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Category Archives: sfNIRS2024-Session-3
Su-092-Towards automated bad channel detection in functional near-infrared spectroscopy
With more channels per device, larger cohorts, and the need for standardized processing procedures, thresholding-based detectors are becoming widely employed in fNIRS to identify unreliable signals. However, despite their potential, un- and semi-supervised detection have yet to be utilized for bad channel detection, and a comprehensive assessment is lacking. We developed three novel detectors and compared them with established methods, un- and semi-supervised techniques. Machine learning approaches that utilize partially rated data, particularly the here developed NiReject, achieved superior performance. This may pave the way for improved, automated quality control in fNIRS and artificial intelligence-based developments for such control. Continue reading
Su-001-Neural Correlates of Multisensory Enhancement during Emotional Speech Perception in Bilingual and Monolingual Adults
Language experience can impact how we process faces (visual cues) and voices (auditory cues) during social interactions. This study explores the influence of spoken-language bilingualism on audiovisual integration during emotional speech perception. Bilingual and monolingual adults will classify emotional speech stimuli expressed through auditory and visual modalities whilst cortical activation is measured from temporal and occipital cortices using the Shimadzu LabNIRS system. It is predicted that the benefit (both behavioral and cortical) of multimodal input, over unimodal input, is greater in bilingual than monolingual adults. Results will elucidate how language experience shapes cortical mechanisms underlying this important element of socio-emotional communication. Continue reading
Su-012-Comparison of Functional Intraoperative Optical and Pre-operative Magnetic Resonance Imaging in Resting-state and Task-based Procedures
Functional Magnetic Resonance Imaging (fMRI) and Functional Optical Imaging (fRGB) are method of identifying functional brain region, preoperatively and intraoperatively, respectively. Each method contains two procedural modes: task-based and resting-state. Unlike task-based imaging, resting-state imaging does not require patient intervention which may facilitate functional identification during neurosurgery. Thus, we evaluated the capability of identifying brain function using intraoperative resting-state fRGB by comparing the functional areas to those identified using fMRI. For nine patients with gliomas, the fMRI data was projected onto the fRGB optical space, and we compared the activated regions using DICE and overlap coefficients. Continue reading
Su-062-Cortical activity during painful and non-painful stimulation over four lower limb body sites: a functional near infrared spectroscopy study
Functional near-infrared spectroscopy (fNIRS) holds potential utility as a measure of neural correlates of pain. However, most studies have focused on upper limb stimulation. In this study, we utilized fNIRS to observe cerebral oxygenated hemoglobin changes in 16 healthy participants undergoing painful/non-painful electrical stimulation of bilateral groins and knees. Results revealed prefrontal cortex deactivation during painful stimulation, notably left groin. Varying lower limb stimulation yields distinct activation patterns in primary somatosensory cortex, providing evidence for cortical pain processing and fNIRS feasibility in studying pain mechanisms across lower limb regions. Continue reading
Su-050-Deep Learning-based prediction of superficial layer depth and optical properties in fNIRS
Superficial layer thickness and optical properties often confound the ability of fNIRS to provide accurate prediction of the derived hemodynamic response of the brain from measurements. A methodology based on Deep Learning is presented, trained on noise-added simulated data, demonstrating accurate recovery of the unknown depth and optical properties of two layer phantoms, using experimental measurements. It is shown to out-perform classical optimization approaches, demonstrating the advantages of data-driven approaches for parameter recovery. Continue reading
Su-005-Impacts of Stress in Neural and Cardiorespiratory Responses Induced by Time-Restricted Arithmetics
Stress at higher intensities can impair cognitive function and alter cardiorespiratory dynamics. In this work, we employed fNIRS and external physiological monitors to investigate how time restriction affects human physiology during an arithmetics test in 60 participants. By quantifying brain activity and systemic physiology alterations to baseline, we found that (1) time restriction elicited bigger changes in cardiorespiratory parameters, and (2) fNIRS brain activity maps were more local during time restriction. Continue reading
Su-025-Fiber-less speckle contrast optical spectroscopy system using a multi-hole aperture method
A multi-hole aperture fiber-less SCOS system is proposed. In conventional SCOS systems, there exists an upper limit on the aperture size, since the minimum speckle size must be greater than the Nyquist pixel rate. Consequently, obtaining high light intensity under long source-detector distance is a challenge. In the solid phantom experiment, the proposed multi-hole aperture SCOS system exhibits higher intensity and contrast compared to conventional single-hole aperture SCOS system. In both two-layer liquid phantom and in-vivo arm-cuff extension experiments, the proposed system exhibits higher sensitivity with respect to the blood flow. Continue reading
Su-043-Feasibility of Simultaneous Near Whole-Head fNIRS and Physiological Measurements
Non-cerebral and physiological systemic activity contaminates fNIRS data and could account for the considerable across-subject variability reported in the literature. Aiming to evaluate global systemic physiology's influence, we have designed an fNIRS task battery combined with simultaneous peripheral physiological measurements. Preliminary data quality results validate the feasibility of this multimodal setup toward a larger dataset to be published and openly available for the fNIRS community. Continue reading
Su-048-A hardware-based, multi-channel, real-time, motion artifact detection technique for fNIRS/DOT systems
We propose a hardware-based, multichannel motion artifact (MA) detector for real-time functional near-infrared spectroscopy/diffuse optical tomography (fNIRS/DOT) applications, implemented on a field programmable gate array (FPGA). This system enhances traditional HomER2-based MA detection, offering improved sensitivity from 83.12% to 91.68%. Capable of processing MAs across 12 channels in just 2.75 ms, our FPGA design supports potential enhancements through deep learning integration. This advancement is especially relevant for future wearable devices, brain-computer interfaces (BCI), and neurofeedback applications, enabling essential real-time analysis. Continue reading
Su-033-The Impact of Extensive Reading on Listening Comprehension: A Functional Near-Infrared Spectroscopy (fNIRS) Study of Frontal Lobe Activation
This study explores how Extensive Reading (ER), used in second language learning, affects listening comprehension. While ER's initial benefits are often seen in listening skills, the underlying mechanisms remain unclear. We investigated this by measuring cerebral blood flow in ER and non-ER groups during a listening task. Findings show the ER group's superior task accuracy and reaction times correlate with distinct brain activity patterns, emphasizing ER's cognitive advantages in language learning. The ER group exhibited significantly higher brain activation in BA46, corresponding to the DLPFC, which is related to working memory. Continue reading