Depth sensitivity and source-detector separations for near infrared spectroscopy based on the Colin27 brain template

Cortical tinnitus evaluation using functional near-infrared spectroscopy

Functional near-infrared spectroscopy (fNIRS) estimates the cortical hemodynamic response induced by sound stimuli. fNIRS can be used to understand the symptomatology of tinnitus and consequently provide effective ways of evaluating and treating the symptom.

OBJECTIVE

Compare the changes in the oxy-hemoglobin and deoxy-hemoglobin concentration of individuals with and without tinnitus using auditory stimulation by fNIRS.

METHODS

A tinnitus group (n = 23) and a control group (n = 23) were evaluated by an auditory task for assessing sound-evoked auditory cortex activity. The fNIRS was composed of 20 channels arranged into 4x2 arrays over the frontal, temporal and parietal cortices. Then, a passive listening block-paradigm design was adopted with reoccurring blocks of tasks with 15 s interspersed with randomized silence periods between 15-25 s.

RESULTS

There was a significant difference in the condition (type of sound), region of interest (ROI) and channel. As well as significant interaction in group and condition, and group and channel. The Tinnitus Frequency decreased HbO levels, while other sounds (white noise - WN and 1KHZ) increased HbO levels. All conditions differed from each other, except 1KHz with Baseline (silence) in the control group. Regarding the channels, the frontal channels (1, 3, and 11) differed in the tinnitus group, while in the control group a difference was observed in the channels of the frontal, temporal and parietal regions.

CONCLUSION

The type of sound presented, and brain region influenced the variations in HbO levels, but there was no difference between tinnitus and control participants. The tinnitus loudness, annoyance, and severity showed a weak correlation with variations in HbO levels.

Simultaneous monitoring of the human brain, spinal cord, and cauda equina activity for movement control: An fNIRS approach

Brain‒spinal cord‒cauda equina interactions are essential for controlling lower body movement. However, current monitoring approaches for spinal and caudal activity are limited to use without body movement and to processing via batches of data. Here, we present a novel optical method based on functional near-infrared spectroscopy that enables simultaneous tracking of human brain-spinal cord-cauda equina hemodynamics during body movement. We first developed a support frame for positioning optical emitters and receivers along the spinal canal to maximize spatial resolution and identify the optimal distance between them. We tested the methodology at this optimal emitter-detector distance by assessing the spatiotemporal activation of the motor clusters associated with human ankle extension-flexion movement in the brain, spinal cord, and cauda equina. These brain and spinal clusters are shown to be functionally connected and comparable to those identified by invasive methods during surgical operations. These findings suggest that hemodynamic responses reflect synchronous neural activity in the human brain-spinal cord-cauda equina system for hindlimb movement control.

Finite Element Modeling of Abdominal Near-Infrared Spectroscopy for Infant Splanchnic Oximetry

Abdominal near-infrared spectroscopy (NIRS) holds promise for early detection of necrotizing enterocolitis and other infant pathologies prior to irreversible injury, but the optimal NIRS sensor design is not well defined. In this study, we develop and demonstrate a computational method to evaluate NIRS sensor designs for infant splanchnic oximetry. We used a finite element (FE) approach to simulate near-infrared light transport through a 3D model of the infant abdomen constructed from computed tomography (CT) images. The simulations enable the measurement of the contrast-to-noise ratio (CNR) for splanchnic oximetry, given a specific NIRS sensor design. A key design criterion is the sensor's source-detector distance (SDD). We calculated the CNR as a function of SDD for two sensor positions near the umbilicus. Contrast-to-noise was maximal at SDDs between 4 and 5 cm, and comparable between sensor positions. Sensitivity to intestinal tissue also exceeded sensitivity to superficial adipose tissue in the 4-5 cm range. FE modeling of abdominal NIRS signals provides a means for rapid and thorough evaluation of sensor designs for infant splanchnic oximetry. By informing optimal NIRS sensor design, the computational methods presented here can improve the reliability and applicability of infant splanchnic oximetry.

Beneath the surface: revealing deep-tissue blood flow in human subjects with massively parallelized diffuse correlation spectroscopy

Significance

Diffuse correlation spectroscopy (DCS) allows label-free, non-invasive investigation of microvascular dynamics deep within tissue, such as cerebral blood flow (CBF). However, the signal-to-noise ratio (SNR) in DCS limits its effective cerebral sensitivity in adults, in which the depth to the brain, through the scalp and skull, is substantially larger than in infants.

Aim

Therefore, we aim to increase its SNR and, ultimately, its sensitivity to CBF through new DCS techniques.

Approach

We present an in vivo demonstration of parallelized DCS (PDCS) to measure cerebral and muscular blood flow in healthy adults. Our setup employs an innovative array with hundreds of thousands single photon avalanche diodes (SPAD) in a 500 × 500 grid to boost SNR by averaging all independent pixel measurements. We tested this device on different total pixel counts and frame rates. A secondary, smaller array was used for reference measurements from shallower tissue at lower source-detector-separation (SDS).

Results

The new system can measure pulsatile blood flow in cerebral and muscular tissue, at up to 4 cm SDS, while maintaining a similar measurement noise as compared with a previously published 32 × 32 PDCS system at 1.5 cm SDS. Data from a cohort of 15 adults provide strong experimental evidence for functional CBF activity during a cognitive memory task and allowed analysis of pulse markers. Additional control experiments on muscular blood flow in the forearm with a different technical configuration provide converging evidence for the efficacy of this technique.

Conclusions

Our results outline successful PDCS measurements with large SPAD arrays to enable detect CBF in human adults. The ongoing development of SPAD camera technology is expected to result in larger and faster detectors in the future. In combination with new data processing techniques, tailored for the sparse signal of binary photon detection events in SPADs, this could lead to even greater SNR increase and ultimately greater depth sensitivity of PDCS.

Method for Using Functional Near-Infrared Spectroscopy (fNIRS) to Explore Music-Induced Brain Activation in Orchestral Musicians in Concert

The act of performing music may induce a specific state of mind, musicians potentially becoming immersed and detached from the rest of the world. May this be measured? Does this state of mind change based on repetition? In collaboration with Stavanger Symphony Orchestra (SSO), we developed protocols to investigate ongoing changes in the brain activation of a first violinist and a second violinist in real time during seven sequential, public concerts using functional near-infrared spectroscopy (fNIRS). Using wireless fNIRS systems (Brite MKII) from Artinis, we measured ongoing hemodynamic changes and projected the brain activation to the audience through the software OxySoft 3.5.15.2. We subsequently developed protocols for further analyses through the Matlab toolboxes Brainstorm and Homer2/Homer3. Our developed protocols demonstrate how one may use "functional dissection" to imply how the state of mind of musicians may alter while performing their art. We focused on a subset of cortical regions in the right hemisphere, but the current study demonstrates how fNIRS may be used to shed light on brain dynamics related to producing art in ecological and natural contexts on a general level, neither restricted to the use of musical instrument nor art form.

High-Density Multi-Distance fNIRS Enhances Detection of Brain Activity during a Word-Color Stroop Task

Significance

Functional Near-Infrared Spectroscopy (fNIRS) enables neuroimaging in scenarios where other modalities are less suitable, such as during motion tasks or in low-resource environments. Sparse fNIRS arrays with 30mm channel spacing are widely used but have limited spatial resolution. High-density (HD) arrays with overlapping, multi-distance channels improve sensitivity and localization but increase costs and setup times. A statistical comparison of HD and sparse arrays is needed for evaluating the benefits and trade-offs of HD arrays.

Aim

This study provides a statistical comparison of HD and sparse fNIRS performance to inform array selection in future research.

Approach

We measured prefrontal cortex (PFC) activation during congruent and incongruent Word-Color Stroop (WCS) tasks using both Sparse and HD arrays for 17 healthy adult participants, comparing dorsolateral PFC channel and image results at the group level.

Results

While both arrays detected activation in channel space during incongruent WCS, channel and image space results demonstrated superior localization and sensitivity with the HD array for all WCS.

Conclusions

Sparse channel data may suitably detect activation from cognitively demanding tasks, like incongruent WCS. However, the HD array outperformed Sparse in detecting and localizing brain activity in image space, particularly during lower cognitive load tasks, making them more suitable for neuroimaging applications.

Capturing shared fNIRS responses to visual affective stimuli in young healthy women

Functional near-infrared spectroscopy (fNIRS) studies focusing on prefrontal cortex (PFC) have shown mixed results in relating hemodynamic changes to emotional processing, posing a challenge for clinical practice. Concerns related to instrumentation, recruited sample, task design, signal processing, and data analysis have been highlighted. To minimize some biasing factors, we proposed an experimental approach based on: (1) a homogeneous recruited sample, (2) an identical sequence of content-grouped affective pictures for emotion induction, (3) multi-distance forehead fNIRS recordings to separate cerebral from extra-cerebral components, and (4) a model-free frequency-based analysis to capture shared response patterns across individuals. We piloted a study to assess the feasibility of the approach in a sample of 20 young healthy women during an emotional task with affective pictures of neutral, sexual and violence content. We found coherent fNIRS responses to sexual and violence content located in slow fluctuations (0-0.019 Hz), characterized by positive and negative oxygenation patterns of extra-cerebral and cerebral origin, respectively. Additionally, we corroborated the strong interference of surface hemodynamics. This study proves the feasibility of our approach to identify frequency-specific fNIRS response patterns to affective visual stimuli, which holds promise for exploring functional biomarkers of healthy and altered emotional processing.

