Improving optical contact for functional near‑infrared brain spectroscopy and imaging with brush optodes

Creating anatomically-derived, standardized, customizable, and three-dimensional printable head caps for functional neuroimaging

Significance

Consistent and accurate probe placement is a crucial step towards enhancing the reproducibility of longitudinal and group-based functional neuroimaging studies. While the selection of headgear is central to these efforts, there does not currently exist a standardized design that can accommodate diverse probe configurations and experimental procedures.

Aim

We aim to provide the community with an open-source software pipeline for conveniently creating low-cost, 3-D printable neuroimaging head caps with anatomically significant landmarks integrated into the structure of the cap.

Approach

We utilize our advanced 3-D head mesh generation toolbox and 10-20 head landmark calculations to quickly convert a subject's anatomical scan or an atlas into a 3-D printable head cap model. The 3-D modeling environment of the open-source Blender platform permits advanced mesh processing features to customize the cap. The design process is streamlined into a Blender add-on named "NeuroCaptain".

Results

Using the intuitive user interface, we create various head cap models using brain atlases, and share those with the community. The resulting mesh-based head cap designs are readily 3-D printable using off-the-shelf printers and filaments while accurately preserving the head topology and landmarks.

Conclusions

The methods developed in this work result in a widely accessible tool for community members to design, customize and fabricate caps that incorporate anatomically derived landmarks. This not only permits personalized head cap designs to achieve improved accuracy, but also offers an open platform for the community to propose standardizable head caps to facilitate multi-centered data collection and sharing.

Using spectral derivatives to remove the influence of hair on optical images of the static absorbing properties of tissue-like turbid media

Significance

Although measurements of near-infrared light diffusely reflected from the head and other biological tissues are commonly used to generate images revealing changes in the concentrations of oxy- and deoxy-hemoglobin, static imaging of absolute concentrations has been inhibited by the unknown and variable coupling between the optical probe and the skin, to which hair is often a significant contributor. Measurements of spectral derivatives provide a means of overcoming this shortcoming.

Aim

The aim is to demonstrate experimentally that measurements of the derivative of the attenuation of the detected signal with respect to wavelength can be used to achieve images that are immune to the spatial variation of hair on the surface. The objective is to generate topographic images representative of static absorbing properties rather than retrieving absolute optical coefficients, which requires a tomographic approach.

Approach

The surface of a tissue-equivalent phantom, containing targets with different concentrations of absorbing dye, was coated with a layer of dark hair. The phantom was then imaged using a broadband source and spectrometer, and prior knowledge of the absorbing characteristics of the dye and of melanin was used to acquire separate images of each.

Results

The targets within the phantom are revealed with remarkable clarity, although a nonlinear relationship between the target contrast and absorption was observed. This nonlinear behavior was confirmed and explained using a Monte Carlo model of light propagation in a slab of similar absorbing properties.

Conclusions

A spectral derivative approach could be an effective tool for in vivo topographic imaging of the static optical properties of the brain and other tissues, avoiding the deleterious effects of hair.

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

Introduction

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

Methods

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

Results

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

Discussion

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

Intraoperative monitoring of the central and peripheral nervous systems: a narrative review

The central and peripheral nervous systems are the primary target organs during anaesthesia. At the time of the inception of the British Journal of Anaesthesia, monitoring of the central nervous system comprised clinical observation, which provided only limited information. During the 100 yr since then, and particularly in the past few decades, significant progress has been made, providing anaesthetists with tools to obtain real-time assessments of cerebral neurophysiology during surgical procedures. In this narrative review article, we discuss the rationale and uses of electroencephalography, evoked potentials, near-infrared spectroscopy, and transcranial Doppler ultrasonography for intraoperative monitoring of the central and peripheral nervous systems.

It takes two (seconds): decreasing encoding time for two-choice functional near-infrared spectroscopy brain-computer interface communication

Significance

Brain-computer interfaces (BCIs) can provide severely motor-impaired patients with a motor-independent communication channel. Functional near-infrared spectroscopy (fNIRS) constitutes a promising BCI-input modality given its high mobility, safety, user comfort, cost-efficiency, and relatively low motion sensitivity.

Aim

The present study aimed at developing an efficient and convenient two-choice fNIRS communication BCI by implementing a relatively short encoding time (2 s), considerably increasing communication speed, and decreasing the cognitive load of BCI users.

Approach

To encode binary answers to 10 biographical questions, 10 healthy adults repeatedly performed a combined motor-speech imagery task within 2 different time windows guided by auditory instructions. Each answer-encoding run consisted of 10 trials. Answers were decoded during the ongoing experiment from the time course of the individually identified most-informative fNIRS channel-by-chromophore combination.

Results

The answers of participants were decoded online with an accuracy of 85.8% (run-based group mean). Post-hoc analysis yielded an average single-trial accuracy of 68.1%. Analysis of the effect of number of trial repetitions showed that the best information-transfer rate could be obtained by combining four encoding trials.

Conclusions

The study demonstrates that an encoding time as short as 2 s can enable immediate, efficient, and convenient fNIRS-BCI communication.

