The EEG Response to Pulsed Forehead Photobiomodulation: Dependence on Wavelength and Frequency
Poster No:
45
Submission Type:
Abstract Submission
Authors:
Alicia Mathew1, Hannah Van Lankveld2, Joanna Chen2, Jean Chen3
Institutions:
1Baycrest Health Sciences, Waterloo, Ontario, 2University of Toronto, Toronto, Ontario, 3Rotman Research Institute, Baycrest, Toronto, Ontario
First Author:
Co-Author(s):
Introduction:
Transcranial photobiomodulation (tPBM) is a treatment that delivers near-infrared (NIR) light through the brain to modulate neural oscillations, enhancing brain function. [1] Uncovering a link between NIR light properties and the strength of neural responses will provide critical insights into the mechanisms of light-brain interaction and lead to more optimized and targeted therapy. Prior work [2] shows increased minute-wise EEG alpha (ɑ) and beta (β) band power with 1064 nm tPBM but gamma (γ) band response, associated with high-level cognitive function, remains understudied. Our study investigates the effects of 808 and 1064 nm tPBM, pulsed at 10 and 40 Hz, frequencies corresponding to α and γ rhythms, respectively, on α and γ EEG power to uncover wavelength and frequency specific neural responses.
Methods:
EEG data were recorded using a 256-channel Magstim system from 35 healthy subjects (17F, age 20-39) during eyes-open resting-state. Subjects were randomly assigned to one of three protocols, each consisting of four tPBM scans with unique wavelength-frequency combinations. Each subject received two scans at 808 nm and two at 1064 nm, delivered either all at 10 Hz, all at 40 Hz, or an even mix of both. The NIR laser was applied to the right forehead at power densities of 100, 150, or 200 mW/cm² over consistent surface area. The stimulation paradigm was [4-min off; 4-min on; 4-min off]. Preprocessing, artifact removal, and independent component analysis were conducted in EEGLAB. Band power was computed in 1-minute epochs as in [2] and using cluster-based permutation testing and general linear modelling, electrodes were identified as significant based on a cluster-wise p-value < 0.05, with their t-statistics reflecting the direction (positive or negative) of response. Power changes are tested for significance relative to the pre-stimulus baseline and then averaged across all electrodes with significantly altered power across all datasets.
Results:
Both temporal (Figure 1) and spatial (Figure 2) profiles show that significant changes in band power from baseline varied with wavelength and frequency. While past studies show post-stimulation increases in α, β, and γ power [2], [3], [4], [5], our real-time results reveal more complex dynamics during stimulation. At 808 nm-10 Hz, ɑ-power increases in left frontal and central regions during minutes 5-8, while γ-power increases in frontal regions and decreases in central areas. For 808 nm-40 Hz, ɑ-power exhibited lower increases while γ-power endured the largest bidirectional change across frontal and central areas. At 1064 nm-10 Hz, the right temporal and parietal regions see consistent rise in ɑ-power with a rise and fall in γ-power. The 1064 nm-40 Hz condition produced the least ɑ-power changes during stimulation but we see sustained bidirectional γ-power modulation, slightly less than with 10 Hz. There was no significant dependence on power density.
·Figure 1
·Figure 2
Conclusions:
This study demonstrates significant increase and decrease in EEG power due to pulsed PBM as well as the importance of wavelength and frequency selection. The 808 nm wavelength evokes the strongest and most widespread changes, potentially reflecting differences in tissue penetration. Also, 40 Hz does not alter ɑ-power while 10 Hz drives both ɑ- and γ-power. Spatial dynamics suggest that prefrontal stimulation may propagate to posterior nodes of the default-mode network, as reflected in γ-power changes. While ɑ-power increases are localized in frontal-central regions, γ-power changes spread across wider networks, suggesting that tPBM engages distinct cortical networks beyond the stimulation site depending on stimulation parameters, highlighting its potential as a precise, non-invasive tool for neuromodulation.
Brain Stimulation:
Non-Invasive Stimulation Methods Other 1
Modeling and Analysis Methods:
EEG/MEG Modeling and Analysis
Novel Imaging Acquisition Methods:
EEG 2
Keywords:
Electroencephaolography (EEG)
NORMAL HUMAN
Other - Neuromodulation
1|2Indicates the priority used for review
Abstract Information
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Please indicate below if your study was a "resting state" or "task-activation” study.
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Was this research conducted in the United States?
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.
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[2] X. Wang, "Transcranial photobiomodulation with 1064-nm laser modulates brain electroencephalogram rhythms," Neurophotonics, pp. 6(2), 025013, 2019.
[3] R. Zomorrodi, G. Loheswaran, A. Pushparaj and L. Lim, "Pulsed Near Infrared Transcranial and Intranasal Photobiomodulation Significantly Modulates Neural Oscillations: a pilot exploratory study," Scientific Reports 9, p. Article 6309, 2019.
[4] S. Shahdadian, "Neuromodulation of brain power topography and network topology by prefrontal transcranial photobiomodulation," Neural Eng, p. 19 066013, 2022.
[5] X. Wang, H. Wanniarachchi, A. Wu and H. Liu, "Combination of Group Singular Value Decomposition and eLORETA Identifies Human EEG Networks and Responses to Transcranial Photobiomodulation," Front. Hum. Neurosci, 2022.