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Objective: Transcranial photobiomodulation (tPBM) has shown promising benefits, including cognitive improvement, in healthy humans and in patients with Alzheimer's disease. In this study, we aimed to identify key cortical regions that present significant changes caused by tPBM in the electroencephalogram (EEG) oscillation powers and functional connectivity in the healthy human brain. Approach: A 64-channel EEG was recorded from 45 healthy participants during a 13-min period consisting of a 2-min baseline, 8-min tPBM/sham intervention, and 3-min recovery. After pre-processing and normalizing the EEG data at the five EEG rhythms, cluster-based permutation tests were performed for multiple comparisons of spectral power topographies, followed by graph-theory analysis (GTA) as a topological approach for quantification of brain connectivity metrics at global and nodal/cluster levels. Main results: EEG power enhancement was observed in clusters of channels over the frontoparietal regions in the alpha band and the centroparietal regions in the beta band. The global measures of the network revealed a reduction in synchronization, global efficiency, and small-worldness of beta band connectivity, implying an enhancement of brain network complexity. In addition, in the beta band, nodal graphical analysis demonstrated significant increases in local information integration and centrality over the frontal clusters, accompanied by a decrease in segregation over the bilateral frontal, left parietal, and left occipital regions. Significance: Frontal tPBM increased EEG alpha and beta powers in the frontal-central-parietal regions, enhanced the complexity of the global beta-wave brain network, and augmented local information flow and integration of beta oscillations across prefrontal cortical regions. This study sheds light on the potential link between electrophysiological effects and human cognitive improvement induced by tPBM.
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Journal of Neural Engineering
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Neuromodulation of brain power topography and
network topology by prefrontal transcranial
photobiomodulation
To cite this article: Sadra Shahdadian et al 2022 J. Neural Eng. 19 066013
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PAPER
Neuromodulation of brain power topography and network topology
by prefrontal transcranial photobiomodulation
Sadra Shahdadian, Xinlong Wang, Hashini Wanniarachchi, Akhil Chaudhari, Nghi Cong Dung Truong
and Hanli Liu
Department of Bioengineering, The University of Texas at Arlington, Arlington, TX 76019, United States of America
Author to whom any correspondence should be addressed.
E-mail: hanli@uta.edu
Keywords: transcranial photobiomodulation, tPBM, EEG, functional connectivity, imaginary part of coherence, graph theory
Supplementary material for this article is available online
Abstract
Objective. Transcranial photobiomodulation (tPBM) has shown promising benefits, including
cognitive improvement, in healthy humans and in patients with Alzheimer’s disease. In this study,
we aimed to identify key cortical regions that present significant changes caused by tPBM in the
electroencephalogram (EEG) oscillation powers and functional connectivity in the healthy human
brain. Approach. A 64-channel EEG was recorded from 45 healthy participants during a 13 min
period consisting of a 2 min baseline, 8 min tPBM/sham intervention, and 3 min recovery. After
pre-processing and normalizing the EEG data at the five EEG rhythms, cluster-based permutation
tests were performed for multiple comparisons of spectral power topographies, followed by
graph-theory analysis as a topological approach for quantification of brain connectivity metrics at
global and nodal/cluster levels. Main results. EEG power enhancement was observed in clusters of
channels over the frontoparietal regions in the alpha band and the centroparietal regions in the
beta band. The global measures of the network revealed a reduction in synchronization, global
efficiency, and small-worldness of beta band connectivity, implying an enhancement of brain
network complexity. In addition, in the beta band, nodal graphical analysis demonstrated
significant increases in local information integration and centrality over the frontal clusters,
accompanied by a decrease in segregation over the bilateral frontal, left parietal, and left occipital
regions. Significance. Frontal tPBM increased EEG alpha and beta powers in the
frontal-central-parietal regions, enhanced the complexity of the global beta-wave brain network,
and augmented local information flow and integration of beta oscillations across prefrontal
cortical regions. This study sheds light on the potential link between electrophysiological effects
and human cognitive improvement induced by tPBM.
1. Introduction
Transcranial photobiomodulation (tPBM) is a non-
invasive neuromodulation technique that delivers
near-infrared (NIR) light to the human brain using
lasers or light-emitting diode (LED) clusters [14].
Recent studies have demonstrated the promising
effects of tPBM in the treatment of traumatic brain
injuries [48], psychiatric or neurological disorders
[912], and enhanced cognitive performance in
normal humans [1318]. To better examine the
underlying mechanism of tPBM, neurophysiological
measurements of the human brain were per-
formed noninvasively from human controls using
optical spectroscopy before, during, and after pre-
frontal tPBM. These measures quantified tPBM-
induced increases in mitochondrial metabolism
(i.e. [CCO]) and hemodynamic oxygenation
(i.e. oxygenated hemoglobin ([HbO])) [1921].
It was also shown that the increases in both [CCO]
and [HbO] were not caused by thermal effects
of tPBM [22], hardware-related noise, or drift
[23,24]. All these published reports strongly sup-
port that tPBM facilitates the photo-oxidization of
© 2022 The Author(s). Published by IOP Publishing Ltd
J. Neural Eng. 19 (2022) 066013 S Shahdadian et al
Table 1. List of references that reported EEG responses to tPBM with related measurement and analysis parameters.
