Theoretical and experimental investigation of near-infrared light propagation in a model of the adult head

Cross-modal representation of chewing food in posterior parietal and visual cortex

Even though the oral cavity is not visible, food chewing can be performed without damaging the tongue, oral mucosa, or other intraoral parts, with cross-modal perception of chewing possibly critical for appropriate recognition of its performance. This study was conducted to clarify the relationship of chewing food cross-modal perception with cortex activities based on examinations of the posterior parietal cortex (PPC) and visual cortex during chewing in comparison with sham chewing without food, imaginary chewing, and rest using functional near-infrared spectroscopy. Additionally, the effects of a deafferent tongue dorsum on PPC/visual cortex activities during chewing performance were examined. The results showed that chewing food increased activity in the PPC/visual cortex as compared with imaginary chewing, sham chewing without food, and rest. Nevertheless, those activities were not significantly different during imaginary chewing or sham chewing without food as compared with rest. Moreover, subjects with a deafferent tongue dorsum showed reduced PPC/visual cortex activities during chewing food performance. These findings suggest that chewing of food involves cross-modal recognition, while an oral somatosensory deficit may modulate such cross-modal activities.

Enhancing Classification Accuracy with Integrated Contextual Gate Network: Deep Learning Approach for Functional Near-Infrared Spectroscopy Brain-Computer Interface Application

Brain-computer interface (BCI) systems include signal acquisition, preprocessing, feature extraction, classification, and an application phase. In fNIRS-BCI systems, deep learning (DL) algorithms play a crucial role in enhancing accuracy. Unlike traditional machine learning (ML) classifiers, DL algorithms eliminate the need for manual feature extraction. DL neural networks automatically extract hidden patterns/features within a dataset to classify the data. In this study, a hand-gripping (closing and opening) two-class motor activity dataset from twenty healthy participants is acquired, and an integrated contextual gate network (ICGN) algorithm (proposed) is applied to that dataset to enhance the classification accuracy. The proposed algorithm extracts the features from the filtered data and generates the patterns based on the information from the previous cells within the network. Accordingly, classification is performed based on the similar generated patterns within the dataset. The accuracy of the proposed algorithm is compared with the long short-term memory (LSTM) and bidirectional long short-term memory (Bi-LSTM). The proposed ICGN algorithm yielded a classification accuracy of 91.23 ± 1.60%, which is significantly (p < 0.025) higher than the 84.89 ± 3.91 and 88.82 ± 1.96 achieved by LSTM and Bi-LSTM, respectively. An open access, three-class (right- and left-hand finger tapping and dominant foot tapping) dataset of 30 subjects is used to validate the proposed algorithm. The results show that ICGN can be efficiently used for the classification of two- and three-class problems in fNIRS-based BCI applications.

Comparison of LED- and LASER-based fNIRS technologies to record the human peri‑spinal cord neurovascular response

Recently, functional Near-Infrared Spectroscopy (fNIRS) was applied to obtain, non-invasively, the human peri‑spinal Neuro-Vascular Response (NVR) under a non-noxious electrical stimulation of a peripheral nerve. This method allowed the measurements of changes in the concentration of oxyhemoglobin (O2Hb) and deoxyhemoglobin (HHb) from the peri‑spinal vascular network. However, there is a lack of clarity about the potential differences in perispinal NVR recorded by the different fNIRS technologies currently available. In this work, the two main noninvasive fNIRS technologies were compared, i.e., LED and LASER-based. The recording of the human peri‑spinal NVR induced by non-noxious electrical stimulation of a peripheral nerve was recorded simultaneously at C7 and T10 vertebral levels. The amplitude, rise time, and full width at half maximum duration of the perispinal NVRs were characterized in healthy volunteers and compared between both systems. The main difference was that the LED-based system shows about one order of magnitude higher values of amplitude than the LASER-based system. No statistical differences were found for rise time and for duration parameters (at thoracic level). The comparison of point-to-point wave patterns did not show significant differences between both systems. In conclusion, the peri‑spinal NRV response obtained by different fNIRS technologies was reproducible, and only the amplitude showed differences, probably due to the power of the system which should be considered when assessing the human peri‑spinal vascular network.

Preterm infants variability in cerebral near-infrared spectroscopy measurements in the first 72-h after birth

BACKGROUND

Cerebral near-infrared spectroscopy is a non-invasive tool used to measure regional cerebral tissue oxygenation (rScO2) initially validated in adult and pediatric populations. Preterm neonates, vulnerable to neurologic injury, are attractive candidates for NIRS monitoring; however, normative data and the brain regions measured by the current technology have not yet been established for this population.

METHODS

This study's aim was to analyze continuous rScO2 readings within the first 6-72 h after birth in 60 neonates without intracerebral hemorrhage born at ≤1250 g and/or ≤30 weeks' gestational age (GA) to better understand the role of head circumference (HC) and brain regions measured.

RESULTS

Using a standardized brain MRI atlas, we determined that rScO2 in infants with smaller HCs likely measures the ventricular spaces. GA is linearly correlated, and HC is non-linearly correlated, with rScO2 readings. For HC, we infer that rScO2 is lower in infants with smaller HCs due to measuring the ventricular spaces, with values increasing in the smallest HCs as the deep cerebral structures are reached.

CONCLUSION

Clinicians should be aware that in preterm infants with small HCs, rScO2 displayed may reflect readings from the ventricular spaces and deep cerebral tissue.

IMPACT

Clinicians should be aware that in preterm infants with small head circumferences, cerebral near-infrared spectroscopy readings of rScO2 displayed may reflect readings from the ventricular spaces and deep cerebral tissue. This highlights the importance of rigorously re-validating technologies before extrapolating them to different populations. Standard rScO2 trajectories should only be established after determining whether the mathematical models used in NIRS equipment are appropriate in premature infants and the brain region(s) NIRS sensors captures in this population, including the influence of both gestational age and head circumference.

Effects of atlas-based anatomy on modelled light transport in the neonatal head

Objective.Diffuse optical tomography (DOT) provides a relatively convenient method for imaging haemodynamic changes related to neuronal activity on the cerebral cortex. Due to practical challenges in obtaining anatomical images of neonates, an anatomical framework is often created from an age-appropriate atlas model, which is individualized to the subject based on measurements of the head geometry. This work studies the approximation error arising from using an atlas instead of the neonate's own anatomical model.Approach.We consider numerical simulations of frequency-domain (FD) DOT using two approaches, Monte Carlo simulations and diffusion approximation via finite element method, and observe the variation in (1) the logarithm of amplitude and phase shift measurements, and (2) the corresponding inner head sensitivities (Jacobians), due to varying segmented anatomy. Varying segmentations are sampled by registering 165 atlas models from a neonatal database to the head geometry of one individual selected as the reference model. Prior to the registration, we refine the segmentation of the cerebrospinal fluid (CSF) by separating the CSF into two physiologically plausible layers.Main results.In absolute measurements, a considerable change in the grey matter or extracerebral tissue absorption coefficient was found detectable over the anatomical variation. In difference measurements, a small local 10%-increase in brain absorption was clearly detectable in the simulated measurements over the approximation error in the Jacobians, despite the wide range of brain maturation among the registered models.Significance.Individual-level atlas models could potentially be selected within several weeks in gestational age in DOT difference imaging, if an exactly age-appropriate atlas is not available. The approximation error method could potentially be implemented to improve the accuracy of atlas-based imaging. The presented CSF segmentation algorithm could be useful also in other model-based imaging modalities. The computation of FD Jacobians is now available in the widely-used Monte Carlo eXtreme software.

