The modified Beer-Lambert law revisited

Multimodal exploration of non-motor neural functions in ALS patients using simultaneous EEG-fNIRS recording

OBJECTIVE

Despite the high prevalence of non-motor impairments reported in patients with amyotrophic lateral sclerosis (ALS), little is known about the functional neural markers underlying such dysfunctions. In this study, a new dual-task multimodal framework relying on simultaneous electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) recordings was developed to characterize integrative non-motor neural functions in people with ALS.

APPROACH

Simultaneous EEG-fNIRS data were recorded from six subjects with ALS and twelve healthy controls. Through a proposed visuo-mental paradigm, subjects performed a set of visuo-mental arithmetic operations. The data recorded were analyzed with respect to event-related changes both in the time and frequency domains for EEG and de/oxygen-hemoglobin level (HbR/HbO) changes for fNIRS. The correlation of EEG spectral features with fNIRS HbO/HbR features were then evaluated to assess the mechanisms of ALS on the electrical (EEG)-vascular (fNIRS) interrelationships.

MAIN RESULTS

We observed overall smaller increases in EEG delta and theta power, decreases in beta power, reductions in HbO responses, and distortions both in early and later EEG event-related potentials in ALS subjects compared to healthy controls. While significant correlations between EEG features and HbO responses were observed in healthy controls, these patterns were absent in ALS patients. Distortions in both electrical and hemodynamic responses are speculated to be associated with cognitive deficits in ALS that center primarily on attentional and working memory processing.

SIGNIFICANCE

Our results highlight the important role of ALS non-motor dysfunctions in electrical and hemodynamic neural dynamics as well as their interrelationships. The insights obtained through this study can enhance our understanding of the underlying non-motor neural processes in ALS and enrich future diagnostic and prognostic techniques.

A Newcomer's Guide to Functional Near Infrared Spectroscopy Experiments

This review presents a practical primer for functional near-infrared spectroscopy (fNIRS) with respect to technology, experimentation, and analysis software. Its purpose is to jump-start interested practitioners considering utilizing a non-invasive, versatile, nevertheless challenging window into the brain using optical methods. We briefly recapitulate relevant anatomical and optical foundations and give a short historical overview. We describe competing types of illumination (trans-illumination, reflectance, and differential reflectance) and data collection methods (continuous wave, time domain and frequency domain). Basic components (light sources, detection, and recording components) of fNIRS systems are presented. Advantages and limitations of fNIRS techniques are offered, followed by a list of very practical recommendations for its use. A variety of experimental and clinical studies with fNIRS are sampled, shedding light on many brain-related ailments. Finally, we describe and discuss a number of freely available analysis and presentation packages suited for data analysis. In conclusion, we recommend fNIRS due to its ever-growing body of clinical applications, state-of-the-art neuroimaging technique and manageable hardware requirements. It can be safely concluded that fNIRS adds a new arrow to the quiver of neuro-medical examinations due to both its great versatility and limited costs.

Assessment of age-related decline of neurovascular coupling responses by functional near-infrared spectroscopy (fNIRS) in humans

Preclinical studies provide strong evidence that age-related impairment of neurovascular coupling (NVC) plays a causal role in the pathogenesis of vascular cognitive impairment (VCI). NVC is a critical homeostatic mechanism in the brain, responsible for adjustment of local cerebral blood flow to the energetic needs of the active neuronal tissue. Recent progress in geroscience has led to the identification of critical cellular and molecular mechanisms involved in neurovascular aging, identifying these pathways as targets for intervention. In order to translate the preclinical findings to humans, there is a need to assess NVC in geriatric patients as an endpoint in clinical studies. Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging technique that enables the investigation of local changes in cerebral blood flow, quantifying task-related changes in oxygenated and deoxygenated hemoglobin concentrations. In the present overview, the basic principles of fNIRS are introduced and the application of this technique to assess NVC in older adults with implications for the design of studies on the mechanistic underpinnings of VCI is discussed.

Fusing Near-Infrared Spectroscopy with Wearable Hemodynamic Measurements Improves Classification of Mental Stress

Human-computer interaction (HCI) technology, and the automatic classification of a person's mental state, are of interest to multiple industries. In this work, the fusion of sensing modalities that monitor the oxygenation of the human prefrontal cortex (PFC) and cardiovascular physiology was evaluated to differentiate between rest, mental arithmetic and N-back memory tasks. A flexible headband to measure near-infrared spectroscopy (NIRS) for quantifying PFC oxygenation, and forehead photoplethysmography (PPG) for assessing peripheral cardiovascular activity was designed. Physiological signals such as the electrocardiogram (ECG) and seismocardiogram (SCG) were collected, along with the measurements obtained using the headband. The setup was tested and validated with a total of 16 human subjects performing a series of arithmetic and N-back memory tasks. Features extracted were related to cardiac and peripheral sympathetic activity, vasomotor tone, pulse wave propagation, and oxygenation. Machine learning techniques were utilized to classify rest, arithmetic, and N-back tasks, using leave-one-subject-out cross validation. Macro-averaged accuracy of 85%, precision of 84%, recall rate of 83%, and F1 score of 80% were obtained from the classification of the three states. Statistical analyses on the subject-based results demonstrate that the fusion of NIRS and peripheral cardiovascular sensing significantly improves the accuracy, precision, recall, and F1 scores, compared to using NIRS sensing alone. Moreover, the fusion significantly improves the precision compared to peripheral cardiovascular sensing alone. The results of this work can be used in the future to design a multi-modal wearable sensing system for classifying mental state for applications such as acute stress detection.

Thickness Dependence of Optical Transmittance of Transparent Wood: Chemical Modification Effects

Transparent wood (TW) is an emerging optical material combining high optical transmittance and haze for structural applications. Unlike nonscattering absorbing media, the thickness dependence of light transmittance for TW is complicated because optical losses are also related to increased photon path length from multiple scattering. In the present study, starting from photon diffusion equation, it is found that the angle-integrated total light transmittance of TW has an exponentially decaying dependence on sample thickness. The expression reveals an attenuation coefficient which depends not only on the absorption coefficient but also on the diffusion coefficient. The total transmittance and thickness were measured for a range of TW samples, from both acetylated and nonacetylated balsa wood templates, and were fitted according to the derived relationship. The fitting gives a lower attenuation coefficient for the acetylated TW compared to the nonacetylated one. The lower attenuation coefficient for the acetylated TW is attributed to its lower scattering coefficient or correspondingly lower haze. The attenuation constant resulted from our model hence can serve as a singular material parameter that facilitates cross-comparison of different sample types, at even different thicknesses, when total optical transmittance is concerned. The model was verified with two other TWs (ash and birch) and is in general applicable to other scattering media.