References Authors
Source of
tPBM
Location of
tPBM # of Channels PSD analysis
Graph-theory
based connectivity
analysis
[35]Berman et al
2017
Multiple LED
clusters
(1070 nm)
Whole head 19 No. It was
based on qEEG
analysis
No
[36] Ghaderi et al
2021
1 cluster of
LED (850 nm)
Right forehead 19 No. Yes; changes in
connectivity within
each of or between
two hemispheres
[37] Spera et al 4 clusters of
LED (830 nm)
Bilateral
frontal
19 Yes, with
topography
No
[16] Vargas et al
2017
Laser
(1064 nm)
Right forehead 19 Yes, but no
topography
No
[38] Wang et al
2021
Laser
(1064 nm)
Right forehead 64 Yes, with
topography
No
[39] Wang et al
2022
Laser
(1064 nm)
Right forehead 64 No. It was
based on
singular value
decompensa-
tion
No
[40] Zomorrodi
et al 2019
3 clusters of
LED (810 nm)
3 default mode
locations
19 Yes, with
topography
Yes; changes in
global connectivity
parameters only
Current study Laser
(1064 nm)
Right forehead 64 Yes, with
topography
Yes; changes of
connectivity in
global network
metrics and 10
nodal regions
mitochondrial CCO to boost the cellular metabolism
of neurons [2,2527]. The enhancement of mito-
chondrial activity is expected to increase cerebral
oxygen demand, blood flow, and blood oxygenation,
as reported in recent literature [19,2830]. One of
these studies suggested the modulation of vasomo-
tion in the cerebral vasculature stimulated by nitric-
oxide release as another effect of tPBM [30]. Fur-
thermore, several recent studies showed the ability
of tPBM of reversing the adverse effect of aging on
oxidative energy metabolism in rats [31] and improv-
ing the flow of cerebrospinal fluid at sleep in humans
[32,33].
However, the electrophysiological response of the
human brain to tPBM is not well studied and under-
stood. Table 1summarizes the recently published
articles that reported scalp electroencephalography
(EEG) responses to tPBM with the respective meas-
urement and analysis parameters. All studies utilized
either laser or LED clusters of NIR light and recor-
ded the electrophysiological responses using a 19-
channel or 64-channel EEG system. The table also
lists two major analysis methods, namely, power spec-
tral density (PSD) analysis and graph theory analysis
(GTA). Graph theory quantifies the specific features
of network architecture (topology). The outcome
of GTA can provide information on the anatomical
localization of areas responding to given stimuli or
human brain functional connectivity [34].
PSD is the most common method for analysing
EEG data and provides absolute power spectra of
EEG in the frequency range of 0.5–70 Hz. Frequency-
dependent PSD values facilitate a better understand-
ing of impacts of external stimuli, cognitive decline,
and certain brain disorders in the human brain
[4146]. Multi-channel EEG requires a multivariate
statistical analysis for spatial identification where sig-
nificant alterations of EEG signals occur. Accordingly,
cluster-based permutation testing (CBPT) is an estab-
lished method for minimizing type-I errors in EEG
multivariate analysis [47,48]. In this study, we util-
ized CBPT to identify topographical clusters of EEG
channels on the human scalp template, where tPBM
significantly altered frequency-specific EEG powers.
GTA enables to characterize functional networks
in the human brain [49]. In this method, a net-
work is a mathematical representation of a real-world
complex system and is defined by the composition
of nodes (vertices) and links (edges) between pairs
of nodes. The outcome of GTA measures represents
the functional integration, segregation, and central-
ity of the network, all of which can topologically
characterize changes in brain functional connectivity
in global and nodal regions [5052]. When GTA is
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J. Neural Eng. 19 (2022) 066013 S Shahdadian et al
used to analyze EEG data, the scalp locations of the
EEG electrodes represent the network nodes, and the
links among the electrodes represent the functional
connections between these nodes [51].
Both PSD and GTA-derived parameters can
provide instructive information on functional brain
networks in the resting state or under external neur-
omodulation. Because multi-channel EEG signals
contain rich information in the temporal, spectral,
and spatial domains, these pieces of information can
be grouped temporally and/or spectrally to visual-
ize brain activation and networks in topographical
clusters and regions [53,54].
Although existing publications (see table 1)
reported that tPBM enables alterations in EEG PSDs,
different tPBM protocols yielded sparse, incompar-
able findings. For example, only two studies showed
64-channel EEG responses to tPBM [38,39], without
quantification of tPBM-induced topological altera-
tions in brain connectivity. Thus, the focus of this
study was to investigate tPBM-induced modulations
of EEG functional connectivity by performing GTA
on a 64-channel EEG, followed by the quantification
of changes in brain connectivity in the global network
and 10 nodal regions.
2. Materials and methods
2.1. Participants
A total of 49 healthy human subjects (30 men and 19
women; 26 ±8.8 years of age) were enrolled from the
local community of the University of Texas at Arling-
ton. The experimental protocol was approved by the
Institutional Review Board of the University of Texas
at Arlington and complied with all applicable federal
and National Institute of Health (NIH) guidelines.
Written informed consent was obtained from each
participant before starting the first measurement.
Four participants were removed from the dataset
because of self-reported or observed sleepiness during
the measurement, resulting in 45 participants being
included for data analysis. The participants were
instructed to refrain from consuming caffeinated
drinks for at least three hours before each experiment.
