Near infrared spectroscopy (NIRS): a new tool to study hemodynamic changes during activation of brain function in human adults

Perception of native vs. non-native language and non-speech sounds in one-week-old neonates: An fNIRS study

BACKGROUND

Early infant phonological and non-phonological perceptual abilities are crucial for future language learning. Previous studies have focused on the changes in the cerebral cortex of infants and toddlers during speech perception, while the changes in the cerebral cortex during non-speech perception remain poorly understood.

OBJECTIVE

This study aimed to investigate cortical activation patterns and differences in full-term healthy newborns under different speech and non-speech stimuli by functional near-infrared spectroscopy (fNIRS).

METHODS

The cohort included 36 full-term healthy neonates (7.4 ± 6.0 days) exposed to two types of speech stimuli (native Mandarin and non-native Spanish) and three non-speech stimuli (music, cat calls, and noise) in a block design. Brain activity was monitored across eight brain regions of interest (ROIs) were monitored using fNIRS (54 channels): frontal pole area (FPA), middle frontal gyrus (MFG), primary sensorimotor cortex, middle temporal gyrus (MTG), superior temporal gyrus (STG), fusiform gyrus (FFG), Wernicke's area, and Broca's area.

RESULTS

Mandarin stimulation activated all ROIs in newborns. Changes in oxygenated hemoglobin concentrations in FPA, MFG, STG, MTG, FFG, Wernicke's area, and Broca's area were significantly higher during Mandarin exposure compared to Spanish (p < 0.05). MTG activation was significantly greater during Mandarin exposure compared to cat calls (p = 0.005), music (p = 0.040), and noise (p < 0.001). Similarly, MFG and Broca's area showed significantly greater activation during music exposure compared to Spanish and noise stimuli (p < 0.05).

CONCLUSIONS

The newborn brain can perceive various speech and non-speech stimuli, demonstrating a preference for native language stimuli, followed by music. The ability to perceive non-native languages, animal calls, and noise appears more limited. These findings could provide some references for future research on infant and toddler language development.

Enhanced cerebral oxygenation during mental and physical activity in older adults is unaltered by amnestic mild cognitive impairment

Background

The impact of amnestic mild cognitive impairment (aMCI) on cerebral oxygenation and cardiovascular responses to mental and physical challenges in elderly adults is unclear. This study compared the responses to mental (serial sevens test) and physical (isometric handgrip) challenges in older adults with vs. without aMCI.

Methods

Thirty-one aMCI (71.5 ± 1.1 years old) and 30 cognitively normal (70.8 ± 1.1 years old) adults participated in the study. Heart rate (HR), mean arterial pressure (MAP), systemic arterial oxygen saturation (SaO2), prefrontal cortical oxyhemoglobin (O2Hb) and deoxyhemoglobin (HHb) contents, and tissue oxygen saturation (ScO2) were continuously monitored during 2-min serial sevens mental arithmetic test and 1-min isometric handgrip at 30% of maximal voluntary contraction. Test results in the aMCI vs. non-MCI subjects were compared by two-factor ANOVA.

Results

Cardiovascular and tissue oxygenation responses to testing were similar in the two groups. Although MAP increased similarly during the mental and physical challenges, increases in HR (P = 0.020), SaO2 (P < 0.001), ScO2 (P = 0.001) and O2Hb (P = 0.022) were greater during the mental vs. physical challenges in both aMCI and cognitively normal subjects.

Conclusion

The mental arithmetic challenge increased the metabolic demand of the prefrontal cortex to a greater extent than the physical task. Cerebral O2 content increased more appreciably during the mental vs. physical challenges, in parallel with greater increases in HR. However, aMCI did not alter these physiological responses to mental or physical challenges.

Utility of Abdominal Near Infrared Spectroscopy in the Management of Neonates: A Review

Near-infrared spectroscopy (NIRS) is a noninvasive technique that utilizes light in the near-infrared spectrum to assess regional tissue oxygenation. The initial application of NIRS focused on measuring cerebral oxygenation. Recently, numerous studies focused on the utility of NIRS in measuring abdominal regional perfusion in preterm and full-term neonates-hepatic (right subcostal) and mesenteric (left lower quadrant/infra-umbilical probe). Abdominal NIRS, specifically the infraumbilical values obtained within the first week of life, is a useful tool for the evaluation of feeding intolerance and an early marker of the development of necrotizing enterocolitis (NEC) as changes in NIRS in the first 24 hours of abdominal symptoms helps define NEC severity. In addition, NIRS holds promise in identifying changes in abdominal regional perfusion with blood transfusion. The goal of this review is to summarize the current knowledge of factors affecting abdominal NIRS measurements, specifically alterations associated with feeding, blood transfusion, and necrotizing enterocolitis (NEC). We present information from the published clinical research in conjunction with information collected from an extensive search in the databases PubMed, EMBASE, and Scopus. · Abdominal NIRS is still an underutilized tool at the bedside in various clinical conditions.. · Compared with cerebral NIRS, splanchnic NIRS has more variability.. · Splanchnic NIRS can be used for clinical conditions such as feeding, blood transfusion, and NEC.. · There is a need for standardized algorithms in infants based on their GA and clinical diagnosis..

Effects of different AI-driven Chatbot feedback on learning outcomes and brain activity

Artificial intelligence (AI) driven chatbots provide instant feedback to support learning. Yet, the impacts of different feedback types on behavior and brain activation remain underexplored. We investigated how metacognitive, affective, and neutral feedback from an educational chatbot affected learning outcomes and brain activity using functional near-infrared spectroscopy. Students receiving metacognitive feedback showed higher transfer scores, greater metacognitive sensitivity, and increased brain activation in the frontopolar area and middle temporal gyrus compared to other feedback types. Such activation correlated with metacognitive sensitivity. Students receiving affective feedback showed better retention scores than those receiving neutral feedback, along with higher activation in the supramarginal gyrus. Students receiving neutral feedback exhibited higher activation in the dorsolateral prefrontal cortex than other feedback types. The machine learning model identified key brain regions that predicted transfer scores. These findings underscore the potential of diverse feedback types in enhancing learning via human-chatbot interaction, and provide neurophysiological signatures.

Is virtual reality-based cognitive training in parallel with functional near-infrared spectroscopy-derived neurofeedback beneficial to improve cognitive function in older adults with mild cognitive impairment?

PURPOSE

Cognitive training in parallel with functional near-infrared spectroscopy (fNIRS)-derived neurofeedback has been identified to be beneficial in enhancing cognitive function in patients with mild cognitive impairment (MCI). However, effects of virtual reality (VR)-based cognitive training ensuring ecological validity in parallel with fNIRS-derived neurofeedback on neural efficiency has received little attention. This study investigated effects of VR-based cognitive training in parallel with fNIRS-derived neurofeedback on cognitive function and neural efficiency in patients with MCI.

METHOD

Ninety participants were randomly assigned into the active group (AG) receiving VR-based cognitive training in parallel with fNIRS-derived neurofeedback, the sham group (SG), or wait-list group (CG). The AG and SG group performed each intervention for fifteen minutes a session, for eight sessions. The Trail Making Test Part B and Backward Digit Span Test were used for outcomes. In addition, activity in the dorsolateral prefrontal cortex (DLPFC) during cognitive testing using fNIRS was measured.

RESULTS

After the eight sessions, the AG achieved greater improvements in all outcomes than the other groups. In addition, the AG showed a lower DLPFC activity during cognitive testing than the other groups.

CONCLUSIONS

VR-based cognitive training in parallel with fNIRS-derived neurofeedback is superior to enhancing cognitive function and neural efficiency.