A Functional Near-Infrared Spectroscopy Study on the Cortical Haemodynamic Responses During the Maastricht Acute Stress Test

In order to better understand stress responses, neuroimaging studies have investigated the underlying neural correlates of stress. Amongst other brain regions, they highlight the involvement of the prefrontal cortex. The aim of the present study was to explore haemodynamic changes in the prefrontal cortex during the Maastricht Acute Stress Test (MAST) using mobile functional Near-Infrared Spectroscopy (fNIRS), examining the stress response in an ecological environment. The MAST includes a challenging mental arithmic task and a physically stressful ice-water task. In a between-subject design, participants either performed the MAST or a non-stress control condition. FNIRS data were recorded throughout the test. Additionally, subjective stress ratings, heart rate and salivary cortisol were evaluated, confirming a successful stress induction. The fNIRS data indicated significantly increased neural activity of brain regions of the dorsolateral prefrontal cortex (dlPFC) and the orbitofrontal cortex (OFC) in response to the MAST, compared to the control condition. Furthermore, the mental arithmetic task indicated an increase in neural activity in brain regions of the dlPFC and OFC; whereas the physically stressful hand immersion task indicated a lateral decrease of neural activity in the left dlPFC. The study highlights the potential use of mobile fNIRS in clinical and applied (stress) research.

In vivo subdiffuse scanning laser oximetry of the human retina

Scanning laser ophthalmoscopes (SLOs) have the potential to perform high speed, high contrast, functional imaging of the human retina for diagnosis and follow-up of retinal diseases. Commercial SLOs typically use a monochromatic laser source or a superluminescent diode for imaging. Multispectral SLOs using an array of laser sources for spectral imaging have been demonstrated in research settings, with applications mainly aiming at retinal oxygenation measurements. Previous SLO-based oximetry techniques are predominantly based on wavelengths that depend on laser source availability. We describe an SLO system based on a supercontinuum (SC) source and a double-clad fiber using the single-mode core for illumination and the larger inner cladding for quasi-confocal detection to increase throughput and signal-to-noise ratio. A balanced detection scheme was implemented to suppress the relative intensity noise of the SC source. The SLO produced dual wavelength, high-quality images at 10  frames  /  s with a maximum 20 deg imaging field-of-view with any desired combination of wavelengths in the visible spectrum. We demonstrate SLO-based dual-wavelength oximetry in vessels down to 50  μm in diameter. Reproducibility was demonstrated by performing three different imaging sessions of the same volunteer, 8 min apart. Finally, by performing a wavelength sweep between 485 and 608 nm, we determined, for our SLO geometry, an approximately linear relationship between the effective path length of photons through the blood vessels and the vessel diameter.

Effects of Acupuncture Therapy on MCI Patients Using Functional Near-Infrared Spectroscopy

Acupuncture therapy (AT) is a non-pharmacological method of treatment that has been applied to various neurological diseases. However, studies on its longitudinal effect on the neural mechanisms of patients with mild cognitive impairment (MCI) for treatment purposes are still lacking in the literature. In this clinical study, we assess the longitudinal effects of ATs on MCI patients using two methods: (i) Montreal Cognitive Assessment test (MoCA-K, Korean version), and (ii) the hemodynamic response (HR) analyses using functional near-infrared spectroscopy (fNIRS). fNIRS signals of a working memory (WM) task were acquired from the prefrontal cortex. Twelve elderly MCI patients and 12 healthy people were recruited as target and healthy control (HC) groups, respectively. Each group went through an fNIRS scanning procedure three times: The initial data were obtained without any ATs, and subsequently a total of 24 AT sessions were conducted for MCI patients (i.e., MCI-0: the data prior to ATs, MCI-1: after 12 sessions of ATs for 6 weeks, MCI-2: another 12 sessions of ATs for 6 weeks). The mean HR responses of all MCI-0–2 cases were lower than those of HCs. To compare the effects of AT on MCI patients, MoCA-K results, temporal HR data, and spatial activation patterns (i.e., t-maps) were examined. In addition, analyses of functional connectivity (FC) and graph theory upon WM tasks were conducted. With ATs, (i) the averaged MoCA-K test scores were improved (MCI-1, p = 0.002; MCI-2, p = 2.9e^–4); (ii) the mean HR response of WM tasks was increased (p < 0.001); and (iii) the t-maps of MCI-1 and MCI-2 were enhanced. Furthermore, an increased FC in the prefrontal cortex in both MCI-1/MCI-2 cases in comparison to MCI-0 was obtained (p < 0.01), and an increasing trend in the graph theory parameters was observed. All these findings reveal that ATs have a positive impact on improving the cognitive function of MCI patients. In conclusion, ATs can be used as a therapeutic tool for MCI patients as a non-pharmacological method (Clinical trial registration number: KCT 0002451 https://cris.nih.go.kr/cris/en/).

An IoT-Based Non-Invasive Glucose Level Monitoring System Using Raspberry Pi

Patients diagnosed with diabetes mellitus must monitor their blood glucose levels in order to control the glycaemia. Consequently, they must perform a capillary test at least three times per day and, besides that, a laboratory test once or twice per month. These standard methods pose difficulty for patients since they need to prick their finger in order to determine the glucose concentration, yielding discomfort and distress. In this paper, an Internet of Things (IoT)-based framework for non-invasive blood glucose monitoring is described. The system is based on Raspberry Pi Zero (RPi) energised with a power bank, using a visible laser beam and a Raspberry Pi Camera, all implemented in a glove. Data for the non-invasive monitoring is acquired by the RPi Zero taking a set of pictures of the user fingertip and computing their histograms. Generated data is processed by an artificial neural network (ANN) implemented on a Flask microservice using the Tensorflow libraries. In this paper, all measurements were performed in vivo and the obtained data was validated against laboratory blood tests by means of the mean absolute error (10.37%) and Clarke grid error (90.32% in zone A). Estimated glucose values can be harvested by an end device such as a smartphone for monitoring purposes.

Estimating the Dependence of Differential Pathlength Factor on Blood Volume and Oxygen Saturation using Monte Carlo method

Differential Pathlength Factor (DPF) is a vital parameter for the Beer-Lambert law based calculations in estimating tissue perfusion using non-invasive optical techniques. A significant error in the measured concentration of oxyhemoglobin and deoxyhemoglobin has been reported due to the usage of wrong DPF values. The dependence of DPF on blood oxygen saturation and blood volume has never been studied earlier. In this work, a Monte Carlo model of perfused skin tissue was developed and executed at 660 nm and 940 nm optical wavelengths at a reflectance geometry. DPFs were simulated through 1-10 mm source detector separations at different blood volumes and oxygen saturations. Results showed higher DPFs at lower wavelengths and considerable variation with blood volume and oxygen saturation.