A pediatric near-infrared spectroscopy brain-computer interface based on the detection of emotional valence

Brain-computer interfaces (BCIs) are being investigated as an access pathway to communication for individuals with physical disabilities, as the technology obviates the need for voluntary motor control. However, to date, minimal research has investigated the use of BCIs for children. Traditional BCI communication paradigms may be suboptimal given that children with physical disabilities may face delays in cognitive development and acquisition of literacy skills. Instead, in this study we explored emotional state as an alternative access pathway to communication. We developed a pediatric BCI to identify positive and negative emotional states from changes in hemodynamic activity of the prefrontal cortex (PFC). To train and test the BCI, 10 neurotypical children aged 8–14 underwent a series of emotion-induction trials over four experimental sessions (one offline, three online) while their brain activity was measured with functional near-infrared spectroscopy (fNIRS). Visual neurofeedback was used to assist participants in regulating their emotional states and modulating their hemodynamic activity in response to the affective stimuli. Child-specific linear discriminant classifiers were trained on cumulatively available data from previous sessions and adaptively updated throughout each session. Average online valence classification exceeded chance across participants by the last two online sessions (with 7 and 8 of the 10 participants performing better than chance, respectively, in Sessions 3 and 4). There was a small significant positive correlation with online BCI performance and age, suggesting older participants were more successful at regulating their emotional state and/or brain activity. Variability was seen across participants in regards to BCI performance, hemodynamic response, and discriminatory features and channels. Retrospective offline analyses yielded accuracies comparable to those reported in adult affective BCI studies using fNIRS. Affective fNIRS-BCIs appear to be feasible for school-aged children, but to further gauge the practical potential of this type of BCI, replication with more training sessions, larger sample sizes, and end-users with disabilities is necessary.

Limb Preference and Skill Level Dependence During the Imagery of a Whole-Body Movement: A Functional Near Infrared Spectroscopy Study

In the past years motor imagery (MI) turned out to be also an innovative and effective tool for motor learning and improvement of sports performance. Whereas many studies investigating sports MI focusing on upper or lower limbs involvement, knowledge about involved neural structures during whole-body movements is still limited. In the present study we investigated brain activity of climbers during a kinesthetic motor imagery (KMI) climbing task with different difficulties by means of functional near infrared spectroscopy (fNIRS). Twenty healthy participants were split into two groups according to their climbing skill level. The aim of the current study is investigating neural correlates of a whole-body sports MI task with an additional focus on skill level dependency. Climbing experts and non-experts imagined bouldering an "easy" and "difficult" route from a first-person perspective while hemodynamic responses were recorded simultaneously. We found significant differences between the two climbing routes, easy and difficult within participants as well as between the two groups of different climbing skill levels. Overall beginners showed increased hemodynamic responses compared to experts in all defined regions of interest (ROI) supporting the claim of the neural efficiency hypothesis (NEH). Even though climbing is a complex, coordinated movement of upper and lower limbs we found a stronger activation focus of the upper limbs, especially of the dominant hand-area, while the foot area seems to be deactivated or inhibited simultaneously. Summarizing, these findings provide novel insights into brain activation during the imagery of a whole-body movement and its relation to climbing expertise.

Combined Non-Invasive Optical Oximeter and Flowmeter with Basic Metrological Equipment

Optical non-invasive diagnostic methods and equipment are used today in many medical disciplines. However, there is still no generally accepted and unifying engineering theory of such systems. Today, they are developed most empirically and do not always have the desired effectiveness in clinics. Among reasons for their insufficient clinical efficiency, we can claim the limited set of measured parameters, the poorly substantiated technical design parameters, and the lack of metrological certification, which all together lead to large uncertainties and inaccuracies in diagnostic data. The purpose of this study is to develop a new instrument for non-invasive optical oximetry by means of substantiating and creating amore informative tissue oximeter with an enhanced number of measured parameters and equipped with the basic metrological tools—imitational measures. The combination of two related optical diagnostic techniques—a tissue oximetry, including a cerebral one, and a fluctuation flowmetry on a single hardware platform—was used. Theoretical modeling of light transport in tissues was applied to substantiate the main technical design parameters of the device. For each measuring channel, relevant imitation measures for metrological verification and adjustment have been proposed. Some common principles for the operation of such equipment are described in the article, as well.

Different brain activation patterns in the prefrontal area between self-paced and high-speed driving tasks

The purpose of this study was to investigate the effects on prefrontal cortex brain activity when participants attempted to stop a car accurately at a stop line when driving at different speeds using functional near-infrared spectroscopy (fNIRS). Twenty healthy subjects with driving experience drove their own cars for a distance of 60 m five times each at their own pace or as fast as possible. The variation in the distance between the stop line and the car was not significantly different between the self-paced and high-speed tasks. However, oxygenated hemoglobin concentration in the prefrontal cortex was significantly higher in the high-speed task than in the self-paced task. These findings suggest that driving at high speed requires more divided attention than driving at self-paced speed, even though the participants were able to stop the car at the same distance from the target. This study shows the advantages and usefulness of fNIRS .

Analyzing Classification Performance of fNIRS-BCI for Gait Rehabilitation Using Deep Neural Networks

This research presents a brain-computer interface (BCI) framework for brain signal classification using deep learning (DL) and machine learning (ML) approaches on functional near-infrared spectroscopy (fNIRS) signals. fNIRS signals of motor execution for walking and rest tasks are acquired from the primary motor cortex in the brain's left hemisphere for nine subjects. DL algorithms, including convolutional neural networks (CNNs), long short-term memory (LSTM), and bidirectional LSTM (Bi-LSTM) are used to achieve average classification accuracies of 88.50%, 84.24%, and 85.13%, respectively. For comparison purposes, three conventional ML algorithms, support vector machine (SVM), k-nearest neighbor (k-NN), and linear discriminant analysis (LDA) are also used for classification, resulting in average classification accuracies of 73.91%, 74.24%, and 65.85%, respectively. This study successfully demonstrates that the enhanced performance of fNIRS-BCI can be achieved in terms of classification accuracy using DL approaches compared to conventional ML approaches. Furthermore, the control commands generated by these classifiers can be used to initiate and stop the gait cycle of the lower limb exoskeleton for gait rehabilitation.

