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Category Archives: sfNIRS2024-Session-0
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
Vi-033-fNIRS brain imaging at 1 month of age in the UK and The Gambia – a multi-paradigm approach
At the first fNIRS session of the Brain Imaging for Global Health (BRIGHT) (www.globalfnirs.org) at 1 months of age, we use a multi-paradigm approach while infants sleep, to investigate brain responses during presentation of a range of auditory stimuli. Our preliminary results show that infants developing in the UK and The Gambia (GM) present different response patterns to the same stimuli. We will investigate further these differences by studying the brain networks underpinning these responses from the functional connectivity (FC) data collected in the same sessions, and by incorporating contextual factors into the analysis. 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-032-Validity of visual processing assessed by fNIRS as a potential biomarker in Neuroscience: systematic evaluation of measure reliability
The temporal reproducibility of fNIRS signals is a crucial issue for establishing its validity as a potential biomarker of brain function. Here, our objective is to systematically evaluate the reliability of a newly standardized fNIRS procedure for measuring visual-evoked hemodynamic responses (vHDR) in the occipital cortex. To validate the consistency of the vHDR metric, we conducted a test-retest study involving a cohort of 50 healthy adults at three different time points. Additionally, we explored the circadian variability of the vHDR metric. Our findings reinforce previous literature highlighting the potential utility of fNIRS in the biomarker domain. Continue reading
Vi-009-Improving classification accuracy using 3D CNN for fNIRS based word generation task
Brain computer interface (BCI) techniques enables communication between brain and computer. Functional near-infrared spectroscopy (fNIRS) is one of the BCI data acquisition technique. In this work, fNIRS data for word generation tasks is represented as three dimensions, Gaussian and Wavelet transformations are applied on data to create a pool of the data to mimicking the top view of the BCI cap having sources and detectors. This data has rich amount of spatial and temporal features that is classified using 3D CNN model. Each optode value is linked with their neighbor’s empty spaces that increase the signal strength and improved accuracy up to 3%. 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-031-Motion Artifact Correction in preschoolers’ data: Comparison of five pipelines
Abstract: This study investigates motion artifact correction methods in preschoolers’ fNIRS data. Using QT-NIRS in the pre- and post-correction, we compared five different motion artifact correction methods using real data in preschoolers at the age of 2.5-4.5 years. We found significant improvements using Wavelet and Wavelet+TDDR corrections over the other methods. This study is the first to compare various pipelines for preschoolers’ data and to use QT-NIRS as an objective comparison of motion artifact correction methods. Continue reading