Exploring the Brain Responses to Driving Fatigue Through Simultaneous EEG and fNIRS Measurements

Fatigue is one problem with driving as it can lead to difficulties with sustaining attention, behavioral lapses, and a tendency to ignore vital information or operations. In this research, we explore multimodal physiological phenomena in response to driving fatigue through simultaneous functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) recordings with the aim of investigating the relationships between hemodynamic and electrical features and driving performance. Sixteen subjects participated in an event-related lane-deviation driving task while measuring their brain dynamics through fNIRS and EEGs. Three performance groups, classified as Optimal, Suboptimal, and Poor, were defined for comparison. From our analysis, we find that tonic variations occur before a deviation, and phasic variations occur afterward. The tonic results show an increased concentration of oxygenated hemoglobin (HbO₂) and power changes in the EEG theta, alpha, and beta bands. Both dynamics are significantly correlated with deteriorated driving performance. The phasic EEG results demonstrate event-related desynchronization associated with the onset of steering vehicle in all power bands. The concentration of phasic HbO₂ decreased as performance worsened. Further, the negative correlations between tonic EEG delta and alpha power and HbO₂ oscillations suggest that activations in HbO₂ are related to mental fatigue. In summary, combined hemodynamic and electrodynamic activities can provide complete knowledge of the brain's responses as evidence of state changes during fatigue driving.

Identifying individuals using fNIRS-based cortical connectomes

The fMRI-based functional connectome was shown to be sufficiently unique to allow individual identification (fingerprinting). We aimed to test whether a fNIRS-based connectome could also be used to identify individuals. Forty-four participants performed experimental protocols that consisted of two periods of resting-state interleaved by a cognitive task period. Connectome identification was performed for all possible pairwise combinations of the three periods. The influence of hemodynamic global variation was tested using global signal regression and principal component analysis. High identification accuracies well-above chance level (2.3%) were observed overall, being particularly high (93%) to the oxyhemoglobin signal between resting conditions. Our results suggest that fNIRS is a suitable technique to assess connectome fingerprints.

Pre-frontal Cortical Activity During Walking and Turning Is Reliable and Differentiates Across Young, Older Adults and People With Parkinson's Disease

Introduction: Mobility declines with age and further with neurodegenerative disorders, such as Parkinson's disease (PD). Walking and turning ability, in particular, are vital aspects of mobility that deteriorate with age and are further impaired in PD. Such deficits have been linked with reduction in automatic control of movement and the need for compensatory cognitive cortical control via the pre-frontal cortex (PFC), however the underlying neural mechanisms remain unclear. Establishing and using a robust methodology to examine PFC activity during continuous walking and turning via mobile functional near infra-red spectroscopy (fNIRS) may aid in the understanding of mobility deficits and help with development of appropriate therapeutics. This study aimed to: (1) examine test re-test reliability of PFC activity during continuous turning and walking via fNIRS measurement; and (2) compare PFC activity during continuous turning and walking in young, old and Parkinson's subjects. Methods: Twenty-five young (32.3 ± 7.5 years), nineteen older (65.4 ± 7.0 years), and twenty-four PD (69.3 ± 4.1 years) participants performed continuous walking and 360° turning-in-place tasks, each lasting 2 min. Young participants repeated the tasks a second time to allow fNIRS measurement reliability assessment. The primary outcome was PFC activity, assessed via measuring changes in oxygenated hemoglobin (HbO₂) concentrations. Results: PFC activity during continuous walking and turning was moderately reproducible (Intra-class correlation coefficient = 0.67). The PD group had higher PFC activation than young and older adults during walking and turning, with significant group differences for bilateral PFC activation (p = 0.025), left PFC activation (p = 0.012), and the early period (first 40 s) of walking (p = 0.007), with greater activation required in PD. Interestingly, older adults had similar PFC activation to young adults across conditions, however older adults required greater activation than young adults during continuous turning, specifically the early period of the turning task (Cohens d = 0.86). Conclusions: PFC activity can be measured during continuous walking and turning tasks with acceptable reliability, and can differentiate young, older and PD groups. PFC activation was significantly greater in PD compared to young and older adults during walking, particularly when beginning to walk.

The hemodynamic changes during cupping therapy monitored by using an optical sensor embedded cup

Cupping therapy is one form of alternative medicine that is used widely across the world. Although the applications of cupping therapy including pain relief have a 1000-year history, the therapeutic effect of cupping is still questionable due to a lack of scientific evidence. Therefore, in the present study, we embedded a near-infrared spectroscopic sensor into a suction cup to monitor the hemodynamic changes on the treated site while the hemodynamics at the surrounding tissue of the cup was also simultaneously monitored by another near-infrared spectroscopic sensor. The results from 10 healthy male subjects show a dramatic increase of the oxy-hemoglobin (OHb) and deoxy-hemoglobin (RHb) concentrations at the treatment site while the OHb and RHb levels were decreased at the surrounding tissue. Moreover, after the treatment, we observed that the OHb concentrations were maintained at a higher level than before treatment at both sites, which may demonstrate how cupping therapy works for treatment. In summary, the results showed that cupping therapy increases blood volume and tissue oxygenation at the treatment site while those were slightly decreased at the surrounding tissue. This study showed that the embedding of near-infrared spectroscopy in a cupping system could offer a better understanding of the mechanism of cupping therapy.

Study of the Effects of Epinephrine on Cerebral Oxygenation and Metabolism During Cardiac Arrest and Resuscitation by Hyperspectral Near-Infrared Spectroscopy

OBJECTIVES

Epinephrine is routinely administered to sudden cardiac arrest patients during resuscitation, but the neurologic effects on patients treated with epinephrine are not well understood. This study aims to assess the cerebral oxygenation and metabolism during ventricular fibrillation cardiac arrest, cardiopulmonary resuscitation, and epinephrine administration.

DESIGN

To investigate the effects of equal dosages of IV epinephrine administrated following sudden cardiac arrest as a continuous infusion or successive boluses during cardiopulmonary resuscitation, we monitored cerebral oxygenation and metabolism using hyperspectral near-infrared spectroscopy.

SETTINGS

A randomized laboratory animal study.

SUBJECTS

Nine healthy pigs.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Our study showed that although continuous epinephrine administration had no significant impact on overall cerebral hemodynamics, epinephrine boluses transiently improved cerebral oxygenation (oxygenated hemoglobin) and metabolism (cytochrome c oxidase) by 15% ± 6.7% and 49% ± 18%, respectively (p < 0.05) compared with the baseline (untreated) ventricular fibrillation. Our results suggest that the effects of epinephrine diminish with successive boluses as the impact of the third bolus on brain oxygen metabolism was 24.6% ± 3.8% less than that of the first two boluses.

CONCLUSIONS

Epinephrine administration by bolus resulted in transient improvements in cerebral oxygenation and metabolism, whereas continuous epinephrine infusion did not, compared with placebo. Future studies are needed to evaluate and optimize the use of epinephrine in cardiac arrest resuscitation, particularly the dose, timing, and mode of administration.