Imaging affective and non-affective touch processing in two-year-old children

Touch is an important component of early parent-child interaction and plays a critical role in the socio-emotional development of children. However, there are limited studies on touch processing amongst children in the age range from one to three years. The present study used frequency-domain diffuse optical tomography (DOT) to investigate the processing of affective and non-affective touch over left frontotemporal brain areas contralateral to the stimulated forearm in two-year-old children. Affective touch was administered by a single stroke with a soft brush over the child's right dorsal forearm at 3 cm/s, while non-affective touch was provided by multiple brush strokes at 30 cm/s. We found that in the insula, the total haemoglobin (HbT) response to slow brushing was significantly greater than the response to fast brushing (slow > fast). Additionally, a region in the postcentral gyrus, Rolandic operculum and superior temporal gyrus exhibited greater response to fast brushing than slow brushing (fast > slow). These findings confirm that an adult-like pattern of haemodynamic responses to affective and non-affective touch can be recorded in two-year-old subjects using DOT. To improve the accuracy of modelling light transport in the two-year-old subjects, we used a published age-appropriate atlas and deformed it to match the exterior shape of each subject's head. We estimated the combined scalp and skull, and grey matter (GM) optical properties by fitting simulated data to calibrated and coupling error corrected phase and amplitude measurements. By utilizing a two-compartment cerebrospinal fluid (CSF) model, the accuracy of estimation of GM optical properties and the localization of activation in the insula was improved. The techniques presented in this paper can be used to study neural development of children at different ages and illustrate that the technology is well-tolerated by most two-year-old children and not excessively sensitive to subject movement. The study points the way towards exciting possibilities in functional imaging of deeper functional areas near sulci in small children.

Measurement of Adult Human Brain Responses to Breath-Holding by Multi-Distance Hyperspectral Near-Infrared Spectroscopy

A major limitation of near-infrared spectroscopy (NIRS) is its high sensitivity to the scalp and low sensitivity to the brain of adult humans. In the present work we used multi-distance hyperspectral NIRS (hNIRS) to investigate the optimal source-detector distances, wavelength ranges, and analysis techniques to separate cerebral responses to 30 s breath-holds (BHs) from the responses in the superficial tissue layer in healthy adult humans. We observed significant responses to BHs in the scalp hemodynamics. Cerebral responses to BHs were detected in the cytochrome C oxidase redox (rCCO) at 4 cm without using data from the short-distance channel. Using the data from the 1 cm channel in the two-layer regression algorithm showed that cerebral hemodynamic and rCCO responses also occurred at 3 cm. We found that the waveband 700–900 nm was optimal for the detection of cerebral responses to BHs in adults.

Brain Light-Tissue Interaction Modelling: Towards a non-invasive sensor for Traumatic Brain Injury

Traumatic brain injury (TBI) is one of the leading causes of death worldwide, yet there is no systematic approach to monitor TBI non-invasively. The main motivation of this work is to create new knowledge relating to light brain interaction using a Monte Carlo Model, which could aid in the development of non-invasive optical sensors for the continuous assessment of TBI. To this aim, a multilayer model tissue-model of adult human head was developed and explored at the near-infrared optical wavelength. Investigation reveals that maximum light (40-50%) is absorbed in the skull and the minimum light is absorbed in the subarachnoid space (0-1%). It was found that the absorbance of light decreases with increasing source-detector separation up to 3cm where light travels through the subarachnoid space, after which the absorbance increases with the increasing separation. Such information will be helpful towards the modelling of neurocritical brain tissue followed by the sensor development.

Near-Infrared Optical Spectroscopy In Vivo Distinguishes Subjects with Alzheimer's Disease from Age-Matched Controls

Background:

Medical imaging methods such as PET and MRI aid clinical assessment of Alzheimer’s disease (AD). Less expensive, less technically demanding, and more widely deployable technologies are needed to expand objective screening for diagnosis, treatment, and research. We previously reported brain tissue near-infrared optical spectroscopy (NIR) in vitro indicating the potential to meet this need.

Objective:

To determine whether completely non-invasive, clinical, NIR in vivo can distinguish AD patients from age-matched controls and to show the potential of NIR as a clinical screen and monitor of therapeutic efficacy.

Methods:

NIR spectra were acquired in vivo. Three groups were studied: autopsy-confirmed AD, control and mild cognitive impairment (MCI). A feature selection approach using the first derivative of the intensity normalized spectra was used to discover spectral regions that best distinguished “AD-alone” (i.e., without other significant neuropathology) from controls. The approach was then applied to other autopsy-confirmed AD cases and to clinically diagnosed MCI cases.

Results:

Two regions about 860 and 895 nm completely separate AD patients from controls and differentiate MCI subjects according to the degree of impairment. The 895 nm feature is more important in separating MCI subjects from controls (ratio-of-weights: 1.3); the 860 nm feature is more important for distinguishing MCI from AD (ratio-of-weights: 8.2).

Conclusion:

These results form a proof of the concept that near-infrared spectroscopy can detect and classify diseased and normal human brain in vivo. A clinical trial is needed to determine whether the two features can track disease progression and monitor potential therapeutic interventions.

Optimization of time domain diffuse correlation spectroscopy parameters for measuring brain blood flow

Significance: Time domain diffuse correlation spectroscopy (TD-DCS) can offer increased sensitivity to cerebral hemodynamics and reduced contamination from extracerebral layers by differentiating photons based on their travel time in tissue. We have developed rigorous simulation and evaluation procedures to determine the optimal time gate parameters for monitoring cerebral perfusion considering instrumentation characteristics and realistic measurement noise. Aim: We simulate TD-DCS cerebral perfusion monitoring performance for different instrument response functions (IRFs) in the presence of realistic experimental noise and evaluate metrics of sensitivity to brain blood flow, signal-to-noise ratio (SNR), and ability to reject the influence of extracerebral blood flow across a variety of time gates to determine optimal operating parameters. Approach: Light propagation was modeled on an MRI-derived human head geometry using Monte Carlo simulations for 765- and 1064-nm excitation wavelengths. We use a virtual probe with a source-detector separation of 1 cm placed in the pre-frontal region. Performance metrics described above were evaluated to determine optimal time gate(s) for different IRFs. Validation of simulation noise estimates was done with experiments conducted on an intralipid-based liquid phantom. Results: We find that TD-DCS performance strongly depends on the system IRF. Among Gaussian pulse shapes, ∼ 300    ps pulse length appears to offer the best performance, at wide gates (500 ps and larger) with start times 400 and 600 ps after the peak of the TPSF at 765 and 1064 nm, respectively, for a 1-s integration time at photon detection rates seen experimentally (600 kcps at 765 nm and 4 Mcps at 1064 nm). Conclusions: Our work shows that optimal time gates satisfy competing requirements for sufficient sensitivity and sufficient SNR. The achievable performance is further impacted by system IRF with ∼ 300    ps quasi-Gaussian pulse obtained using electro-optic laser shaping providing the best results.

Quantitative evaluation of frequency domain measurements in high density diffuse optical tomography

SIGNIFICANCE

High density diffuse optical tomography (HD-DOT) as applied in functional near-infrared spectroscopy (fNIRS) is largely limited to continuous wave (CW) data. Using a single modulation frequency, frequency domain (FD) HD-DOT has recently demonstrated better localization of focal activation as compared to CW data. We show that combining CW and FD measurements and multiple modulation frequencies increases imaging performance in fNIRS.

AIM

We evaluate the benefits of multiple modulation frequencies, combining different frequencies as well as CW data in fNIRS HD-DOT.

APPROACH

A layered model was used, with activation occurring within a cortex layer. CW and FD measurements were simulated at 78, 141, and 203 MHz with and without noise. The localization error, full width half maximum, and effective resolution were evaluated.

RESULTS

Across the average of the three metrics, at 141 MHz, FD performed 8.4% better than CW, and the combination of CW and FD was 21.7% better than CW. FD measurements at 203 MHz performed 5% better than 78 MHz. Moreover, the three combined modulation frequencies of FD and CW performed up to 3.92% better than 141 MHz alone.

