Functional dual-slope frequency-domain near-infrared spectroscopy data interpreted with two- and three-layer models.

Cardiac responses (e.g., heart rate changes) due to an autonomous response to sensory stimuli have been reported in several studies. This study investigated whether heart rate information extracted from functional near-infrared spectroscopy (fNIRS) data can be used to assess the discrimination of speech sounds in sleeping infants. This study also investigated the adaptation of the heart rate response over multiple, sequential stimulus presentations. fNIRS data were recorded from 23 infants with no known hearing loss, aged 2 to 10 months. Speech syllables were presented using a habituation/dishabituation test paradigm: the infant's heart rate response was first habituated by repeating blocks of one speech sound; then, the heart rate response was dishabituated with the contrasting (novel) speech sound. This stimulus presentation sequence was repeated for as long as the infants were asleep. The group-level average heart rate response to the novel stimulus was greater than that to the habituated first sound, indicating that sleeping infants were able to discriminate the speech sound contrast. A significant adaptation of the heart rate responses was seen over the session duration. The dishabituation response could be a valuable marker for speech discrimination, especially when used in conjunction with the fNIRS hemodynamic response.

Region of interest (ROI) determination is necessary when using functional near-infrared spectroscopy (fNIRS) data to detect brain activity. To extract ROIs from multiple fNIRS channels, we investigated the validity of applying decision mode analysis to the fNIRS dataset. This classifies a dataset into clusters with similar features. For each cluster, the dataset is decomposed into a mean vector and a linear combination of eigenvectors. Applying this to fNIRS signals, the mean vector can be used to represent change in hemoglobin (Hb), and the eigenvectors interpreted as a signal component constructing the arbitrary signal. Characterizing these vectors by correlating them with a theoretical model of brain function aids our understanding of where Hb changes occur and what type of Hb changes reflect brain activity in fNIRS data. Decision mode analysis of fNIRS data measured during viewing stereoscopic images identified ROIs around the right inferior frontal gyrus associated with attentional control, and frontal association area associated with decision on action and prediction. Our experimental results showed that information obtained from decision mode analysis can aid quantitative and qualitative ROI determination.

Functional near infrared spectroscopy (fNIRS) is non-invasive brain imaging techniques that detects the cortical activity by measuring the change in the concentration of oxy-hemoglobin and de-oxy hemoglobin. It uses near infrared light of two wave lengths, 760 nm and 830 nm. NIRS is emerging neuro imaging modality with high temporal resolution. The advantage of NIRS system over other neuro imaging modalities is low cost, portable, safe and somehow results in short period of time. The scalp remains intact throughout the experiment. In this study we present a method for identification of brain activity by using fNIRS data. The general linear model has been used in study with predicted blood oxygen level dependent (BOLD) response signal and its delayed versions. The normalized least mean square (NLMS) algorithm has been used for identification of unknown parameters in the model recursively. A one way t-test has been performed for the significance of results.

Comparison of near infrared spectroscopy with functional MRI for detection of physiological changes in the brain independent of superficial tissue

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Functional near-infrared (fNIR) spectroscopy is a promising new technology that has demonstrated utility in the study of normal human cognition. We utilized fNIR spectroscopy to examine the effect of social anxiety and performance on hemodynamic activity in the dorsolateral prefrontal cortex (DLPFC). Socially phobic participants and non-clinical participants with varying levels of social anxiety completed a public speaking task in front of a small virtual audience while the DLPFC was being monitored by the fNIR device. The relationship between anxiety and both blood volume (BV) and deoxygenated hemoglobin (Hb) varied significantly as a function of speech performance, such that individuals with low social anxiety who performed well showed an increase in DLPFC activation relative to those who did not perform well. This result suggests that effortful thinking and/or efficient top-down inhibitory control may have been required to complete an impromptu speech task with good performance. In contrast, good performers who were highly socially anxious showed lower DLPFC activation relative to good performers who were low in social anxiety, suggesting autopilot thinking or less-effortful thinking. In poor performers, slight increases in DLPFC activation were observed from low to highly anxious individuals, which may reflect a shift from effortless thinking to heightened self-focused attention. Heightened self-focused attention, poor inhibitory control resulting in excessive fear or anxiety, or low motivation may lower performance. These results suggest that there can be different underlying mechanisms in the brain that affect the level of speech performance in individuals with varying degrees of social anxiety. This study highlights the utility of the fNIR device in the assessment of changes in DLPFC in response to exposure to realistic phobic stimuli, and further supports the potential utility of this technology in the study of the neurophysiology of anxiety disorders.