Exploring Effects of Mental Stress with Data Augmentation and Classification Using fNIRS

Accurately identifying and discriminating between different brain states is a major emphasis of functional brain imaging research. Various machine learning techniques play an important role in this regard. However, when working with a small number of study participants, the lack of sufficient data and achieving meaningful classification results remain a challenge. In this study, we employ a classification strategy to explore stress and its impact on spatial activation patterns and brain connectivity caused by the Stroop color-word task (SCWT). To improve our results and increase our dataset, we use data augmentation with a deep convolutional generative adversarial network (DCGAN). The study is carried out at two separate times of day (morning and evening) and involves 21 healthy participants. Additionally, we introduce binaural beats (BBs) stimulation to investigate its potential for stress reduction. The morning session includes a control phase with 10 SCWT trials, whereas the afternoon session is divided into three phases: stress, mitigation (with 16 Hz BB stimulation), and post-mitigation, each with 10 SCWT trials. For a comprehensive evaluation, the acquired fNIRS data are classified using a variety of machine-learning approaches. Linear discriminant analysis (LDA) showed a maximum accuracy of 60%, whereas non-augmented data classified by a convolutional neural network (CNN) provided the highest classification accuracy of 73%. Notably, after augmenting the data with DCGAN, the classification accuracy increases dramatically to 96%. In the time series data, statistically significant differences were noticed in the data before and after BB stimulation, which showed an improvement in the brain state, in line with the classification results. These findings illustrate the ability to detect changes in brain states with high accuracy using fNIRS, underline the need for larger datasets, and demonstrate that data augmentation can significantly help when data are scarce in the case of brain signals.

Evaluating the impact of boxing on prefrontal cortex activation and cognitive performance: A pilot study using fNIRS technology and the Stroop test

This research sets out to investigate the differences in hemoglobin concentration occurring in the prefrontal cortex (PFC) during the administration of the Stroop test in active amateur boxers and to compare the obtained data regarding chronic traumatic brain injury with those of healthy individuals. The research was conducted at the Atatürk University Neuropsychology Laboratory. Participants consisted of 6 male boxers, aged 19.66 ± 2.94 years, who had been actively boxing for 7.5 ± 3.8 years and had received at least high school level education, with right-hand dominance, and 8 healthy males, aged 19.62 ± 1.18 years, who had not engaged in any combat sports. fNIRS recordings were taken over the Prefrontal Cortex (PFC) while Stroop test stimuli were presented to the participants in a block design. The data were analyzed using the JASP program. Mann-Whitney U test was applied to evaluate the differences between groups in Stroop test data. The activation levels on the prefrontal cortex during the test were evaluated using the Repeated Measures ANOVA test. A significance level of p <0.05 was accepted for the analyses. In conclusion, compared to the control group, boxers demonstrated a significantly higher level of cerebral activation in the right dlPFC/vlPFC regions during the congruent task and in the right dmPFC as well as the left dmPFC/vmPFC/OFC regions during the incongruent task in the Stroop test. When the Stroop test results of the participants were evaluated between groups, it was found that although statistically insignificant compared to healthy subjects, boxers generally exhibited failure. In conclusion, it was found that boxers exhibit higher neural activation responses and lower cognitive performance during neurophysiological testing compared to healthy controls. These two conditions are thought to be interconnected and are considered to result from neural inefficiency.

Identifying neuroimaging biomarkers in major depressive disorder using machine learning algorithms and functional near-infrared spectroscopy (fNIRS) during verbal fluency task

One of the most prevalent psychiatric disorders is major depressive disorder (MDD), which increases the probability of suicidal ideation or untimely demise. Abnormal frontal hemodynamic changes detected by functional near-infrared spectroscopy (fNIRS) during verbal fluency task (VFT) have the potential to be used as an objective indicator for assessing clinical symptoms. However, comprehensive quantitative and objective assessment instruments for individuals who exhibit symptoms suggestive of depression remain undeveloped. Drawing from a total of 467 samples in a large-scale dataset comprising 289 MDD patients and 178 healthy controls, fNIRS measurements were obtained throughout the VFT. To identify unique MDD biomarkers, this research introduced a data representation approach for extracting spatiotemporal features from fNIRS signals, which were subsequently utilized as potential predictors. Machine learning classifiers (e.g., Gradient Boosted Decision Trees (GBDT) and Multilayer Perceptron) were implemented to assess the ability to predict selected features. The mean and standard deviation of the cross-validation indicated that the GBDT model, when combined with the 180-feature pattern, distinguishes patients with MDD from healthy controls in the most effective manner. The accuracy of correct classification for the test set was 0.829 ± 0.053, with an AUC of 0.895 (95 % CI: 0.864-0.925) and a sensitivity of 0.914 ± 0.051. Channels that made the most important contribution to the identification of MDD were identified using Shapley Additive Explanations method, located in the frontopolar area and the dorsolateral prefrontal cortex, as well as pars triangularis Broca's area. Assessment of abnormal prefrontal activity during the VFT in MDD serves as an objectively measurable biomarker that could be utilized to evaluate cognitive deficits and facilitate early screening for MDD. The model suggested in this research could be applied to large-scale case-control fNIRS datasets to detect unique characteristics of MDD and offer clinicians an objective biomarker-based analytical instrument to assist in the evaluation of suspicious cases.

A feasibility study on using fNIRS brain signals to recognize personal thermal sensation and thermal comfort conditions

BACKGROUND

Many studies have shown some relationships between thermal perception (including thermal sensation and thermal comfort) and human physiological parameters, such as brain signals. However, further research is still needed on how these parameters can help recognize the state of a human's personal thermal perception.

OBJECTIVE

This study aims to investigate the potential of using fNIRS brain signals to evaluate and predict personal thermal perception and cognitive performance in a steady-state temperature.

METHODS

The present study investigated changes in the fNIRS signal during ambient temperature manipulation. Thirty healthy young individuals were selected as the subjects, and they were exposed to two steady temperatures of 28.8 and 19 °C. After acclimatizing to either temperature, the oxy/deoxy-hemoglobin changes of the prefrontal cortex (PFC) were measured in both rest and cognitive task states using 16-channel fNIRS.

RESULTS

Results showed that exposure to different temperatures was significantly associated with the brain signals recorded during the task state. Many significant correlations were discovered between fNIRS signals and thermal perception indices. Furthermore, subjects' performance changes led to changes in the fNIRS signals. Logistic regression showed that fNIRS can determine whether a person is thermally comfortable or uncomfortable.

Whole-Head Noninvasive Brain Signal Measurement System with High Temporal and Spatial Resolution Using Static Magnetic Field Bias to the Brain

Noninvasive brain signal measurement techniques are crucial for understanding human brain function and brain-machine interface applications. Conventionally, noninvasive brain signal measurement techniques, such as electroencephalography, magnetoencephalography, functional magnetic resonance imaging, and near-infrared spectroscopy, have been developed. However, currently, there is no practical noninvasive technique to measure brain function with high temporal and spatial resolution using one instrument. We developed a novel noninvasive brain signal measurement technique with high temporal and spatial resolution by biasing a static magnetic field emitted from a coil on the head to the brain. In this study, we applied this technique to develop a groundbreaking system for noninvasive whole-head brain function measurement with high spatiotemporal resolution across the entire head. We validated this system by measuring movement-related brain signals evoked by a right index finger extension movement and demonstrated that the proposed system can measure the dynamic activity of brain regions involved in finger movement with high spatiotemporal accuracy over the whole brain.