Functional near-infrared spectroscopy evidence for the development of topological asymmetry between hemispheric brain networks from childhood to adulthood

Cerebral asymmetry is considered an important marker of the successful development of the human brain. Recent studies have demonstrated topological asymmetries between structurally hemispheric networks in the human brain. However, it remains largely unknown whether and how the functionally topological asymmetries evolve from childhood to adulthood, a critical period that constitutes the primary peak of human brain and cognitive development. Here, we adopted resting-state functional near-infrared spectroscopy imaging data to construct hemispheric functional networks and then applied graph theory analysis to quantify the topological characteristics of the hemispheric networks. We found that the adult group exhibited consistent leftward hemispheric asymmetries in both global and local network efficiency, and the degree of leftward asymmetry in local network efficiency was significantly increased with development from childhood to adulthood. At the nodal level, the degree of leftward asymmetry in nodal efficiency, mainly involving the frontal, parietal-occipital junction, and occipital regions, increased with development. These developmental patterns of topological asymmetries suggest that the protracted maturation of functional segregation in the left hemisphere could underlie language development from childhood to adulthood and provide insight into the development of human brain functional networks.

Noninvasive Electromagnetic Wave Sensing of Glucose

Diabetic patients need long-term and frequent glucose monitoring to assist in insulin intake. The current finger-prick devices are painful and costly, which places noninvasive glucose sensors in high demand. In this review paper, we list several advanced electromagnetic (EM)-wave-based technologies for noninvasive glucose measurement, including infrared (IR) spectroscopy, photoacoustic (PA) spectroscopy, Raman spectroscopy, fluorescence, optical coherence tomography (OCT), Terahertz (THz) spectroscopy, and microwave sensing. The development of each method is discussed regarding the fundamental principle, system setup, and experimental results. Despite the promising achievements that have been previously reported, no established product has obtained FDA approval or survived a marketing test. The limitations of, and prospects for, these techniques are presented at the end of this review.

The Use of Functional Near-Infrared Spectroscopy to Differentiate Alcohol-Related Neurodevelopmental Impairment

Oxygenated (HBO) and deoxygenated hemoglobin (HBR) levels in the prefrontal cortex (PFC) were measured using functional near-infrared spectroscopy (fNIRS) to determine if PFC activity during a cognitive inhibition task distinguishes children with prenatal alcohol exposure (PAE, n = 26) from both typically developing controls (n = 19) and a contrast group of children with other neurobehavioral problems (n = 14). Despite showing evidence of increased PFC activity in the non-inhibitory condition relative to controls, children in the PAE group displayed reduced PFC HBO and increased HBR relative to both other groups in the inhibitory condition, suggesting reduced PFC activity but increased oxygen consumption without sufficient oxygen replacement.

fNIRS improves seizure detection in multimodal EEG-fNIRS recordings

In the context of epilepsy monitoring, electroencephalography (EEG) remains the modality of choice. Functional near-infrared spectroscopy (fNIRS) is a relatively innovative modality that cannot only characterize hemodynamic profiles of seizures but also allow for long-term recordings. We employ deep learning methods to investigate the benefits of integrating fNIRS measures for seizure detection. We designed a deep recurrent neural network with long short-term memory units and subsequently validated it using the CHBMIT scalp EEG database-a compendium of 896 h of surface EEG seizure recordings. After validating our network using EEG, fNIRS, and multimodal data comprising a corpus of 89 seizures from 40 refractory epileptic patients was used as model input to evaluate the integration of fNIRS measures. Following heuristic hyperparameter optimization, multimodal EEG-fNIRS data provide superior performance metrics (sensitivity and specificity of 89.7% and 95.5%, respectively) in a seizure detection task, with low generalization errors and loss. False detection rates are generally low, with 11.8% and 5.6% for EEG and multimodal data, respectively. Employing multimodal neuroimaging, particularly EEG-fNIRS, in epileptic patients, can enhance seizure detection performance. Furthermore, the neural network model proposed and characterized herein offers a promising framework for future multimodal investigations in seizure detection and prediction.

WearLight: Toward a Wearable, Configurable Functional NIR Spectroscopy System for Noninvasive Neuroimaging

Functional near-infrared spectroscopy (fNIRS) has emerged as an effective brain monitoring technique to measure the hemodynamic response of the cortical surface. Its wide popularity and adoption in recent time attribute to its portability, ease of use, and flexibility in multimodal studies involving electroencephalography. While fNIRS is still emerging on various fronts including hardware, software, algorithm, and applications, it still requires overcoming several scientific challenges associated with brain monitoring in naturalistic environments where the human participants are allowed to move and required to perform various tasks stimulating brain behaviors. In response to these challenges and demands, we have developed a wearable fNIRS system, WearLight that was built upon an Internet-of-Things embedded architecture for onboard intelligence, configurability, and data transmission. In addition, we have pursued detailed research and comparative analysis on the design of the optodes encapsulating an near-infrared light source and a detector into 3-D printed material. We performed rigorous experimental studies on human participants to test reliability, signal-to-noise ratio, and configurability. Most importantly, we observed that WearLight has a capacity to measure hemodynamic responses in various setups including arterial occlusion on the forearm and frontal lobe brain activity during breathing exercises in a naturalistic environment. Our promising experimental results provide an evidence of preliminary clinical validation of WearLight. This encourages us to move toward intensive studies involving brain monitoring.

MAESTROS: A Multiwavelength Time-Domain NIRS System to Monitor Changes in Oxygenation and Oxidation State of Cytochrome-C-Oxidase

We present a multiwavelength, multichannel, time-domain near-infrared spectroscopy system named MAESTROS. This instrument can measure absorption and scattering coefficients and can quantify the concentrations of oxy- and deoxy-haemoglobin ([HbO₂], [HHb]), and oxidation state of cytochrome-c-oxidase ([oxCCO]). This system is composed of a supercontinuum laser source coupled with two acousto-optic tuneable filters. The light is collected by four photomultipliers tubes, connected to a router to redirect the signal to a single time-correlated single-photon counting card. The interface between the system and the tissue is based on optical fibres. This arrangement allows us to resolve up to 16 wavelengths, within the range of 650-900 nm, at a sampling rate compatible with the physiology (from 0.5 to 2 Hz). In this paper, we describe the system and assess its performance based on two specifically designed protocols for photon migration instruments, the basic instrument protocol and nEUROPt protocols, and on a well characterized liquid phantom based on Intralipid and water. Then, the ability to resolve [HbO₂ ], [HHb], and [oxCCO] is demonstrated on a homogeneous liquid phantom, based on blood for [HbO₂], [HHb], and yeast for [oxCCO]. In the future, the system could be used to monitor brain tissue physiology.