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We present theoretical and experimental demonstrations of a novel, to the best of our knowledge, diffuse optical imaging method that is based on the concept of dual slopes (DS) in frequency-domain near-infrared spectroscopy. We consider a special array of sources and detectors that collects intensity (I) and phase (ϕ) data with multiple DS sets. We have recently shown that DSϕ reflectance data features a deeper sensitivity with respect to DSI reflectance data. Here, for the first time, we describe a DS imaging approach based on the Moore-Penrose inverse of the sensitivity matrix for multiple DS data sets. Using a circular 8-source/9-detector array that generates 16 DS data sets at source-detector distances in the range 20-40 mm, we show that DSI images are more sensitive to superficial (<5mm) perturbations, whereas DSϕ images are more sensitive to deeper (>10mm) perturbations in highly scattering media.

Frequency-domain near-infrared spectroscopy (FD-NIRS) is a noninvasive technique used to characterize in vivo tissue structure and molecular composition by leveraging the deep tissue penetration of red and near-infrared light. However, the size, complexity, expense, and lack of scalability of current FD-NIRS hardware have hindered its widespread clinical adoption and use outside the lab/clinic. The goal of this dissertation project is to address these limitations by developing a compact FD-NIRS device for wearable optical sensing and imaging. We hypothesize that the wearable design will enable quantitative and real-time measurement of tissue composition in an application such as measuring muscle oxygenation for athletes. In this work, we present the first wearable FD-NIRS systems, enabled by custom broad-bandwidth application-specific integrated circuits (ASICs). This is the first time a complete transceiver has been implemented on a chip for a multifrequency FD-NIRS system. Initially, the ASIC was characterized using a benchtop setup for its potential and performance in FD-NIRS measurements. It was then integrated into a single-channel, two-wavelength wearable system for the quantitative measurement of tissue oxygenation. This wearable FD-NIRS system accurately measured tissue optical properties during in vivo arteriovenous occlusion experiments at 14.7~Hz, quantifying oxy- and deoxyhemoglobin concentrations and confirming the functionality of the wearable FD-NIRS technology. In a high-speed configuration, this device was used to sample the cardiac pulsatile waveform at 250Hz. Encouraged by the success of the single-channel FD-NIRS device, a multichannel device intended for diffuse optical tomography (DOT) has been developed. The use of current multichannel FD-NIRS DOT systems are restricted to laboratory environments and are not comfortable for long-term monitoring. We designed our multichannel system for functional near-infrared spectroscopy (fNIRS) brain imaging in a wearable, modular, and fiber-free format to improve comfort and ease of use. This system consists of a high-density optode array with 16 sources and 16 detectors and FD-NIRS measurements based on a compact a vector network analyzer (VNA). A tile-based design approach was adopted, incorporating silicon photomultipliers (SiPMs), vertical cavity surface-emitting lasers (VCSELs), and radio frequency (RF)/direct current (DC) switching. A wearable forehead probe was designed to house these tiles, providing continuous, comfortable measurements and enabling real-time monitoring of brain activity and muscle oxygenation. Preliminary data on tile performance using tissue-simulating phantoms will be presented. We anticipate that our work will ultimately improve the tracking of neurological conditions, the efficacy of treatment, and brain function in both clinical and naturalistic (i.e., outside of the clinic / lab) settings.