Can infrared light really be doing what we claim it is doing? Infrared light penetration principles, practices, and limitations

Near infrared (NIR) light has been shown to provide beneficial treatment of traumatic brain injury (TBI) and other neurological problems. This concept has spawned a plethora of commercial entities and practitioners utilizing panels of light emitting diodes (LEDs) and promising to treat patients with TBI and other disorders, who are desperate for some treatment for their untreatable conditions. Unfortunately, an LED intended to deliver photonic energy to the human brain does not necessarily do what an LED pointed at a mouse brain does. There is a problem of scale. Extensive prior research has shown that infrared light from a 0.5-watt LED will not penetrate the scalp and skull of a human. Both the properties of NIR light and the manner in which it interacts with tissue are examined. Based on these principles, the shortcomings of current approaches to treating neurological disorders with NIR light are explored. Claims of clinical benefit from low-level LED-based devices are explored and the proof of concept challenged. To date, that proof is thin with marginal benefits which are largely transient. Extensive research has shown fluence at the level of the target tissue which falls within the range of 0.9 J/cm2 to 15 J/cm2 is most effective in activating the biological processes at the cellular level which underlie direct photobiomodulation. If low-level infrared light from LED devices is not penetrating the scalp and skull, then these devices certainly are not delivering that level of fluence to the neurons of the subjacent brain. Alternative mechanisms, such as remote photobiomodulation, which may underlie the small and transient benefits for TBI symptoms reported for low-power LED-based NIR studies are presented. Actionable recommendations for the field are offered.

Distinct Time-Resolved Brain-Wide Coactivations in Oxygenated and Deoxygenated Hemoglobin

OBJECTIVE

Human resting-state networks (RSNs) estimated from oxygenated (HbO) and deoxygenated hemoglobin (HbR) data exhibit strong similarities, while task-based studies show different dynamics in HbR and HbO responses. Such a discrepancy might be explained due to time-averaged estimations of RSNs. Our study investigated differences between HbO and HbR on time-resolved brain-wide coactivation patterns (CAPs).

METHODS

Diffuse optical tomography was reconstructed from resting-state whole-head functional near-infrared spectroscopy data of HbR and HbO in individual healthy participants. Time-averaged RSNs were obtained using the group-level independent component analysis. Time-resolved CAPs were estimated using a clustering approach on the time courses of all obtained RSNs. Characteristics of the RSNs and CAPs from HbR and HbO were compared.

RESULTS

Spatial patterns of HbR and HbO RSNs exhibited significant similarities. Meanwhile, HbR CAPs revealed much more organized spatial and dynamic characteristics than HbO CAPs. The entire set of HbR CAPs suggests a superstructure resulted from brain-wide neuronal dynamics, which is less evident in the set of HbO CAPs. These differences between HbO and HbR CAPs were consistently replicated in individual session data.

CONCLUSION

Our results suggest that human resting brain-wide neuronal activations are preserved better in time-resolved brain-wide patterns, i.e., CAPs, from HbR than those from HbO, while such a difference is lost between time-averaged HbR and HbO RSNs.

SIGNIFICANCE

Our results reveal, for the first time, HbR concentration fluctuations are more directly coupled with resting dynamics of brain-wide neuronal activations in human brains.

Quantitative Optical Imaging of Oxygen in Brain Vasculature

The intimate relationship between neuronal activity and cerebral oxygenation underpins fundamental brain functions like cognition, sensation, and motor control. Optical imaging offers a noninvasive approach to assess brain oxygenation and often serves as an indirect proxy for neuronal activity. However, deciphering neurovascular coupling─the intricate interplay between neuronal activity, blood flow, and oxygen delivery─necessitates independent, high spatial resolution, and high temporal resolution measurements of both microvasculature oxygenation and neuronal activation. This Perspective examines the established optical techniques employed for brain oxygen imaging, specifically functional near-infrared spectroscopy, photoacoustic imaging, optical coherence tomography, and two-photon phosphorescent lifetime microscopy, highlighting their fundamental principles, strengths, and limitations. Several other emerging optical techniques are also introduced. Finally, we discuss key technological challenges and future directions for quantitative optical oxygen imaging, paving the way for a deeper understanding of oxygen metabolism in the brain.

Impact of repetitive transcranial magnetic stimulation on cortical activity: a systematic review and meta-analysis utilizing functional near-infrared spectroscopy evaluation

BACKGROUND

Repeated transcranial magnetic stimulation (rTMS) could induce alterations in cortical excitability and promote neuroplasticity. To precisely quantify these effects, functional near-infrared spectroscopy (fNIRS), an optical neuroimaging modality adept at detecting changes in cortical hemodynamic responses, has been employed concurrently alongside rTMS to measure and tailor the impact of diverse rTMS protocols on the brain cortex.

OBJECTIVE

This systematic review and meta-analysis aimed to elucidate the effects of rTMS on cortical hemodynamic responses over the primary motor cortex (M1) as detected by fNIRS.

METHODS

Original articles that utilized rTMS to stimulate the M1 cortex in combination with fNIRS for the assessment of cortical activity were systematically searched across the PubMed, Embase, and Scopus databases. The search encompassed records from the inception of these databases up until April, 2024. The assessment for risk of bias was also conducted. A meta-analysis was also conducted in studies with extractable raw data.

RESULTS

Among 312 studies, 14 articles were eligible for qualitative review. 7 studies were eligible for meta-analysis. A variety of rTMS protocols was employed on M1 cortex. In inhibitory rTMS, multiple studies observed a reduction in the concentration of oxygenated hemoglobin [HbO] at the ipsilateral M1, contrasted by an elevation at the contralateral M1. Meta-analysis also corroborated this consistent trend. Nevertheless, certain investigations unveiled diminished [HbO] in bilateral M1. Several studies also depicted intricate inhibitory or excitatory interplay among distinct cortical regions.

CONCLUSION

Diverse rTMS protocols led to varied patterns of cortical activity detected by fNIRS. Meta-analysis revealed a trend of increasing [HbO] in the contralateral cortices and decreasing [HbO] in the ipsilateral cortices following low frequency inhibitory rTMS. However, due to the heterogeneity between studies, further research is necessary to comprehensively understand rTMS-induced alterations in brain activity.

A multimodal dataset for investigating working memory in presence of music: a pilot study

Introduction

Decoding an individual's hidden brain states in responses to musical stimuli under various cognitive loads can unleash the potential of developing a non-invasive closed-loop brain-machine interface (CLBMI). To perform a pilot study and investigate the brain response in the context of CLBMI, we collect multimodal physiological signals and behavioral data within the working memory experiment in the presence of personalized musical stimuli.

Methods

Participants perform a working memory experiment called the n-back task in the presence of calming music and exciting music. Utilizing the skin conductance signal and behavioral data, we decode the brain's cognitive arousal and performance states, respectively. We determine the association of oxygenated hemoglobin (HbO) data with performance state. Furthermore, we evaluate the total hemoglobin (HbT) signal energy over each music session.

Results

A relatively low arousal variation was observed with respect to task difficulty, while the arousal baseline changes considerably with respect to the type of music. Overall, the performance index is enhanced within the exciting session. The highest positive correlation between the HbO concentration and performance was observed within the higher cognitive loads (3-back task) for all of the participants. Also, the HbT signal energy peak occurs within the exciting session.

Discussion

Findings may underline the potential of using music as an intervention to regulate the brain cognitive states. Additionally, the experiment provides a diverse array of data encompassing multiple physiological signals that can be used in the brain state decoder paradigm to shed light on the human-in-the-loop experiments and understand the network-level mechanisms of auditory stimulation.