Toward a Multi-Modal Brain-Body Assessment in Parkinson's Disease: A Systematic Review in fNIRS

Parkinson's disease (PD) causes impairments in cortical structures leading to motor and cognitive symptoms. While common disease management and treatment strategies mainly depend on the subjective assessment of clinical scales and patients' diaries, research in recent years has focused on advances in automatic and objective tools to help with diagnosing PD and determining its severity. Due to the link between brain structure deficits and physical symptoms in PD, objective brain activity and body motion assessment of patients have been studied in the literature. This study aimed to explore the relationship between brain activity and body motion measures of people with PD to look at the feasibility of diagnosis or assessment of PD using these measures. In this study, we summarised the findings of 24 selected papers from the complete literature review using the Scopus database. Selected studies used both brain activity recording using functional near-infrared spectroscopy (fNIRS) and motion assessment using sensors for people with PD in their experiments. Results include 1) the most common study protocol is a combination of single tasks. 2) Prefrontal cortex is mostly studied region of interest in the literature. 3) Oxygenated haemoglobin (HbO 2) concentration is the predominant metric utilised in fNIRS, compared to deoxygenated haemoglobin (HHb). 4) Motion assessment in people with PD is mostly done with inertial measurement units (IMUs) and electronic walkway. 5) The relationship between brain activity and body motion measures is an important factor that has been neglected in the literature.

Naturalistic auditory stimuli with fNIRS prefrontal cortex imaging: A potential paradigm for disorder of consciousness diagnostics (a study with healthy participants)

Disorder of consciousness (DOC) is a devastating condition due to brain damage. A patient in this condition is non-responsive, but nevertheless might be conscious at least at some level. Determining the conscious level of DOC patients is important for both medical and ethical reasons, but reliably achieving this has been a major challenge. Naturalistic stimuli in combination with neuroimaging have been proposed as a promising approach for DOC patient diagnosis. Capitalizing on and extending this proposal, the goal of the present study conducted with healthy participants was to develop a new paradigm with naturalistic auditory stimuli and functional near-infrared spectroscopy (fNIRS) - an approach that can be used at the bedside. Twenty-four healthy participants passively listened to 9 min of auditory story, scrambled auditory story, classical music, and scrambled classical music segments while their prefrontal cortex activity was recorded using fNIRS. We found much higher intersubject correlation (ISC) during story compared to scrambled story conditions both at the group level and in the majority of individual subjects, suggesting that fNIRS imaging of the prefrontal cortex might be a sensitive method to capture neural changes associated with narrative comprehension. In contrast, the ISC during the classical music segment did not differ reliably from scrambled classical music and was also much lower than the story condition. Our main result is that naturalistic auditory stories with fNIRS might be used in a clinical setup to identify high-level processing and potential consciousness in DOC patients.

Demographic reporting and phenotypic exclusion in fNIRS

Functional near-infrared spectroscopy (fNIRS) promises to be a leading non-invasive neuroimaging method due to its portability and low cost. However, concerns are rising over its inclusivity of all skin tones and hair types (Parker and Ricard, 2022, Webb et al., 2022). Functional NIRS relies on direct contact of light-emitting optodes to the scalp, which can be blocked more by longer, darker, and especially curlier hair. Additionally, NIR light can be attenuated by melanin, which is accounted for in neither fNIRS hardware nor analysis methods. Recent work has shown that overlooking these considerations in other modalities like EEG leads to the disproportionate exclusion of individuals with these phenotypes-especially Black people-in both clinical and research literature (Choy, 2020; Bradford et al., 2022; Louis et al., 2023). In this article, we sought to determine if (Jöbsis, 1977) biomedical optics developers and researchers report fNIRS performance variability between skin tones and hair textures, (2a) fNIRS neuroscience practitioners report phenotypic and demographic details in their articles, and thus, (2b) is a similar pattern of participant exclusion found in EEG also present in the fNIRS literature. We present a literature review of top Biomedical Optics and Human Neuroscience journals, showing that demographic and phenotypic reporting is unpopular in both fNIRS development and neuroscience applications. We conclude with a list of recommendations to the fNIRS community including examples of Black researchers addressing these issues head-on, inclusive best practices for fNIRS researchers, and recommendations to funding and regulatory bodies to achieve an inclusive neuroscience enterprise in fNIRS and beyond.

Differential Neural Correlates in the Prefrontal Cortex during a Delay Discounting Task in Healthy Adults: An fNIRS Study

The phenomenon of future rewards being devalued as a function of delay is referred to as delay discounting (DD). It is considered a measure of impulsivity, and steep DD characterizes psychiatric problems such as addictive disorders and attention deficit/hyperactivity disorder. This preliminarily study examined prefrontal hemodynamic activity using functional near-infrared spectroscopy (fNIRS) in healthy young adults performing a DD task. Prefrontal activity during a DD task with hypothetical monetary rewards was measured in 20 participants. A discounting rate (k-value) in the DD task was determined on the basis of a hyperbolic function. To validate the k-value, a DD questionnaire and the Barratt impulsiveness scale (BIS) were administered after fNIRS. The DD task induced a significant increase in oxygenated hemoglobin (oxy-Hb) concentration bilaterally in the frontal pole and dorsolateral prefrontal cortex (PFC) compared with a control task. Significant positive correlations were detected between left PFC activity and discounting parameters. Right frontal pole activity, however, showed significantly negative correlation with motor impulsivity as a BIS subscore. These results suggest that left and right PFCs have differential contributions when performing the DD task. The present findings suggest the idea that fNIRS measurement of prefrontal hemodynamic activity can be useful for understanding the neural mechanisms underlying DD and is applicable for assessing PFC function among psychiatric patients with impulsivity-related problems.

