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Vi-011-Effects of rTMS and Cue Stimuli on Resting-State Functional Connectivity in Methamphetamine-Dependent Individuals
This research investigated repetitive transcranial magnetic stimulation (rTMS) treatment and drug-related cue stimuli’s effect on orbitofrontal cortex (OFC)-related resting-state functional connectivity (rsFC) in Methamphetamine (METH)-dependent individuals. Using fNIRS signals from healthy and METH-dependent individuals, pre- and post-rTMS treatment, METH-dependent individuals initially showed hyperexcitability, alleviated by rTMS. Healthy participants exhibited increased rsFC post-stimuli, contrasting with decreased connectivity in METH-dependent individuals, indicating inadequate craving suppression. Post-treatment, hyperexcitability decreased, with some connections resembling healthy patterns, suggesting rTMS efficacy in restoring inhibition under drug-related stimuli. These findings deepen understanding of addiction-related neural mechanisms and identify biomarkers for addiction discrimination and intervention efficacy assessment. Continue reading
Vi-029-Shedding light on Fibromyalgia: Developing a Machine-Learning-Based Diagnostic Tool Using fNIRS
This study develops a machine learning-based tool for diagnosing fibromyalgia (FM) using functional near-infrared spectroscopy (fNIRS). We recorded cortical activity from 36 FM patients and 33 age-matched controls, focusing on frontal and sensory-motor areas. Data was processed to remove artifacts and analyzed for connectivity and task-based features during rest and during stress. A convolutional neural network, trained on 85% of our dataset, achieved an 89% accuracy rate in diagnosing FM, identifying all FM patients accurately while misdiagnosing one control. This biomarker predominantly reflects frontal cortex activity, offering clinical utility and insights into the role of stress mechanisms in FM. Continue reading
Vi-023-The Utility of Continuous Cerebral NIRS Monitoring to Identify Hemodynamically Significant Patent Ductus Arteriosus in Extremely Premature Infants
In this retrospective study, we aimed to determine if cerebral NIRS oxygenation is associated with Hemodynamically Significant Patent Ductus Arteriosus (HSPDA). Using an Iowa PDA Score threshold of 8 points, cerebral NIRS values were significantly lower for infants with HSPDA between the 72nd – 84th HoL, and 120th – 132nd HoL, while marginal significance was found between the 84th – 96th HoL. Continue reading
Vi-022-Blood Pressure Prediction through FlexNIRS Monitoring during Carotid Endarterectomy
This study investigates Near-Infrared Spectroscopy (NIRS) photoplethysmography (PPG) as a noninvasive method to predict Mean Arterial Blood Pressure (MAP) during Carotid Endarterectomy (CEA), aiming to overcome the invasiveness of radial artery BP measurement. FlexNIRS data collected from nine CEA patients underwent preprocessing and feature extraction for MAP prediction using a Gaussian regression model. The model, incorporating heart rate and PPG features, demonstrated accurate MAP prediction (R2 = 0.82, 1.3±11 mmHg accuracy) across subjects. Results suggest NIRS-PPG as a potential noninvasive continuous BP monitoring solution during cardiovascular surgery. Continue reading
Vi-019-Two Types of Cognitive Processes of The Criminals Who Conceal Involvement of The Case Appears as Bimodal Peaks in Their Cerebral Hemodynamic Responses
The CIT is a criminal investigation method. We examined the relationship between temporally synchronized autonomic responses and cortical activation. Thirty of sixty participants committed a mock crime, and the others did not. Then, they performed the CIT task. As a result, in addition to the guilty-specific autonomic responses, we observed the distinct cortical activation patterns; (1) bimodal peaks for a crime-relevant question, (2) the greater activation of the right S/MTG and M/IFG. Moreover, the mean Δ[oxyHb] of 1st peak on the S/MTG and that of 2nd peak on the M/IFG were positively correlated with sympathetic and parasympathetic indices, respectively. Continue reading
Vi-018-Study on improvement of spatial resolution of topography
We propose to use three kinds of source-detector pairs with different distances to improve spatial resolution and reduce artifacts. The simulation results using a depth-selective filter algorithm show that surface signal can be reduced with minimum target signal deterioration, and the use of two different measurement signals allows to detect target signal of different optical transfer path. Continue reading
Vi-010-Analyzing mental concentration level with and without music using fNIRS-BCI
This study uses fNIRS-BCI and Sustained Attention to Response Task (SART) to examine how music affects mental concentration. Twenty-one participants had their prefrontal brain signals recorded during both music and non-music sessions. The findings indicate that thirteen subjects had increased concentration, as measured by SART performance and brain activation, while eight subjects had decreased concentration. In both conditions, statistical analysis verified significant difference in activation (p < 0.05). The overall result validates the hypothesis that brain concentration levels are increased while listening to music than without music. Continue reading
Vi-006-Channel Selection using Ant Colony Optimization for fNIRS Based BCI
The availability of fast and accurate fNIRS signals is crucial for the rehabilitation of disabled individuals. Signal processing and classification can be expedited and enhanced in accuracy by selecting channels with higher activation levels. In this study, we apply a meta-heuristic algorithm, Ant Colony Optimization (ACO), to fNIRS signals for channel selection. We compare the results with state-of-the-art methods such as the t-value and z-score methods. Our findings demonstrate that utilizing ACO for channel selection can significantly improve classifier accuracy. Continue reading
Vi-005-Analysis of Word Processing in a Child with Down’s Syndrome: An fNIRS-based Case Study
Abstract: Word processing plays a vital role in developing language, communication skills, and educational achievements. Yet, the understanding of how individuals with Down's Syndrome (DS) process words at the neural level is not thoroughly examined. This study seeks to fill this knowledge gap by using functional Near-Infrared Spectroscopy (fNIRS) through lexical tasks. Specifically, it explores how a child with DS processes nouns and verbs, aiming to uncover the neural mechanisms behind word processing. Initial results indicate the activation of Frontal and Temporal lobes with nouns prompting sharp neural responses, whereas verbs trigger extended cognitive engagement. Continue reading
Vi-028-Adjusted Meff for family-wise error rate in fNIRS data with a small sample size
Multi-channel fNIRS analysis often requires correction for family-wise error rate in null-hypothesis-significance testing. One of the plausible approaches is the Meff method, which balances Type I and Type II errors by considering inter-channel correlation. However, there is a concern about too liberal correction in the case of small sample size. In this study, we aimed to reevaluate the applicability of Meff method to fNIRS data with a small sample size, utilizing simulations. Consequently, a valid Meff can be derived by employing a typical exponential model. We demonstrated that the Meff approach remains effective. Continue reading