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Randomized Controlled Trial
. 2019 Apr 19;9(1):6309.
doi: 10.1038/s41598-019-42693-x.

Pulsed Near Infrared Transcranial and Intranasal Photobiomodulation Significantly Modulates Neural Oscillations: a pilot exploratory study

Affiliations
Randomized Controlled Trial

Pulsed Near Infrared Transcranial and Intranasal Photobiomodulation Significantly Modulates Neural Oscillations: a pilot exploratory study

Reza Zomorrodi et al. Sci Rep. .

Abstract

Transcranial photobiomodulation (tPBM) is the application of low levels of red or near-infrared (NIR) light to stimulate neural tissues. Here, we administer tPBM in the form of NIR light (810 nm wavelength) pulsed at 40 Hz to the default mode network (DMN), and examine its effects on human neural oscillations, in a randomized, sham-controlled, double-blinded trial. Using electroencephalography (EEG), we found that a single session of tPBM significantly increases the power of the higher oscillatory frequencies of alpha, beta and gamma and reduces the power of the slower frequencies of delta and theta in subjects in resting state. Furthermore, the analysis of network properties using inter-regional synchrony via weighted phase lag index (wPLI) and graph theory measures, indicate the effect of tPBM on the integration and segregation of brain networks. These changes were significantly different when compared to sham stimulation. Our preliminary findings demonstrate for the first time that tPBM can be used to non-invasively modulate neural oscillations, and encourage further confirmatory clinical investigations.

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Conflict of interest statement

Reza Zomorrodi and Abhi Pushparaj were advisors to the device manufacturer, Vielight Inc., and were compensated for their time. They had no other competing or conflict of interest, financial and non-financial. Genane Loheswaran is an employee of Vielight Inc. as the Research Manager and Lew Lim is the Founder & Chief Executive Officer who owns shares in Vielight Inc., and both have no other competing interest. All the authors declare that these interests had no influence on the results and discussion in the study.

Figures

Figure 1
Figure 1
Schematic diagram of study design. Twenty healthy participants randomized to receive either active or sham tPBM with a minimum 1-week washout period between the two visits. 10 minutes eye-closed rest EEG recorded pre and post of each intervention.
Figure 2
Figure 2
The Vielight Neuro Gamma in use. The stimulation modules consist of a Nasal Applicator, and a Head Set with four light emitting diode (LED) modules intended to be positioned over the hubs of the default mode network (DMN).
Figure 3
Figure 3
Non-parametric cluster-based permutation test comparing the rest EEG power spectrum between active and sham tPBM. Topographical maps are color-coded according to the permutation tests t-values. Clusters of electrodes with significant difference between the two conditions are marked in ‘+’ sign (p < 0.05 and αcluster = 0.01). (a) Difference between post and pre active tPBM. (b) Difference between post and pre sham tPBM. (c) Difference between pre active and sham tPMB. (d) Difference between post active and sham tPMB.
Figure 4
Figure 4
Influence of tPBM on resting-state electroencephalography. Box plot illustrates the median and range of power spectrum across all electrodes for each oscillatory frequency bands. (a) Effect of active tPBM on power spectrum pre (green line) and post (red line). (b) Effect of sham tPBM on power spectrum pre (green line) and post (red line). (c) Difference between Active and Sham tPBM: Change of power spectrum Post-Pre for active (red line) and sham (green line) tPBM. Active versus sham stimulation revealed significant lower alteration in delta and theta power and higher change in alpha, beta and gamma frequency bands.
Figure 5
Figure 5
Connectivity assessment using Clustering coefficient (CC). (a) Active tPBM caused index significantly changed CC for wide range of 45–80% sparsity levels in the alpha band, and 35–55% sparsity levels in the gamma band. (b) Sham tPBM did not caused significant change in CC index, but beta at 75, 82 and 90% of sparsity levels. Blue and red lines line indicate pre and post conditions, respectively. The gray lines indicate a significant difference (p < 0.01) at a certain sparsity level.
Figure 6
Figure 6
Connectivity assessment using the characteristic path length (CPL). (a) Active tPBM caused index significantly changed CLP in the alpha band for 40–55% of sparsity levels and the gamma band for 50–55% and 80–85%. (b) Sham tPBM did not cause any significant change in CPL index. Blue and red lines line indicates pre and post conditions, respectively. The gray lines indicate a significant difference (P < 0.01) at a certain sparsity level.
Figure 7
Figure 7
Connectivity assessment using Local Efficiency measure. (a) Active tPBM caused significant changes in network local efficacy mostly in the alpha band for 45–60% and 70–75% of sparsity levels, in the gamma band for 40–50% of sparsity levels, in the beta band for 80–85% of sparsity levels, and in delta and theta bands for 85% and 80% of sparsity levels, respectively. (b) Sham tPBM did not cause any significant change in the local efficacy except in the beta band for 80 and 90% of sparsity levels. Blue and red lines line indicate pre and post conditions, respectively. The gray lines indicate a significant difference (P < 0.01) at a certain sparsity level.
Figure 8
Figure 8
Connectivity assessment using Global Efficiency measure. (a) Active tPBM caused significant changes in network global efficacy in the alpha band for 50–60%, 75%, 85–90% of sparsity levels, in the gamma band for 15%, 50–60%, 70–75% and 90% of sparsity levels. (b) Sham tPBM did not cause any significant change in the global efficacy. Blue and red lines line indicate pre and post conditions, respectively. The gray lines indicate a significant difference (P < 0.01) at a certain sparsity level.

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