Selective photobiomodulation for emotion regulation: model-based dosimetry study

The transcranial photobiomodulation (t-PBM) technique is a promising approach for the treatment of a wide range of neuropsychiatric disorders, including disorders characterized by poor regulation of emotion such as major depressive disorder (MDD). We examine various approaches to deliver red and near-infrared light to the dorsolateral prefrontal cortex (dlPFC) and ventromedial prefrontal cortex (vmPFC) in the human brain, both of which have shown strong relevance to the treatment of MDD. We apply our hardware-accelerated Monte Carlo simulations to systematically investigate the light penetration profiles using a standard adult brain atlas. To better deliver light to these regions-of-interest, we study, in particular, intranasal and transcranial illumination approaches. We find that transcranial illumination at the F3-F4 location (based on 10-20 system) provides excellent light delivery to the dlPFC, while a light source located in close proximity to the cribriform plate is well-suited for reaching the vmPFC, despite the fact that accessing the latter location may require a minimally invasive approach. Alternative noninvasive illumination strategies for reaching vmPFC are also studied and both transcranial illumination at the Fp1-FpZ-Fp2 location and intranasal illumination in the mid-nose region are shown to be valid. Different illumination wavelengths, ranging from 670 to 1064 nm, are studied and the amounts of light energy deposited to a wide range of brain regions are quantitatively compared. We find that 810 nm provided the overall highest energy delivery to the targeted regions. Although our simulations carried out on locations and wavelengths are not designed to be exhaustive, the proposed illumination strategies inform the design of t-PBM systems likely to improve brain emotion regulation, both in clinical research and practice.

Inequality signals in dorsolateral prefrontal cortex inform social preference models

Humans typically display inequality aversion in social situations, which manifests itself as a preference for fairer distributions of resources. However, people differ in the degree to which they dislike being worse off [disadvantageous inequality (DI) aversion] or better off [advantageous inequality (AI) aversion] than others. Competing models explain such behavior by focusing on aversion to payoff differences, maximization of total payoff or reciprocity. Using functional near-infrared spectroscopy, we asked which of these theories could better explain dorsolateral prefrontal cortex (dlPFC) activity while participants accepted or punished fair vs unfair monetary transfers in an anonymous norm compliance task. We found that while all participants exhibited DI aversion, there were substantial differences in preferences for AI, which were strongly predicted by dlPFC activation. Model comparisons revealed that both punishment behavior and prefrontal activity were best explained by a model that allowed for AI seeking rather than imposing aversion. Moreover, enhancing this model by taking into account behavioral response times, as a proxy for choice difficulty, further improved model fits. Our data provide evidence that the dlPFC encodes subjective values of payoff inequality and that this representation is richer than envisaged by standard models of social preferences.

Performance Prediction for a Near-Infrared Spectroscopy-Brain–Computer Interface Using Resting-State Functional Connectivity of the Prefrontal Cortex

One of the most important issues in current brain–computer interface (BCI) research is the prediction of a user’s BCI performance prior to the main BCI session because it would be useful to reduce the time required to determine the BCI paradigm best suited to that user. In electroencephalography (EEG)-BCI research, whether a user has low BCI performance toward a specific BCI paradigm has been estimated using a variety of resting-state EEG features. However, no previous study has attempted to predict the performance of near-infrared spectroscopy (NIRS)-BCI using resting-state NIRS data recorded before the main BCI experiment. In this study, we investigated whether the performance of an NIRS-BCI discriminating a mental arithmetic task from the baseline state could be predicted using resting-state functional connectivity (RSFC) of the prefrontal cortex. The investigation of NIRS signals recorded from 29 participants revealed that the RSFC between bilateral channels in the prefrontal area was negatively correlated with subsequent BCI performance (e.g. a fitted line for the RSFC between L2 and R2 channels explains 41% of BCI performance variation). We expect that our indicator can be used to predict BCI performance of an individual user prior to the main NIRS-BCI experiments, thereby facilitating implementation of more efficient NIRS-BCI systems.

A Modified Common Spatial Pattern Algorithm Customized for Feature Dimensionality Reduction in fNIRS-Based BCIs

Functional near-infrared spectroscopy (fNIRS) is a non-invasive multi-channel imaging tool for assessing brain activities, which has shown its high potential in brain-computer interface (BCI) technique. Most previous studies have focused on constructing high dimensional features from whole channels, adding to the complexity of their classifiers. Another multi-channel source for BCI is electroencephalograph (EEG), which possesses different spatial and temporal features from fNIRS. In EEG field, Common Spatial Pattern (CSP) algorithm is widely used aimed at dimensionality reduction. In our article, we modified it based on the characteristics of fNIRS and evaluated its effectiveness in discriminating Mental Arithmetic (MA) against resting status in an open-access dataset. The Modified Common Spatial Pattern algorithm significantly outperforms CSP algorithm in fNIRS-based BCI and shows its potential in further BCI related explorations.

The Application of Mobile fNIRS in Marketing Research-Detecting the "First-Choice-Brand" Effect

Recent research in the field of "neuro-marketing" shows promise to substantially increase knowledge on marketing issues for example price-perception, advertising efficiency, branding and shopper behaviour. Recently, an innovative and mobile applicable neuroimaging method has been proposed, namely functional near-infrared spectroscopy (fNIRS). However, this method is, in the research field of marketing, still in its infancy and is, consequently, lacking substantial validity. Against this background, this research work applied a convergent validity approach to challenge the validity of (mobile) fNIRS in the field of "neuro-marketing" and consumer neuroscience. More precisely, we aim to replicate a robust and well-investigated neural effect previously detected with fMRI-namely the "first-choice-brand" effect-by using mobile fNIRS. The research findings show that mobile fNIRS appears to be an appropriate neuroimaging method for research in the field of "neuro-marketing" and consumer neuroscience. Additionally, this research work presents guidelines, enabling marketing scholars to utilise mobile fNIRS in their research work.

Cross-section and feasibility study on the non-invasive evaluation of muscle hemodynamic responses in Duchenne muscular dystrophy by using a near-infrared diffuse optical technique

Duchenne muscular dystrophy (DMD) is an X-linked debilitating muscular disease that may decrease nitric oxide (NO) production and lead to functional muscular ischemia. Currently, the 6-minute walk test (6-MWT) and the North Star Ambulatory Assessment (NSAA) are the primary outcome measures in clinical trials, but they are severely limited by the subjective consciousness and mood of patients, and can only be used in older and ambulatory boys. This study proposed using functional near-infrared spectroscopy (fNIRS) to evaluate the dynamic changes in muscle hemodynamic responses (gastrocnemius and forearm muscle) during a 6-MWT and a venous occlusion test (VOT), respectively. Muscle oxygenation of the forearm was evaluated non-invasively before, during and after VOT in all participants (included 30 DMD patients and 30 age-matched healthy controls), while dynamic muscle oxygenation of gastrocnemius muscle during 6-MWT was determined in ambulatory participants (n = 18) and healthy controls (n = 30). The results reveal that impaired muscle oxygenation was observed during 6-MWT in DMD patients that may explain why the DMD patients walked shorter distances than healthy controls. Moreover, the results of VOT implied that worsening muscle function was associated with a lower supply of muscle oxygenation and may provide useful information on the relationship between muscular oxygen consumption and supply for the clinical diagnosis of DMD. Therefore, the method of fNIRS with VOT possesses great potential in future evaluations of DMD patients that implies a good feasibility for clinical application such as for monitoring disease severity of DMD.