2.2. Experimental setup and protocol
In this study, tPBM and sham experiments were per-
formed using a continuous-wave laser at 1064 nm
(Model CG-5000 Laser, Cell Gen. Therapeutics LLC,
Dallas, TX, USA), which was cleared by the Food
and Drug Administration. The laser was delivered to
each participant’s right forehead, with an aperture of
4.2 cm in diameter and a period of 8 min. A sham
experiment was performed with the laser power set to
be 0.1 W and the laser aperture covered with a black
cap. Table 2lists the key parameters of light deliv-
ery used in the study. Note that a penetration rate of
1%–2% was used to estimate light deposition on the
cortex [55,56].
Table 2. Parameters for 8 min tPBM and sham by a 4.2 cm
diameter laser at 1064 nm over the right forehead.
Stimulation
Irradiance
(mW cm2)
Dose density
(J cm2) Total Dose (J)
tPBM on
scalp
250 120 1662
tPBM on
cortex
2.5 1.20 16.62
Sham 0 0 0
Figure 1. A crossover experimental protocol for tPBM and
sham experiments (n=45) with simultaneous EEG
recording. The participants were at wakeful resting state
with eyes closed.
Our tPBM protocol was designed based on pre-
vious studies [3,1316,57]. The reason for using
the 8 min tPBM period was because it was effect-
ive in significantly improving human cognition. The
estimated dose density delivered to the human cortex
was within the range of positive or photo-stimulatory
responses (0.001–10 J cm2) [26,58].
Participants wore protective goggles throughout
the experiment. EEG data were collected using a
64-channel EEG instrument (Biosemi, Netherlands).
Each subject wore an EEG cap according to the stand-
ard 10–10 EEG electrode placement [59]. Electrode
gel was used for keeping the electrode impedances
below a pre-set threshold (<10 k). The recorded
EEG time series were directed to a computer. We fol-
lowed the EEG measurement procedures described in
[38,60].
The stimulation protocol (figure 1) consisted of
a 2 min baseline (pre), an 8 min stimulation (tPBM
or sham), and a 3 min recovery (post) period. The
EEG data were acquired at either 256 Hz or 512 Hz;
all 512 Hz data were down-sampled to 256 Hz dur-
ing data pre-processing. tPBM was delivered near
electrodes FP2 and AF8, under either sham or act-
ive conditions. The study was conducted in a single-
blind crossover design, with each subject completing
both sham and active tPBM experiments in a random
order, with a minimum five day interval between the
two experiments.
2.3. Overview of data processing steps
Each EEG dataset represented a 13 min time series
of 64 channels during both active and sham tPBM
experiments from 45 participants. Because the data
processing and analysis included multiple steps in this
study, we outline a flow chart in figure 2to guide
the reader through them easily. The five subgroups in
3
J. Neural Eng. 19 (2022) 066013 S Shahdadian et al
Figure 2. A data processing flow chart, including steps for (1) data pre-processing (blue boxes), (2) PSD-based analysis and
permutation tests to form power topographies (orange boxes), (3) graphical edge formation based on the ‘imaginary part
of coherence’ analysis (green boxes), (4) GTA-based assessment for global graphical connectivity metrics (pink boxes),
and (5) GTA-based assessment for nodal graphical connectivity metrics (gray boxes).
data processing are: (a) data pre-processing, (b) PSD-
based analysis to obtain frequency-specific power
topography, (c) graphical edge formation based on
the ‘imaginary part of coherence’ analysis, (d) GTA-
based quantification of global connectivity altered by
tPBM, and (e) GTA-based analysis to identify local
and nodal graphical metrics changed by tPBM.
2.4. Data pre-processing for EEG time series
EEGLAB (an open-source package) was used for data
pre-processing. First, EEGLAB’s ‘filtfilt’ function was
used to band-pass filter (0.5–70 Hz) the raw EEG data
with zero phase distortion, followed by a 60 Hz notch
filter to remove line noise. Next, each EEG series was
re-referenced by the voltage averaged over all the 64
channels. Robust PCA was then applied to identify
and remove significant signal artifacts and outliers
from EEG signals [61,62], followed by independ-
ent component analysis [63,64] to further remove
motion artifacts [65,66], such as eye movements, sac-
cades, and jaw clenching.
To quantify the dose-dependent responses of EEG
to tPBM, each artifact-free time series was divided
into four temporal sections: (a) the last minute of the
2 min baseline before the onset of stimulation (pre);
(b) the first 4 min stimulation period (Stim1); (c) the
second 4 min stimulation period (Stim2); and (d) the
first 2 min recovery (post).
2.5. EEG PSD and changes in power
We used Welch’s method to quantify EEG PSD [67].
Specifically, with the use of the ‘Pwelch function
(with a 4 sec window and 75% overlap [68]) in
EEGLAB, a PSD curve of artifact-free time series for
each EEG channel in each time section was calculated.