Delayed cerebrovascular reactivity in individuals with spinal cord injury in the right inferior parietal lobe: a breath-hold functional near-infrared spectroscopy study

Cerebrovascular reactivity (CVR) reflects the ability of blood vessels to dilate or constrict in response to a vasoactive stimulus, and allows researchers to assess the brain's vascular health. Individuals with spinal cord injury (SCI) are at an increased risk for autonomic dysfunction in addition to cognitive impairments, which have been linked to a decline in CVR; however, there is currently a lack of brain-imaging studies that investigate how CVR is altered after SCI. In this study, we used a breath-holding hypercapnic stimulus and functional near-infrared spectroscopy (fNIRS) to investigate CVR alterations in individuals with SCI (n = 20, 14M, 6F, mean age = 46.3 ± 10.2 years) as compared to age- and sex-matched able-bodied (AB) controls (n = 25, 19M, 6F, mean age = 43.2 ± 12.28 years). CVR was evaluated by its amplitude and delay components separately by using principal component analysis and cross-correlation analysis, respectively. We observed significantly delayed CVR in the right inferior parietal lobe in individuals with SCI compared to AB controls (linear mixed-effects model, fixed-effects estimate = 6.565, Satterthwaite's t-test, t = 2.663, p = 0.008), while the amplitude of CVR was not significantly different. The average CVR delay in the SCI group in the right inferior parietal lobe was 14.21 s (sd: 6.60 s), and for the AB group, the average delay in the right inferior parietal lobe was 7.08 s (sd: 7.39 s). CVR delays were also associated with the duration since injury in individuals with SCI, in which a longer duration since injury was associated with a shortened delay in CVR in the right inferior parietal region (Pearson's r-correlation, r = -0.59, p = 0.04). This study shows that fNIRS can be used to quantify changes in CVR in individuals with SCI, and may be further used in rehabilitative settings to monitor the cerebrovascular health of individuals with SCI.

Hammerstein-Wiener Motion Artifact Correction for Functional Near-Infrared Spectroscopy: A Novel Inertial Measurement Unit-Based Technique

Participant movement is a major source of artifacts in functional near-infrared spectroscopy (fNIRS) experiments. Mitigating the impact of motion artifacts (MAs) is crucial to estimate brain activity robustly. Here, we suggest and evaluate a novel application of the nonlinear Hammerstein-Wiener model to estimate and mitigate MAs in fNIRS signals from direct-movement recordings through IMU sensors mounted on the participant's head (head-IMU) and the fNIRS probe (probe-IMU). To this end, we analyzed the hemodynamic responses of single-channel oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) signals from 17 participants who performed a hand tapping task with different levels of concurrent head movement. Additionally, the tapping task was performed without head movements to estimate the ground-truth brain activation. We compared the performance of our novel approach with the probe-IMU and head-IMU to eight established methods (PCA, tPCA, spline, spline Savitzky-Golay, wavelet, CBSI, RLOESS, and WCBSI) on four quality metrics: SNR, △AUC, RMSE, and R. Our proposed nonlinear Hammerstein-Wiener method achieved the best SNR increase (p < 0.001) among all methods. Visual inspection revealed that our approach mitigated MA contaminations that other techniques could not remove effectively. MA correction quality was comparable with head- and probe-IMUs.

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.

Construction and evaluation of a neurofeedback system using finger tapping and near-infrared spectroscopy

Introduction

Neurofeedback using near-infrared spectroscopy (NIRS) has been used in patients with stroke and other patients, but few studies have included older people or patients with cognitive impairment.

Methods

We constructed a NIRS-based neurofeedback system and used finger tapping to investigate whether neurofeedback can be implemented in older adults while finger tapping and whether brain activity improves in older adults and healthy participants. Our simple neurofeedback system was constructed using a portable wearable optical topography (WOT-HS) device. Brain activity was evaluated in 10 older and 31 healthy young individuals by measuring oxygenated hemoglobin concentration during finger tapping and neurofeedback implementation.

Results

During neurofeedback, the concentration of oxygenated hemoglobin increased in the prefrontal regions in both the young and older participants.

Discussion

The results of this study demonstrate the usefulness of neurofeedback using simple NIRS devices for older adults and its potential to mitigate cognitive decline.

Intermittent neck flexion induces greater sternocleidomastoid deoxygenation than inspiratory threshold loading

PURPOSE

To compare deoxygenation of the sternocleidomastoid, scalenes, and diaphragm/intercostals (Dia/IC) during submaximal intermittent neck flexion (INF) versus submaximal inspiratory threshold loading (ITL) in healthy adults.

METHODS

Fourteen participants performed a randomized, cross-over, repeated measures design. After evaluation of maximal inspiratory pressures (MIP) and maximum voluntary contraction (MVC) for isometric neck flexion, participants were randomly assigned to submaximal ITL or INF until task failure. At least 2 days later, they performed the submaximal exercises in the opposite order. ITL or INF targeted 50 ± 5% of the MIP or MVC, respectively, until task failure. Near-infrared spectroscopy (NIRS) was applied to evaluate changes of deoxy-hemoglobin (ΔHHb), oxy-hemoglobin (ΔO2Hb), total hemoglobin (ΔtHb), and tissue saturation of oxygen (StO2) of the sternocleidomastoid, scalenes, and Dia/IC. Breathlessness and perceived exertion were evaluated using Borg scales.

RESULTS

Initially during INF, sternocleidomastoid HHb slope was greatest compared to the scalenes and Dia/IC. At isotime (6.5-7 min), ΔtHb (a marker of blood volume) and ΔO2Hb of the sternocleidomastoid were higher during INF than ITL. Sternocleidomastoid HHb, O2Hb, and tHb during INF also increased at quartile and task failure timepoints. In contrast, scalene ΔO2Hb was higher during ITL than INF at isotime. Further, Dia/IC O2Hb and tHb increased during ITL at the third quartile and at task failure. Borg scores were lower at task failure during INF compared to ITL.

CONCLUSION

Intermittent INF induces significant metabolic activity of the sternocleidomastoid and a lower perception of effort, which may provide an alternative inspiratory muscle training approach for mechanically ventilated patients.

Classification of Mild Cognitive Impairment Using Functional Near-Infrared Spectroscopy-Derived Biomarkers With Convolutional Neural Networks

OBJECTIVE

To date, early detection of mild cognitive impairment (MCI) has mainly depended on paper-based neuropsychological assessments. Recently, biomarkers for MCI detection have gained a lot of attention because of the low sensitivity of neuropsychological assessments. This study proposed the functional near-infrared spectroscopy (fNIRS)-derived data with convolutional neural networks (CNNs) to identify MCI.

METHODS

Eighty-two subjects with MCI and 148 healthy controls (HC) performed the 2-back task, and their oxygenated hemoglobin (HbO2) changes in the prefrontal cortex (PFC) were recorded during the task. The CNN model based on fNIRS-derived spatial features with HbO2 slope within time windows was trained to classify MCI. Thereafter, the 5-fold cross-validation approach was used to evaluate the performance of the CNN model.

RESULTS

Significant differences in averaged HbO2 values between MCI and HC groups were found, and the CNN model could better discriminate MCI with over 89.57% accuracy than the Korean version of the Montreal Cognitive Assessment (MoCA) (89.57%). Specifically, the CNN model based on HbO2 slope within the time window of 20-60 seconds from the left PFC (96.09%) achieved the highest accuracy.

CONCLUSION

These findings suggest that the fNIRS-derived spatial features with CNNs could be a promising way for early detection of MCI as a surrogate for a conventional screening tool and demonstrate the superiority of the fNIRS-derived spatial features with CNNs to the MoCA.

Combined effects of mild hypothermia and nitrous-oxide-induced narcosis on manual and cognitive performance

Divers are at enhanced risk of suffering from acute cognitive deterioration because of the low ambient temperatures and the narcotic action of inert gases inspired at high pressures. Yet, the behavioral effects of cold and inert gas narcosis have commonly been assessed in isolation and during short-term provocations. We therefore evaluated the interactive influence of mild hypothermia and narcosis engendered by a subanesthetic dose of nitrous oxide (N2O; a normobaric intervention analog of hyperbaric nitrogen) on cognitive function during prolonged iterative exposure. Fourteen men partook in two ∼12-h sessions (separated by ≥4 days), wherein they performed sequentially three 120-min cold (20°C) water immersions (CWIs), while inhaling, in a single-blinded manner, either normal air or a normoxic gas mixture containing 30% N2O. CWIs were separated by a 120-min rewarming in room-air breathing conditions. Before the first CWI and during each CWI, subjects performed a finger dexterity test, and the Spaceflight Cognitive Assessment Tool for Windows (WinSCAT) test assessing aspects of attention, memory, learning, and visuospatial ability. Rectal and skin temperatures were, on average, reduced by ∼1.2 °C and ∼8 °C, respectively (P < 0.001). Cooling per se impaired (P ≤ 0.01) only short-term memory (∼37%) and learning (∼18%); the impairments were limited to the first CWI. N2O also attenuated (P ≤ 0.02) short-term memory (∼37%) and learning (∼35%), but the reductions occurred in all CWIs. Furthermore, N2O invariably compromised finger dexterity, attention, concentration, working memory, and spatial processing (P < 0.05). The present results demonstrate that inert gas narcosis aggravates, in a persistent manner, basic and higher-order cognitive abilities during protracted cold exposure.