Wearable, high-density fNIRS and diffuse optical tomography technologies: a perspective

Recent progress in optoelectronics has made wearable and high-density functional near-infrared spectroscopy (fNIRS) and diffuse optical tomography (DOT) technologies possible for the first time. These technologies have the potential to open new fields of real-world neuroscience by enabling functional neuroimaging of the human cortex at a resolution comparable to fMRI in almost any environment and population. In this perspective article, we provide a brief overview of the history and the current status of wearable high-density fNIRS and DOT approaches, discuss the greatest ongoing challenges, and provide our thoughts on the future of this remarkable technology.

Multi-mode fiber-based speckle contrast optical spectroscopy: analysis of speckle statistics

Speckle contrast optical spectroscopy/tomography (SCOS/T) provides a real-time, non-invasive, and cost-efficient optical imaging approach to mapping of cerebral blood flow. By measuring many speckles (n>>10), SCOS/T has an increased signal-to-noise ratio relative to diffuse correlation spectroscopy, which measures one or a few speckles. However, the current free-space SCOS/T designs are not ideal for large field-of-view imaging in humans because the curved head contour cannot be readily imaged with a single flat sensor and hair obstructs optical access. Herein, we evaluate the feasibility of using cost-efficient multi-mode fiber (MMF) bundles for use in SCOS/T systems. One challenge with speckle contrast measurements is the potential for confounding noise sources (e.g., shot noise, readout noise) which contribute to the standard deviation measure and corrupt the speckle contrast measure that is central to the SCOS/T systems. However, for true speckle measurements, the histogram of pixel intensities from light interference follows a non-Gaussian distribution, specifically a gamma distribution with non-zero skew, whereas most noise sources have pixel intensity distributions that are Gaussian. By evaluating speckle data from static and dynamic targets imaged through an MMF, we use histograms and statistical analysis of pixel histograms to evaluate whether the statistical properties of the speckles are retained. We show that flow-based speckle can be distinguished from static speckle and from sources of system noise through measures of skew in the pixel intensity histograms. Finally, we illustrate in humans that MMF bundles relay blood flow information.

Shining a light on cultural neuroscience: Recommendations on the use of fNIRS to study how sociocultural contexts shape the brain

Functional near-infrared spectroscopy (fNIRS) is a portable neuroimaging technique that may serve as a methodological tool for studying how sociocultural contexts can shape the human brain and impact cognition and behavior. The use of fNIRS in community-based research may (a) advance theoretical knowledge in psychology and neuroscience, particularly regarding underrepresented ethnic-racial communities; (b) increase diversity in samples; and (c) provide neurobiological evidence of sociocultural factors supporting human development. The review aims to introduce the use of fNIRS, including its practicalities and limitations, to new adopters inquiring how sociocultural inputs affect the brain. The review begins with an introduction to cultural neuroscience, and a review on the use of fNIRS follows. Next, benefits and guidelines to the design of fNIRS research in naturalistic environments (in the community or in the field) using a cultural lens are discussed. Strengths-based and community-based approaches in cultural neuroscience are recommended throughout. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Near-Infrared Spectroscopy as a Tool for Marine Mammal Research and Care

Developments in wearable human medical and sports health trackers has offered new solutions to challenges encountered by eco-physiologists attempting to measure physiological attributes in freely moving animals. Near-infrared spectroscopy (NIRS) is one such solution that has potential as a powerful physio-logging tool to assess physiology in freely moving animals. NIRS is a non-invasive optics-based technology, that uses non-ionizing radiation to illuminate biological tissue and measures changes in oxygenated and deoxygenated hemoglobin concentrations inside tissues such as skin, muscle, and the brain. The overall footprint of the device is small enough to be deployed in wearable physio-logging devices. We show that changes in hemoglobin concentration can be recorded from bottlenose dolphins and gray seals with signal quality comparable to that achieved in human recordings. We further discuss functionality, benefits, and limitations of NIRS as a standard tool for animal care and wildlife tracking for the marine mammal research community.

Characterizing reproducibility of cerebral hemodynamic responses when applying short-channel regression in functional near-infrared spectroscopy

Significance: Functional near-infrared spectroscopy (fNIRS) enables the measurement of brain activity noninvasively. Optical neuroimaging with fNIRS has been shown to be reproducible on the group level and hence is an excellent research tool, but the reproducibility on the single-subject level is still insufficient, challenging the use for clinical applications. Aim: We investigated the effect of short-channel regression (SCR) as an approach to obtain fNIRS measurements with higher reproducibility on a single-subject level. SCR simultaneously considers contributions from long- and short-separation channels and removes confounding physiological changes through the regression of the short-separation channel information. Approach: We performed a test-retest study with a hand grasping task in 15 healthy subjects using a wearable fNIRS device, optoHIVE. Relevant brain regions were localized with transcranial magnetic stimulation to ensure correct placement of the optodes. Reproducibility was assessed by intraclass correlation, correlation analysis, mixed effects modeling, and classification accuracy of the hand grasping task. Further, we characterized the influence of SCR on reproducibility. Results: We found a high reproducibility of fNIRS measurements on a single-subject level (ICC single = 0.81 and correlation r = 0.81 ). SCR increased the reproducibility from 0.64 to 0.81 (ICC single ) but did not affect classification (85% overall accuracy). Significant intersubject variability in the reproducibility was observed and was explained by Mayer wave oscillations and low raw signal strength. The raw signal-to-noise ratio (threshold at 40 dB) allowed for distinguishing between persons with weak and strong activations. Conclusions: We report, for the first time, that fNIRS measurements are reproducible on a single-subject level using our optoHIVE fNIRS system and that SCR improves reproducibility. In addition, we give a benchmark to easily assess the ability of a subject to elicit sufficiently strong hemodynamic responses. With these insights, we pave the way for the reliable use of fNIRS neuroimaging in single subjects for neuroscientific research and clinical applications.