CONCLUSIONS

We show that combining CW and FD measurements offers better performance than FD alone, with higher modulation frequencies increasing accuracy. Combining CW and FD measurements at multiple modulation frequencies yields the best overall performance.

Correlating functional near-infrared spectroscopy with underlying cortical regions of 0-, 1-, and 2-year-olds using theoretical light propagation analysis

Significance: The establishment of a light propagation analysis-based scalp-cortex correlation (SCC) between the scalp location of the source-detector (SD) pair and brain regions is essential for measuring functional brain development in the first 2 years of life using functional near-infrared spectroscopy (fNIRS). Aim: We aimed to reveal the optics-based SCC of 0-, 1-, and 2-year-olds (yo) and the suitable SD distance for this age period. Approach: Light propagation analyses using age-appropriate head models were conducted on SD pairs at 10-10 fiducial points on the scalp to obtain optics-based SCC and its metrics: the number of corresponding brain regions ( N C B R ), selectivity and sensitivity of the most likely corresponding brain region (MLCBR), and consistency of the MLCBR across developmental ages. Moreover, we assessed the suitable SD distances for 0-, 1-, and 2-yo by simultaneously considering the selectivity and sensitivity of the MLCBR. Results: Age-related changes in the SCC metrics were observed. For instance, the N C B R of 0-yo was larger than that of 1- and 2-yo. Conversely, the selectivity of 0-yo was lower than that of 1- and 2-yo. The sensitivity of 1-yo was higher than that of 0-yo at 15- to 30-mm SD distances and higher than that of 2-yo at 10-mm SD distance. Notably, the MLCBR of the fiducial points around the longitudinal fissure was inconsistent across age groups. An SD distance between 15 and 25 mm was found to be appropriate for satisfying both sensitivity and selectivity requirements. In addition, this work provides reference tables of optics-based SCC for 0-, 1-, and 2-yo. Conclusions: Optics-based SCC will be informative in designing and explaining child developmental studies using fNIRS. The suitable SD distances were between 15 and 25 mm for the first 2 years of life.

Diffuse optical tomography in the human brain: A briefly review from the neurophysiology to its applications

The present work describes the use of noninvasive diffuse optical tomography (DOT) technology to measure hemodynamic changes, providing relevant information which helps to understand the basis of neurophysiology in the human brain. Advantages such as portability, direct measurements of hemoglobin state, temporal resolution, non‐restricted movements as occurs in magnetic resonance imaging (MRI) devices mean that DOT technology can be used in research and clinical fields. In this review we covered the neurophysiology, physical principles underlying optical imaging during tissue‐light interactions, and technology commonly used during the construction of a DOT device including the source‐detector requirements to improve the image quality. DOT provides 3D cerebral activation images due to complex mathematical models which describe the light propagation inside the tissue head. Moreover, we describe briefly the use of Bayesian methods for raw DOT data filtering as an alternative to linear filters widely used in signal processing, avoiding common problems such as the filter selection or a false interpretation of the results which is sometimes due to the interference of background physiological noise with neural activity.

Targeting brain regions of interest in functional near-infrared spectroscopy-Scalp-cortex correlation using subject-specific light propagation models

Targeting specific brain regions of interest by the accurate positioning of optodes (emission and detection probes) on the scalp remains a challenge for functional near‐infrared spectroscopy (fNIRS). Since fNIRS data does not provide any anatomical information on the brain cortex, establishing the scalp‐cortex correlation (SCC) between emission‐detection probe pairs on the scalp and the underlying brain regions in fNIRS measurements is extremely important. A conventional SCC is obtained by a geometrical point‐to‐point manner and ignores the effect of light scattering in the head tissue that occurs in actual fNIRS measurements. Here, we developed a sensitivity‐based matching (SBM) method that incorporated the broad spatial sensitivity of the probe pair due to light scattering into the SCC for fNIRS. The SCC was analyzed between head surface fiducial points determined by the international 10–10 system and automated anatomical labeling brain regions for 45 subject‐specific head models. The performance of the SBM method was compared with that of three conventional geometrical matching (GM) methods. We reveal that the light scattering and individual anatomical differences in the head affect the SCC, which indicates that the SBM method is compulsory to obtain the precise SCC. The SBM method enables us to evaluate the activity of cortical regions that are overlooked in the SCC obtained by conventional GM methods. Together, the SBM method could be a promising approach to guide fNIRS users in designing their probe arrangements and in explaining their measurement data.

Performance Improvement for Detecting Brain Function Using fNIRS: A Multi-Distance Probe Configuration With PPL Method

To improve the spatial resolution of imaging and get more effective brain function information, a multi-distance probe configuration with three distances (28.2, 40, and 44.7 mm) and 52 channels is designed. At the same time, a data conversion method of modified Beer–Lambert law (MBLL) with partial pathlength (PPL) is proposed. In the experiment, three kinds of tasks, grip of left hand, grip of right hand, and rest, are performed with eight healthy subjects. First, with a typical single-distance probe configuration (30 mm, 24 channels), the feasibility of the proposed MBLL with PPL is preliminarily validated. Further, the characteristic of the proposed method is evaluated with the multi-distance probe configuration. Compared with MBLL with differential pathlength factor (DPF), the proposed MBLL with PPL is able to acquire more obvious concentration change and can achieve higher classification accuracy of the three tasks. Then, with the proposed method, the performance of the multi-distance probe configuration is discussed. Results show that, compared with a single distance, the combination of the three distances has better spatial resolution and could explore more accurate brain activation information. Besides, the classification accuracy of the three tasks obtained with the combination of three distances is higher than that of any combination of two distances. Also, with the combination of the three distances, the two-class classification between different tasks is carried out. Both theory and experimental results demonstrate that, using multi-distance probe configuration and the MBLL with PPL method, the performance of brain function detected by NIRS can be improved.

A comparison between plausible models in layered turbid media with geometrical variations applying a Bayesian selection criterion

One possible application of Near Infrared techniques is to analyze human brain metabolic activity. Currently used models take into account the layered structure of the human head but, usually, they do not consider the non-planar surface of some of the boundaries, i.e. gray matter, which results in a much more complex structure, thus leading to more sophisticated models and longer calculation times. The main objective of this work is to determine if it is worth to replace a planar layered structure by a non-planar one. To this end we implement a Bayesian-based quantitative methodology for choosing between two competitive models describing light propagation in layered turbid media. Experiments of time-resolved diffuse reflectance measurements are performed in layered phantoms and complemented with numerical calculations. The resulting Distributions of Time of Flight of both models are compared using Bayesian model selection analysis. The non-planar interface was introduced in the simulations by a simple surface parametrization. Results suggest that, under certain conditions, a multilayer model with planar boundaries is good enough.