This study aimed at understanding the neurobiological mechanisms associated with inattention induced by traumatic brain injury (TBI). To eliminate the potential confounding caused by the heterogeneity of TBI, we focused on young adults postsports-related concussion (SRC). Functional near-infrared spectroscopy (fNIRS) data were collected from 27 young adults post-SRC and 27 group-matched normal controls (NCs), while performing a visual sustained attention task. Task responsive cortical activation maps and pairwise functional connectivity among six regions of interest were constructed for each subject. Correlations among the brain imaging measures and clinical measures of attention were calculated in each group. Compared to the NCs, the SRC group showed significantly increased brain activation in left middle frontal gyrus (MFG) and increased functional connectivity between right inferior occipital cortex (IOC) bilateral calcarine gyri (CG). The left MFG activation magnitude was significantly negatively correlated with the hyperactive/impulsive symptom severity measure in the NCs, but not in the patients. The right hemisphere CG-IOC functional connectivity showed a significant positive correlation with the hyperactive/impulsive symptom severity measure in patients, but not in NCs. The current data suggest that abnormal left MFG activation and hyper-communications between right IOC and bilateral CG during visual attention processing may significantly contribute to behavioral manifestations of attention deficits in patients with TBI.

MP27-19 A NEW CLINICAL PROTOCOL FOR DEMONSTRATION OF CORTICAL BRAIN ACTIVITY MAPPING DURING VOLUNTARY UROFLOW AND PELVIC FLOOR MUSCLE ACTIVITY USING FUNCTIONAL NEAR INFRA-RED SPECTROSCOPY (FNIRS)

An improved understanding of the mechanisms underlying locomotor networks has the potential to benefit the neurorehabilitation of patients with neurological locomotor deficits. However, the specific locomotor networks that mediate adaptive locomotor performance and changes in gait speed remain unknown. The aim of the present study was to examine patterns of cortical activation associated with the walking speeds of 1.5, 2.0, 2.5, and 3.0 km/h on a treadmill. Functional near-infrared spectroscopy (fNIRS) was performed on a 30-year-old right-handed healthy female subject, and cerebral hemodynamic changes were observed in cortical locomotor network areas including the primary sensorimotor cortex (SMC), premotor cortex (PMC), supplementary motor area (SMA), prefrontal cortex (PFC), and sensory association cortex (SAC). The software package NIRS-statistical parametric mapping (NIRS-SPM) was utilized to analyze fNIRS data in the MATLAB environment. SPM t-statistic maps were computed at an uncorrected threshold of p< 0.00001. At faster walking speeds, oxygenated hemoglobin (OxyHb) was concentrated in the PFC and indicated globalized locomotor network activation of the SMC, PMC, SMA, and PMC; additionally, the site with the highest cortical activation ratio shifted from the SMC to the SMA. Global locomotor network recruitment, in particular PFC activation indicated by OxyHb in our study, may indicate a response to increased cognitive-locomotor demand due to simultaneous postural maintenance and leg movement coordination.

Analysis of cerebral hemodynamics reveals a wide spectrum of oscillations ranging from 0.0095 to 2 Hz. While most of these oscillations can be filtered out during analysis of functional near-infrared spectroscopy (fNIRS) signals when estimating stimulus evoked hemodynamic responses, oscillations around 0.1 Hz are an exception. This is due to the fact that they share a common spectral range with typical stimulus evoked hemodynamic responses from the brain. Here we investigate the effect of hemodynamic oscillations around 0.1 Hz on the estimation of hemodynamic response functions from fNIRS data. Our results show that for an expected response of ~1 µM in oxygenated hemoglobin concentration (HbO), Mayer wave oscillations with an amplitude > ~1 µM at 0.1 Hz reduce the accuracy of the estimated response as quantified by a 3 fold increase in the mean squared error and decrease in correlation (R(2) below 0.78) when compared to the true HRF. These results indicate that the amplitude of oscillations at 0.1 Hz can serve as an objective metric of the expected HRF estimation accuracy. In addition, we investigated the effect of short separation regression on the recovered HRF, and found that this improves the recovered HRF when large amplitude 0.1 Hz oscillations are present in fNIRS data. We suspect that the development of other filtering strategies may provide even further improvement.