A low-cost, wearable, do-it-yourself functional near-infrared spectroscopy (DIY-fNIRS) headband

Neuromonitoring in naturalistic environments is of increasing interest for a variety of research fields including psychology, economics, and productivity. Among functional neuromonitoring modalities, functional near-infrared spectroscopy (fNIRS) is well regarded for its potential for miniaturization, good spatial and temporal resolutions, and resilience to motion artifacts. Historically, the large size and high cost of fNIRS systems have precluded widespread adoption of the technology. In this article, we describe the first open source, fully integrated wireless fNIRS headband system with a single LED-pair source and four detectors. With ease of operation and comfort in mind, the system is encased in a soft, lightweight cloth and silicone enclosure. Accompanying computer and smartphone data collection software have also been provided, and the hardware has been validated using classic fNIRS tasks. This wear-and-go design can easily be scaled to accommodate a larger number of fNIRS channels and opens the door to easily collecting fNIRS data during routine activities in naturalistic conditions.

High optode-density wearable diffuse optical probe for monitoring paced breathing hemodynamics in breast tissue

SIGNIFICANCE

Diffuse optical imaging (DOI) provides in vivo quantification of tissue chromophores such as oxy- and deoxyhemoglobin (HbO2 and HHb, respectively). These parameters have been shown to be useful for predicting neoadjuvant treatment response in breast cancer patients. However, most DOI devices designed for the breast are nonportable, making frequent longitudinal monitoring during treatment a challenge. Furthermore, hemodynamics related to the respiratory cycle are currently unexplored in the breast and may have prognostic value.

AIM

To design, fabricate, and validate a high optode-density wearable continuous wave diffuse optical probe for the monitoring of breathing hemodynamics in breast tissue.

APPROACH

The probe has a rigid-flex design with 16 dual-wavelength sources and 16 detectors. Performance was characterized on tissue-simulating phantoms, and validation was performed through flow phantom and cuff occlusion measurements. The breasts of N  =  4 healthy volunteers were measured while performing a breathing protocol.

RESULTS

The probe has 512 unique source-detector (S-D) pairs that span S-D separations of 10 to 54 mm. It exhibited good performance characteristics: μa drift of 0.34%/h, μa precision of 0.063%, and mean SNR  ≥  24  dB up to 41 mm S-D separation. Absorption contrast was detected in flow phantoms at depths exceeding 28 mm. A cuff occlusion measurement confirmed the ability of the probe to track expected hemodynamics in vivo. Breast measurements on healthy volunteers during paced breathing revealed median signal-to-motion artifact ratios ranging from 8.1 to 8.7 dB. Median ΔHbO2 and ΔHHb amplitudes ranged from 0.39 to 0.67  μM and 0.08 to 0.12  μM, respectively. Median oxygen saturations at the respiratory rate ranged from 82% to 87%.

CONCLUSIONS

A wearable diffuse optical probe has been designed and fabricated for the measurement of breast tissue hemodynamics. This device is capable of quantifying breathing-related hemodynamics in healthy breast tissue.

Clinical Utility of Functional Near-Infrared Spectroscopy for Assessment and Prediction of Suicidality: A Systematic Review

Introduction: Suicide is a pressing psychiatric concern worldwide with no established biomarker. While there is some evidence of the clinical utility of functional near-infrared spectroscopy (fNIRS) in assessing and predicting suicidality, no systematic review of such evidence has been conducted to date. Therefore, this review aimed to systematically review and gather evidence from existing studies that used fNIRS signals to assess suicidality and its associated changes in the brain, and those that examined how such signals correlated with suicide symptomatology. Methods: PubMed, EMBASE, and Cochrane Library databases were used in a systematic literature search for English-language articles published between 2000 and December 19, 2020 that focused on the utility of fNIRS for (i) assessing suicidality and its associated changes in the brain, and (ii) correlating with suicide symptomatology. Studies were included if they utilised fNIRS to evaluate variations in fNIRS-measured cerebral hemodynamic responses in patients with different mental disorders (e.g., major depressive disorder, schizophrenia), as well as in healthy controls, of any age group. Quality of evidence was assessed using the Newcastle-Ottawa quality assessment scale. Results: A total of 7 cross-sectional studies were included in this review, all of which had acceptable quality. Across all studies, fNIRS demonstrated reduced cerebral hemodynamic changes in suicidal individuals when compared to non-suicidal individuals. One study also demonstrated the potential of fNIRS signals in correlating with the severity of suicidality. Conclusions: This review provides a comprehensive, updated review of evidence supporting the clinical utility of fNIRS in the assessment and prediction of suicidality. Further studies involving larger sample sizes, standardised methodology, and longitudinal follow-ups are needed.

