, and Histological Changes in Rats Exposed During Various Developmental Stages To ELF Magnetic Fields.- Oxygen and Biochemical Changes Following ELF Exposure.- Precambrian ELF and Abiogenesis.- ELF Electric and Magnetic Field Effects: The Patterns and the Problems.- Contributors.
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Objective: To investigate the properties of a sleep spindle harmonic oscillation previously predicted by a theoretical neural field model of the brain. Methods: Spindle oscillations were extracted from EEG data from nine subjects using an automated algorithm. The power and frequency of the spindle oscillation and the harmonic oscillation were compared across subjects. The bicoherence of the EEG was calculated to identify nonlinear coupling. Results: All subjects displayed a spindle harmonic at almost exactly twice the frequency of the spindle. The power of the harmonic scaled nonlinearly with that of the spindle peak, consistent with model predictions. Bicoherence was observed at the spindle frequency, confirming the nonlinear origin of the harmonic oscillation. Conclusions: The properties of the sleep spindle harmonic were consistent with the theoretical modeling of the sleep spindle harmonic as a nonlinear phenomenon. Significance: Most models of sleep spindle generation are unable to produce a spindle harmonic oscillation, so the observation and theoretical explanation of the harmonic is a significant step in understanding the mechanisms of sleep spindle generation. Unlike seizures, sleep spindles produce nonlinear effects that can be observed in healthy controls, and unlike the alpha oscillation, there is no linearly generated harmonic that can obscure nonlinear effects. This makes the spindle harmonic a good candidate for future investigation of nonlinearity in the brain.