Brain activation during the N-back working memory task in individuals with spinal cord injury: a functional near-infrared spectroscopy study

Cognitive impairments have frequently been reported in individuals with spinal cord injury (SCI) across different domains such as working memory, attention, and executive function. The mechanism of cognitive impairment after SCI is not well understood due to the heterogeneity of SCI sample populations, and may possibly be due to factors such as cardiovascular dysfunction, concomitant traumatic brain injury (TBI), hypoxia, sleep disorders, and body temperature dysregulation. In this study, we implement the Neuropsychiatric Unit Cognitive Assessment Tool (NUCOG) to assess cognitive differences between individuals with SCI and age-matched able-bodied (AB) controls. We then use an N-back working memory task and functional near-infrared spectroscopy (fNIRS) to elucidate the neurovascular correlates of cognitive function in individuals with SCI. We observed significant differences between the SCI and AB groups on measures of executive function on the NUCOG test. On the N-back task, across the three levels of difficulty: 0-back, 2-back, and 3-back, no significant differences were observed between the SCI and AB group; however, both groups performed worse as the level of difficulty increased. Although there were no significant differences in N-back performance scores between the two groups, functional brain hemodynamic activity differences were observed between the SCI and AB groups, with the SCI group exhibiting higher maximum oxygenated hemoglobin concentration in the right inferior parietal lobe. These findings support the use of fNIRS to study cognitive function in individuals with SCI and may provide a useful tool during rehabilitation to obtain quantitative functional brain activity metrics.

Molecularly generated light and its biomedical applications

Molecularly generated light, referred to here as "molecular light", mainly includes bioluminescence, chemiluminescence, and Cerenkov luminescence. Molecular light possesses unique dual features of being both a molecule and a source of light. Its molecular nature enables it to be delivered as molecules to regions deep within the body, overcoming the limitations of natural sunlight and physically generated light sources like lasers and LEDs. Simultaneously, its light properties make it valuable for applications such as imaging, photodynamic therapy, photo-oxidative therapy, and photobiomodulation. In this review article, we provide an updated overview of the diverse applications of molecular light and discuss the strengths and weaknesses of molecular light across various domains. Lastly, we present forward-looking perspectives on the potential of molecular light in the realms of molecular imaging, photobiological mechanisms, therapeutic applications, and photobiomodulation. While some of these perspectives may be considered bold and contentious, our intent is to inspire further innovations in the field of molecular light applications.

Unveiling Neurocognitive Disparities in Encoding and Retrieval between Paper and Digital Tablet-Based Learning

The widespread use of mobile devices and laptops has replaced traditional paper-based learning and the question of how the brain efficiency of digital tablet-based learning differs from that of paper-based learning remains unclear. The purpose of this study was to investigate the difference in brain efficiency for learning between paper-based and digital tablet-based learning by measuring activity in the prefrontal cortex (PFC) using functional near-infrared spectroscopy. Thirty-two subjects were randomly assigned to the paper-based learning or the digital tablet-based learning group. Subjects in each group performed a memory task that required memorizing a three-minute novel (encoding phase) on a paper or digital tablet, followed by a test in which they answered four multiple-choice questions based on the novel's content. To compare both groups, behavioral performance on the test (retrieval phase) and activity in the PFC were measured. As a result, no significant difference in behavioral performance between both groups was observed (p > 0.05). However, the paper-based learning group showed significantly lower activity in the PFC in the encoding phase than the digital tablet-based learning group (p < 0.05) but not in the retrieval phase. The current study demonstrated that brain efficiency in encoding is higher in subjects with paper-based learning than those with digital tablet-based learning. This finding has important implications for education, particularly in terms of the pros and cons of electronic document-based learning.

Unraveling neural pathways of political engagement: bridging neuromarketing and political science for understanding voter behavior and political leader perception

Introduction

Political neuromarketing is an emerging interdisciplinary field integrating marketing, neuroscience, and psychology to decipher voter behavior and political leader perception. This interdisciplinary field offers novel techniques to understand complex phenomena such as voter engagement, political leadership, and party branding.

Methods

This study aims to understand the neural activation patterns of voters when they are exposed to political leaders using functional near-infrared spectroscopy (fNIRS) and machine learning methods. We recruited participants and recorded their brain activity using fNIRS when they were exposed to images of different political leaders.

Results

This neuroimaging method (fNIRS) reveals brain regions central to brand perception, including the dorsolateral prefrontal cortex (dlPFC), the dorsomedial prefrontal cortex (dmPFC), and the ventromedial prefrontal cortex (vmPFC). Machine learning methods were used to predict the participants' perceptions of leaders based on their brain activity. The study has identified the brain regions that are involved in processing political stimuli and making judgments about political leaders. Within this study, the best-performing machine learning model, LightGBM, achieved a highest accuracy score of 0.78, underscoring its efficacy in predicting voters' perceptions of political leaders based on the brain activity of the former.

Discussion

The findings from this study provide new insights into the neural basis of political decision-making and the development of effective political marketing campaigns while bridging neuromarketing, political science, and machine learning, in turn enabling predictive insights into voter preferences and behavior.

Mental workload classification using convolutional neural networks based on fNIRS-derived prefrontal activity

BACKGROUND

Functional near-infrared spectroscopy (fNIRS) is a tool to assess brain activity during cognitive testing. Despite its usefulness, its feasibility in assessing mental workload remains unclear. This study was to investigate the potential use of convolutional neural networks (CNNs) based on functional near-infrared spectroscopy (fNIRS)-derived signals to classify mental workload in individuals with mild cognitive impairment.

METHODS

Spatial images by constructing a statistical activation map from the prefrontal activity of 120 subjects with MCI performing three difficulty levels of the N-back task (0, 1, and 2-back) were used for CNNs. The CNNs were evaluated using a 5 and 10-fold cross-validation method.

RESULTS

As the difficulty level of the N-back task increased, the accuracy decreased and prefrontal activity increased. In addition, there was a significant difference in the accuracy and prefrontal activity across the three levels (p's < 0.05). The accuracy of the CNNs based on fNIRS-derived spatial images evaluated by 5 and 10-fold cross-validation in classifying the difficulty levels ranged from 0.83 to 0.96.

CONCLUSION

fNIRS could also be a promising tool for measuring mental workload in older adults with MCI despite their cognitive decline. In addition, this study demonstrated the feasibility of the classification performance of the CNNs based on fNIRS-derived signals from the prefrontal cortex.