Frequency-specific PSD bandwidths were then selec-
ted to cover the delta (1–4 Hz), theta (4–8 Hz), alpha
(8–13 Hz), beta (13–30 Hz), and gamma (30–70 Hz)
bands. Next, the mean power change at each of the
five frequency bands (f), mPowerf, during each of
the three temporal segments (Stim1, Stim2, and post)
was normalized to the last minute of its baseline (pre),
as expressed [38]:
mPowerif=PSDfiPSDfpre
PSDfpre
×100%
=PSDfiPSDfpre×fband
PSDfpre ×fband
×100%
=PowerfiPowerfpre
Powerfpre
×100%(1)
where superscript f denotes the five frequency
bands, subscript i represents the three temporal
segments (Stim1, Stim2, or post), subscript ‘pre’
represents the baseline segment, fband denotes
the bandwidth of a chosen frequency band for
PSD calculations, and PSDiand PSDpre indicate
bandwidth-averaged PSD values. Note that mPower
is a relative value or percentage change in the
bandwidth-averaged power caused by tPBM or
sham treatment (see the first two orange boxes in
figure 2). To illustrate the difference in mPower
between the two conditions, we calculated the sham-
subtracted (ss) and tPBM-induced change in power
(mPowerss) at each electrode for each of the five
frequency bands within each of the three temporal
periods:
mPowerf
ss,i= mPowerf
tPBM,imPowerf
sham,i.
(2)
4
J. Neural Eng. 19 (2022) 066013 S Shahdadian et al
2.6. Statistical analysis for EEG power topography
Because EEG data at neighbouring time points and
spatial channels are highly correlated, it is necessary to
perform advanced statistical analysis to remove such
correlations and for multi-variable comparisons. For
this purpose, we utilized several functions (including
‘ft_freqstatistics’) available in the FieldTrip toolbox
[69,70] to perform CBPT for statistical comparisons
of changes in EEG power (i.e. mPowerss fas shown
in equation (2)) among the 64 electrodes in each of
the five bands within each of the three temporal peri-
ods. In principle, CBPT has two components. The
first is the cluster-forming algorithm, which converts
one high-dimensional observation into a quantifiable
summary of the cluster structure. The second one cre-
ates a surrogate null distribution, against which the
observed data are compared to obtain p-values [71].
Accordingly, we first grouped electrodes as
clusters within a given scalp distance (e.g. 4–5 cm),
followed by the identification of the EEG channels
whose mPowerssfvalues were significantly different
from zero for each electrode at a significance level
of 0.05. Second, statistical evaluation was performed
by taking the sum of the t-values for each cluster.
Third, the summed t-value was compared with a
null distribution. The null distribution for both
permutation tests and cluster-based correction was
obtained by randomly permuting the mPowerssf
values 1000 times (see the last orange box in figure 2).
The corresponding brain regions with modulated
powers were identified in this way.
2.7. Amplitude and phase decomposition of EEG
signal
For GTA-based connectivity quantification, we
determined the edges or links of a graphical network
between all pairs of EEG electrodes. Since correla-
tions between the phases or amplitudes of these EEG
channels are interpreted as functional connectivity
between these points [41,51], we performed amp-
litude and phase decompositions of the time series
for all the 64 channels. The amplitude and phase
of an EEG time-point can be represented as a com-
plex number [41,52]. Moreover, we utilized mul-
tiple tapers, namely, Slepian sequences, to taper the
EEG signal in the time domain before performing
the Fourier transform [72,73]. This part of the cal-
culation was conducted using the ‘ft_freqanalysis’
function within the FieldTrip toolbox [69].
2.8. Imaginary part of coherence as connectivity
measure
Coherence, a widely used connectivity measure, is a
frequency-domain function equivalent to the time-
domain cross-correlation function. The coherence
coefficient is a normalized quantity between 0 and 1
and is computed mathematically for the frequency of
ωas follows [41]:
cohxy (ω) =
Sxy (ω)
pSxx (ω)Syy (ω),(3)
where Sxx and Syy denote the power estimates of the
signals xand y, respectively, and Sxy represents the
averaged cross-spectral density term of the two sig-
nals. These terms were calculated using complex val-
ues obtained using the multitaper method.
Because of volume conduction in the human
brain, signals generated in one region can be detec-
ted by several electrodes, resulting in an artificially
high coherence value among these channels. To over-
come this effect, the magnitude of the operation can
be removed from equation (3), the imaginary part
of Sxy is considered, and the cross-spectral density
of the signals with a phase difference of 0 or 2π
is set to zero. This method is called the ‘imaginary
part of coherence’, which explicitly removes instant-
aneous interactions [41]. Studies have shown that this
method is excellent to minimize the volume conduc-
tion issue in EEG data analysis [74].
The pairwise connectivity values for all pairs of
electrodes (64 in this study) can be represented by
an n×n(i.e. 64 ×64) adjacency matrix, where n is
the number of nodes (i.e. 64 channels). The FieldTrip
toolbox facilitates the computation of the imaginary
part of coherence for all pairs of channels using the
‘ft_connectivityanalysis’ (the first two green boxes in
figure 2).
In this study, each temporal segment was divided
into 10 sec epochs, and the adjacency matrices gen-
erated for all epochs in each frequency band were
averaged for each of the three temporal segments and
five frequency bands for each subject individually.
These averaged matrices were binarized by varying
the sparsity level and used for GTA-based global and
nodal connectivity analyses, as described below.
2.9. Global and nodal graphical metrics selected for
GTA
The GTA enables the exploration of topological
changes in brain networks through pairwise func-
tional connectivity between channels. A network can
be characterized based on functional segregation,
functional integration, and centrality. Previous stud-
ies showed tPBM-induced alterations in graph meas-
ures of the brain network with different setups and
protocols [36,40]. However, these studies focused
on residual modulation in post stimulation with 19
channels.