Anatomical and physiological variables influencing measurement of regional cerebral oxygen saturation by near infrared spectroscopy using the Sensmart Model X-100TM

The Sensmart Model X-100 (Nonin Medical Inc, Plymouth, MN, USA) is a relatively new device that possesses two sets of emitters and detectors and uses near infrared spectroscopy (NIRS) to measure regional cerebral oxygen saturation (rSO₂). The value of rSO₂ obtained by other NIRS devices is affected by physiological and anatomical variables such as hemoglobin concentration, area of cerebrospinal fluid (CSF) layer and skull thickness. The effects of these variables have not yet been determined in measurement of rSO₂ by Sensmart Model X-100. We examined the effects of area of CSF, hemoglobin concentration, and skull thickness on the values of rSO₂ measured by Sensmart Model X-100 and tissue oxygen index (TOI) measured by NIRO-200NX (Hamamatsu Photonix, Hamamatsu, Japan). Forty neurosurgical, cardiac and vascular surgical patients who underwent preoperative computed tomographic (CT) scan of the brain were enrolled in this study. Regional cerebral oxygen saturation (rSO₂) at the forehead was measured sequentially by NIRO-200NX and by Sensmart Model X-100. Simultaneously, mean arterial pressure, hemoglobin concentration, and partial pressure of carbon dioxide in arterial blood (PaCO₂) were measured. To evaluate the effects of anatomical factors on rSO₂, we measured skull thickness and area of CSF layer using CT images of the brain. Multiple regression analysis was used to examine the relationships between the rSO₂ values and anatomical and physiological factors. The area of the CSF layer and hemoglobin concentration had significant associations with rSO₂ measured by the Sensmart Model X-100, whereas none of the studied variables was significantly associated with TOI. The measurement of rSO₂ by Sensmart Model X-100 is not affected by the skull thickness of patients. Area of the CSF layer and hemoglobin concentration may be the main biases in measurement of rSO₂ by Sensmart Model X-100.

Dual wavelength spread-spectrum time-resolved diffuse optical instrument for the measurement of human brain functional responses

Near-infrared spectroscopy has proven to be a valuable method to monitor tissue oxygenation and haemodynamics non-invasively and in real-time. Quantification of such parameters requires measurements of the time-of-flight of light through tissue, typically achieved using picosecond pulsed lasers, with their associated cost, complexity, and size. In this work, we present an alternative approach that employs spread-spectrum excitation to enable the development of a small, low-cost, dual-wavelength system using vertical-cavity surface-emitting lasers. Since the optimal wavelengths and drive parameters for optical spectroscopy are not served by commercially available modules as used in our previous single-wavelength demonstration platform, we detail the design of a custom instrument and demonstrate its performance in resolving haemodynamic changes in human subjects during apnoea and cognitive task experiments.

NICA: A Novel Toolbox for Near-Infrared Spectroscopy Calculations and Analyses

Functional near-infrared spectroscopy (fNIRS) measures the functional activity of the cerebral cortex. The concentration changes of oxygenated (oxy-Hb) and deoxygenated hemoglobin (deoxy-Hb) can be detected and associated with activation of the cortex in the investigated area (neurovascular coupling). Recorded signals of hemodynamic responses may contain influences from physiological signals (systemic influences, physiological artifacts) which do not originate from the cerebral cortex activity. The physiological artifacts contain the blood pressure (BP), respiratory patterns, and the pulsation of the heart. In order to perform a comprehensive analysis of recorded fNIRS data, a proper correction of these physiological artifacts is necessary. This article introduces NICA - a novel toolbox for near-infrared spectroscopy calculations and analyses based on MATLAB. With NICA it is possible to process and visualize fNIRS data, including different signal processing methods for physiological artifact correction. The artifact correction methods used in this toolbox are common average reference (CAR), independent component analysis (ICA), and transfer function (TF) models. A practical example provides results from a study, where NICA was used for analyzing the measurement data, in order to demonstrate the signal processing steps and the physiological artifact correction. The toolbox was developed for fNIRS data recorded with the NIRScout 1624 measurement device and the corresponding recording software NIRStar.

Prefrontal functional connectivity analysis of cognitive decline for early diagnosis of mild cognitive impairment: a functional near-infrared spectroscopy study

Cognitive decline (CD) is a major symptom of mild cognitive impairment (MCI). Patients with MCI have an increased likelihood of developing Alzheimer's disease (AD). Although a cure for AD is currently lacking, medication therapies and/or daily training in the early stage can alleviate disease progression and improve patients' quality of life. Accordingly, investigating CD-related biomarkers via brain imaging devices is crucial for early diagnosis. In particular, "portable" brain imaging devices enable frequent diagnostic checks as a routine clinical tool, and therefore increase the possibility of early AD diagnosis. This study aimed to comprehensively investigate functional connectivity (FC) in the prefrontal cortex measured by a portable functional near-infrared spectroscopy (fNIRS) device during a working memory (WM) task known as the delayed matching to sample (DMTS) task. Differences in prefrontal FC between healthy control (HC) (n = 23) and CD groups (n = 23) were examined. Intra-group analysis (one-sample t-test) revealed significantly greater prefrontal FC, especially left- and inter-hemispheric FC, in the CD group than in the HC. These observations could be due to a compensatory mechanism of the prefrontal cortex caused by hippocampal degeneration. Inter-group analysis (unpaired two-sample t-test) revealed significant intergroup differences in left- and inter-hemispheric FC. These attributes may serve as a novel biomarker for early detection of MCI. In addition, our findings imply that portable fNIRS devices covering the prefrontal cortex may be useful for early diagnosis of MCI.

MBLL with weighted partial path length for multi-distance probe configuration of fNIRS

Functional near-infrared spectroscopy (fNIRS) has broad prospects in both clinical application and brain-computer interface. To improve the spatial resolution, modified Beer-Lambert law with weighted partial optical path length (wMBLL) is proposed for multi-distance probe configuration. Taking both surface tissue layers and deep tissue layers into consideration, the partial optical path length is estimated as a function of the distance between source and detector. Besides, a multi-distance, 15mm and 30mm, probe configuration is designed, which approximates a rectangle. Constructed with 9 sources and 14 detectors, 40 channels are produced, including 20 short short-separation channel and 20 long-separation channel. Also, experiment is implemented with left hand grip-stretch movement and involves five healthy subjects. The concentration of HbO is used to image the brain activation map. Results demonstrate that, compared with the conventional method, the proposed wMBLL method is effective to detect brain activity with higher spatial resolution.

Investigation of the source-detector separation in near infrared spectroscopy for healthy and clinical applications

Understanding near infrared light propagation in tissue is vital for designing next generation optical brain imaging devices. Monte Carlo (MC) simulations provide a controlled mechanism to characterize and evaluate contributions of diverse near infrared spectroscopy (NIRS) sensor configurations and parameters. In this study, we developed a multilayer adult digital head model under both healthy and clinical settings and assessed light-tissue interaction through MC simulations in terms of partial differential pathlength, mean total optical pathlength, diffuse reflectance, detector light intensity and spatial sensitivity profile of optical measurements. The model incorporated four layers: scalp, skull, cerebrospinal-fluid and cerebral cortex with and without a customizable lesion for modeling hematoma of different sizes and depths. The effect of source-detector separation (SDS) on optical measurements' sensitivity to brain tissue was investigated. Results from 1330 separate simulations [(4 lesion volumes × 4 lesion depths for clinical +3 healthy settings) × 7 SDS × 10 simulation = 1330)] each with 100 million photons indicated that selection of SDS is critical to acquire optimal measurements from the brain and recommended SDS to be 25 to 35 mm depending on the wavelengths to obtain optical monitoring of the adult brain function. The findings here can guide the design of future NIRS probes for functional neuroimaging and clinical diagnostic systems.