Correlation and asynchronization of electroencephalogram and cerebral blood flow in active and passive stimulations

Objective.Real-time brain monitoring is of importance for intraoperative surgeries and intensive care unit, in order to take timely clinical interventions. Electroencephalogram (EEG) is a conventional technique for recording neural excitations (e.g. brain waves) in the cerebral cortex, and near infrared diffuse correlation spectroscopy (DCS) is an emerging technique that can directly measure the cerebral blood flow (CBF) in microvasculature system. Currently, the relationship between the neural activities and cerebral hemodynamics that reflects the vasoconstriction features of cerebral vessels, especially under both active and passive situation, has not been elucidated thus far, which triggers the motivation of this study.Approach.We used the verbal fluency test as an active cognitive stimulus to the brain, and we manipulated blood pressure changes as a passive challenge to the brain. Under both protocols, the CBF and EEG responses were longitudinally monitored throughout the cerebral stimulus. Power spectrum approaches were applied the EEG signals and compared with CBF responses.Main results.The results show that the EEG response was significantly faster and larger in amplitude during the active cognitive task, when compared to the CBF, but with larger individual variability. By contrast, CBF is more sensitive when response to the passive task, and with better signal stability. We also found that there was a correlation (p< 0.01,r= 0.866,R2= 0.751) between CBF and EEG in initial response during the active task, but no significant correlation (p> 0.05) was found during the passive task. The similar relations were also found between regional brain waves and blood flow.Significance.The asynchronization and correlation between the two measurements indicates the necessity of monitoring both variables for comprehensive understanding of cerebral physiology. Deep exploration of their relationships provides promising implications for DCS/EEG integration in the diagnosis of various neurovascular and psychiatric diseases.

Effects of Personalized Cognitive Training Using Mental Workload Monitoring on Executive Function in Older Adults With Mild Cognitive Impairment

Although a variety of cognitive training has been performed, its optimally personalized delivery is still unknown. This study established the mental workload classification model using a convolutional neural network based on functional near-infrared spectroscopy-derived data. The dorsolateral prefrontal cortex (DLPFC) while thirty individuals with mild cognitive impairment (MCI) performed spatial working memory testing was found to be a considerable indicator to classify 3 levels of mental workload with an accuracy of over 86%. In the next step, forty subjects with MCI were randomly allocated into the experimental group (EG) that received cognitive training with mental workload-based difficulty adjustment or the control group (CG) that received conventional cognitive training. To compare both groups, the Trail Making Test Part B (TMT-B) and hemodynamic responses in the DLPFC during the TMT-B were measured. After the 16 training sessions, the EG subjects achieved a greater improvement in the TMT-B than the CG subjects (p < 0.05). Also, the EG subject showed a significantly lower DLPFC activity during the TMT-B than the CG subject (p < 0.05). In sum, the EG subjects better performed executive function with lower energy from the DLPFC. These findings imply that the importance of mental workload monitoring to provide personalized cognitive training.

High-Density Functional Near-Infrared Spectroscopy and Machine Learning for Visual Perception Quantification

The main application scenario for wearable sensors involves the generation of data and monitoring metrics. fNIRS (functional near-infrared spectroscopy) allows the nonintrusive monitoring of human visual perception. The quantification of visual perception by fNIRS facilitates applications in engineering-related fields. This study designed a set of experimental procedures to effectively induce visible alterations and to quantify visual perception in conjunction with the acquisition of Hbt (total hemoglobin), Hb (hemoglobin), and HbO2 (oxygenated hemoglobin) data obtained from HfNIRS (high-density functional near-infrared spectroscopy). Volunteers completed the visual task separately in response to different visible changes in the simulated scene. HfNIRS recorded the changes in Hbt, Hb, and HbO2 during the study, the time point of the visual difference, and the time point of the task change. This study consisted of one simulated scene, two visual variations, and four visual tasks. The simulation scene featured a car driving location. The visible change suggested that the brightness and saturation of the car operator interface would change. The visual task represented the completion of the layout, color, design, and information questions answered in response to the visible change. This study collected data from 29 volunteers. The volunteers completed the visual task separately in response to different visual changes in the same simulated scene. HfNIRS recorded the changes in Hbt, Hb, and HbO2 during the study, the time point of the visible difference, and the time point of the task change. The data analysis methods in this study comprised a combination of channel dimensionality reduction, feature extraction, task classification, and score correlation. Channel downscaling: This study used the data of 15 channels in HfNIRS to calculate the mutual information between different channels to set a threshold, and to retain the data of the channels that were higher than those of the mutual information. Feature extraction: The statistics derived from the visual task, including time, mean, median, variance, extreme variance, kurtosis, bias, information entropy, and approximate entropy were computed. Task classification: This study used the KNN (K-Nearest Neighbors) algorithm to classify different visual tasks and to calculate the accuracy, precision, recall, and F1 scores. Scoring correlation: This study matched the visual task scores with the fluctuations of Hbt, Hb, and HbO2 and observed the changes in Hbt, Hb, and HbO2 under different scoring levels. Mutual information was used to downscale the channels, and seven channels were retained for analysis under each visual task. The average accuracy was 96.3% ± 1.99%; the samples that correctly classified the visual task accounted for 96.3% of the total; and the classification accuracy was high. By analyzing the correlation between the scores on different visual tasks and the fluctuations of Hbt, Hb, and HbO2, it was found that the higher the score, the more obvious, significant, and higher the fluctuations of Hbt, Hb, and HbO2. Experiments found that changes in visual perception triggered changes in Hbt, Hb, and HbO2. HfNIRS combined with Hbt, Hb, and HbO2 recorded by machine learning algorithms can effectively quantify visual perception. However, the related research in this paper still needs to be further refined, and the mathematical relationship between HfNIRS and visual perception needs to be further explored to realize the quantitative study of subjective and objective visual perception supported by the mathematical relationship.

Measurements of the lateral cerebellar hemispheres using near-infrared spectroscopy through comparison between autism spectrum disorder and typical development

The cerebellum plays a vital role in cognition, communication with the cerebral cortex, and fine motor coordination. Near-infrared spectroscopy (NIRS) is a portable, less restrictive, and noninvasive functional brain imaging method that can capture brain activity during movements by measuring the relative oxyhemoglobin (oxy-Hb) concentrations in the blood. However, the feasibility of using NIRS to measure cerebellar activity requires discussion. We compared NIRS responses between areas assumed to be the cerebellum and the occipital lobe during a fine motor task (tying a bow knot) and a visual task. Our results showed that the oxy-Hb concentration increased more in the occipital lobe than in the cerebellum during the visual task (p =.034). In contrast, during the fine motor task, the oxy-Hb concentration decreased in the occipital lobe but increased significantly in the cerebellum, indicating a notable difference (p =.015). These findings suggest that we successfully captured cerebellar activity associated with processing, particularly fine motor coordination. Moreover, the observed responses did not differ between individuals with autism spectrum disorder and those with typical development. Our study demonstrates the meaningful utility of NIRS as a method for measuring cerebellar activity during movements.

Editorial Special Section on Biomedical Diffuse Optics for the Brain

This special section collects four articles on the application of diffuse optics to measure cerebral hemodynamics and oxygenation. The possibility of using near-infrared light to collect cerebral hemodynamic and metabolic information through the intact scalp and skull was first proposed in the 1970s [1]. Commercial cerebral oximeters were developed in the 1990s, and functional measurements of brain activation, which signaled the birth of functional near-infrared spectroscopy (fNIRS), were first reported in 1993 [2], [3], [4], [5]. Oscillatory cerebral hemodynamics were also investigated in relation to functional and diagnostic applications [6], [7], [8], [9]. Journal special issues were published to celebrate the 20th [10] and 30th [11] anniversaries of fNIRS, and numerous review articles have provided overviews of the field of noninvasive optical measurements of the brain [12], [13], [14], [15].