In this study, we used GRETNA [75], a widely
used GTA toolbox, to quantify the global and nodal
graphical metrics of the human brain network for
individual subjects under active and sham tPBM in
four temporal segments and five frequency bands.
This step was repeated 19 times to assess the chosen
metrics under a sparsity range of 5%–95% with an
increment of 5% (see the last two green boxes in
figure 2).
5
J. Neural Eng. 19 (2022) 066013 S Shahdadian et al
Figure 3. A layout of ten clusters for the 64 EEG electrodes.
Circles represent electrodes; lines separate clusters. The ten
medial electrodes are grouped twice in left and right
regions. The overlapped regions are marked by the two
dashed lines. LF: Left frontal; RF: Right frontal; LC: Left
central; RC: Right central; LP: Left parietal; RP: Right
parietal; LT: Left temporal; RT: Right temporal; LO: Left
occipital; RO: Right occipital.
To examine tPBM-induced effects, three global
graphical measures were chosen for analysis: syn-
chronization (S), global efficiency (GE), and small-
worldness (SW). The group-level values for each
global measure at each sparsity level were statistically
compared between the active tPBM and sham condi-
tions using a paired t-test (pink boxes in figure 2).
Two previous publications showed alterations
only in global network metrics [40] and within each
hemisphere or between two hemispheres [36]. In this
study, our analysis quantified five nodal graphical
metrics, namely, nodal clustering coefficient (nCC),
nodal efficiency (nE), nodal local efficiency (nLE),
betweenness centrality (BC), and degree centrality
(DC). The respective definitions of graph metrics are
listed in supplementary material A.
2.10. Topographical clusters for nodal connectivity
Although GTA was performed on the 64-channel
EEG, resulting in tPBM-induced changes in nodal
network metrics, the 64 nodal locations were too dis-
persed to identify the cortical regions on the human
scalp. Thus, we focused on ten local sections accord-
ing to prefrontal, central, temporal, parietal, and
occipital regions [76]. Thus, 64 nodes were grouped
into ten clusters with 6–10 electrodes in each cluster
(figure 3).
At the subject level, each nodal graphical met-
ric within each cluster area was obtained by aver-
aging the specific metric over all the electrodes within
the respective region (for each of the three temporal
segments and five frequency bands). To compare the
changes induced by tPBM and sham, nodal measures
for each temporal segment were baseline-normalized
by subtracting the corresponding baseline (pre) val-
ues from those in each of the three time windows
(Stim1, Stim2, and post). Next, for each cluster
region, group-level (n=45) and baseline-subtracted
nodal metric values were compared between the act-
ive and sham conditions using paired t tests. To cor-
rect for multiple comparisons, false discovery rate
(FDR) correction was performed for ten regions with
a corrected significance level of 0.05 (see the two
vertical gray boxes in figure 2).
3. Results
3.1. Topographic changes in EEG power between
tPBM and sham stimulations
As described in sections 2.5 and 2.6, the baseline-
normalized values of mPowerf(see equation (1))
for each group of tPBM and sham conditions
among the three temporal segments (Stim1, Stim2,
and post) and in five frequency bands were cal-
culated. To demonstrate clear statistical differences
in mPowerfbetween the two stimulation con-
ditions, baseline-normalized and sham-subtracted
topographical maps of mPowerssf(%) values (see
equation (2)) over 64 channels were achieved, as
shown in figure 4, for all five frequency bands. In
addition, after CBPT for 64-channel statistical com-
parison, the electrode sites/clusters that were signific-
antly affected by tPBM are superimposed on the topo-
graphies in figure 4with denoting p< 0.01 and ×
denoting p< 0.05.
These results illustrate a significant, dose-
dependent increase in EEG rhythm powers at 8–13 Hz
and 13–30 Hz during the last 4 min of tPBM (Stim2).
Specifically, the increase in alpha mPowerss was
seen as two major clusters of channels in the bilateral
frontal and left parietal-occipital regions, whereas
the increase in beta mPowerss was mainly seen
as one cluster of electrodes in the central/parietal
region of the scalp. The enhanced alpha mPowerss
remained in the affected locations during the post-
tPBM period, whereas the significant increase in beta
mPowerss ceased during the recovery time. Fur-
thermore, delta power was reduced in the frontal, left
temporal, and occipital regions during tPBM, and in
the right frontal region during recovery.
3.2. Global graphical metrics of functional
connectivity altered by tPBM
Following the steps given in sections 2.72.9, adja-
cency matrices for all three temporal segments and
five frequency bands were generated. These matrices
were further binarized for different sparsity values,
resulting in the GTA-derived graphical networks. In
this study, we identified three global network met-
rics (S, GE, and SW) that were significantly altered by
tPBM with respect to the sham condition and only in
the beta band. As shown in figure 5, the three rows
illustrate the respective global metrics during Stim1,
6
J. Neural Eng. 19 (2022) 066013 S Shahdadian et al
Figure 4. Topographic maps of group-averaged (n=45), baseline-normalized, and sham-subtracted changes in mPowerss (see
equation (2)) in delta (1–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), beta (13–30 Hz), and gamma (30–70 Hz) bands during the first
4 min of tPBM (Stim1), second 4 min of tPBM (Stim2), and post tPBM period. Also, statistical results after the cluster-based
permutation testing are superimposed in each topographical map, showing significant differences in mPower between the
tPBM and sham stimulations during respective three time segments and in five frequency bands with corrected significance levels
of p< 0.05 (×) and p< 0.01 ().