Penetration Profiles of Visible and Near-Infrared Lasers and Light-Emitting Diode Light Through the Head Tissues in Animal and Human Species: A Review of Literature

Background and objective: Photobiomodulation (PBM) therapy is a promising and noninvasive approach to stimulate neuronal function and improve brain repair. The optimization of PBM parameters is important to maximize effectiveness and tolerability. Several studies have reported on the penetration of visible-to-near-infrared (NIR) light through various animal and human tissues. Scientific findings on the penetration of PBM light vary, likely due to use of different irradiation parameters and to different characteristics of the subject such as species, age, and gender. Materials and methods: In this article, we review published data on PBM penetration through the tissues of the head in both animal and human species. The patterns of visible-to-NIR light penetration are summarized based on the following study specifications: wavelength, coherence, operation mode, beam type and size, irradiation site, species, age, and gender. Results: The average penetration of transcranial red/NIR (630-810 nm) light ranged 60-70% in C57BL/6 mouse (skull), 1-10% in BALB/c mouse (skull), 10-40% in Sprague-Dawley rats (scalp plus skull), 20% in Oryctolagus cuniculus rabbit (skull), 0.11% in pig (scalp plus skull), and 0.2-10% in humans (scalp plus skull). The observed variation in the reported values is due to the difference in factors (e.g., wavelengths, light coherence, tissue thickness, and anatomic irradiation site) used by researchers. It seems that these data challenge the applicability of the animal model data on transcranial PBM to humans. Nevertheless, two animal models seem particularly promising, as they approximate penetration in humans: (I) Penetration of 808 nm laser through the scalp plus skull was 0.11% in the pig head; (II) Penetration of 810 nm laser through intact skull was 1.75% in BALB/c mouse. Conclusions: In conclusion, it is worthwhile mentioning that since the effectiveness of brain PBM is closely dependent on the amount of light energy reaching the target neurons, further quantitative estimation of light penetration depth should be performed to validate the current findings.

FullMonteCUDA: a fast, flexible, and accurate GPU-accelerated Monte Carlo simulator for light propagation in turbid media

Optimizing light delivery for photodynamic therapy, quantifying tissue optical properties or reconstructing 3D distributions of sources in bioluminescence imaging and absorbers in diffuse optical imaging all involve solving an inverse problem. This can require thousands of forward light propagation simulations to determine the parameters to optimize treatment, image tissue or quantify tissue optical properties, which is time-consuming and computationally expensive. Addressing this problem requires a light propagation simulator that produces results quickly given modelling parameters. In previous work, we developed FullMonteSW: currently the fastest, tetrahedral-mesh, Monte Carlo light propagation simulator written in software. Additional software optimizations showed diminishing performance improvements, so we investigated hardware acceleration methods. This work focuses on FullMonteCUDA: a GPU-accelerated version of FullMonteSW which targets NVIDIA GPUs. FullMonteCUDA has been validated across several benchmark models and, through various GPU-specific optimizations, achieves a 288-936x speedup over the single-threaded, non-vectorized version of FullMonteSW and a 4-13x speedup over the highly optimized, hand-vectorized and multi-threaded version. The increase in performance allows inverse problems to be solved more efficiently and effectively.

Approach to optimize 3-dimensional brain functional activation image with high resolution: a study on functional near-infrared spectroscopy

In this study, 3-dimensional (3-D) enhanced brain-function-map generation and estimation methodology is presented. Optical signals were modelled in the form of numerical optimization problem to infer the best existing waveform of canonical hemodynamic response function. Inter-channel activity patterns were also estimated. The estimation of activation of inter-channel gap depends on the minimization of generalized cross-validation. 3-D brain activation maps were produced through inverse discrete cosine transform. The proposed algorithm acquired significant results for 3-D functional maps with high resolution, in comparison with that of 2-D functional t-maps. A comprehensive analysis by exhibiting images corresponding to several layers has also been appended.

Origin of improved depth penetration in dual-axis optical coherence tomography: a Monte Carlo study

Recent studies have demonstrated that extended imaging depth can be achieved using dual-axis optical coherence tomography (DA-OCT). By illuminating and collecting at an oblique angle, multiple forward scattered photons from large probing depths are preferentially detected. However, the mechanism behind the enhancement of imaging depth needs further illumination. Here, the signal of a DA-OCT system is studied using a Monte Carlo simulation. We modeled light transport in tissue and recorded the spatial and angular distribution of photons exiting the tissue surface. Results indicate that the spatial separation and offset angle created by the non-telecentric scanning configuration promote the collection of more deeply propagating photons than conventional on-axis OCT.

Non-invasive methods for measuring vascular changes in neurovascular headaches

Vascular changes during spontaneous headache attacks have been studied over the last 30 years. The interest in cerebral vessels in headache research was initially due to the hypothesis of cerebral vessels as the pain source. Here, we review the knowledge gained by measuring the cerebral vasculature during spontaneous primary headache attacks with the use of single photon emission tomography (SPECT), positron emission tomography (PET), magnetic resonance imaging (MRA) and transcranial Doppler (TCD). Furthermore, the use of near-infrared spectroscopy in headache research is reviewed. Existing TCD studies of migraine and other headache disorders do not provide solid evidence for cerebral blood flow velocity changes during spontaneous attacks of migraine headache. SPECT studies have clearly shown cortical vascular changes following migraine aura and the differences between migraine with aura compared to migraine without aura. PET studies have shown focal activation in brain structures related to headache, but whether the changes are specific to different primary headaches have yet to be demonstrated. MR angiography has shown precise changes in large cerebral vessels during spontaneous migraine without aura attacks. Future development in more precise imaging methods may further elucidate the pathophysiological mechanisms in primary headaches.

Time-Domain Near-Infrared Spectroscopy and Imaging: A Review

This article reviews the past and current statuses of time-domain near-infrared spectroscopy (TD-NIRS) and imaging. Although time-domain technology is not yet widely employed due to its drawbacks of being cumbersome, bulky, and very expensive compared to commercial continuous wave (CW) and frequency-domain (FD) fNIRS systems, TD-NIRS has great advantages over CW and FD systems because time-resolved data measured by TD systems contain the richest information about optical properties inside measured objects. This article focuses on reviewing the theoretical background, advanced theories and methods, instruments, and studies on clinical applications for TD-NIRS including some clinical studies which used TD-NIRS systems. Major events in the development of TD-NIRS and imaging are identified and summarized in chronological tables and figures. Finally, prospects for TD-NIRS in the near future are briefly described.

Is it possible to measure hemodynamic changes in the prefrontal cortex through the frontal sinus using continuous wave DOT systems?

The present work shows the capability of near infrared (NIR) light to reach the cerebral cortex through the frontal sinus using continuous-wave techniques (CW-DOT) in a dual study. On the one hand, changes in time during the tracking of a blood dye in the prefrontal cortex were monitored. On the other hand, hemodynamic changes induced by low frequency of transcranial magnetic stimulation applied on the prefrontal cortex were recorded. The results show how NIR light projected through the frontal sinus reaches the cerebral cortex target, providing enough information to have a reliable measurement of cortical hemodynamic changes using CW-DOT.