Transcranial brain atlas based on photon measurement density function in a triple-parameter standard channel space

Functional near-infrared spectroscopy (fNIRS) is a widely-used transcranial brain imaging technique in neuroscience research. Nevertheless, the lack of anatomical information from recordings poses challenges for designing appropriate optode montages and for localizing fNIRS signals to underlying anatomical regions. The photon measurement density function (PMDF) is often employed to address these issues, as it accurately measures the sensitivity of an fNIRS channel to perturbations of absorption coefficients at any brain location. However, existing PMDF-based localization methods have two limitations: (1) limited channel space, and (2) estimation based on a single standard head model, which usually differ anatomically from individuals. To overcome these limitations, this study proposes a continuous standard channel space for fNIRS and constructs a PMDF-based transcranial brain atlas (PMDF-TBA) by calculating PMDFs using MRI data from 48 adults. The PMDF-TBA contains group-averaged sensitivities of channels to gray matter and brain regions as defined in 3 atlases: Brodmann, AAL2, and LPBA40. We evaluated the prediction ability of PMDF-TBA for sensitivity of unseen individuals. The results show that it outperformed PMDFs based on single standard head models, making PMDF-TBA a more generalizable fNIRS spatial localization tool. Therefore, in the absence of individual sMRI data, PMDF-TBA can optimize optode montage design, enhance channel sensitivity in target brain regions, and assist in source localization for fNIRS data, thereby facilitating the application of fNIRS in neuroscience research.

Age group classification based on optical measurement of brain pulsation using machine learning

Optical techniques, such as functional near-infrared spectroscopy (fNIRS), contain high potential for the development of non-invasive wearable systems for evaluating cerebral vascular condition in aging, due to their portability and ability to monitor real-time changes in cerebral hemodynamics. In this study, thirty-six healthy adults were measured by single channel fNIRS to explore differences between two age groups using machine learning (ML). The subjects, measured during functional magnetic resonance imaging (fMRI) at Oulu University Hospital, were divided into young (age ≤ 32) and elderly (age ≥ 57) groups. Brain pulses were extracted from fNIRS using a single 830 nm wavelength. Four feature sets were derived from log-normal parameters estimated by pulse decomposition algorithm. ML experiments utilized support vector machines and random forest learners, along with maximum relevance minimum redundancy and principal component analysis for feature selection. Performance with increasing sample size was estimated using learning curve method. The best mean balanced accuracies for each feature set were over 75% (75.9%, 76.4%, 79.3%, 76.9%), indicating the pulse features containing age related information. Learning curves indicated stable classification performance with increasing sample size. The results demonstrate the potential of using single channel fNIRS in the analysis of aging.

Evaluation of Neural, Systemic and Extracerebral Activations During Active Walking Tasks in Older Adults Using fNIRS

Functional near infrared spectroscopy (fNIRS) is being increasingly used to assess brain hemodynamic responses during active walking in older adults due to its wearability, and relative immunity to motion artifacts. Specifically, fNIRS allows for continuous monitoring of brain activations that vary in response to experimental manipulations of cognitive demands during active walking tasks. Studies using fNIRS highlighted increased involvement of the prefrontal cortex (PFC) in dual compared to single task walking, operationalized using oxygenated hemoglobin (HbO), due to increasing attention demands inherent in the former task condition in aging and clinical populations. However, current literature utilizing fNIRS in mobility research has not been uniform in terms of fNIRS instrumentation characteristics and the accompanying signal processing methods to separate various signal sources (i.e. neural activations, extracerebral signals, systemic responses) which can raise questions about prior research findings. In our previous studies, we have used a forehead fNIR sensor (fNIR Imager 1100 by fNIR Devices, LLC) with 2.5 cm source detector separation (SDS) at 2 Hz sampling rate which allowed us to reliably evaluate changes in brain activations in the PFC during active walking. However, there exists other fNIRS devices incorporating a number of different types of light sources and detectors allowing multiple channels of long (3 cm SDS) and short (0.8 cm SDS) distance measurements in complex configurations for the monitoring of cognitive activations on various head locations at different depths with higher sampling rates of ~5 Hz (i.e. NIRx sensor, NIR Sport2 by NIRx Medizintechnik GmbH). Such involved designs further allowed the implementation of advanced signal processing algorithms to separate and evaluate neural, systemic and extracerebral signal contributions on the overall measurements. In this study, we collected brain imaging data on a sample of healthy older adults (n =15, age ) under single (STW) and dual task walking (DTW) conditions; participants were evaluated twice during one study visit, once wearing fNIR sensor and a second time while wearing NIRx sensor. This study design allowed us to address critical gaps in the extant literature concerning fNIRS-derived brain activations during active walking. Specifically, we evaluated potential effects of penetration depth as defined by the SDS of the fNIRS device, extracerebral activations (i.e. skin blood flow) and systemic signals (i.e. heart rate) on the observed HbO increases from STW to DTW. Our findings suggested that PFC activation differences between STW and DTW conditions observed in older adults were consistent across fNIRS instrumentations and the observed differences in HbO between STW and DTW were not materially influenced by scalp activations or systemic changes. Nevertheless, efforts to optimize extraction of fNIRS-derived brain signal measurements should continue taking advantage of technological advancement.

Programmable scanning diffuse speckle contrast imaging of cerebral blood flow

Significance

Cerebral blood flow (CBF) imaging is crucial for diagnosing cerebrovascular diseases. However, existing large neuroimaging techniques with high cost, low sampling rate, and poor mobility make them unsuitable for continuous and longitudinal CBF monitoring at the bedside.

Aim

We aimed to develop a low-cost, portable, programmable scanning diffuse speckle contrast imaging (PS-DSCI) technology for fast, high-density, and depth-sensitive imaging of CBF in rodents.

Approach

The PS-DSCI employed a programmable digital micromirror device (DMD) for remote line-shaped laser (785 nm) scanning on tissue surface and synchronized a 2D camera for capturing boundary diffuse laser speckle contrasts. New algorithms were developed to address deformations of line-shaped scanning, thus minimizing CBF reconstruction artifacts. The PS-DSCI was examined in head-simulating phantoms and adult mice.

Results

The PS-DSCI enables resolving intralipid particle flow contrasts at different tissue depths. In vivo experiments in adult mice demonstrated the capability of PS-DSCI to image global/regional CBF variations induced by 8%CO 2 inhalation and transient carotid artery ligations.

Conclusions

Compared with conventional point scanning, line scanning in PS-DSCI significantly increases spatiotemporal resolution. The high sampling rate of PS-DSCI is crucial for capturing rapid CBF changes while high spatial resolution is important for visualizing brain vasculature.

Portable six-channel laser speckle system for simultaneous measurement of cerebral blood flow and volume with potential applications in characterization of brain injury

Significance

Cerebral blood flow (CBF) and cerebral blood volume (CBV) are key metrics for regional cerebrovascular monitoring. Simultaneous, non-invasive measurement of CBF and CBV at different brain locations would advance cerebrovascular monitoring and pave the way for brain injury detection as current brain injury diagnostic methods are often constrained by high costs, limited sensitivity, and reliance on subjective symptom reporting.

Aim

We aim to develop a multi-channel non-invasive optical system for measuring CBF and CBV at different regions of the brain simultaneously with a cost-effective, reliable, and scalable system capable of detecting potential differences in CBF and CBV across different regions of the brain.

Approach

The system is based on speckle contrast optical spectroscopy and consists of laser diodes and board cameras, which have been both tested and investigated for safe use on the human head. Apart from the universal serial bus connection for the camera, the entire system, including its battery power source, is integrated into a wearable headband and is powered by 9-V batteries.

Results

The temporal dynamics of both CBF and CBV in a cohort of five healthy subjects were synchronized and exhibited similar cardiac period waveforms across all six channels. The potential use of our six-channel system for detecting the physiological sequelae of brain injury was explored in two subjects, one with moderate and one with significant structural brain damage, where the six-point CBF and CBV measurements were referenced to structural magnetic resonance imaging (MRI) scans.

Conclusions

We pave the way for a viable multi-point optical instrument for measuring CBF and CBV. Its cost-effectiveness allows for baseline metrics to be established prior to injury in populations at risk for brain injury.

Brain activation patterns in normal hearing adults: An fNIRS Study using an adapted clinical speech comprehension task

OBJECTIVES

Understanding brain processing of auditory and visual speech is essential for advancing speech perception research and improving clinical interventions for individuals with hearing impairment. Functional near-infrared spectroscopy (fNIRS) is deemed to be highly suitable for measuring brain activity during language tasks. However, accurate data interpretation also requires validated stimuli and behavioral measures.

DESIGN

Twenty-six adults with normal hearing listened to sentences from the Oldenburg Sentence Test (OLSA), and brain activation in the temporal, occipital, and prefrontal areas was measured by fNIRS. The sentences were presented in one of the four different modalities: speech-in-quiet, speech-in-noise, audiovisual speech or visual speech (i.e., lipreading). To support the interpretation of our fNIRS data, and to obtain a more comprehensive understanding of the study population, we performed hearing tests (pure tone and speech audiometry) and collected behavioral data using validated questionnaires, in-task comprehension questions, and listening effort ratings.

RESULTS

In the auditory conditions (i.e., speech-in-quiet and speech-in-noise), we observed cortical activity in the temporal regions bilaterally. During the visual speech condition, we measured significant activation in the occipital area. Following the audiovisual condition, cortical activation was observed in both regions. Furthermore, we established a baseline for how individuals with normal hearing process visual cues during lipreading, and we found higher activity in the prefrontal cortex in noise conditions compared to quiet conditions, linked to higher listening effort.