Optimal positioning of optodes on the scalp for personalized functional near-infrared spectroscopy investigations

BACKGROUND

Application of functional Near InfraRed Spectroscopy (fNIRS) in neurology is still limited as a good optical coupling and optimized optode coverage of specific brain regions remains challenging, notably for prolonged monitoring.

METHODS

We propose to evaluate a new procedure allowing accurate investigation of specific brain regions. The procedure consists in: (i) A priori maximization of spatial sensitivity of fNIRS measurements targeting specific brain regions, while reducing the number of applied optodes in order to decrease installation time and improve subject comfort. (ii) Utilization of a 3D neuronavigation device and usage of collodion to glue optodes on the scalp, ensuring good optical contact for prolonged investigations. (iii) Local reconstruction of the hemodynamic activity along the cortical surface using inverse modelling.

RESULTS

Using realistic simulations, we demonstrated that maps derived from optimal montage acquisitions showed, after reconstruction, spatial resolution only slightly lower to that of ultra high density montages while significantly reducing the number of optodes. The optimal montages provided overall good quantitative accuracy especially at the peak of the spatially reconstructed map. We also evaluated real motor responses in two healthy subjects and obtained reproducible motor responses over different sessions.

COMPARISON WITH EXISTING METHODS

We are among the first to propose a mathematical optimization strategy, allowing high sensitivity measurements.

CONCLUSIONS

Our results support that using personalized optimal montages should allow to conduct accurate fNIRS studies in clinical settings and realistic lifestyle conditions.

Impact of Healthy Aging on Multifractal Hemodynamic Fluctuations in the Human Prefrontal Cortex

Fluctuations in resting-state cerebral hemodynamics show scale-free behavior over two distinct scaling ranges. Changes in such bimodal (multi) fractal pattern give insight to altered cerebrovascular or neural function. Our main goal was to assess the distribution of local scale-free properties characterizing cerebral hemodynamics and to disentangle the influence of aging on these multifractal parameters. To this end, we obtained extended resting-state records (N = 2¹⁴) of oxyhemoglobin (HbO), deoxyhemoglobin (HbR) and total hemoglobin (HbT) concentration time series with continuous-wave near-infrared spectroscopy technology from the brain cortex. 52 healthy volunteers were enrolled in this study: 24 young (30.6 ± 8.2 years), and 28 elderly (60.5 ± 12.0 years) subjects. Using screening tests on power-law, multifractal noise, and shuffled data sets we evaluated the presence of true multifractal hemodynamics reflecting long-range correlation (LRC). Subsequently, scaling-range adaptive bimodal signal summation conversion (SSC) was performed based on standard deviation (σ) of signal windows across a range of temporal scales (s). Building on moments of different order (q) of the measure, σ(s), multifractal SSC yielded generalized Hurst exponent function, H(q), and singularity spectrum, D(h) separately for a fast and slow component (the latter dominating the highest temporal scales). Parameters were calculated reflecting the estimated measure at s = N (focus), degree of LRC [Hurst exponent, H(2) and maximal Hölder exponent, h_max] and measuring strength of multifractality [full-width-half-maximum of D(h) and ΔH₁₅ = H(−15)−H(15)]. Correlation-based signal improvement (CBSI) enhanced our signal in terms of interpreting changes due to neural activity or local/systemic hemodynamic influences. We characterized the HbO-HbR relationship with the aid of fractal scale-wise correlation coefficient, r_σ(s) and SSC-based multifractal covariance analysis. In the majority of subjects, cerebral hemodynamic fluctuations proved bimodal multifractal. In case of slow component of raw HbT, h_max, and Ĥ(2) were lower in the young group explained by a significantly increased r_σ(s) among elderly at high temporal scales. Regarding the fast component of CBSI-pretreated HbT and that of HbO-HbR covariance, h_max, and focus were decreased in the elderly group. These observations suggest an attenuation of neurovascular coupling reflected by a decreased autocorrelation of the neuronal component concomitant with an accompanying increased autocorrelation of the non-neuronal component in the elderly group.

Optimal wavelengths for subdiffuse scanning laser oximetry of the human retina

Retinal blood vessel oxygenation is considered to be an important marker for numerous eye diseases. Oxygenation is typically assessed by imaging the retinal vessels at different wavelengths using multispectral imaging techniques, where the choice of wavelengths will affect the achievable measurement accuracy. Here, we present a detailed analysis of the error propagation of measurement noise in retinal oximetry, to identify optimal wavelengths that will yield the lowest uncertainty in saturation estimation for a given measurement noise level. In our analysis, we also investigate the effect of hemoglobin packing in discrete blood vessels (pigment packaging), which may result in a nonnegligible bias in saturation estimation if unaccounted for under specific geometrical conditions, such as subdiffuse sampling of smaller blood vessels located deeper within the retina. Our analyses show that using 470, 506, and 592 nm, a fairly accurate estimation of the whole oxygen saturation regime [0 1] can be realized, even in the presence of the pigment packing effect. To validate the analysis, we developed a scanning laser ophthalmoscope to produce high contrast images with a maximum pixel rate of 60 kHz and a maximum 30-deg imaging field of view. Confocal reflectance measurements were then conducted on a tissue-mimicking scattering phantom with optical properties similar to retinal tissue including narrow channels filled with absorbing dyes to mimic blood vessels. By imaging at three optimal wavelengths, the saturation of the dye combination was calculated. The experimental values show good agreement with our theoretical derivations.

Spinal Cord Stimulation Frequency Influences the Hemodynamic Response in Patients with Disorders of Consciousness

Spinal cord stimulation (SCS) is a promising technique for treating disorders of consciousness (DOCs). However, differences in the spatio-temporal responsiveness of the brain under varied SCS parameters remain unclear. In this pilot study, functional near-infrared spectroscopy was used to measure the hemodynamic responses of 10 DOC patients to different SCS frequencies (5 Hz, 10 Hz, 50 Hz, 70 Hz, and 100 Hz). In the prefrontal cortex, a key area in consciousness circuits, we found significantly increased hemodynamic responses at 70 Hz and 100 Hz, and significantly different hemodynamic responses between 50 Hz and 70 Hz/100 Hz. In addition, the functional connectivity between prefrontal and occipital areas was significantly improved with SCS at 70 Hz. These results demonstrated that SCS modulates the hemodynamic responses and long-range connectivity in a frequency-specific manner (with 70 Hz apparently better), perhaps by improving the cerebral blood volume and information transmission through the reticular formation-thalamus-cortex pathway.