Optimizing interstitial photodynamic therapy with custom cylindrical diffusers

Interstitial photodynamic therapy (iPDT) has shown promise recently as a minimally invasive cancer treatment, partially due to the development of non-toxic photosensitizers in the absence of activation light. However, a major challenge in iPDT is the pre-treatment planning process that specifies the number of diffusers needed, along with their positions and allocated powers, to confine the light distribution to the target volume as much as possible. In this work, a new power allocation algorithm for cylindrical light diffusers including those that can produce customized longitudinal (tailored) emission profiles is introduced. The proposed formulation is convex to guarantee the minimum over-dose possible on the surrounding organs-at-risk. The impact of varying the diffuser lengths and penetration angles on the quality of the plan is evaluated. The results of this study are demonstrated for different photosensitizers activated at different wavelengths and simulated on virtual tumors modeling virtual glioblastoma multiforme cases. Results show that manufacturable cylindrical diffusers with tailored emission profiles can significantly outperform those with conventional flat profiles with an average damage reduction on white matter of 15% to 55% and on gray matter of 23% to 58%.

Measuring Cortical Activity During Auditory Processing with Functional Near-Infrared Spectroscopy

Functional near-infrared spectroscopy (fNIRS) is an optical, non-invasive neuroimaging technique that investigates human brain activity by calculating concentrations of oxy- and deoxyhemoglobin. The aim of this publication is to review the current state of the art as to how fNIRS has been used to study auditory function. We address temporal and spatial characteristics of the hemodynamic response to auditory stimulation as well as experimental factors that affect fNIRS data such as acoustic and stimulus-driven effects. The rising importance that fNIRS is generating in auditory neuroscience underlines the strong potential of the technology, and it seems likely that fNIRS will become a useful clinical tool.

The association between skin auto-fluorescence of palmoplantar sites and microvascular complications in Asian patients with type 2 diabetes mellitus

Skin auto-fluorescence (SAF) has generated broad interest about the prospects for non-invasive advanced glycation end product assessment and its direct interplay with the development of microvascular complications, but clinical application of the existing SAF measuring of non-palmoplantar sites in non-Caucasian subjects with dark skin type is still controversial. Here, we tested the diabetic complication screening performance of a novel SAF measuring system in Asian type 2 diabetes mellitus (T2DM) subjects. A total of 166 Korean patients with T2DM were enrolled in this study and palmoplantar SAF was measured by a newly developed transmission-geometry noninvasive optical system. We found that transmitted SAF values of palmoplantar sites, 1st dorsal interossei muscles of the hand, in a complication group were significantly higher than in a non-complication group while no differences were observed between the two groups in reflected SAF of non-palmoplantar sites. The transmitted SAF values of palmoplantar sites were dramatically increased in subjects with multiple complications and were tightly correlated with the duration of microvascular complications. In conclusion, the SAF measurement in the palmoplantar sites with a non-invasive transmission-geometry optical system provided better microvascular complication screening performance compared to the SAF measurement of non-palmoplantar sites specifically in Asian T2DM subjects.

Explicit Performance in Girls and Implicit Processing in Boys: A Simultaneous fNIRS-ERP Study on Second Language Syntactic Learning in Young Adolescents

Learning a second language (L2) proceeds with individual approaches to proficiency in the language. Individual differences including sex, as well as working memory (WM) function appear to have strong effects on behavioral performance and cortical responses in L2 processing. Thus, by considering sex and WM capacity, we examined neural responses during L2 sentence processing as a function of L2 proficiency in young adolescents. In behavioral tests, girls significantly outperformed boys in L2 tests assessing proficiency and grammatical knowledge, and in a reading span test (RST) assessing WM capacity. Girls, but not boys, showed significant correlations between L2 tests and RST scores. Using functional near-infrared spectroscopy (fNIRS) and event-related potential (ERP) simultaneously, we measured cortical responses while participants listened to syntactically correct and incorrect sentences. ERP data revealed a grammaticality effect only in boys in the early time window (100–300 ms), implicated in phrase structure processing. In fNIRS data, while boys had significantly increased activation in the left prefrontal region implicated in syntactic processing, girls had increased activation in the posterior language-related region involved in phonology, semantics, and sentence processing with proficiency. Presumably, boys implicitly focused on rule-based syntactic processing, whereas girls made full use of linguistic knowledge and WM function. The present results provide important fundamental data for learning and teaching in L2 education.

Cortical activation patterns to spatially presented pure tone stimuli with different intensities measured by functional near-infrared spectroscopy

Functional near-infrared spectroscopy (fNIRS) is an emerging technique for the assessment of functional activity of the cerebral cortex. Recently fNIRS was also envisaged as a novel neuroimaging approach for measuring the auditory cortex activity in the field of in auditory diagnostics. This study aimed to investigate differences in brain activity related to spatially presented sounds with different intensities in 10 subjects by means of functional near-infrared spectroscopy (fNIRS). We found pronounced cortical activation patterns in the temporal and frontal regions of both hemispheres. In contrast to these activation patterns, we found deactivation patterns in central and parietal regions of both hemispheres. Furthermore our results showed an influence of spatial presentation and intensity of the presented sounds on brain activity in related regions of interest. These findings are in line with previous fMRI studies which also reported systematic changes of activation in temporal and frontal areas with increasing sound intensity. Although clear evidence for contralaterality effects and hemispheric asymmetries were absent in the group data, these effects were partially visible on the single subject level. Concluding, fNIRS is sensitive enough to capture differences in brain responses during the spatial presentation of sounds with different intensities in several cortical regions. Our results may serve as a valuable contribution for further basic research and the future use of fNIRS in the area of central auditory diagnostics.

Human subarachnoid space width oscillations in the resting state

Abnormal cerebrospinal fluid (CSF) pulsatility has been implicated in patients suffering from various diseases, including multiple sclerosis and hypertension. CSF pulsatility results in subarachnoid space (SAS) width changes, which can be measured with near-infrared transillumination backscattering sounding (NIR-T/BSS). The aim of this study was to combine NIR-T/BSS and wavelet analysis methods to characterise the dynamics of the SAS width within a wide range of frequencies from 0.005 to 2 Hz, with low frequencies studied in detail for the first time. From recordings in the resting state, we also demonstrate the relationships between SAS width in both hemispheres of the brain, and investigate how the SAS width dynamics is related to the blood pressure (BP). These investigations also revealed influences of age and SAS correlation on the dynamics of SAS width and its similarity with the BP. Combination of NIR-T/BSS and time-frequency analysis may open up new frontiers in the understanding and diagnosis of various neurodegenerative and ageing related diseases to improve diagnostic procedures and patient prognosis.

Automatic interstitial photodynamic therapy planning via convex optimization

Finding a high-quality treatment plan is an essential, yet difficult, stage of Photodynamic therapy (PDT) as it will determine the therapeutic efficacy in eradicating malignant tumors. A high-quality plan is patient-specific, and provides clinicians with the number of fiber-based spherical diffusers, their powers, and their interstitial locations to deliver the required light dose to destroy the tumor while minimizing the damage to surrounding healthy tissues. In this work, we propose a general convex light source power allocation algorithm that, given light source locations, guarantees optimality of the resulting solution in minimizing the over/under-dosage of volumes of interest. Furthermore, we provide an efficient framework for source selection with concomitant power reallocation to achieve treatment plans with a clinically feasible number of sources and comparable quality. We demonstrate our algorithms on virtual test cases that model glioblastoma multiforme tumors, and evaluate the performance of four different photosensitizers with different activation wavelengths and specific tissue uptake ratios. Results show an average reduction of the damage to organs-at-risk (OAR) by 29% to 31% with comparable runtime to existing power allocation techniques.