Figure 5. Three GTA-derived global graphical metrics,
namely, synchronization (the 1st column), global efficiency
(the 2nd column), and small-worldness (the 3rd column),
of the EEG brain network in the beta band (13–30 Hz)
under both active tPBM and sham stimulation during
Stim1 (the 1st row), Stim2 (the 2nd row), and the post
period (the 3rd row). In each panel, the yaxis denotes
respective metric values while the xaxis presents sparsity
values with an increment of 5%. The grey bars mark
sparsity values at which the corresponding graphical
metrics were altered significantly by tPBM with respect to
sham based on paired t-tests (p< 0.05).
Stim2, and the post period under both active and
sham stimulation.
These results clearly show that tPBM significantly
reduces the global synchronization, GE, and SW of
the network connectivity of the human brain. Spe-
cifically, significant decreases in synchronization and
GE occurred during Stim1 and the recovery period
with more sparsity values, while a significant reduc-
tion in SW appeared in Stim2 with more sparsity
units. We also confirmed that there was no signific-
ant difference between the pre-stimulation baselines
under tPBM and sham conditions for any of the three
global network metrics.
3.3. Nodal graphical metrics of functional
connectivity altered by tPBM
After performing the analysis steps given in
sections 2.9 and 2.10, cluster-averaged, baseline-
subtracted values for each of the five nodal graph-
ical metrics (i.e. nCC, nE, nLE, BC, and DC) were
obtained for each of the ten spatial clusters under
both tPBM and sham conditions. After performing
paired t-tests with FDR correction for ten spatial
clusters (i.e. p< 0.05, FDR corrected), we identified
the clusters whose nodal metric values were signi-
ficantly altered by tPBM for each of the five met-
rics at all three temporal periods and only in the
beta rhythm band. Topographical representations of
the results for the five nodal metrics are shown in
figure 6.
Based on figure 6, we made the following obser-
vations. (a) During Stim1, significant increases in nE,
BC, and DC were observed in the right frontal region
near the tPBM stimulation site. (b) During Stim2
and post stimulation, significant changes occurred in
the bilateral frontal regions for all five nodal met-
rics. More specifically, tPBM significantly decreased
the clustering coefficient and nLE, whereas stimu-
lation significantly increased the other three nodal
metrics. (c) Combined temporal and spatial results
revealed that both nE and DC were initially enhanced
7
J. Neural Eng. 19 (2022) 066013 S Shahdadian et al
Figure 6. Comparative topographical maps of ten-Cluster-distributed nodal network metrics at the beta band (13–30 Hz). The
comparison was made between tPBM and sham stimulation conditions for each of the five nodal metrics, namely, the clustering
coefficient (the 1st column), nodal local efficiency (the 2nd column), nodal efficiency (the 3rd column), betweenness centrality
(the 4th column), and degree centrality (the 5th column) of the EEG brain network during Stim1 (the 1st row), Stim2 (the 2nd
row), and the post period (the 3rd row). LF: Left frontal, RF: Right frontal, LC: Left central, RC: Right central, LP: Left parietal,
RP: Right parietal, LT: Left temporal, RT: Right temporal, LO: Left occipital, RO: Right occipital. Red color represents
tPBM > sham; blue color indicates tPBM < sham with p< 0.05 (FDR corrected).
by tPBM in the right frontal region during Stim1,
followed by expansion of this enhancement to the
contralateral side during Stim2, which persisted dur-
ing the post-tPBM period. (d) In the case of BC,
unilateral enhancement in the right frontal region
remained during the entire stimulation time (Stim1
and Stim2) and then expanded to the contralateral
side in the post. (e) On the other hand, during Stim2
and post-stimulation, significant decreases occurred
in the bilateral frontal regions for the nCC and nLE.
(f) During the same time periods for the same two
metrics (nCC and nLE), decreases were observed in
the left parietal and occipital regions. (g) Moreover,
the left temporal region showed a reduction in nE and
BC only for Stim2. (h) The only significant modula-
tion in the right occipital region was a decrease in BC
in Stim2.
4. Discussion
In section 3, we describe the clusters and regions
on the scalp where tPBM modulates EEG oscillation
powers and GTA-based EEG beta network connectiv-
ity. In this section, we will interpret our observations,
compare our results with previous studies, and associ-
ate the neurophysiological changes in different brain
regions with behavioral improvement by tPBM that
has been reported by others [3,11,1317,57].
4.1. tPBM-induced alterations on EEG m Power
in clusters of electrodes
As shown in figure 4, under the eyes-closed resting-
state condition, tPBM significantly increased the
power of alpha oscillations in clusters over the bilat-
eral frontal, left parietal, and left occipital regions, as
well as the beta power over the bilateral central and
parietal regions during the second 4 min of stimula-
tion. These observations agree with previous reports
on eyes-open tPBM experiments [60,77].