Concurrent Changes of Brain Functional Connectivity and Motor Variability When Adapting to Task Constraints

In behavioral neuroscience, the adaptability of humans facing different constraints has been addressed on one side at the brain level, where a variety of functional networks dynamically support the same performance, and on the other side at the behavioral level, where fractal properties in sensorimotor variables have been considered as a hallmark of adaptability. To bridge the gap between the two levels of observation, we have jointly investigated the changes of network connectivity in the sensorimotor cortex assessed by modularity analysis and the properties of motor variability assessed by multifractal analysis during a prolonged tapping task. Four groups of participants had to produce the same tapping performance while being deprived from 0, 1, 2, or 3 sensory feedbacks simultaneously (auditory and/or visual and/or tactile). Whereas tapping performance was not statistically different across groups, the number of brain networks involved and the degree of multifractality of the inter-tap interval series were significantly correlated, increasing as a function of feedback deprivation. Our findings provide first evidence that concomitant changes in brain modularity and multifractal properties characterize adaptations underlying unchanged performance. We discuss implications of our findings with respect to the degeneracy properties of complex systems, and the entanglement of adaptability and effective adaptation.

Investigating optical path and differential pathlength factor in reflectance photoplethysmography for the assessment of perfusion

Photoplethysmography (PPG) is an optical noninvasive technique with the potential for assessing tissue perfusion. The relative time-change in the concentration of oxyhemoglobin and deoxyhemoglobin in the blood can be derived from DC part of the PPG signal. However, the absolute concentration cannot be determined due to the inadequate data on PPG optical paths. The optical path and differential pathlength factor (DPF) for PPG at red (660 nm) and infrared (880 nm) wavelengths were investigated using a heterogeneous Monte Carlo model of the human forearm. Using the simulated DPFs, the absolute time-change in concentrations were determined from PPG signals recorded from the same tissue site. Results were compared with three conditions of approximated DPFs. Results showed the variation of the optical-path and DPF with different wavelengths and source-detector separations. Approximations resulted in significant errors, for example, using NIRS DPF in PPG led to "cross talk" of -0.4297 and 0.060 and an error of 15.16% to 25.18%. Results confirmed the feasibility of using the PPG (DC) for the assessment of tissue perfusion. The study also identified the inappropriateness of the assumption that DPF is independent of wavelength or source-detector separations and set the platform for further studies on investigating optical pathlengths and DPF in PPG.

Measurement of blood-oxygen saturation using a photoacoustic technique in the rabbit hypoxemia model

The golden standard method to obtain accurate blood oxygen saturation is blood gas analysis that needs invasive procedure of blood sampling. Photoacoustic technique enables us to measure real-time blood oxygen saturation without invasive procedure. The aim of this study is to use the photoacoustic technique, an optical method, for accurately determining oxygen saturation in vivo. We measured induced photoacoustic signals of arterial blood in the rabbit model of stable hypoxemia after irradiation at 750 and 800 nm. Oxygen saturation was calculated from the photoacoustic signals using two calibration curves. Calibration curve 1 is a conventional curve derived from the absorbance coefficient of hemoglobin, whereas calibration curve 2 is derived from the photoacoustic signals obtained from the original blood vessel model. Simultaneously, blood-gas analysis was performed to obtain the reference standard of oxygen saturation. Regression analysis and Bland-Altman analysis were performed to assess the accuracy of oxygen saturation obtained using the two methods. The oxygen saturation calculated using calibration curves 1 and 2 showed strong correlations with the reference standard in regression analysis (R = 0.965, 0.964, respectively). The Bland-Altman analysis revealed better agreement and precision with calibration curve 2, whereas there was significant underestimation of values obtained using calibration curve 1. Photoacoustic measurement of oxygen saturation using calibration curve 2 provided an accurate estimate of oxygen saturation, which was similar to that obtained using a portable blood-gas analyzer.

Improvement of Information Transfer Rates Using a Hybrid EEG-NIRS Brain-Computer Interface with a Short Trial Length: Offline and Pseudo-Online Analyses

Electroencephalography (EEG) and near-infrared spectroscopy (NIRS) are non-invasive neuroimaging methods that record the electrical and metabolic activity of the brain, respectively. Hybrid EEG-NIRS brain-computer interfaces (hBCIs) that use complementary EEG and NIRS information to enhance BCI performance have recently emerged to overcome the limitations of existing unimodal BCIs, such as vulnerability to motion artifacts for EEG-BCI or low temporal resolution for NIRS-BCI. However, with respect to NIRS-BCI, in order to fully induce a task-related brain activation, a relatively long trial length (≥10 s) is selected owing to the inherent hemodynamic delay that lowers the information transfer rate (ITR; bits/min). To alleviate the ITR degradation, we propose a more practical hBCI operated by intuitive mental tasks, such as mental arithmetic (MA) and word chain (WC) tasks, performed within a short trial length (5 s). In addition, the suitability of the WC as a BCI task was assessed, which has so far rarely been used in the BCI field. In this experiment, EEG and NIRS data were simultaneously recorded while participants performed MA and WC tasks without preliminary training and remained relaxed (baseline; BL). Each task was performed for 5 s, which was a shorter time than previous hBCI studies. Subsequently, a classification was performed to discriminate MA-related or WC-related brain activations from BL-related activations. By using hBCI in the offline/pseudo-online analyses, average classification accuracies of 90.0 ± 7.1/85.5 ± 8.1% and 85.8 ± 8.6/79.5 ± 13.4% for MA vs. BL and WC vs. BL, respectively, were achieved. These were significantly higher than those of the unimodal EEG- or NIRS-BCI in most cases. Given the short trial length and improved classification accuracy, the average ITRs were improved by more than 96.6% for MA vs. BL and 87.1% for WC vs. BL, respectively, compared to those reported in previous studies. The suitability of implementing a more practical hBCI based on intuitive mental tasks without preliminary training and with a shorter trial length was validated when compared to previous studies.

Resting-state functional connectivity analysis of the mouse brain using intrinsic optical signal imaging of cerebral blood volume dynamics

OBJECTIVE

Resting-state functional connectivity (rsFC) of the human brain is closely related with neurological and psychiatric disorders. Mice are widely used to investigate the physiological mechanisms of such disorders, because of the applicability of invasive experimental techniques. Thus, studies on rsFC of the mouse brain are essential to link physiological mechanisms with these disorders in humans. In this study, we investigated the applicability of intrinsic optical signal imaging of cerebral blood volume (IOSI-CBV) for rsFC analysis of the mouse brain.

APPROACH

Transcranial IOSI-CBV images were collected from the brains of un-anesthetized wild-type mice with a cooled-CCD camera. The time traces of all pixels were averaged to create a global signal (GS). Marginal and partial correlation analyses were performed to estimate the rsFC based on CBV signals both with and without GS removal. The consistency of the results were confirmed by comparing them with to the rsFCs data reported in the previous studies.

MAIN RESULTS

We confirmed that GS correlated with heart rate fluctuation in the FC frequency band. The marginal correlation coefficient of CBV with GS removal was consistent with measurements using conventional optical imaging methods relying on oxygenated hemoglobin concentration and cerebral blood flow.

SIGNIFICANCE

These results suggest the applicability and usefulness of the transcranial IOSI-CBV method to estimate rsFC of the mouse brain.