CONCLUSIONS

We demonstrated the applicability of a clinically inspired audiovisual speech-comprehension task in participants with normal hearing. The measured brain activation patterns were supported and complemented by objective and behavioral parameters.

Portable Six-Channel Laser Speckle System for Simultaneous Cerebral Blood Flow and Volume Measurement with Potential Application for Characterization of Brain Injury

In regional cerebrovascular monitoring, cerebral blood flow (CBF) and cerebral blood volume (CBV) are key metrics. Simultaneous, non-invasive measurement of CBF and CBV at different brain locations would advance cerebrovascular monitoring and pave the way for brain injury detection, as current brain injury diagnostic methods are often constrained by high costs, limited sensitivity, and reliance on subjective symptom reporting. This study's aim is to develop a multi-channel non-invasive optical system for measuring CBF and CBV at different regions of the brain simultaneously with a cost-effective, reliable, and scalable system capable of detecting potential differences in CBF and CBV across different regions of the brain. The system is based on speckle contrast optical spectroscopy (SCOS) and consists of laser diodes and board cameras which have been both tested and investigated for safe use on the human head. Results on a cohort of five healthy subjects indicated that the dynamics of both CBF and CBV were synchronized and exhibited similar cardiac period waveforms across all six channels. As a preliminary investigation, we also explored the potential use of our six-channel system for detecting the physiological sequela of brain injury, involving a subject with significant structural brain damage compared to another with lesser structural brain damage. The six-point CBF and CBV measurements were compared to MRI scans, revealing that regions with altered blood dynamics closely correlated with the injury sites identified by MRI.

Aesthetic evaluation of body movements shaped by embodied and arts experience: Insights from behaviour and fNIRS

Aesthetic appreciation of full-body movements is likely shaped by our cumulative bodily experiences, yet most of the extant literature in this domain has focused on expertise and familiarity. We ran two experiments exploring individual differences in embodied experience and experience with the arts: In Study 1, we explored how participants' (n = 41) abilities to learn a choreography shaped their aesthetic perceptions while viewing learned vs. unknown movements, using functional near-infrared spectroscopy (fNIRS) to measure cortical activation over the Action Observation Network (i.e., inferior frontal gyrus [IFG], inferior parietal lobule, middle temporal gyrus [MTG]). Study 1 demonstrated that embodied experience enhanced ratings of enjoyment, familiarity, and reproducibility of movements, and that individual differences in participants' performance of the learned choreography were not associated with aesthetic ratings, but rather cortical activation in IFG and right MTG while viewing learned choreography. In Study 2, we combined the behavioural data from Study 1 with data from additional participants (total n = 141) to examine the relationship between arts experience and aesthetic perceptions of movements robustly. Study 2 revealed that previous arts and sports experience correlated with aesthetic judgements of familiarity and reproducibility of movements. Our findings highlight the relevance of examining individual experiences to fill theoretical gaps in our understanding of action aesthetics.

Computer Vision-Driven Movement Annotations to Advance fNIRS Pre-Processing Algorithms

Functional near-infrared spectroscopy (fNIRS) is beneficial for studying brain activity in naturalistic settings due to its tolerance for movement. However, residual motion artifacts still compromise fNIRS data quality and might lead to spurious results. Although some motion artifact correction algorithms have been proposed in the literature, their development and accurate evaluation have been challenged by the lack of ground truth information. This is because ground truth information is time- and labor-intensive to manually annotate. This work investigates the feasibility and reliability of a deep learning computer vision (CV) approach for automated detection and annotation of head movements from video recordings. Fifteen participants performed controlled head movements across three main rotational axes (head up/down, head left/right, bend left/right) at two speeds (fast and slow), and in different ways (half, complete, repeated movement). Sessions were video recorded and head movement information was obtained using a CV approach. A 1-dimensional UNet model (1D-UNet) that detects head movements from head orientation signals extracted via a pre-trained model (SynergyNet) was implemented. Movements were manually annotated as a ground truth for model evaluation. The model's performance was evaluated using the Jaccard index. The model showed comparable performance between the training and test sets (J train = 0.954; J test = 0.865). Moreover, it demonstrated good and consistent performance at annotating movement across movement axes and speeds. However, performance varied by movement type, with the best results being obtained for repeated (J test = 0.941), followed by complete (J test = 0.872), and then half movements (J test = 0.826). This study suggests that the proposed CV approach provides accurate ground truth movement information. Future research can rely on this CV approach to evaluate and improve fNIRS motion artifact correction algorithms.

Optical Taxonomic Signal and the Diagnosis of Alzheimer's Disease

Goal: We previously demonstrated that near-infrared spectroscopy in vivo presents spectral features at 895 and 861 nm that accurately classify Alzheimer's disease, mild cognitive impairment, and age-matched control subjects. Our purpose here is to associate the 895 nm signal with [Formula: see text]-amyloid. Methods: We applied our feature selection technique to subjects with and without leptomeningeal amyloid. We developed a novel concept, optical taxonomic signal, to determine the dependence of signal on source-detector distance. Results: Features at 891 and 768 nm discriminate between subjects with and without leptomeningeal [Formula: see text]-amyloid. The variation of optical taxonomic signal with source-detector distance indicates that both signals come from the leptomeninges and not cerebral cortex. The two features are highly correlated and likely result from the same cellular material. Conclusions: The discovery of an 891 nm feature that clearly depends upon the presence of [Formula: see text]-amyloid supports our hypothesis that the 895 nm feature previously discovered also reports [Formula: see text]-amyloid.

Correlating stroke risk with non-invasive cerebrovascular perfusion dynamics using a portable speckle contrast optical spectroscopy laser device

Stroke poses a significant global health threat, with millions affected annually, leading to substantial morbidity and mortality. Current stroke risk assessment for the general population relies on markers such as demographics, blood tests, and comorbidities. A minimally invasive, clinically scalable, and cost-effective way to directly measure cerebral blood flow presents an opportunity. This opportunity has the potential to positively impact effective stroke risk assessment prevention and intervention. Physiological changes in the cerebrovascular system, particularly in response to hypercapnia and hypoxia during voluntary breath-holding can offer insights into stroke risk assessment. However, existing methods for measuring cerebral perfusion reserves, such as blood flow and blood volume changes, are limited by either invasiveness or impracticality. Herein we propose a non-invasive transcranial approach using speckle contrast optical spectroscopy (SCOS) to non-invasively monitor regional changes in brain blood flow and volume during breath-holding. Our study, conducted on 50 individuals classified into two groups (low-risk and higher-risk for stroke), shows significant differences in blood dynamic changes during breath-holding between the two groups, providing physiological insights for stroke risk assessment using a non-invasive quantification paradigm. Given its cost-effectiveness, scalability, portability, and simplicity, this laser-centric tool has significant potential for early diagnosis and treatment of stroke in the general population.

Programmable scanning diffuse speckle contrast imaging of cerebral blood flow

Significance

Cerebral blood flow (CBF) imaging is crucial for diagnosing cerebrovascular diseases. However, existing large neuroimaging techniques with high cost, low sampling rate, and poor mobility make them unsuitable for continuous and longitudinal CBF monitoring at the bedside.

Aim

This study aimed to develop a low-cost, portable, programmable scanning diffuse speckle contrast imaging (PS-DSCI) technology for fast, high-density, and depth-sensitive imaging of CBF in rodents.

Approach

The PS-DSCI employed a programmable digital micromirror device (DMD) for remote line-shape laser (785 nm) scanning on tissue surface and synchronized a 2D camera for capturing boundary diffuse laser speckle contrasts. New algorithms were developed to address deformations of line-shape scanning, thus minimizing CBF reconstruction artifacts. The PS-DSCI was examined in head-simulating phantoms and adult mice.

Results

The PS-DSCI enables resolving Intralipid particle flow contrasts at different tissue depths. In vivo experiments in adult mice demonstrated the capability of PS-DSCI to image global/regional CBF variations induced by 8% CO2 inhalation and transient carotid artery ligations.

Conclusions

Compared to conventional point scanning, the line scanning in PS-DSCI significantly increases spatiotemporal resolution. The high sampling rate of PS-DSCI is crucial for capturing rapid CBF changes while high spatial resolution is important for visualizing brain vasculature.

Phase-based structured interrogation frequency-domain near-infrared spectroscopy

Frequency-domain near-infrared spectroscopy (FD-NIRS) is a noninvasive method for quantitatively measuring optical absorption and scattering in tissue. This study introduces structured interrogation (SI) as an interference-based approach for implementing FD-NIRS in order to enhance optical property estimation in multilayered tissues and sensitivity to deeper layers. We find that, in the presence of realistic noise, SI accurately estimates properties and chromophore concentrations with less than a 5% error. Particularly noteworthy, the phase-only component of SI FD-NIRS can quantify both the optical absorption and reduced scattering in homogeneous tissues and shows a 20% improved sensitivity to absorption changes in deeper tissues compared to conventional methods. We show that this enhanced sensitivity is promising for improving the accuracy of functional brain monitoring in the cortex of an infant with less superficial contamination.