A significant increase in alpha power over the
frontal-parietal regions clearly confirmed the abil-
ity of tPBM to neuromodulate the frontoparietal
network, which is an executive network facilitating
rapid instantiation of new tasks [78]. It is reported
that alpha rhythm is associated with awareness [79]
and cognitive functions, such as memory encoding
and attention [8082]. The same experimental pro-
tocol with a 1064 nm laser was used previously and
demonstrated a significant improvement in human
cognitive performance [3,1315,57]. Moreover, the
presence of stronger beta waves has been linked to
better cognitive ability, as reported in several studies
[83,84]. Thus, the beneficial outcome of frontal
tPBM in human cognition can be, at least partially,
attributed to its significant modulation of electro-
physiological alpha and beta powers in the frontopari-
etal network. In addition, we attributed the reduction
8
J. Neural Eng. 19 (2022) 066013 S Shahdadian et al
in delta power in the channel clusters during tPBM to
the sensation of laser-induced warmness in the fore-
head skin [38].
4.2. tPBM-induced alterations in global measures
of functional network in beta band
As shown in figure 5, tPBM significantly changed
three global graph measures, namely, synchroniza-
tion, GE, and SW, in the beta wave only. We discuss
each of these changes as follows.
Our observation that brain network synchroniz-
ation in the beta band was significantly reduced dur-
ing Stim1 and recovery agrees with a recent study that
reported the effects of tPBM on brain network syn-
chronization with 850 nm LEDs [36]. In addition, a
behavioral study attributed a decrease in synchron-
ization in the healthy human brain to awareness and
cognitive processing [85].
Similarly, the GE was significantly reduced by
tPBM compared with sham during Stim1 and post.
This reduction indicates a decrease in brain net-
work integration, which may imply less efficient or
more complex information paths in the network. In
other words, tPBM may increase the energy and wir-
ing costs of information flow owing to the trade-
off between network efficiency, energy, and wiring
costs [86,87]. This could be an indicator of increased
brain complexity related to higher cognitive function
[88]. This observation supports the expected benefit
of tPBM, namely, the beneficial effects of tPBM on
cognitive improvement.
SW is calculated as the ratio of normalized integ-
ration to normalized segregation [50]. Thus, the
reduction in this metric could be attributed to a sig-
nificant reduction in global integration (as reflected
by a reduction in GE) and/or a significant increase
in global segregation of the brain network caused by
tPBM. These observed significant effects of tPBM on
SW taking place only in Stim2 could result from the
resistance of resting-state networks against changes in
network composition as well as the dose-dependent
nature of tPBM-induced effects on neural activity [89,
90]. However, a possible explanation for the lack of
significant alterations in synchronization and GE in
Stim2 could be the high variability in the functional
topography of the frontoparietal network [78].
In addition, the observation that tPBM altered
only the beta-wave oscillation in the EEG graphical
network was in agreement with other studies [36,49].
Several studies have shown the role of the beta band in
different brain networks [91] and cognitive functions
[92,93].
4.3. tPBM-induced alterations in nodal graphical
measures in beta band
Significant reductions in nCC and nLE in bilat-
eral frontal regions and in the left parietal and left
occipital regions during Stim2 and post implied that
the clusters of nodes in these regions of the network
became less segregated during the 2nd 4 min and post
period of tPBM. In other words, tPBM facilitated less
separation and more integration of nodal graphical
connectivity. Consistently, nE (reflecting nodal integ-
ration) increased in the right frontal region in the
beginning of tPBM. This increase indicates enhanced
integrity of the nodes over this region in the informa-
tion flow [94] and parallel information transfer. Fur-
thermore, during the last 4 min of tPBM, the bilat-
eral frontal regions showed an increase in integration
into the functional network, while the integrity of the
left temporal region in the network was significantly
reduced. This phenomenon implies that tPBM stimu-
lated more network integration at the beta rhythm in
the frontal regions, with the cost of reducing network
integration in the left temporal segment/cluster.
BC represents the fraction of all shortest paths
in the network that pass through a particular cent-
ral node [95]. A large value of BC means a large
impact of this central node on information flow over
the network. Also, DC quantifies the number of links
from nodes in a specific region to other nodes in
the same or other regions [50]. Increases in both
BC and DC in the frontal region during and post
tPBM suggested that the frontal regions became more
prominent in connecting disparate parts of the net-
work. The enhancement of BC and DC revealed that
these cortical regions could be prominently stimu-
lated by tPBM for more information connections at
beta oscillations. It has also been reported that a work-
ing memory task during the encoding phase triggers
similar increases in DC over the frontal regions of the
beta band [93].
Combining all these observations, we concluded
that tPBM facilitated a reduction in local segregation,
increases in nodal integration and centrality of frontal
regions, and the growth of connection links between
nodes in these frontal regions compared to other
regions. These results agree with the observed changes
in the flow of information reported in a tPBM-evoked
causal connectivity study [96].
4.4. The role of the beta band in tPBM-induced
network modulation
The alpha and beta powers of the human brain, espe-
cially in the frontoparietal network, are believed to be
related to cognitive functions, such as memory encod-
ing and attention [8082]. Our observations clearly
demonstrated that tPBM increased the alpha and beta
powers in the frontal-central-parietal regions, indic-
ating the underlying association between tPBM and
the enhancement of human memory.
However, our results showed that tPBM altered
EEG graphical network metrics only in the beta band,
which was consistent with the results given in [36].