<bold>Objective</bold> To explore the neurobehavioral mechanism of cross-education phenomenon and asymmetry in the upper limb based on functional near-infrared spectroscopy (fNIRS). <bold>Methods</bold> A total of 17 healthy subjects recruited by Sir Run Run Hospital of Nanjing Medical University from November 2023 to January 2024 were selected in a randomized cross-over trial. Purdue pegboard training with the contralateral upper limb of unilateral limb was taken as the contralateral training, and the number of Purdue pegboard plug-ins completed within a limited time as the task performance. fNIRS was used to collect the cerebral hemodynamic changes of healthy right-handed individuals after contralateral training when the left and right hand performed operational activities and record the behavioral data, and compare the cerebral cortex activation and behavioral performance of the left and right hands before and after contralateral training. <bold>Results</bold> After contralateral training, the performance of the left hand was significantly better than that before training (<italic>t</italic>=-8.865, <italic>P</italic>&lt;0.010), while the performance of the right hand did not change after training (<italic>t</italic>=-1.689, <italic>P</italic>=0.606). In addition, the left pre-motor and supplementary motor area (CH 29), right pre-motor and supplementary motor area (CH 16, CH 17) and right primary motor cortex (CH 09) were more significantly activated after contralateral training when subjects performed the Purdue pegboard task with left hand (<italic>P</italic>&lt;0.05). However, the right pre-motor and supplementary motor area (CH 19), right primary somatosensory cortex (CH 08) and right primary motor cortex (CH 10) showed a decreasing trend in the activation after contralateral training when subjects performed the Purdue pegboard task with right hand (<italic>P</italic>&lt;0.05). <bold>Conclusion</bold> Cross-education of the upper limbs is asymmetrical, indicating that the non-dominant hand experiences greater benefits compared to the dominant hand. Cross-education may be attributed to enhance the cortical activation of the bilateral pre-motor and supplementary motor area (pSMA) to improve the task performance of the non-training limb.

Evidence suggests that transcranial direct current stimulation (tDCS) combined with repetitive transcranial magnetic stimulation (rTMS) is more effective than either modality alone. However, the underlying neural mechanisms remain unclear. To explore the effects of combined tDCS-rTMS on cortical functional networks and neural regulation processes in chronic insomnia. In this randomised, double-blind, sham-controlled trial, 111 adults with chronic insomnia were allocated to real tDCS+real rTMS or sham tDCS+real rTMS. Participants received 20 weekday sessions over 4 weeks. Of these, 106 completed treatment and 103 provided functional near-infrared spectroscopy (fNIRS) data meeting predefined quality criteria. fNIRS measured oxygenated haemoglobin (Oxy-Hb) responses in prefrontal and temporal regions during a verbal fluency task (VFT) before and after treatment. The primary outcome was haemodynamic activation; secondary outcomes were functional connectivity and sleep quality. Sleep quality improved in both groups, with significantly greater reduction in Pittsburgh Sleep Quality Index (PSQI) scores in the real tDCS+real rTMS group (p<0.05). No between-group differences were observed in VFT performance. However, the combined stimulation group showed significantly increased Oxy-Hb responses across multiple fronto-temporal channels, particularly in bilateral temporal regions, and greater enhancement in mean functional connectivity (p<0.05). Both interventions were well tolerated, with no serious adverse events. This study provides neuroimaging evidence that combined tDCS and rTMS may improve chronic insomnia by enhancing activation of fronto-temporal cortices and strengthening inter-regional functional connectivity. These findings offer objective support for the clinical efficacy of the combined stimulation protocol, link neurophysiological changes to treatment optimisation and suggest potential advantages of this approach for neuromodulation-based therapeutic strategies. These findings suggest that tDCS combined with rTMS may represent a feasible and well tolerated non-pharmacological strategy for chronic insomnia, with potential advantages over rTMS alone at both clinical and neurophysiological levels. This study was registered as a clinical trial with the China Clinical Trial Registration Centre (ChiCTR2100052681).