Respiratory Rate Extraction from Neonatal Near-Infrared Spectroscopy Signals

Background: Near-infrared spectroscopy (NIRS) relative concentration signals contain 'noise' from physiological processes such as respiration and heart rate. Simultaneous assessment of NIRS and respiratory rate (RR) using a single sensor would facilitate a perfectly time-synced assessment of (cerebral) physiology. Our aim was to extract respiratory rate from cerebral NIRS intensity signals in neonates admitted to a neonatal intensive care unit (NICU). Methods: A novel algorithm, NRR (NIRS RR), is developed for extracting RR from NIRS signals recorded from critically ill neonates. In total, 19 measurements were recorded from ten neonates admitted to the NICU with a gestational age and birth weight of 38 ± 5 weeks and 3092 ± 990 g, respectively. We synchronously recorded NIRS and reference RR signals sampled at 100 Hz and 0.5 Hz, respectively. The performance of the NRR algorithm is assessed in terms of the agreement and linear correlation between the reference and extracted RRs, and it is compared statistically with that of two existing methods. Results: The NRR algorithm showed a mean error of 1.1 breaths per minute (BPM), a root mean square error of 3.8 BPM, and Bland-Altman limits of agreement of 6.7 BPM averaged over all measurements. In addition, a linear correlation of 84.5% (p < 0.01) was achieved between the reference and extracted RRs. The statistical analyses confirmed the significant (p < 0.05) outperformance of the NRR algorithm with respect to the existing methods. Conclusions: We showed the possibility of extracting RR from neonatal NIRS in an intensive care environment, which showed high correspondence with the reference RR recorded. Adding the NRR algorithm to a NIRS system provides the opportunity to record synchronously different physiological sources of information about cerebral perfusion and respiration by a single monitoring system. This allows for a concurrent integrated analysis of the impact of breathing (including apnea) on cerebral hemodynamics.

Brightening the Study of Listening Effort with Functional Near-Infrared Spectroscopy: A Scoping Review

Listening effort is a long-standing area of interest in auditory cognitive neuroscience. Prior research has used multiple techniques to shed light on the neurophysiological mechanisms underlying listening during challenging conditions. Functional near-infrared spectroscopy (fNIRS) is growing in popularity as a tool for cognitive neuroscience research, and its recent advances offer many potential advantages over other neuroimaging modalities for research related to listening effort. This review introduces the basic science of fNIRS and its uses for auditory cognitive neuroscience. We also discuss its application in recently published studies on listening effort and consider future opportunities for studying effortful listening with fNIRS. After reading this article, the learner will know how fNIRS works and summarize its uses for listening effort research. The learner will also be able to apply this knowledge toward generation of future research in this area.

Laterality Index Calculations in a Control Study of Functional Near Infrared Spectroscopy

Hemispheric dominance has been used to understand the influence of central and peripheral neural damage on the motor function of individuals with stroke, cerebral palsy, and limb loss. It has been well established that greater activation occurs in the contralateral hemisphere to the side of the body used to perform the task. However, there is currently a large variability in calculation procedures for brain laterality when using functional near-infrared spectroscopy (fNIRS) as a non-invasive neuroimaging tool. In this study, we used fNIRS to measure brain activity over the left and right sensorimotor cortices while participants (n = 20, healthy and uninjured) performed left and right-hand movement tasks. Then, we analyzed the fNIRS data using two different processing pipelines (block averaging or general linear model [GLM]), two different criteria of processing for negative values (include all beta values or include only positive beta values), and three different laterality index (LI) formulas. The LI values produced using the block averaging analysis indicated an expected contralateral dominance with some instances of bilateral dominance, which agreed with the expected contralateral activation. However, the inclusion criteria nor the LI formulas altered the outcome. The LI values produced using the GLM analysis displayed a robust left hemisphere dominance regardless of the hand performing the task, which disagreed with the expected contralateral activation but did provide instances of correctly identifying brain laterality. In conclusion, both analysis pipelines were able to correctly determine brain laterality, but processes to account for negative beta values were recommended especially when utilizing the GLM analysis to determine brain laterality.

Practical Guidance for Developing Small-Molecule Optical Probes for In Vivo Imaging

The WMIS Education Committee (2019-2022) reached a consensus that white papers on molecular imaging could be beneficial for practitioners of molecular imaging at their early career stages and other scientists who are interested in molecular imaging. With this consensus, the committee plans to publish a series of white papers on topics related to the daily practice of molecular imaging. In this white paper, we aim to provide practical guidance that could be helpful for optical molecular imaging, particularly for small molecule probe development and validation in vitro and in vivo. The focus of this paper is preclinical animal studies with small-molecule optical probes. Near-infrared fluorescence imaging, bioluminescence imaging, chemiluminescence imaging, image-guided surgery, and Cerenkov luminescence imaging are discussed in this white paper.

Haptic shared control improves neural efficiency during myoelectric prosthesis use

Clinical myoelectric prostheses lack the sensory feedback and sufficient dexterity required to complete activities of daily living efficiently and accurately. Providing haptic feedback of relevant environmental cues to the user or imbuing the prosthesis with autonomous control authority have been separately shown to improve prosthesis utility. Few studies, however, have investigated the effect of combining these two approaches in a shared control paradigm, and none have evaluated such an approach from the perspective of neural efficiency (the relationship between task performance and mental effort measured directly from the brain). In this work, we analyzed the neural efficiency of 30 non-amputee participants in a grasp-and-lift task of a brittle object. Here, a myoelectric prosthesis featuring vibrotactile feedback of grip force and autonomous control of grasping was compared with a standard myoelectric prosthesis with and without vibrotactile feedback. As a measure of mental effort, we captured the prefrontal cortex activity changes using functional near infrared spectroscopy during the experiment. It was expected that the prosthesis with haptic shared control would improve both task performance and mental effort compared to the standard prosthesis. Results showed that only the haptic shared control system enabled users to achieve high neural efficiency, and that vibrotactile feedback was important for grasping with the appropriate grip force. These results indicate that the haptic shared control system synergistically combines the benefits of haptic feedback and autonomous controllers, and is well-poised to inform such hybrid advancements in myoelectric prosthesis technology.

Review: Emerging Eye-Based Diagnostic Technologies for Traumatic Brain Injury

The study of ocular manifestations of neurodegenerative disorders, Oculomics, is a growing field of investigation for early diagnostics, enabling structural and chemical biomarkers to be monitored overtime to predict prognosis. Traumatic brain injury (TBI) triggers a cascade of events harmful to the brain, which can lead to neurodegeneration. TBI, termed the "silent epidemic" is becoming a leading cause of death and disability worldwide. There is currently no effective diagnostic tool for TBI, and yet, early-intervention is known to considerably shorten hospital stays, improve outcomes, fasten neurological recovery and lower mortality rates, highlighting the unmet need for techniques capable of rapid and accurate point-of-care diagnostics, implemented in the earliest stages. This review focuses on the latest advances in the main neuropathophysiological responses and the achievements and shortfalls of TBI diagnostic methods. Validated and emerging TBI-indicative biomarkers are outlined and linked to ocular neuro-disorders. Methods detecting structural and chemical ocular responses to TBI are categorised along with prospective chemical and physical sensing techniques. Particular attention is drawn to the potential of Raman spectroscopy as a non-invasive sensing of neurological molecular signatures in the ocular projections of the brain, laying the platform for the first tangible path towards alternative point-of-care diagnostic technologies for TBI.

Characterization of forehead blood flow bias on NIRS signals during neural activation with a verbal fluency task

The major problem of near-infrared spectroscopy (NIRS) for brain activity measurement during verbal fluency task is the overlapping forehead scalp blood flow (FBF) on the target cerebral blood flow (CBF). There could be among-individual differences in the influence of FBF on CBF. We investigated effects of FBF on CBF by comparing signals obtained through a laser Doppler flowmeter (LDF) and NIRS using the modified Beer-Lambert Law (MBLL). Among 25 healthy individuals, 7 participants showed a strong correlation between LDF and NIRS signals (r_s >0.500). There were no significant differences according to age or sex. Subsequently, we applied the hemodynamic separation method to the values calculated using the MBLL (Δ[oxy-Hb]_M): to separate the concentration of oxygenated hemoglobin in the forehead (Δ[oxy-Hb]_F) and cerebral cortex (Δ[oxy-Hb]_C). First, we found that the influence of Δ[oxy-Hb]_F on Δ[oxy-Hb]_C in the high r_s group was almost twice as large as that in the low r_s group. Second, presence of sex and age differences in the influence of Δ[oxy-Hb]_F on Δ[oxy-Hb]_C were suggested. Based on the results, we discuss the factors affecting FBF and the resulting variations in NIRS signals.