9
J. Neural Eng. 19 (2022) 066013 S Shahdadian et al
According to [91], beta oscillations in the prefrontal
region appear to serve as short-term memory execut-
ors and focus enhancers during executable tasks. In
addition, the beta rhythm in the temporal lobe plays
an important role in long-term memory retrieval
[97]. Memory retrieval starts in the temporal lobe,
passes through different parts of the neocortex, and
stops in the prefrontal cortex [91]. There is always a
balance in the information flow in this order, even
during the resting state. We speculated that tPBM
enables neuromodulation of beta oscillations and the
corresponding network connectivity globally across
the scalp and regionally in several nodal regions. The
significant modulation of beta-wave connectivity in
the human brain may be an underlying association
between tPBM and the enhancement of human cog-
nition. This speculation may be validated through
PET imaging using fluorodeoxyglucose [98].
4.5. Comparisons to two other publications
As shown in table 1, only two recent studies repor-
ted tPBM-induced modulations of global network
metrics [40] and alterations in brain connectivity
between the two hemispheres [36]. It would be help-
ful to compare the results from the two studies with
those found in this study. Detailed summaries and
comparisons are given in supplementary material B.
4.6. Two opinions on basic mechanism of tPBM
There is a relatively unresolved debate regarding the
basic mechanism of action of tPBM. One side of
the debate states that a red or NIR photon can
photo-dissociate nitric oxide (NO), a molecule that
may inhibit CCO by noncovalent binding [99,100].
This view emphasizes the greater effects of tPBM
on diseased/damaged cells because unhealthy cells
are more likely to have inhibitory concentrations of
NO. On the other hand, the other opinion high-
lights tPBM-induced effects on CCO, which stim-
ulates ATP production by increasing mitochondrial
membrane potential and oxygen consumption [26,
58]. This view enables to explain the tPBM-induced
augmentation of human cognition in healthy humans
besides in patients with brain disorders [26,58,101].
This side of opinions has been supported by several
publications [58], and now by two other independent
studies that also reported significant improvement of
working memory in healthy young [102] and older
adults [103] by repeated tPBM. However, the two
opinions on the basic mechanism of tPBM have coex-
isted for years, without one outweighing the other.
Further confirmation of each remains to be explored
in future studies.
4.7. Limitations and future work
First, the international 10–10 electrode placement
system in this study was not strictly followed on
the human head because a clear area with a 4.2 cm
diameter was needed for tPBM light delivery. The
EEG cap was shifted 1–2 cm backwards. Second, our
power spectral and connectivity analyses were per-
formed in the sensor space. Source space analysis
can be conducted to observe cortical and subcor-
tical regions in the brain that are affected by tPBM.
Third, the current study was based on EEG sig-
nals of the tPBM-treated human brain in the resting
state. Concurrent assessments of changes in cognit-
ive enhancement and brain connectivity after tPBM
would provide quantitative correlation and associ-
ation between functional connectivity and behavioral
effects of tPBM.
As for future work, there is a lack of systematic
studies on the optimization parameters of tPBM, such
as the wavelengths used, light irradiance, stimula-
tion dose, and sites, as well as the effective period
after stimulation. In particular, tPBM has a hormetic
dose response, which is characterized by stimulation
of a biological process at a low dose and inhibi-
tion of that process at a high dose [26,58]. Namely,
photo-stimulatory or photo-inhibitory effects occur
with low (0.001–10 J cm2) and high (>10 J cm2)
optical energy (dose) density [104106]. However,
the documented dose range for positive responses
results from in vitro experiments and is quite broad
(0.001–10 J cm2). It is difficult to select an optimal
irradiance for non-invasive human treatments with
tPBM. Accordingly, more research is needed with
both healthy humans and selected populations of
patients before tPBM becomes an effective device to
treat patients with brain disorders and for healthy
aging in the rapidly growing aging population.
5. Conclusion
In this study, we utilized three analytical steps to
identify the electrophysiological effects of tPBM in
a healthy human brain. First, power spectral ana-
lysis revealed that alterations in EEG spectral power
were mainly present in the alpha and beta bands of
the fronto-central-parietal regions. Second, a topo-
logical approach, GTA, facilitated findings on signi-
ficant modulation of the EEG beta rhythm in the
information path and enhancement of the brain net-
work complexity at the global network level dur-
ing and after the stimulation. Finally, assessment of
the nodal measures of the network at the regional
and cluster levels confirmed that tPBM had a major
effect on frontal and parietal clusters in the beta band.
The information paths were enhanced during and
post tPBM in prefrontal regions near the stimula-
tion site. Further studies are needed to better under-
stand the relationship between tPBM-induced altera-
tion of brain networks and improvement in human
cognition if tPBM is to be developed as a useful
tool for treating patients with brain disorders and
supporting healthy aging in the aging population
worldwide.
10
J. Neural Eng. 19 (2022) 066013 S Shahdadian et al
Data availability statement
The data that support the findings of this study are
available upon reasonable request from the authors.
Funding
This work was supported in part by the National Insti-
tute of Mental Health at the National Institutes of
Health under the BRAIN Initiative (RF1MH114285).
Conflict of interest
The authors declare that they have no affiliations with
or involvement in any organization or entity with any
financial interest in the subject matter or materials
discussed in this manuscript.
ORCID iD
Hanli Liu https://orcid.org/0000-0002-9312-5691
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