Functional Near-Infrared Spectroscopy-Based Computer-Aided Diagnosis of Major Depressive Disorder Using Convolutional Neural Network with a New Channel Embedding Layer Considering Inter-Hemispheric Asymmetry in Prefrontal Hemodynamic Responses

Background

Functional near-infrared spectroscopy (fNIRS) is being extensively explored as a potential primary screening tool for major depressive disorder (MDD) because of its portability, cost-effectiveness, and low susceptibility to motion artifacts. However, the fNIRS-based computer-aided diagnosis (CAD) of MDD using deep learning methods has rarely been studied. In this study, we propose a novel deep learning framework based on a convolutional neural network (CNN) for the fNIRS-based CAD of MDD with high accuracy.

Materials and Methods

The fNIRS data of participants-48 patients with MDD and 68 healthy controls (HCs)-were obtained while they performed a Stroop task. The hemodynamic responses calculated from the preprocessed fNIRS data were used as inputs to the proposed CNN model with an ensemble CNN architecture, comprising three 1D depth-wise convolutional layers specifically designed to reflect interhemispheric asymmetry in hemodynamic responses between patients with MDD and HCs, which is known to be a distinct characteristic in previous MDD studies. The performance of the proposed model was evaluated using a leave-one-subject-out cross-validation strategy and compared with those of conventional machine learning and CNN models.

Results

The proposed model exhibited a high accuracy, sensitivity, and specificity of 84.48%, 83.33%, and 85.29%, respectively. The accuracies of conventional machine learning algorithms-shrinkage linear discriminator analysis, regularized support vector machine, EEGNet, and ShallowConvNet-were 73.28%, 74.14%, 62.93%, and 62.07%, respectively.

Conclusions

In conclusion, the proposed deep learning model can differentiate between the patients with MDD and HCs more accurately than the conventional models, demonstrating its applicability in fNIRS-based CAD systems.

Detectability of hemodynamic oscillations in cerebral cortex through functional near-infrared spectroscopy: a simulation study

Significance

We explore the feasibility of using time-domain (TD) and continuous-wave (CW) functional near-infrared spectroscopy (fNIRS) to monitor brain hemodynamic oscillations during resting-state activity in humans, a phenomenon that is of increasing interest in the scientific and medical community and appears to be crucial to advancing the understanding of both healthy and pathological brain functioning.

Aim

Our general object is to maximize fNIRS sensitivity to brain resting-state oscillations. More specifically, we aim to define comprehensive guidelines for optimizing main operational parameters in fNIRS measurements [average photon count rate, measurement length, sampling frequency, and source-detector distance (SSD)]. In addition, we compare TD and CW fNIRS performance for the detection and localization of oscillations.

Approach

A series of synthetic TD and CW fNIRS signals were generated by exploiting the solution of the diffusion equation for two different geometries of the probed medium: a homogeneous medium and a bilayer medium. Known and periodical perturbations of the concentrations of oxy- and deoxy-hemoglobin were imposed in the medium, determining changes in its optical properties. The homogeneous slab model was used to determine the effect of multiple measurement parameters on fNIRS sensitivity to oscillatory phenomena, and the bilayer model was used to evaluate and compare the abilities of TD and CW fNIRS in detecting and isolating oscillations occurring at different depths. For TD fNIRS, two approaches to enhance depth-selectivity were evaluated: first, a time-windowing of the photon distribution of time-of-flight was performed, and then, the time-dependent mean partial pathlength (TMPP) method was used to retrieve the hemoglobin concentrations in the medium.

Results

In the homogeneous medium case, the sensitivity of TD and CW fNIRS to periodical perturbations of the optical properties increases proportionally with the average photon count rate, the measurement length, and the sampling frequency and approximatively with the square of the SSD. In the bilayer medium case, the time-windowing method can detect and correctly localize the presence of oscillatory components in the TD fNIRS signal, even in the presence of very low photon count rates. The TMPP method demonstrates how to correctly retrieve the periodical variation of hemoglobin at different depths from the TD fNIRS signal acquired at a single SSD. For CW fNIRS, measurements taken at typical SSDs used for short-separation channel regression show notable sensitivity to oscillations occurring in the deep layer, challenging the assumptions underlying this correction method when the focus is on analyzing oscillatory phenomena.

Conclusions

We demonstrated that the TD fNIRS technique allows for the detection and depth-localization of periodical fluctuations of the hemoglobin concentrations within the probed medium using an acquisition at a single SSD, offering an alternative to multi-distance CW fNIRS setups. Moreover, we offered some valuable guidelines that can assist researchers in defining optimal experimental protocols for fNIRS studies.

Compact and cost-effective laser-powered speckle contrast optical spectroscopy fiber-free device for measuring cerebral blood flow

Significance

In the realm of cerebrovascular monitoring, primary metrics typically include blood pressure, which influences cerebral blood flow (CBF) and is contingent upon vessel radius. Measuring CBF noninvasively poses a persistent challenge, primarily attributed to the difficulty of accessing and obtaining signal from the brain.

Aim

Our study aims to introduce a compact speckle contrast optical spectroscopy device for noninvasive CBF measurements at long source-to-detector distances, offering cost-effectiveness, and scalability while tracking blood flow (BF) with remarkable sensitivity and temporal resolution.

Approach

The wearable sensor module consists solely of a laser diode and a board camera. It can be easily placed on a subject's head to measure BF at a sampling rate of 80 Hz.

Results

Compared to the single-fiber-based version, the proposed device achieved a signal gain of about 70 times, showed superior stability, reproducibility, and signal-to-noise ratio for measuring BF at long source-to-detector distances. The device can be distributed in multiple configurations around the head.

Conclusions

Given its cost-effectiveness, scalability, and simplicity, this laser-centric tool offers significant potential in advancing noninvasive cerebral monitoring technologies.

Classification of motor imagery using chaotic entropy based on sub-band EEG source localization

Objective.Electroencephalography (EEG) has been widely used in motor imagery (MI) research by virtue of its high temporal resolution and low cost, but its low spatial resolution is still a major criticism. The EEG source localization (ESL) algorithm effectively improves the spatial resolution of the signal by inverting the scalp EEG to extrapolate the cortical source signal, thus enhancing the classification accuracy.Approach.To address the problem of poor spatial resolution of EEG signals, this paper proposed a sub-band source chaotic entropy feature extraction method based on sub-band ESL. Firstly, the preprocessed EEG signals were filtered into 8 sub-bands. Each sub-band signal was source localized respectively to reveal the activation patterns of specific frequency bands of the EEG signals and the activities of specific brain regions in the MI task. Then, approximate entropy, fuzzy entropy and permutation entropy were extracted from the source signal as features to quantify the complexity and randomness of the signal. Finally, the classification of different MI tasks was achieved using support vector machine.Main result.The proposed method was validated on two MI public datasets (brain-computer interface (BCI) competition III IVa, BCI competition IV 2a) and the results showed that the classification accuracies were higher than the existing methods.Significance.The spatial resolution of the signal was improved by sub-band EEG localization in the paper, which provided a new idea for EEG MI research.

fNIRS is capable of distinguishing laterality of lower body contractions

The use of functional near-infrared spectroscopy (fNIRS) for brain imaging during human movement continues to increase. This technology measures brain activity non-invasively using near-infrared light, is highly portable, and robust to motion artifact. However, the spatial resolution of fNIRS is lower than that of other imaging modalities. It is unclear whether fNIRS has sufficient spatial resolution to differentiate nearby areas of the cortex, such as the leg areas of the motor cortex. Therefore, the purpose of this study was to determine fNIRS' ability to discern laterality of lower body contractions. Activity in the primary motor cortex was recorded in forty participants (mean = 23.4 years, SD = 4.5, female = 23, male = 17) while performing unilateral lower body contractions. Contractions were performed at 30% of maximal force against a handheld dynamometer. These contractions included knee extension, knee flexion, dorsiflexion, and plantar flexion of the left and right legs. fNIRS signals were recorded and stored for offline processing and analysis. Channels of fNIRS data were grouped into regions of interest, with five tolerance conditions ranging from strict to lenient. Four of five tolerance conditions resulted in significant differences in cortical activation between hemispheres. During right leg contractions, the left hemisphere was more active than the right hemisphere. Similarly, during left leg contractions, the right hemisphere was more active than the left hemisphere. These results suggest that fNIRS has sufficient spatial resolution to distinguish laterality of lower body contractions. This makes fNIRS an attractive technology in research and clinical applications in which laterality of brain activity is required during lower body activity.

Spatial correspondence of cortical activity measured with whole head fNIRS and fMRI: Toward clinical use within subject

Functional near infrared spectroscopy (fNIRS) and functional magnetic resonance imaging (fMRI) both measure the hemodynamic response, and so both imaging modalities are expected to have a strong correspondence in regions of cortex adjacent to the scalp. To assess whether fNIRS can be used clinically in a manner similar to fMRI, 22 healthy adult participants underwent same-day fMRI and whole-head fNIRS testing while they performed separate motor (finger tapping) and visual (flashing checkerboard) tasks. Analyses were conducted within and across subjects for each imaging approach, and regions of significant task-related activity were compared on the cortical surface. The spatial correspondence between fNIRS and fMRI detection of task-related activity was good in terms of true positive rate, with fNIRS overlap of up to 68 % of the fMRI for analyses across subjects (group analysis) and an average overlap of up to 47.25 % for individual analyses within subject. At the group level, the positive predictive value of fNIRS was 51 % relative to fMRI. The positive predictive value for within subject analyses was lower (41.5 %), reflecting the presence of significant fNIRS activity in regions without significant fMRI activity. This could reflect task-correlated sources of physiologic noise and/or differences in the sensitivity of fNIRS and fMRI measures to changes in separate (vs. combined) measures of oxy and de-oxyhemoglobin. The results suggest whole-head fNIRS as a noninvasive imaging modality with promising clinical utility for the functional assessment of brain activity in superficial regions of cortex physically adjacent to the skull.