Brain-Based Binary Communication Using Spatiotemporal Features of fNIRS Responses

“Locked-in” patients lose their ability to communicate naturally due to motor system dysfunction. Brain-computer interfacing offers a solution for their inability to communicate by enabling motor-independent communication. Straightforward and convenient in-session communication is essential in clinical environments. The present study introduces a functional near-infrared spectroscopy (fNIRS)-based binary communication paradigm that requires limited preparation time and merely nine optodes. Eighteen healthy participants performed two mental imagery tasks, mental drawing and spatial navigation, to answer yes/no questions during one of two auditorily cued time windows. Each of the six questions was answered five times, resulting in five trials per answer. This communication paradigm thus combines both spatial (two different mental imagery tasks, here mental drawing for “yes” and spatial navigation for “no”) and temporal (distinct time windows for encoding a “yes” and “no” answer) fNIRS signal features for information encoding. Participants’ answers were decoded in simulated real-time using general linear model analysis. Joint analysis of all five encoding trials resulted in an average accuracy of 66.67 and 58.33% using the oxygenated (HbO) and deoxygenated (HbR) hemoglobin signal respectively. For half of the participants, an accuracy of 83.33% or higher was reached using either the HbO signal or the HbR signal. For four participants, effective communication with 100% accuracy was achieved using either the HbO or HbR signal. An explorative analysis investigated the differentiability of the two mental tasks based solely on spatial fNIRS signal features. Using multivariate pattern analysis (MVPA) group single-trial accuracies of 58.33% (using 20 training trials per task) and 60.56% (using 40 training trials per task) could be obtained. Combining the five trials per run using a majority voting approach heightened these MVPA accuracies to 62.04 and 75%. Additionally, an fNIRS suitability questionnaire capturing participants’ physical features was administered to explore its predictive value for evaluating general data quality. Obtained questionnaire scores correlated significantly (r = -0.499) with the signal-to-noise of the raw light intensities. While more work is needed to further increase decoding accuracy, this study shows the potential of answer encoding using spatiotemporal fNIRS signal features or spatial fNIRS signal features only.

Toward a compact hybrid brain-computer interface (BCI): Performance evaluation of multi-class hybrid EEG-fNIRS BCIs with limited number of channels

It has been demonstrated that the performance of typical unimodal brain-computer interfaces (BCIs) can be noticeably improved by combining two different BCI modalities. This so-called "hybrid BCI" technology has been studied for decades; however, hybrid BCIs that particularly combine electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) (hereafter referred to as hBCIs) have not been widely used in practical settings. One of the main reasons why hBCI systems are so unpopular is that their hardware is generally too bulky and complex. Therefore, to make hBCIs more appealing, it is necessary to implement a lightweight and compact hBCI system with minimal performance degradation. In this study, we investigated the feasibility of implementing a compact hBCI system with significantly less EEG channels and fNIRS source-detector (SD) pairs, but that can achieve a classification accuracy high enough to be used in practical BCI applications. EEG and fNIRS data were acquired while participants performed three different mental tasks consisting of mental arithmetic, right-hand motor imagery, and an idle state. Our analysis results showed that the three mental states could be classified with a fairly high classification accuracy of 77.6 ± 12.1% using an hBCI system with only two EEG channels and two fNIRS SD pairs.

Transcranial direct current stimulation for the treatment of motor impairment following traumatic brain injury

After traumatic brain injury (TBI), motor impairment is less common than neurocognitive or behavioral problems. However, about 30% of TBI survivors have reported motor deficits limiting the activities of daily living or participation. After acute primary and secondary injuries, there are subsequent changes including increased GABA-mediated inhibition during the subacute stage and neuroplastic alterations that are adaptive or maladaptive during the chronic stage. Therefore, timely and appropriate neuromodulation by transcranial direct current stimulation (tDCS) may be beneficial to patients with TBI for neuroprotection or restoration of maladaptive changes.Technologically, combination of imaging-based modelling or simultaneous brain signal monitoring with tDCS could result in greater individualized optimal targeting allowing a more favorable neuroplasticity after TBI. Moreover, a combination of task-oriented training using virtual reality with tDCS can be considered as a potent tele-rehabilitation tool in the home setting, increasing the dose of rehabilitation and neuromodulation, resulting in better motor recovery.This review summarizes the pathophysiology and possible neuroplastic changes in TBI, as well as provides the general concepts and current evidence with respect to the applicability of tDCS in motor recovery. Through its endeavors, it aims to provide insights on further successful development and clinical application of tDCS in motor rehabilitation after TBI.