Eyes-closed hybrid brain-computer interface employing frontal brain activation

Brain-computer interfaces (BCIs) have been studied extensively in order to establish a non-muscular communication channel mainly for patients with impaired motor functions. However, many limitations remain for BCIs in clinical use. In this study, we propose a hybrid BCI that is based on only frontal brain areas and can be operated in an eyes-closed state for end users with impaired motor and declining visual functions. In our experiment, electroencephalography (EEG) and near-infrared spectroscopy (NIRS) were simultaneously measured while 12 participants performed mental arithmetic (MA) and remained relaxed (baseline state: BL). To evaluate the feasibility of the hybrid BCI, we classified MA- from BL-related brain activation. We then compared classification accuracies using two unimodal BCIs (EEG and NIRS) and the hybrid BCI in an offline mode. The classification accuracy of the hybrid BCI (83.9 ± 10.3%) was shown to be significantly higher than those of unimodal EEG-based (77.3 ± 15.9%) and NIRS-based BCI (75.9 ± 6.3%). The analytical results confirmed performance improvement with the hybrid BCI, particularly for only frontal brain areas. Our study shows that an eyes-closed hybrid BCI approach based on frontal areas could be applied to neurodegenerative patients who lost their motor functions, including oculomotor functions.

Multimodal 2D Brain Computer Interface

In this work we used multimodal, non-invasive brain signal recording systems, namely Near Infrared Spectroscopy (NIRS), disc electrode electroencephalography (EEG) and tripolar concentric ring electrodes (TCRE) electroencephalography (tEEG). 7 healthy subjects participated in our experiments to control a 2-D Brain Computer Interface (BCI). Four motor imagery task were performed, imagery motion of the left hand, the right hand, both hands and both feet. The signal slope (SS) of the change in oxygenated hemoglobin concentration measured by NIRS was used for feature extraction while the power spectrum density (PSD) of both EEG and tEEG in the frequency band 8-30Hz was used for feature extraction. Linear Discriminant Analysis (LDA) was used to classify different combinations of the aforementioned features. The highest classification accuracy (85.2%) was achieved by using features from all the three brain signals recording modules. The improvement in classification accuracy was highly significant (p = 0.0033) when using the multimodal signals features as compared to pure EEG features.

Narrative Discourse in Young and Older Adults: Behavioral and NIRS Analyses

Discourse comprehension is at the core of communication capabilities, making it an important component of elderly populations' quality of life. The aim of this study is to evaluate changes in discourse comprehension and the underlying brain activity. Thirty-six participants read short stories and answered related probes in three conditions: micropropositions, macropropositions and situation models. Using near-infrared spectroscopy (NIRS), the variation in oxyhemoglobin (HbO₂) and deoxyhemoglobin (HbR) concentrations was assessed throughout the task. The results revealed that the older adults performed with equivalent accuracy to the young ones at the macroproposition level of discourse comprehension, but were less accurate at the microproposition and situation model levels. Similar to what is described in the compensation-related utilization of neural circuits hypothesis (CRUNCH) model, older participants tended to have greater activation in the left dorsolateral prefrontal cortex while reading in all conditions. Although it did not enable them to perform similarly to younger participants in all conditions, this over-activation could be interpreted as a compensation mechanism.

Simultaneous acquisition of EEG and NIRS during cognitive tasks for an open access dataset

We provide an open access multimodal brain-imaging dataset of simultaneous electroencephalography (EEG) and near-infrared spectroscopy (NIRS) recordings. Twenty-six healthy participants performed three cognitive tasks: 1) n-back (0-, 2- and 3-back), 2) discrimination/selection response task (DSR) and 3) word generation (WG) tasks. The data provided includes: 1) measured data, 2) demographic data, and 3) basic analysis results. For n-back (dataset A) and DSR tasks (dataset B), event-related potential (ERP) analysis was performed, and spatiotemporal characteristics and classification results for 'target' versus 'non-target' (dataset A) and symbol 'O' versus symbol 'X' (dataset B) are provided. Time-frequency analysis was performed to show the EEG spectral power to differentiate the task-relevant activations. Spatiotemporal characteristics of hemodynamic responses are also shown. For the WG task (dataset C), the EEG spectral power and spatiotemporal characteristics of hemodynamic responses are analyzed, and the potential merit of hybrid EEG-NIRS BCIs was validated with respect to classification accuracy. We expect that the dataset provided will facilitate performance evaluation and comparison of many neuroimaging analysis techniques.

Spontaneous activity forms a foundation for odor-evoked activation maps in the rat olfactory bulb

Fluctuations in spontaneous activity have been observed by many neuroimaging techniques, but because these resting-state changes are not evoked by stimuli, it is difficult to determine how they relate to task-evoked activations. We conducted multi-modal neuroimaging scans of the rat olfactory bulb, both with and without odor, to examine interaction between spontaneous and evoked activities. Independent component analysis of spontaneous fluctuations revealed resting-state networks, and odor-evoked changes revealed activation maps. We constructed simulated activation maps using resting-state networks that were highly correlated to evoked activation maps. Simulated activation maps derived by intrinsic optical signal (IOS), which covers the dorsal portion of the glomerular sheet, significantly differentiated one odor's evoked activation map from the other two. To test the hypothesis that spontaneous activity of the entire glomerular sheet is relevant for representing odor-evoked activations, we used functional magnetic resonance imaging (fMRI) to map the entire glomerular sheet. In contrast to the IOS results, the fMRI-derived simulated activation maps significantly differentiated all three odors' evoked activation maps. Importantly, no evoked activation maps could be significantly differentiated using simulated activation maps produced using phase-randomized resting-state networks. Given that some highly organized resting-state networks did not correlate with any odors' evoked activation maps, we posit that these resting-state networks may characterize evoked activation maps associated with odors not studied. These results emphasize that fluctuations in spontaneous activity form a foundation for active processing, signifying the relevance of resting-state mapping to functional neuroimaging.

In vitro validation of measurement of volume elastic modulus using photoplethysmography

Arterial stiffness (AS) is one of the earliest detectable symptoms of cardiovascular diseases and their progression. Current AS measurement methods provide an indirect and qualitative estimation of AS. The purpose of this study is to explore the utilisation of Photoplethysmography (PPG) as a measure of volumetric strain in providing a direct quantification of the Volume Elastic modulus (E_v). An in vitro experimental setup was designed using an arterial model to simulate the human circulation in health (Model 2) and disease (Model 1). Flow, pressure, and PPG signals were recorded continuously under varied conditions of flow dynamics. The obtained E_v values were validated with the gold standard mechanical testing techniques. Values obtained from both methods had no significant difference for both models with a percent error of 0.26% and 1.9% for Model 1 and Model 2, respectively. This study shows that PPG and pressure signals can provide a direct measure of AS in an in vitro setup. With emerging noninvasive pressure measurement methods, this research paves the way for the direct quantification of AS in vivo.