The efficacy and methodology of using near-infrared spectroscopy to determine resting-state brain networks

Functional connectivity is a critical aspect of brain function and is essential for understanding, diagnosing, and treating neurological and psychiatric disorders. It refers to the synchronous activity between different regions of the brain, which gives rise to communication and information processing. Resting-state functional connectivity is a subarea of study that allows researchers to examine brain activity in the absence of a task or stimulus. This can provide insight into the brain's intrinsic functional architecture and help identify neural networks that are active during rest. Thus, determining functional connectivity topography is valuable both clinically and in research. Traditional methods using functional magnetic resonance imaging have proven to be effective, however, they have their limitations. In this review, we investigate the feasibility of using functional near-infrared spectroscopy (fNIRS) as a low-cost, portable alternative for measuring functional connectivity. We first establish fNIRS' ability to detect localized brain activity during task-based experiments. Next, we verify its use in resting-state studies with results showing a high degree of correspondence with resting-state functional magnetic resonance imaging (rs-fMRI). Also discussed are various data-processing methods and the validity of filtering the global signal, which is the current standard for analysis. We consider the possible origins of the global signal, if it contains pertinent neuronal information that could be of importance in better understanding neuronal networks, and what we believe is the best method of approaching signal analysis and regression.

On decoding of rapid motor imagery in a diverse population using a high-density NIRS device

Introduction

Functional near-infrared spectroscopy (fNIRS) aims to infer cognitive states such as the type of movement imagined by a study participant in a given trial using an optical method that can differentiate between oxygenation states of blood in the brain and thereby indirectly between neuronal activity levels. We present findings from an fNIRS study that aimed to test the applicability of a high-density (>3000 channels) NIRS device for use in short-duration (2 s) left/right hand motor imagery decoding in a diverse, but not explicitly balanced, subject population. A side aim was to assess relationships between data quality, self-reported demographic characteristics, and brain-computer interface (BCI) performance, with no subjects rejected from recruitment or analysis.

Methods

BCI performance was quantified using several published methods, including subject-specific and subject-independent approaches, along with a high-density fNIRS decoder previously validated in a separate study.

Results

We found that decoding of motor imagery on this population proved extremely challenging across all tested methods. Overall accuracy of the best-performing method (the high-density decoder) was 59.1 +/- 6.7% after excluding subjects where almost no optode-scalp contact was made over motor cortex and 54.7 +/- 7.6% when all recorded sessions were included. Deeper investigation revealed that signal quality, hemodynamic responses, and BCI performance were all strongly impacted by the hair phenotypical and demographic factors under investigation, with over half of variance in signal quality explained by demographic factors alone.

Discussion

Our results contribute to the literature reporting on challenges in using current-generation NIRS devices on subjects with long, dense, dark, and less pliable hair types along with the resulting potential for bias. Our findings confirm the need for increased focus on these populations, accurate reporting of data rejection choices across subject intake, curation, and final analysis in general, and signal a need for NIRS optode designs better optimized for the general population to facilitate more robust and inclusive research outcomes.

A compact and cost-effective laser-powered speckle visibility spectroscopy (SVS) device for measuring cerebral blood flow

In the realm of cerebrovascular monitoring, primary metrics typically include blood pressure, which influences cerebral blood flow (CBF) and is contingent upon vessel radius. Measuring CBF non-invasively poses a persistent challenge, primarily attributed to the difficulty of accessing and obtaining signal from the brain. This study aims to introduce a compact speckle visibility spectroscopy (SVS) device designed for non-invasive CBF measurements, offering cost-effectiveness and scalability while tracking CBF with remarkable sensitivity and temporal resolution. The wearable hardware has a modular design approach consisting solely of a laser diode as the source and a meticulously selected board camera as the detector. They both can be easily placed on a subject's head to measure CBF with no additional optical elements. The SVS device can achieve a sampling rate of 80 Hz with minimal susceptibility to external disturbances. The device also achieves better SNR compared with traditional fiber-based SVS devices, capturing about 70 times more signal and showing superior stability and reproducibility. It is designed to be paired and distributed in multiple configurations around the head, and measure signals that exceed the quality of prior optical CBF measurement techniques. Given its cost-effectiveness, scalability, and simplicity, this laser-centric tool offers significant potential in advancing non-invasive cerebral monitoring technologies.

Retrieval of chromophore concentration changes in a digital human head model using analytical mean partial pathlengths of photons

Significance

Continuous-wave functional near-infrared spectroscopy has proved to be a valuable tool for assessing hemodynamic activity in the human brain in a non-invasively and inexpensive way. However, most of the current processing/analysis methods assume the head is a homogeneous medium, and hence do not appropriately correct for the signal coming from the scalp. This effect can be reduced by considering light propagation in a layered model of the human head, being the Monte Carlo (MC) simulations the gold standard to this end. However, this implies large computation times and demanding hardware capabilities.

Aim

In this work, we study the feasibility of replacing the homogeneous model and the MC simulations by means of analytical multilayered models, combining in this way, the speed and simplicity of implementation of the former with the robustness and accuracy of the latter.

Approach

Oxy- and deoxyhemoglobin (HbO and HbR, respectively) concentration changes were proposed in two different layers of a magnetic resonance imaging (MRI)-based meshed model of the human head, and then these changes were retrieved by means of (i) a typical homogeneous reconstruction and (ii) a theoretical layered reconstruction.

Results

Results suggest that the use of analytical models of light propagation in layered models outperforms the results obtained using traditional homogeneous reconstruction algorithms, providing much more accurate results for both, the extra- and the cerebral tissues. We also compare the analytical layered reconstruction with MC-based reconstructions, achieving similar degrees of accuracy, especially in the gray matter layer, but much faster (between 4 and 5 orders of magnitude).

Conclusions

We have successfully developed, implemented, and validated a method for retrieving chromophore concentration changes in the human brain, combining the simplicity and speed of the traditional homogeneous reconstruction algorithms with robustness and accuracy much more similar to those provided by MC simulations.

Brain-behavior analysis of transcranial direct current stimulation effects on a complex surgical motor task

Transcranial Direct Current Stimulation (tDCS) has demonstrated its potential in enhancing surgical training and performance compared to sham tDCS. However, optimizing its efficacy requires the selection of appropriate brain targets informed by neuroimaging and mechanistic understanding. Previous studies have established the feasibility of using portable brain imaging, combining functional near-infrared spectroscopy (fNIRS) with tDCS during Fundamentals of Laparoscopic Surgery (FLS) tasks. This allows concurrent monitoring of cortical activations. Building on these foundations, our study aimed to explore the multi-modal imaging of the brain response using fNIRS and electroencephalogram (EEG) to tDCS targeting the right cerebellar (CER) and left ventrolateral prefrontal cortex (PFC) during a challenging FLS suturing with intracorporeal knot tying task. Involving twelve novices with a medical/premedical background (age: 22-28 years, two males, 10 females with one female with left-hand dominance), our investigation sought mechanistic insights into tDCS effects on brain areas related to error-based learning, a fundamental skill acquisition mechanism. The results revealed that right CER tDCS applied to the posterior lobe elicited a statistically significant (q < 0.05) brain response in bilateral prefrontal areas at the onset of the FLS task, surpassing the response seen with sham tDCS. Additionally, right CER tDCS led to a significant (p < 0.05) improvement in FLS scores compared to sham tDCS. Conversely, the left PFC tDCS did not yield a statistically significant brain response or improvement in FLS performance. In conclusion, right CER tDCS demonstrated the activation of bilateral prefrontal brain areas, providing valuable mechanistic insights into the effects of CER tDCS on FLS peformance. These insights motivate future investigations into the effects of CER tDCS on error-related perception-action coupling through directed functional connectivity studies.

HyperTRCSS: A hyperspectral time-resolved compressive sensing spectrometer for depth-sensitive monitoring of cytochrome-c-oxidase and blood oxygenation

Significance

Hyperspectral time-resolved (TR) near-infrared spectroscopy offers the potential to monitor cytochrome-c-oxidase (oxCCO) and blood oxygenation in the adult brain with minimal scalp/skull contamination. We introduce a hyperspectral TR spectrometer that uses compressive sensing to minimize acquisition time without compromising spectral range or resolution and demonstrate oxCCO and blood oxygenation monitoring in deep tissue.

Aim

Develop a hyperspectral TR compressive sensing spectrometer and use it to monitor oxCCO and blood oxygenation in deep tissue.

Approach

Homogeneous tissue-mimicking phantom experiments were conducted to confirm the spectrometer's sensitivity to oxCCO and blood oxygenation. Two-layer phantoms were used to evaluate the spectrometer's sensitivity to oxCCO and blood oxygenation in the bottom layer through a 10 mm thick static top layer.

Results

The spectrometer was sensitive to oxCCO and blood oxygenation changes in the bottom layer of the two-layer phantoms, as confirmed by concomitant measurements acquired directly from the bottom layer. Measures of oxCCO and blood oxygenation by the spectrometer were highly correlated with "gold standard" measures in the homogeneous and two-layer phantom experiments.

Conclusions

The results show that the hyperspectral TR compressive sensing spectrometer is sensitive to changes in oxCCO and blood oxygenation in deep tissue through a thick static top layer.