Navigation in Real-World Environments: New Opportunities Afforded by Advances in Mobile Brain Imaging

A central question in neuroscience and psychology is how the mammalian brain represents the outside world and enables interaction with it. Significant progress on this question has been made in the domain of spatial cognition, where a consistent network of brain regions that represent external space has been identified in both humans and rodents. In rodents, much of the work to date has been done in situations where the animal is free to move about naturally. By contrast, the majority of work carried out to date in humans is static, due to limitations imposed by traditional laboratory based imaging techniques. In recent years, significant progress has been made in bridging the gap between animal and human work by employing virtual reality (VR) technology to simulate aspects of real-world navigation. Despite this progress, the VR studies often fail to fully simulate important aspects of real-world navigation, where information derived from self-motion is integrated with representations of environmental features and task goals. In the current review article, we provide a brief overview of animal and human imaging work to date, focusing on commonalties and differences in findings across species. Following on from this we discuss VR studies of spatial cognition, outlining limitations and developments, before introducing mobile brain imaging techniques and describe technical challenges and solutions for real-world recording. Finally, we discuss how these advances in mobile brain imaging technology, provide an unprecedented opportunity to illuminate how the brain represents complex multifaceted information during naturalistic navigation.

Regional Cerebral Abnormalities Measured by Frequency-Domain Near-Infrared Spectroscopy in Pediatric Patients During Extracorporeal Membrane Oxygenation

Extracorporeal membrane oxygenation (ECMO) is a form of advanced cardiorespiratory support provided to critically ill patients with severe respiratory or cardiovascular failure. While children undergoing ECMO therapy have significant risk for neurological morbidity, currently there is a lack of reliable bedside tool to detect the neurologic events for patients on ECMO. This study assessed the feasibility of frequency-domain near-infrared spectroscopy (NIRS) for detection of intracranial complications during ECMO therapy. The frequency-domain NIRS device measured the absorption coefficient (µa) and reduced scattering coefficient (µs') at six cranial positions from seven pediatric patients (0-16 years) during ECMO support and five healthy controls (2-14 years). Regional abnormalities in both absorption and scattering were identified among ECMO patients. A main finding in this study is that the abnormalities in scattering appear to be associated with lower-than-normal µs' values in regional areas of the brain. Because light scattering originates from the intracellular structures (such as nuclei and mitochondria), a reduction in scattering primarily reflects loss or decreased density of the brain matter. The results from this study indicate a potential to use the frequency-domain NIRS as a safe and complementary technology for detection of intracranial complications during ECMO therapy.

A Ternary Hybrid EEG-NIRS Brain-Computer Interface for the Classification of Brain Activation Patterns during Mental Arithmetic, Motor Imagery, and Idle State

The performance of a brain-computer interface (BCI) can be enhanced by simultaneously using two or more modalities to record brain activity, which is generally referred to as a hybrid BCI. To date, many BCI researchers have tried to implement a hybrid BCI system by combining electroencephalography (EEG) and functional near-infrared spectroscopy (NIRS) to improve the overall accuracy of binary classification. However, since hybrid EEG-NIRS BCI, which will be denoted by hBCI in this paper, has not been applied to ternary classification problems, paradigms and classification strategies appropriate for ternary classification using hBCI are not well investigated. Here we propose the use of an hBCI for the classification of three brain activation patterns elicited by mental arithmetic, motor imagery, and idle state, with the aim to elevate the information transfer rate (ITR) of hBCI by increasing the number of classes while minimizing the loss of accuracy. EEG electrodes were placed over the prefrontal cortex and the central cortex, and NIRS optodes were placed only on the forehead. The ternary classification problem was decomposed into three binary classification problems using the "one-versus-one" (OVO) classification strategy to apply the filter-bank common spatial patterns filter to EEG data. A 10 × 10-fold cross validation was performed using shrinkage linear discriminant analysis (sLDA) to evaluate the average classification accuracies for EEG-BCI, NIRS-BCI, and hBCI when the meta-classification method was adopted to enhance classification accuracy. The ternary classification accuracies for EEG-BCI, NIRS-BCI, and hBCI were 76.1 ± 12.8, 64.1 ± 9.7, and 82.2 ± 10.2%, respectively. The classification accuracy of the proposed hBCI was thus significantly higher than those of the other BCIs (p < 0.005). The average ITR for the proposed hBCI was calculated to be 4.70 ± 1.92 bits/minute, which was 34.3% higher than that reported for a previous binary hBCI study.

A functional near-infrared spectroscopic investigation of speech production during reading

This study was designed to test the extent to which speaking processes related to articulation and voicing influence Functional Near Infrared Spectroscopy (fNIRS) measures of cortical hemodynamics and functional connectivity. Participants read passages in three conditions (oral reading, silent mouthing, and silent reading) while undergoing fNIRS imaging. Area under the curve (AUC) analyses of the oxygenated and deoxygenated hemodynamic response function concentration values were compared for each task across five regions of interest. There were significant region main effects for both oxy and deoxy AUC analyses, and a significant region × task interaction for deoxy AUC favoring the oral reading condition over the silent reading condition for two nonmotor regions. Assessment of functional connectivity using Granger Causality revealed stronger networks between motor areas during oral reading and stronger networks between language areas during silent reading. There was no evidence that the hemodynamic flow from motor areas during oral reading compromised measures of language-related neural activity in nonmotor areas. However, speech movements had small, but measurable effects on fNIRS measures of neural connections between motor and nonmotor brain areas across the perisylvian region, even after wavelet filtering. Therefore, researchers studying speech processes with fNIRS should use wavelet filtering during preprocessing to reduce speech motion artifacts, incorporate a nonspeech communication or language control task into the research design, and conduct a connectivity analysis to adequately assess the impact of functional speech on the hemodynamic response across the perisylvian region.