Prefrontal hemodynamic changes measured using near-infrared spectroscopy during the Valsalva maneuver in patients with orthostatic intolerance

The Valsalva maneuver (VM) with beat-to-beat blood pressure and heart rate monitoring are used to evaluate orthostatic intolerance (OI). However, they lack the ability to detect cerebral hemodynamic changes, which may be a cause of OI symptoms. Therefore, we utilized near-infrared spectroscopy during VM. Patients with OI symptoms and normal healthy subjects were recruited. Patients were subgrouped according to VM results: patients with normal VM (NVM) and abnormal VM (AbVM). Oxyhemoglobin (HbO), deoxyhemoglobin, and total hemoglobin changes were measured at four different source-detector distances (SD) (15, 30, 36, and 45 mm), and latency, amplitude, duration, and integrated total signal were calculated. Those parameters were compared between a normal healthy control (HC) group and the two OI patient subgroups. We found that HbO increment latency at 30-mm SD in the HC, NVM, and AbVM groups was as follows: [Formula: see text], [Formula: see text], and [Formula: see text], respectively ([Formula: see text]). Among the four parameters we evaluated, latency of HbO increment was the best marker for differentiating OI.

Graph theoretical approach to functional connectivity in prefrontal cortex via fNIRS

Functional near-infrared spectroscopy (fNIRS) has been proposed as an affordable, fast, and robust alternative to many neuroimaging modalities yet it still has long way to go to be adapted in the clinic. One request from the clinicians has been the delivery of a simple and straightforward metric (a so-called biomarker) from the vast amount of data a multichannel fNIRS system provides. We propose a simple-straightforward signal processing algorithm derived from [Formula: see text] data collected during a modified version of the color-word matching Stroop task that consists of three different conditions. The algorithm starts with a wavelet-transform-based preprocessing, then uses partial correlation analysis to compute the functional connectivity matrices at each condition and then computes the global efficiency values. To this end, a continuous wave 16 channels fNIRS device (ARGES Cerebro, Hemosoft Inc., Turkey) was used to measure the changes in [Formula: see text] concentrations from 12 healthy volunteers. We have considered 10% of strongest connections in each network. A strong Stroop interference effect was found between the incongruent against neutral condition ([Formula: see text]) while a similar significance was observed for the global efficiency values decreased from neutral to congruent to incongruent conditions [[Formula: see text], [Formula: see text]]. The findings bring us closer to delivering a biomarker derived from fNIRS data that can be reliably and easily adopted by the clinicians.

The role of expectation in multisensory body representation - neural evidence

Sensory events contribute to body ownership, the feeling that the body belongs to me. However, the encoding of sensory events is not only reactive, but also proactive in that our brain generates prediction about forthcoming stimuli. In previous studies, we have shown that prediction of sensory events is a sufficient condition to induce the sense of body ownership. In this study, we investigated the underlying neural mechanisms. Participants were seated with their right arm resting upon a table just below another smaller table. Hence, the real hand was hidden from the participant's view and a life-sized rubber model of a right hand was placed on the small table in front of them. Participants observed a wooden plank while approaching - without touching - the rubber hand. We measured the phenomenology of the illusion by means of questionnaire. Neural activity was recorded by means of near-infrared spectroscopy (fNIRS). Results showed higher activation of multisensory parietal cortices in the rubber hand illusion induced by touch expectation. Furthermore, such activity was correlated with the subjective feeling of owning the rubber hand. Our results enrich current models of body ownership suggesting that our multisensory brain regions generate prediction on what could be my body and what could not. This finding might have interesting implications in all those cases in which body representation is altered, anorexia, bulimia nervosa and obesity, among others.

Epidermal Inorganic Optoelectronics for Blood Oxygen Measurement

Flexible and stretchable optoelectronics, built-in inorganic semiconductor materials, offer a wide range of unprecedented opportunities and will redefine the conventional rigid optoelectronics in biological application and medical measurement. However, a significant bottleneck lies in the brittleness nature of rigid semiconductor materials and the performance's extreme sensitivity to the light intensity variation due to human skin deformation while measuring physical parameters. In this study, the authors demonstrate a systematic strategy to design an epidermal inorganic optoelectronic device by using specific strain-isolation design, nanodiamond thinning, and hybrid transfer printing. The authors propose all-in-one suspension structure to achieve the stretchability and conformability for surrounding environment, and they propose a two-step transfer printing method for hybrid integrating III-V group emitting elements, Si-based photodetector, and interconnects. Owing to the excellent flexibility and stretchability, such device is totally conformal to skin and keeps the constant light transmission between emitting element and photodetector as well as the signal stability due to skin deformation. This method opens a route for traditional inorganic optoelectronics to achieve flexibility and stretchability and improve the performance of optoelectronics for biomedical application.

Challenges of implementing a personalized mental task near-infrared spectroscopy brain-computer interface for a non-verbal young adult with motor impairments

PURPOSE

Near-infrared spectroscopy brain-computer interfaces (NIRS-BCIs) have been proposed as potential motor-free communication pathways. This paper documents the challenges of implementing an NIRS-BCI with a non-verbal, severely and congenitally impaired, but cognitively intact young adult.

METHODS

A 5-session personalized mental task NIRS-BCI training paradigm was invoked, whereby participant-specific mental tasks were selected either by the researcher or by the user, on the basis of prior performance or user preference.

RESULTS

Although the personalized mental task selection and training framework had been previously demonstrated with able-bodied participants, the participant was not able to exceed chance-level accuracies. Challenges to the acquisition of BCI control may have included disinclination to BCI training, structural or functional brain atypicalities, heightened emotional arousal and confounding haemodynamic patterns associated with novelty and reward processing.

CONCLUSIONS

Overall, we stress the necessity for further clinical NIRS-BCI research involving non-verbal individuals with severe motor impairments.

Functional near-infrared spectroscopy study on tonic pain activation by cold pressor test

Functional near-infrared spectroscopy (fNIRS) has recently been suggested for monitoring cortical hemodynamic response to experimental and clinical acute pain. However, the hemodynamic response to a tonic, noxious cold stimulus, and its relation with subjective pain sensation is not fully characterized. We investigated the relationship between pain threshold and tolerance and the evoked hemodynamic response to cold pressor tests (CPTs) at varying intensities and explored the gender effect. Twenty-one healthy individuals (10 males and 11 females) performed four CPTs at 1°C, 5°C, 10°C, and 15°C. Deoxyhemoglobin (HHb) and oxyhemoglobin ([Formula: see text]) were measured continuously on the forehead by two "far" and two "near" channels in addition to pain scores, threshold, and tolerance. We found a significant within-subject correlation between pain threshold and the immediate [Formula: see text] response at the right frontal region. Gender difference and asymmetrical activation were observed in the "far" channels but not the "near" channels, suggesting a hemispheric preference in response to noxious cold stimuli. No gender difference was found in pain threshold, tolerance, or scores. This research adds to the body of literature suggesting the use of fNIRS for bedside assessment of pain in addition to behavioral and subjective measures for comprehensive, multimodal pain management.