Comparing the performance potential of speckle contrast optical spectroscopy and diffuse correlation spectroscopy for cerebral blood flow monitoring using Monte Carlo simulations in realistic head geometries

Significance

The non-invasive measurement of cerebral blood flow based on diffuse optical techniques has seen increased interest as a research tool for cerebral perfusion monitoring in critical care and functional brain imaging. Diffuse correlation spectroscopy (DCS) and speckle contrast optical spectroscopy (SCOS) are two such techniques that measure complementary aspects of the fluctuating intensity signal, with DCS quantifying the temporal fluctuations of the signal and SCOS quantifying the spatial blurring of a speckle pattern. With the increasing interest in the use of these techniques, a thorough comparison would inform new adopters of the benefits of each technique.

Aim

We systematically evaluate the performance of DCS and SCOS for the measurement of cerebral blood flow.

Approach

Monte Carlo simulations of dynamic light scattering in an MRI-derived head model were performed. For both DCS and SCOS, estimates of sensitivity to cerebral blood flow changes, coefficient of variation of the measured blood flow, and the contrast-to-noise ratio of the measurement to the cerebral perfusion signal were calculated. By varying complementary aspects of data collection between the two methods, we investigated the performance benefits of different measurement strategies, including altering the number of modes per optical detector, the integration time/fitting time of the speckle measurement, and the laser source delivery strategy.

Results

Through comparison across these metrics with simulated detectors having realistic noise properties, we determine several guiding principles for the optimization of these techniques and report the performance comparison between the two over a range of measurement properties and tissue geometries. We find that SCOS outperforms DCS in terms of contrast-to-noise ratio for the cerebral blood flow signal in the ideal case simulated here but note that SCOS requires careful experimental calibrations to ensure accurate measurements of cerebral blood flow.

Conclusion

We provide design principles by which to evaluate the development of DCS and SCOS systems for their use in the measurement of cerebral blood flow.

Machines, mathematics, and modules: the potential to provide real-time metrics for pain under anesthesia

The brain-based assessments under anesthesia have provided the ability to evaluate pain/nociception during surgery and the potential to prevent long-term evolution of chronic pain. Prior studies have shown that the functional near-infrared spectroscopy (fNIRS)-measured changes in cortical regions such as the primary somatosensory and the polar frontal cortices show consistent response to evoked and ongoing pain in awake, sedated, and anesthetized patients. We take this basic approach and integrate it into a potential framework that could provide real-time measures of pain/nociception during the peri-surgical period. This application could have significant implications for providing analgesia during surgery, a practice that currently lacks quantitative evidence to guide patient tailored pain management. Through a simple readout of "pain" or "no pain," the proposed system could diminish or eliminate levels of intraoperative, early post-operative, and potentially, the transition to chronic post-surgical pain. The system, when validated, could also be applied to measures of analgesic efficacy in the clinic.

Surface-based integration approach for fNIRS-fMRI reliability assessment

INTRODUCTION

Studies integrating functional near-infrared spectroscopy (fNIRS) with functional MRI (fMRI) employ heterogeneous methods in defining common regions of interest in which similarities are assessed. Therefore, spatial agreement and temporal correlation may not be reproducible across studies. In the present work, we address this issue by proposing a novel method for integration and analysis of fNIRS and fMRI over the cortical surface.

MATERIALS AND METHODS

Eighteen healthy volunteers (age mean±SD 30.55 ± 4.7, 7 males) performed a motor task during non-simultaneous fMRI and fNIRS acquisitions. First, fNIRS and fMRI data were integrated by projecting subject- and group-level source maps over the cortical surface mesh to define anatomically constrained functional ROIs (acfROI). Next, spatial agreement and temporal correlation were quantified as Dice Coefficient (DC) and Pearson's correlation coefficient between fNIRS-fMRI in the acfROIs.

RESULTS

Subject-level results revealed moderate to substantial spatial agreement (DC range 0.43 - 0.64), confirmed at the group-level only for blood oxygenation level-dependent (BOLD) signal vs. HbO2 (0.44 - 0.69), while lack of agreement was found for BOLD vs. HbR in some instances (0.05 - 0.49). Subject-level temporal correlation was moderate to strong (0.79 - 0.85 for BOLD vs. HbO2 and -0.62 to -0.72 for BOLD vs. HbR), while an overall strong correlation was found for group-level results (0.95 - 0.98 for BOLD vs. HbO2 and -0.91 to -0.94 for BOLD vs. HbR).

CONCLUSION

The proposed method directly compares fNIRS and fMRI by projecting individual source maps to the cortical surface. Our results indicate spatial and temporal correspondence between fNIRS and fMRI, and promotes the use of fNIRS when more ecological acquision settings are required, such as longitudinal monitoring of brain activity before and after rehabilitation.

Assessing depth sensitivity in laser interferometry speckle visibility spectroscopy (iSVS) through source-to-detector distance variation and cerebral blood flow monitoring in humans and rabbits

Recently, speckle visibility spectroscopy (SVS) was non-invasively applied on the head to monitor cerebral blood flow. The technique, using a multi-pixel detecting device (e.g., camera), allows the detection of a larger number of speckles, increasing the proportion of light that is detected. Due to this increase, it is possible to collect light that has propagated deeper through the brain. As a direct consequence, cerebral blood flow can be monitored. However, isolating the cerebral blood flow from the other layers, such as the scalp or skull components, remains challenging. In this paper, we report our investigations on the depth-sensitivity of laser interferometry speckle visibility spectroscopy (iSVS). Specifically, we varied the depth of penetration of the laser light into the head by tuning the source-to-detector distance, and identified the transition point at which cerebral blood flow in humans and rabbits starts to be detected.

Subjective feeling of control during fNIRS-based neurofeedback targeting the DL-PFC is related to neural activation determined with short-channel correction

Neurofeedback (NF) training is a promising preventive and therapeutic approach for brain and behavioral impairments, the dorsolateral prefrontal cortex (DL-PFC) being a relevant region of interest. Functional near-infrared spectroscopy (NIRS) has recently been applied in NF training. However, this approach is highly sensitive to extra-cerebral vascularization, which could bias measurements of cortical activity. Here, we examined the feasibility of a NF training targeting the DL-PFC and its specificity by assessing the impact of physiological confounds on NF success via short-channel offline correction under different signal filtering conditions. We also explored whether the individual mental strategies affect the NF success. Thirty volunteers participated in a single 15-trial NF session in which they had to increase the oxy-hemoglobin (HbO2) level of their bilateral DL-PFC. We found that 0.01-0.09 Hz band-pass filtering was more suited than the 0.01-0.2 Hz band-pass filter to highlight brain activation restricted to the NF channels in the DL-PFC. Retaining the 10 out of 15 best trials, we found that 18 participants (60%) managed to control their DL-PFC. This number dropped to 13 (43%) with short-channel correction. Half of the participants reported a positive subjective feeling of control, and the "cheering" strategy appeared to be more effective in men (p<0.05). Our results showed successful DL-PFC fNIRS-NF in a single session and highlighted the value of accounting for extra cortical signals, which can profoundly affect the success and specificity of NF training.

Vascular mechanisms leading to progression of mild cognitive impairment to dementia after COVID-19: Protocol and methodology of a prospective longitudinal observational study

INTRODUCTION

Mild cognitive impairment (MCI) is a prodromal stage to dementia, affecting up to 20% of the aging population worldwide. Patients with MCI have an annual conversion rate to dementia of 15-20%. Thus, conditions that increase the conversion from MCI to dementia are of the utmost public health concern. The COVID-19 pandemic poses a significant impact on our aging population with cognitive decline as one of the leading complications following recovery from acute infection. Recent findings suggest that COVID-19 increases the conversion rate from MCI to dementia in older adults. Hence, we aim to uncover a mechanism for COVID-19 induced cognitive impairment and progression to dementia to pave the way for future therapeutic targets that may mitigate COVID-19 induced cognitive decline.

METHODOLOGY

A prospective longitudinal study is conducted at the University of Oklahoma Health Sciences Center. Patients are screened in the Department of Neurology and must have a formal diagnosis of MCI, and MRI imaging prior to study enrollment. Patients who meet the inclusion criteria are enrolled and followed-up at 18-months after their first visit. Visit one and 18-month follow-up will include an integrated and cohesive battery of vascular and cognitive measurements, including peripheral endothelial function (flow-mediated dilation, laser speckle contrast imaging), retinal and cerebrovascular hemodynamics (dynamic vessel retinal analysis, functional near-infrared spectroscopy), and fluid and crystalized intelligence (NIH-Toolbox, n-back). Multiple logistic regression will be used for primary longitudinal data analysis to determine whether COVID-19 related impairment in neurovascular coupling and increases in white matter hyperintensity burden contribute to progression to dementia.

Non-Invasive Mapping of Cerebral Autoregulation Using Near-Infrared Spectroscopy: A Study Protocol

The ability of cerebral vessels to maintain a fairly constant cerebral blood flow is referred to as cerebral autoregulation (CA). Using near-infrared spectroscopy (NIRS) paired with arterial blood pressure (ABP) monitoring, continuous CA can be assessed non-invasively. Recent advances in NIRS technology can help improve the understanding of continuously assessed CA in humans with high spatial and temporal resolutions. We describe a study protocol for creating a new wearable and portable imaging system that derives CA maps of the entire brain with high sampling rates at each point. The first objective is to evaluate the CA mapping system's performance during various perturbations using a block-trial design in 50 healthy volunteers. The second objective is to explore the impact of age and sex on regional disparities in CA using static recording and perturbation testing in 200 healthy volunteers. Using entirely non-invasive NIRS and ABP systems, we hope to prove the feasibility of deriving CA maps of the entire brain with high spatial and temporal resolutions. The development of this imaging system could potentially revolutionize the way we monitor brain physiology in humans since it would allow for an entirely non-invasive continuous assessment of regional differences in CA and improve our understanding of the impact of the aging process on cerebral vessel function.