Plasticity in bilateral superior temporal cortex: Effects of deafness and cochlear implantation on auditory and visual speech processing

While many individuals can benefit substantially from cochlear implantation, the ability to perceive and understand auditory speech with a cochlear implant (CI) remains highly variable amongst adult recipients. Importantly, auditory performance with a CI cannot be reliably predicted based solely on routinely obtained information regarding clinical characteristics of the CI candidate. This review argues that central factors, notably cortical function and plasticity, should also be considered as important contributors to the observed individual variability in CI outcome. Superior temporal cortex (STC), including auditory association areas, plays a crucial role in the processing of auditory and visual speech information. The current review considers evidence of cortical plasticity within bilateral STC, and how these effects may explain variability in CI outcome. Furthermore, evidence of audio-visual interactions in temporal and occipital cortices is examined, and relation to CI outcome is discussed. To date, longitudinal examination of changes in cortical function and plasticity over the period of rehabilitation with a CI has been restricted by methodological challenges. The application of functional near-infrared spectroscopy (fNIRS) in studying cortical function in CI users is becoming increasingly recognised as a potential solution to these problems. Here we suggest that fNIRS offers a powerful neuroimaging tool to elucidate the relationship between audio-visual interactions, cortical plasticity during deafness and following cochlear implantation, and individual variability in auditory performance with a CI.

Diffuse optical tomography using multi-directional sources and detectors

Diffuse optical tomography (DOT) is an advanced imaging method used to visualize the internal state of biological tissues as 3D images. However, current continuous-wave DOT requires high-density probe arrays for measurement (less than 15-mm interval) to gather enough information for 3D image reconstruction, which makes the experiment time-consuming. In this paper, we propose a novel DOT measurement system using multi-directional light sources and multi-directional photodetectors instead of high-density probe arrays. We evaluated this system's multi-directional DOT through computer simulation and a phantom experiment. From the results, we achieved DOT with less than 5-mm localization error up to a 15-mm depth with low-density probe arrays (30-mm interval), indicating that the multi-directional measurement approach allows DOT without requiring high-density measurement.

NIR light propagation in a digital head model for traumatic brain injury (TBI)

Near infrared spectroscopy (NIRS) is capable of detecting and monitoring acute changes in cerebral blood volume and oxygenation associated with traumatic brain injury (TBI). Wavelength selection, source-detector separation, optode density, and detector sensitivity are key design parameters that determine the imaging depth, chromophore separability, and, ultimately, clinical usefulness of a NIRS instrument. We present simulation results of NIR light propagation in a digital head model as it relates to the ability to detect intracranial hematomas and monitor the peri-hematomal tissue viability. These results inform NIRS instrument design specific to TBI diagnosis and monitoring.

Effect of motion artifacts and their correction on near-infrared spectroscopy oscillation data: a study in healthy subjects and stroke patients

Functional near-infrared spectroscopy is prone to contamination by motion artifacts (MAs). Motion correction algorithms have previously been proposed and their respective performance compared for evoked rain activation studies. We study instead the effect of MAs on "oscillation" data which is at the basis of functional connectivity and autoregulation studies. We use as our metric of interest the interhemispheric correlation (IHC), the correlation coefficient between symmetrical time series of oxyhemoglobin oscillations. We show that increased motion content results in a decreased IHC. Using a set of motion-free data on which we add real MAs, we find that the best motion correction approach consists of discarding the segments of MAs following a careful approach to minimize the contamination due to band-pass filtering of data from "bad" segments spreading into adjacent "good" segments. Finally, we compare the IHC in a stroke group and in a healthy group that we artificially contaminated with the MA content of the stroke group, in order to avoid the confounding effect of increased motion incidence in the stroke patients. After motion correction, the IHC remains lower in the stroke group in the frequency band around 0.1 and 0.04 Hz, suggesting a physiological origin for the difference. We emphasize the importance of considering MAs as a confounding factor in oscillation-based functional near-infrared spectroscopy studies.

A synchrony-dependent influence of sounds on activity in visual cortex measured using functional near-infrared spectroscopy (fNIRS)

Evidence from human neuroimaging and animal electrophysiological studies suggests that signals from different sensory modalities interact early in cortical processing, including in primary sensory cortices. The present study aimed to test whether functional near-infrared spectroscopy (fNIRS), an emerging, non-invasive neuroimaging technique, is capable of measuring such multisensory interactions. Specifically, we tested for a modulatory influence of sounds on activity in visual cortex, while varying the temporal synchrony between trains of transient auditory and visual events. Related fMRI studies have consistently reported enhanced activation in response to synchronous compared to asynchronous audiovisual stimulation. Unexpectedly, we found that synchronous sounds significantly reduced the fNIRS response from visual cortex, compared both to asynchronous sounds and to a visual-only baseline. It is possible that this suppressive effect of synchronous sounds reflects the use of an efficacious visual stimulus, chosen for consistency with previous fNIRS studies. Discrepant results may also be explained by differences between studies in how attention was deployed to the auditory and visual modalities. The presence and relative timing of sounds did not significantly affect performance in a simultaneously conducted behavioral task, although the data were suggestive of a positive relationship between the strength of the fNIRS response from visual cortex and the accuracy of visual target detection. Overall, the present findings indicate that fNIRS is capable of measuring multisensory cortical interactions. In multisensory research, fNIRS can offer complementary information to the more established neuroimaging modalities, and may prove advantageous for testing in naturalistic environments and with infant and clinical populations.

