Poster No:
71
Submission Type:
Abstract Submission
Authors:
Boeun Choi1, Ukeob Park1, DeaKeun Kim1, Seung Wan Kang1
Institutions:
1iMediSync, Inc., Seoul
First Author:
Co-Author(s):
Introduction:
Mild cognitive impairment (MCI) is a preliminary stage of dementia characterized by a decline in cognitive function compared to the same age group, yet with retained abilities to perform activities of daily living. Early diagnosis and treatment during this stage can slow down the progression of dementia. Near-infrared (NIR) LED therapy is being researched for its potential to improve brain nerve function through light stimulation. NIR therapy targeting the brain is known to promote the activation of mitochondria in brain cells within the cerebral cortex, facilitating increased blood flow and simultaneously enhancing neurological activity. This study conducted LED therapy on participants diagnosed with MCI at the community level and investigated any changes in the EEG signal-based brain network. As previous studies have indicated, particularly about brain network, small-worldness is identified as an indicator that can differentiate between dementia, MCI, and the normal control group. Among the frequency bands, the small-worldness value in the theta band has been shown to be higher in MCI patients compared to dementia patients, and higher in healthy group compared to MCI patients. These findings demonstrate the potential utility of the small-worldness in distinguishing between these cognitive states.
Methods:
A total of 48 participants, consisting of 11 males and 37 females, with an average age of 74.26, took part in the experiment. The experiment spanned 8 weeks, and to assess the effects of the experiment, brain networks were calculated based on EEG measurements at both baseline and the conclusion of the 8-week period. The equipment used in this experiment was the dry type, 10-20 system EEG measurement device (iSyncWave) developed by iMediSync, the organization conducting this study. This device is equipped with near-infrared LED diodes with a wavelength of 850nm on each electrode, allowing for the provision of individualized therapy protocols tailored to the participant's EEG patterns. The calculated features were based on a network with 68 regions of interest (ROIs) using the Desikan–Killiany atlas. Features were calculated for different frequency bands of EEG signals, including Theta (4~8Hz), Alpha1 (8~10Hz), Alpha2 (10~12Hz), and Beta1 (12~15Hz). The brain network features examined included characteristic path length and small-worldness. Characteristic path length is an indicator of the efficiency of information integration in the network. Small-worldness is a feature describing the efficiency of network structure.
Results:
After the therapy, there was a noteworthy reduction in characteristic path lengths across all frequency bands (Theta: 0.001<p≤0.01, Alpha1: 0.01<p≤0.05, Alpha2: 0.001<p≤0.01, Beta1: 0.0001<p≤0.001). Moreover, small-worldness significantly increased after treatment in all frequency bands (Theta: 0.0001<p≤0.001, Alpha1: 0.01<p≤0.05, Alpha2: 0.0001<p≤0.001, Beta1: 0.001<p≤0.01).
Conclusions:
Through personalized LED therapy, we examined brain network features, including characteristic path length and small-worldness. Characteristic path length is known to increase when connections between brain regions are disrupted. Therefore, the observed decrease in characteristic path length after therapy can be considered a result of improved overall brain network integration. Furthermore, small-worldness significantly increased after therapy, with a trend towards values closer to 1. This tendency suggests an enhancement in the structural efficiency of the network. In particular, the increase in small-worldness in the theta band can be viewed as a positive change, considering previous research indicating that normal individuals exhibit greater small-worldness in the theta band compared to MCI patients. This is a pilot study of the impact of LED therapy. Future research will delve into quantitative EEG(QEEG) changes based on different types of LED therapy protocols and explore indicators of brain network across various frequency bands.
Brain Stimulation:
Non-Invasive Stimulation Methods Other 1
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 2
Keywords:
Electroencephaolography (EEG)
Other - NIR therapy; MCI; brain network; characteristic path length; small-worldness
1|2Indicates the priority used for review
Provide references using author date format
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[2] F. Vecchio et al. (2021), “Contribution of Graph Theory Applied to EEG Data Analysis for Alzheimer’s Disease Versus Vascular Dementia Diagnosis,” Journal of Alzheimer’s Disease, vol. 82, no. 2, pp. 871–879
[3] Y. He, Z. Chen, and A. Evans (2008), “Structural Insights into Aberrant Topological Patterns of Large-Scale Cortical Networks in Alzheimer’s Disease,” The Journal of Neuroscience, vol. 28, no. 18, pp. 4756–4766
[4] J. Tsai, J. Grutzendler, K. Duff, and W.-B. Gan (2004), “Fibrillar amyloid deposition leads to local synaptic abnormalities and breakage of neuronal branches,” Nature Neuroscience, vol. 7, no. 11, pp. 1181–1183