Functional near infrared spectroscopy detects cortical activation changes concurrent with memory loss in postmenopausal women with Type II Diabetes

Older adults with Type II Diabetes Mellitus (DM) experience mild cognitive impairment, specifically in the domain of recall/working memory. No consistent causative structural cortical deficits have been identified in persons with DM (PwDM). Memory deficits may be exacerbated in older adult females, who are at the highest risk of cardiovascular decline due to DM. The focus of the current study was to evaluate functional cortical hemodynamic activity during memory tasks in postmenopausal PwDM. Functional Near Infrared Spectroscopy (fNIRS) was used to monitor oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) during memory-based tasks in a cross-sectional sample of postmenopausal women with DM. Twenty-one community-dwelling DM females (age = 65 ± 6 years) and twenty-one age- and sex-matched healthy controls (age = 66 ± 6 years) were evaluated. Working memory performance (via N-back) was evaluated while study participants donned cortical fNIRS. Health state, metabolic data, and menopausal status data were also collected. Deficits in working memory accuracy were found in the DM group as compared to controls. Differences in HbO responses emerged in the DM group. The DM group exhibited altered PFC activity magnitudes and increased functional cortical activity across ROIs compared to controls. HbO and HbR responses were not associated with worsened health state measures. These data indicate a shift in cortical activity patterns with memory deficits in postmenopausal PwDM. This DM-specific shift of HbO is a novel finding that is unlikely to be detected by fMRI. This underscores the value of using non-MRI-based neuroimaging techniques to evaluate cortical hemodynamic function to detect early mild cognitive impairment.

Optical neuroimaging and neurostimulation in surgical training and assessment: A state-of-the-art review

Introduction

Functional near-infrared spectroscopy (fNIRS) is a non-invasive optical neuroimaging technique used to assess surgeons' brain function. The aim of this narrative review is to outline the effect of expertise, stress, surgical technology, and neurostimulation on surgeons' neural activation patterns, and highlight key progress areas required in surgical neuroergonomics to modulate training and performance.

Methods

A literature search of PubMed and Embase was conducted to identify neuroimaging studies using fNIRS and neurostimulation in surgeons performing simulated tasks.

Results

Novice surgeons exhibit greater haemodynamic responses across the pre-frontal cortex than experts during simple surgical tasks, whilst expert surgical performance is characterized by relative prefrontal attenuation and upregulation of activation foci across other regions such as the supplementary motor area. The association between PFC activation and mental workload follows an inverted-U shaped curve, activation increasing then attenuating past a critical inflection point at which demands outstrip cognitive capacity Neuroimages are sensitive to the impact of laparoscopic and robotic tools on cognitive workload, helping inform the development of training programs which target neural learning curves. FNIRS differs in comparison to current tools to assess proficiency by depicting a cognitive state during surgery, enabling the development of cognitive benchmarks of expertise. Finally, neurostimulation using transcranial direct-current-stimulation may accelerate skill acquisition and enhance technical performance.

Conclusion

FNIRS can inform the development of surgical training programs which modulate stress responses, cognitive learning curves, and motor skill performance. Improved data processing with machine learning offers the possibility of live feedback regarding surgeons' cognitive states during operative procedures.

Quantitative Comparison of Analytical Solution and Finite Element Method for Investigation of Near-infrared Light Propagation in Brain Tissue Model

Introduction

Functional near-infrared spectroscopy (fNIRS) is an imaging method in which a light source and detector are installed on the head; consequently, the re-emission of light from human skin contains information about cerebral hemodynamic alteration. The spatial probability distribution profile of photons penetrating tissue at a source spot, scattering into the tissue, and being released at an appropriate detector position, represents the spatial sensitivity.

Methods

Modeling light propagation in a human head is essential for quantitative near-infrared spectroscopy and optical imaging. The specific form of the distribution of light is obtained using the theory of perturbation. An analytical solution of the perturbative diffusion equation (DE) and finite element method (FEM) in a Slab media (similar to the human head) makes it possible to study light propagation due to absorption and scattering of brain tissue.

Results

The simulation result indicates that sensitivity is slowly decreasing in the deep area, and the sensitivity below the source and detector is the highest. The depth sensitivity and computation time of both analytical and FEM methods are compared. The simulation time of the analytical approach is four times larger than the FEM.

Conclusion

In this paper, an analytical solution and the performance of FEM methods when applied to the diffusion equation for heterogeneous media with a single spherical defect are compared. The depth sensitivity along with the computation time of simulation has been investigated for both methods. For simple and Slab modes of the human brain, the analytical solution is the right candidate. Whenever the brain model is sophisticated, it is possible to use FEM methods, but it costs a higher computation time.

Highlights

Analytical and finite element method (FEM) depth sensitivity are almost the same.FEM requires more computation time, but can handle complicated head models.The analytical method is proposed for the first step and simple head models.

Plain Language Summary

The functional near-infrared spectroscopy (fNIRS) is a type of neuromonitoring that uses near-infrared light to measure brain activity indirectly and is similar to electroencephalography (EEG). A single-channel fNIRS system contains a near-infrared light source, which emits near-infrared light (NIR), and a detector is placed near the source. A light intensity change received by detectors indicates brain activity when NIR light penetrates into the gray matter. It is necessary to have a prior understanding of light penetration depth in order to measure brain activity more accurately. fNIRS can be better understood, optimized, and investigated through modeling light propagation in brain tissue. In order to study light in tissues, analytical and numerical methods can be used. In this work, we compared these two approaches quantitatively in a simple slab medium. We concluded that the numerical method takes too much time to calculate the results, but it can be applied to complicated head models. The results of these studies provide researchers with new insights into the modeling and simulation of fNIRS and diffuse optical tomography.

Impact of Anatomical Variability on Sensitivity Profile in fNIRS-MRI Integration

Functional near-infrared spectroscopy (fNIRS) is an important non-invasive technique used to monitor cortical activity. However, a varying sensitivity of surface channels vs. cortical structures may suggest integrating the fNIRS with the subject-specific anatomy (SSA) obtained from routine MRI. Actual processing tools permit the computation of the SSA forward problem (i.e., cortex to channel sensitivity) and next, a regularized solution of the inverse problem to map the fNIRS signals onto the cortex. The focus of this study is on the analysis of the forward problem to quantify the effect of inter-subject variability. Thirteen young adults (six males, seven females, age 29.3 ± 4.3) underwent both an MRI scan and a motor grasping task with a continuous wave fNIRS system of 102 measurement channels with optodes placed according to a 10/5 system. The fNIRS sensitivity profile was estimated using Monte Carlo simulations on each SSA and on three major atlases (i.e., Colin27, ICBM152 and FSAverage) for comparison. In each SSA, the average sensitivity curves were obtained by aligning the 102 channels and segmenting them by depth quartiles. The first quartile (depth < 11.8 (0.7) mm, median (IQR)) covered 0.391 (0.087)% of the total sensitivity profile, while the second one (depth < 13.6 (0.7) mm) covered 0.292 (0.009)%, hence indicating that about 70% of the signal was from the gyri. The sensitivity bell-shape was broad in the source-detector direction (20.953 (5.379) mm FWHM, first depth quartile) and steeper in the transversal one (6.082 (2.086) mm). The sensitivity of channels vs. different cortical areas based on SSA were analyzed finding high dispersions among subjects and large differences with atlas-based evaluations. Moreover, the inverse cortical mapping for the grasping task showed differences between SSA and atlas based solutions. In conclusion, integration with MRI SSA can significantly improve fNIRS interpretation.

Effect of Acupuncture Treatment on Cortical Activation in Patients With Tinnitus: A Functional Near-Infrared Spectroscopy Study

Tinnitus is an auditory phantom percept that affects the perception of sound in the patient's ears, and the incidence of prolonged tinnitus is as high as ten to fifteen percent. Acupuncture is a unique treatment method in Chinese medicine, and it has great advantages in the treatment of tinnitus. However, tinnitus is a subjective symptom of patients, and there is currently no objective detection method to reflect the improvement effect of acupuncture on tinnitus. We used functional near-infrared spectroscopy (fNIRS) to explore the effect of acupuncture on the cerebral cortex of tinnitus patients. We collected the scores of the tinnitus disorder inventory (THI), tinnitus evaluation questionnaire (TEQ), hamilton anxiety scale (HAMA), and hamilton depression scale (HAMD) of eighteen subjects before and after acupuncture treatment, and the fNIRS signals of these subjects in sound-evoked activity before and after acupuncture treatment. According to the fNIRS detection results of tinnitus patients, acupuncture increased the concentration of oxygenated hemoglobin in the temporal lobe of tinnitus patients, and affected the activation of the auditory cortex. The study may reflect the neural mechanisms of acupuncture treatment for tinnitus and ultimately help to provide an objective evaluation method for the therapeutic effect of acupuncture treatment for tinnitus.