Motion tracking and electromyography-assisted identification of mirror hand contributions to functional near-infrared spectroscopy images acquired during a finger-tapping task performed by children with cerebral palsy

Recent studies have demonstrated functional near-infrared spectroscopy (fNIRS) to be a viable and sensitive method for imaging sensorimotor cortex activity in children with cerebral palsy (CP). However, during unilateral finger tapping, children with CP often exhibit unintended motions in the nontapping hand, known as mirror motions, which confuse the interpretation of resulting fNIRS images. This work presents a method for separating some of the mirror motion contributions to fNIRS images and demonstrates its application to fNIRS data from four children with CP performing a finger-tapping task with mirror motions. Finger motion and arm muscle activity were measured simultaneously with fNIRS signals using motion tracking and electromyography (EMG), respectively. Subsequently, subject-specific regressors were created from the motion capture or EMG data and independent component analysis was combined with a general linear model to create an fNIRS image representing activation due to the tapping hand and one image representing activation due to the mirror hand. The proposed method can provide information on how mirror motions contribute to fNIRS images, and in some cases, it helps remove mirror motion contamination from the tapping hand activation images.

Unleashing the future potential of functional near-infrared spectroscopy in brain sciences

The wondrous innovations bound to the introduction of functional near-infrared spectroscopy in cognitive neuroscience are characterized by a multifaceted nature, ranging from technological improvements to sophisticated signal processing methods; the outstanding progress enabled scientists to investigate a variety of hard-to-test clinical populations and to successfully employ optical imaging in fields that were almost unimaginable twenty years ago. Here we illustrate how the emerging use of fNIRS methodologies might represent a drawing power in a variety of challenging experimental and medical contexts; we expect in the near future a wide increase of the use of wireless fNIRS, especially in children and in particular clinical populations, as well as a striking progress of fNIRS-BCI and hybrid BCI systems for neurofeedback and neurorehabilitation. These emerging trends might dramatically foster the future potential of fNIRS in brain sciences, provided that they are properly supported by a significant progress in signal processing and cognitive neuroscience.

TARGETED PRINCIPLE COMPONENT ANALYSIS: A NEW MOTION ARTIFACT CORRECTION APPROACH FOR NEAR-INFRARED SPECTROSCOPY

As near-infrared spectroscopy (NIRS) broadens its application area to different age and disease groups, motion artifacts in the NIRS signal due to subject movement is becoming an important challenge. Motion artifacts generally produce signal fluctuations that are larger than physiological NIRS signals, thus it is crucial to correct for them before obtaining an estimate of stimulus evoked hemodynamic responses. There are various methods for correction such as principle component analysis (PCA), wavelet-based filtering and spline interpolation. Here, we introduce a new approach to motion artifact correction, targeted principle component analysis (tPCA), which incorporates a PCA filter only on the segments of data identified as motion artifacts. It is expected that this will overcome the issues of filtering desired signals that plagues standard PCA filtering of entire data sets. We compared the new approach with the most effective motion artifact correction algorithms on a set of data acquired simultaneously with a collodion-fixed probe (low motion artifact content) and a standard Velcro probe (high motion artifact content). Our results show that tPCA gives statistically better results in recovering hemodynamic response function (HRF) as compared to wavelet-based filtering and spline interpolation for the Velcro probe. It results in a significant reduction in mean-squared error (MSE) and significant enhancement in Pearson's correlation coefficient to the true HRF. The collodion-fixed fiber probe with no motion correction performed better than the Velcro probe corrected for motion artifacts in terms of MSE and Pearson's correlation coefficient. Thus, if the experimental study permits, the use of a collodion-fixed fiber probe may be desirable. If the use of a collodion-fixed probe is not feasible, then we suggest the use of tPCA in the processing of motion artifact contaminated data.

Reducing motion artifacts for long-term clinical NIRS monitoring using collodion-fixed prism-based optical fibers

As the applications of near-infrared spectroscopy (NIRS) continue to broaden and long-term clinical monitoring becomes more common, minimizing signal artifacts due to patient movement becomes more pressing. This is particularly true in applications where clinically and physiologically interesting events are intrinsically linked to patient movement, as is the case in the study of epileptic seizures. In this study, we apply an approach common in the application of EEG electrodes to the application of specialized NIRS optical fibers. The method provides improved optode-scalp coupling through the use of miniaturized optical fiber tips fixed to the scalp using collodion, a clinical adhesive. We investigate and quantify the performance of this new method in minimizing motion artifacts in healthy subjects, and apply the technique to allow continuous NIRS monitoring throughout epileptic seizures in two epileptic in-patients. Using collodion-fixed fibers reduces the percent signal change of motion artifacts by 90% and increases the SNR by 6 and 3 fold at 690 and 830 nm wavelengths respectively when compared to a standard Velcro-based array of optical fibers. The SNR has also increased by 2 fold during rest conditions without motion with the new probe design because of better light coupling between the fiber and scalp. The change in both HbO and HbR during motion artifacts is found to be statistically lower for the collodion-fixed fiber probe. The collodion-fixed optical fiber approach has also allowed us to obtain good quality NIRS recording of three epileptic seizures in two patients despite excessive motion in each case.