Interferometric diffusing wave spectroscopy imaging with an electronically variable time-of-flight filter

Diffuse optics (DO) is a light-based technique used to study the human brain, but it suffers from low brain specificity. Interferometric diffuse optics (iDO) promises to improve the quantitative accuracy and depth specificity of DO, and particularly, coherent light fluctuations (CLFs) arising from blood flow. iDO techniques have alternatively achieved either time-of-flight (TOF) discrimination or highly parallel detection, but not both at once. Here, we break this barrier with a single iDO instrument. Specifically, we show that rapid tuning of a temporally coherent laser during the sensor integration time increases the effective linewidth seen by a highly parallel interferometer. Using this concept to create a continuously variable and user-specified TOF filter, we demonstrate a solution to the canonical problem of DO, measuring optical properties. Then, with a deep TOF filter, we reduce scalp sensitivity of CLFs by 2.7 times at 1 cm source-collector separation. With this unique combination of desirable features, i.e., TOF-discrimination, spatial localization, and highly parallel CLF detection, we perform multiparametric imaging of light intensities and CLFs via the human forehead.

Molecular Recognition and In Vivo Detection of Temozolomide and 5-Aminoimidazole-4-carboxamide for Glioblastoma Using Near-Infrared Fluorescent Carbon Nanotube Sensors

There is a pressing need for sensors and assays to monitor chemotherapeutic activity within the human body in real time to optimize drug dosimetry parameters such as timing, quantity, and frequency in an effort to maximize efficacy while minimizing deleterious cytotoxicity. Herein, we develop near-infrared fluorescent nanosensors based on single walled carbon nanotubes for the chemotherapeutic Temozolomide (TMZ) and its metabolite 5-aminoimidazole-4-carboxamide using Corona Phase Molecular Recognition as a synthetic molecular recognition technique. The resulting nanoparticle sensors are able to monitor drug activity in real-time even under in vivo conditions. Sensors can be engineered to be biocompatible by encapsulation in poly(ethylene glycol) diacrylate hydrogels. Selective detection of TMZ was demonstrated using U-87 MG human glioblastoma cells and SKH-1E mice with detection limits below 30 μM. As sensor implants, we show that such systems can provide spatiotemporal therapeutic information in vivo, as a valuable tool for pharmacokinetic evaluation. Sensor implants are also evaluated using intact porcine brain tissue implanted 2.1 cm below the cranium and monitored using a recently developed Wavelength-Induced Frequency Filtering technique. Additionally, we show that by taking the measurement of spatial and temporal analyte concentrations within each hydrogel implant, the direction of therapeutic flux can be resolved. In all, these types of sensors enable the real time detection of chemotherapeutic concentration, flux, directional transport, and metabolic activity, providing crucial information regarding therapeutic effectiveness.

Functional near-infrared spectroscopy is a useful tool for multi-perspective psychobiological study of neurophysiological correlates of parenting behaviour

The quality of the relationship between caregiver and child has long-term effects on the cognitive and socio-emotional development of children. A process involved in human parenting is the bio-behavioural synchrony that occurs between the partners in the relationship during interaction. Through interaction, bio-behavioural synchronicity allows the adaptation of the physiological systems of the parent to those of the child and promotes the positive development and modelling of the child's social brain. The role of bio-behavioural synchrony in building social bonds could be investigated using functional near-infrared spectroscopy (fNIRS). In this paper we have (a) highlighted the importance of the quality of the caregiver-child relationship for the child's cognitive and socio-emotional development, as well as the relevance of infantile stimuli in the activation of parenting behaviour; (b) discussed the tools used in the study of the neurophysiological substrates of the parental response; (c) proposed fNIRS as a particularly suitable tool for the study of parental responses; and (d) underlined the need for a multi-systemic psychobiological approach to understand the mechanisms that regulate caregiver-child interactions and their bio-behavioural synchrony. We propose to adopt a multi-system psychobiological approach to the study of parental behaviour and social interaction.

Impacts of complex electromagnetic radiation and low-frequency noise exposure conditions on the cognitive function of operators

Background

Both electromagnetic radiation (EMR) and low-frequency noise (LFN) are widespread and influential environmental factors, and operators are inevitably exposed to both EMR and LFN within a complex exposure environment. The potential adverse effects of such exposure on human health must be considered seriously. This study aimed to investigate the effects of EMR and LFN on cognitive function as well as their interaction effect, which remain unclear.

Methods

Sixty young male college students were randomly grouped and experiments were conducted with a 2 × 2 factorial design in a shielded chamber. Mental workload (MWL) levels of the study subjects were measured and assessed using the NASA-task load index (TLX) subjective scale, an n-back task paradigm, and the functional near-infrared spectroscopy (fNIRS) imaging technique.

Results

For the 3-back task, the NASA-TLX subjective scale revealed a statistically significant main effect of LFN intensity, which enhanced the subjects' MWL level (F = 8.716, p < 0.01). Behavioral performance revealed that EMR intensity (430.1357 MHz, 10.75 W/m²) and LFN intensity (0-200 Hz, 72.9 dB) had a synergistic interaction effect, and the correct response time was statistically significantly prolonged by the combined exposure (F = 4.343, p < 0.05). The fNIRS imaging technique revealed a synergistic interaction effect between operational EMR intensity and operational LFN intensity, with statistically significant effects on the activation levels in the left and right dorsolateral prefrontal cortex (DLPFC). The mean β values of DLPFC were significantly increased (L-DLPFC F = 5.391, p < 0.05, R-DLPFC F = 4.222, p < 0.05), and the relative concentrations of oxyhemoglobin in the DLPFC were also significantly increased (L-DLPFC F = 4.925, p < 0.05, R-DLPFC F = 9.715, p < 0.01).

Conclusion

We found a statistically significant interaction effect between EMR (430.1357 MHz, 10.75 W/m²) and LFN (0-200 Hz, 72.9 dB) when simultaneously exposing subjects to both for 30 min. We conclude that exposure to this complex environment can cause a statistically significant increase in the MWL level of operators, and even alterations in their cognitive function.

Noninvasive optical monitoring of pulmonary embolism: a Monte Carlo study on visible Chinese human thoracic tissues

SIGNIFICANCE

In recent years, the incidence rate of pulmonary embolism (PE) has increased dramatically. Currently, the correct diagnosis rate of PE in China is relatively low, and the diagnosis error rate and missed diagnosis rate were as high as about 80%. The most standard method of PE detection is pulmonary artery digital subtraction angiography (DSA), but pulmonary artery DSA is an invasive examination, and patients can have certain risks and discomfort. Noninvasive monitoring of PE remains challenging in cardiovascular medicine.

AIM

We attempt to study the light propagation in human thoracic tissues and explore the possibility of near-infrared spectroscopy (NIRS) in noninvasive detection of PE.

APPROACH

In this study, by utilizing the Monte Carlo simulation method for voxelized media and the Visible Chinese Human dataset, we quantified and visualized the photon migration in human thoracic region. The influence of the development (three levels) of PE on the light migration was observed.

RESULTS

Results showed that around 4.6% light fluence was absorbed by the pulmonary tissue. The maximum signal sensitivity distribution reached 0.073% at the 2.8- to 3.1-cm light source-detector separation. The normalized light intensity was significantly different among different PE levels and formed a linear relationship (r 2 = 0.998 , p < 10 - 5 ).

CONCLUSIONS

The study found that photons could reach the pulmonary artery tissue, the light intensity was linearly related to the degrees of embolism, PE could be quantitatively diagnosed by NIRS. Meanwhile, the optimized distance in between the light source and detector, 2.8 to 3.1 cm, was recommended to be used in future potential noninvasive optical diagnosis of PE.

Whole-Head Functional Near-Infrared Spectroscopy as an Ecological Monitoring Tool for Assessing Cortical Activity in Parkinson's Disease Patients at Different Stages

Functional near-infrared spectroscopy (fNIRS) is increasingly employed as an ecological neuroimaging technique in assessing age-related chronic neurological disorders, such as Parkinson's disease (PD), mainly providing a cross-sectional characterization of clinical phenotypes in ecological settings. Current fNIRS studies in PD have investigated the effects of motor and non-motor impairment on cortical activity during gait and postural stability tasks, but no study has employed fNIRS as an ecological neuroimaging tool to assess PD at different stages. Therefore, in this work, we sought to investigate the cortical activity of PD patients during a motor grasping task and its relationship with both the staging of the pathology and its clinical variables. This study considered 39 PD patients (age 69.0 ± 7.64, 38 right-handed), subdivided into two groups at different stages by the Hoehn and Yahr (HY) scale: early PD (ePD; N = 13, HY = [1; 1.5]) and moderate PD (mPD; N = 26, HY = [2; 2.5; 3]). We employed a whole-head fNIRS system with 102 measurement channels to monitor brain activity. Group-level activation maps and region of interest (ROI) analysis were computed for ePD, mPD, and ePD vs. mPD contrasts. A ROI-based correlation analysis was also performed with respect to contrasted subject-level fNIRS data, focusing on age, a Cognitive Reserve Index questionnaire (CRIQ), disease duration, the Unified Parkinson's Disease Rating Scale (UPDRS), and performances in the Stroop Color and Word (SCW) test. We observed group differences in age, disease duration, and the UPDRS, while no significant differences were found for CRIQ or SCW scores. Group-level activation maps revealed that the ePD group presented higher activation in motor and occipital areas than the mPD group, while the inverse trend was found in frontal areas. Significant correlations with CRIQ, disease duration, the UPDRS, and the SCW were mostly found in non-motor areas. The results are in line with current fNIRS and functional and anatomical MRI scientific literature suggesting that non-motor areas-primarily the prefrontal cortex area-provide a compensation mechanism for PD motor impairment. fNIRS may serve as a viable support for the longitudinal assessment of therapeutic and rehabilitation procedures, and define new prodromal, low-cost, and ecological biomarkers of disease progression.