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

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

Impact of hyperoxia and phenylephrine on cerebral oxygenation: An experimental clinical study

BACKGROUND

Oxygen supply to the brain is of special importance during intracranial surgery because it may be compromised by intracranial pathology. A high arterial blood pressure (mean arterial pressure above 80 mmHg) and a high arterial oxygen tension (PaO₂ above 12 kPa) is therefore often targeted in these patients, when for example intracranial pressure is increased or when a mass effect on brain tissue from a tumour is present, and it is pursued by administering vasopressors such as phenylephrine and by increasing inspiratory oxygen fraction (FiO₂ ). However, whether these interventions increase cerebral oxygenation remains uncertain. We aimed to investigate the effect of hyperoxia and phenylephrine on brain tissue oxygen tension (PbtO₂ ) in patients undergoing craniotomy.

METHODS

In this experimental study, we included 17 adult patients scheduled for elective craniotomy. After securing a stable baseline of the oxygen probe, PbtO₂ was measured in white matter peripherally in the surgical field during general anaesthesia. Primary comparisons were PbtO₂ before versus after an increase in FiO₂ from 0.30 to 0.80 as well as before versus after a bolus dose of phenylephrine (0.1-0.2 mg depending on patient haemodynamics). Data were analysed with the Wilcoxon signed rank test.

RESULTS

We obtained complete data sets in 11 patients undergoing the FiO₂ increase and six patients receiving the phenylephrine bolus. PbtO₂ was 22 (median; 5%-95% range, 4.6-54) mmHg during 30% oxygen, 68 (8.4-99) mmHg during 80% oxygen (p = .004 compared to 30% oxygen), 21 (4.5-81) mmHg before phenylephrine, and 19 (4.2-56) mmHg after phenylephrine (p = .56 compared to before phenylephrine).

CONCLUSION

In patients undergoing craniotomy under general anaesthesia, brain tissue oxygen tension increased with a high inspiratory oxygen fraction but remained unchanged after a bolus dose of phenylephrine.

Interferometric diffuse optics: recent advances and future outlook

The field of diffuse optics has provided a rich set of neurophotonic tools to measure the human brain noninvasively. Interferometric detection is a recent, exciting methodological development in this field. The approach is especially promising for the measurement of diffuse fluctuation signals related to blood flow. Benefitting from inexpensive sensor arrays, the interferometric approach has already dramatically improved throughput, enabling the measurement of brain blood flow faster and deeper. The interferometric approach can also achieve time-of-flight resolution, improving the accuracy of acquired signals. We provide a historical perspective and summary of recent work in the nascent area of interferometric diffuse optics. We predict that the convergence of interferometric technology with existing economies of scale will propel many advances in the years to come.

Can the fNIRS-derived neural biomarker better discriminate mild cognitive impairment than a neuropsychological screening test?

Introduction

Early detection of mild cognitive impairment (MCI), a pre-clinical stage of Alzheimer's disease (AD), has been highlighted as it could be beneficial to prevent progression to AD. Although prior studies on MCI screening have been conducted, the optimized detection way remain unclear yet. Recently, the potential of biomarker for MCI has gained a lot of attention due to a relatively low discriminant power of clinical screening tools.

Methods

This study evaluated biomarkers for screening MCI by performing a verbal digit span task (VDST) using functional near-infrared spectroscopy (fNIRS) to measure signals from the prefrontal cortex (PFC) from a group of 84 healthy controls and 52 subjects with MCI. The concentration changes of oxy-hemoglobin (HbO) were explored during the task in subject groups.

Results

Findings revealed that significant reductions in HbO concentration were observed in the PFC in the MCI group. Specially, the mean of HbO (mHbO) in the left PFC showed the highest discriminant power for MCI, which was higher than that of the Korean version of montreal cognitive assessment (MoCA-K) widely used as a screening tool for MCI. Furthermore, the mHbO in the PFC during the VDST was identified to be significantly correlated to the MoCA-K scores.

Discussion

These findings shed new light on the feasibility and superiority of fNIRS-derived neural biomarker for screening MCI.

Reliable Fast (20 Hz) Acquisition Rate by a TD fNIRS Device: Brain Resting-State Oscillation Studies

A high power setup for multichannel time-domain (TD) functional near infrared spectroscopy (fNIRS) measurements with high efficiency detection system was developed. It was fully characterized based on international performance assessment protocols for diffuse optics instruments, showing an improvement of the signal-to-noise ratio (SNR) with respect to previous analogue devices, and allowing acquisition of signals with sampling rate up to 20 Hz and source-detector distance up to 5 cm. A resting-state measurement on the motor cortex of a healthy volunteer was performed with an acquisition rate of 20 Hz at a 4 cm source-detector distance. The power spectrum for the cortical oxy- and deoxyhemoglobin is also provided.

Error-related brain state analysis using electroencephalography in conjunction with functional near-infrared spectroscopy during a complex surgical motor task

Error-based learning is one of the basic skill acquisition mechanisms that can be modeled as a perception-action system and investigated based on brain-behavior analysis during skill training. Here, the error-related chain of mental processes is postulated to depend on the skill level leading to a difference in the contextual switching of the brain states on error commission. Therefore, the objective of this paper was to compare error-related brain states, measured with multi-modal portable brain imaging, between experts and novices during the Fundamentals of Laparoscopic Surgery (FLS) "suturing and intracorporeal knot-tying" task (FLS complex task)-the most difficult among the five psychomotor FLS tasks. The multi-modal portable brain imaging combined functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) for brain-behavior analysis in thirteen right-handed novice medical students and nine expert surgeons. The brain state changes were defined by quasi-stable EEG scalp topography (called microstates) changes using 32-channel EEG data acquired at 250 Hz. Six microstate prototypes were identified from the combined EEG data from experts and novices during the FLS complex task that explained 77.14% of the global variance. Analysis of variance (ANOVA) found that the proportion of the total time spent in different microstates during the 10-s error epoch was significantly affected by the skill level (p < 0.01), the microstate type (p < 0.01), and the interaction between the skill level and the microstate type (p < 0.01). Brain activation based on the slower oxyhemoglobin (HbO) changes corresponding to the EEG band power (1-40 Hz) changes were found using the regularized temporally embedded Canonical Correlation Analysis of the simultaneously acquired fNIRS-EEG signals. The HbO signal from the overlying the left inferior frontal gyrus-opercular part, left superior frontal gyrus-medial orbital, left postcentral gyrus, left superior temporal gyrus, right superior frontal gyrus-medial orbital cortical areas showed significant (p < 0.05) difference between experts and novices in the 10-s error epoch. We conclude that the difference in the error-related chain of mental processes was the activation of cognitive top-down attention-related brain areas, including left dorsolateral prefrontal/frontal eye field and left frontopolar brain regions, along with a 'focusing' effect of global suppression of hemodynamic activation in the experts, while the novices had a widespread stimulus(error)-driven hemodynamic activation without the 'focusing' effect.

Characteristics of psychomotor retardation distinguishes patients with depression using multichannel near-infrared spectroscopy and finger tapping task

BACKGROUND

Psychomotor retardation (PMR) is frequently noted as a characteristic feature of major depressive disorder (MDD). In patients with depression, it is characterized by retardation of speech, emotion, thinking, and cognition. This study explored the activation pattern of the prefrontal cortex (PFC) during the finger-tapping task (FTT) in subjects with MDD, aiming to provide additional understanding on the connection between PMR and PFC activation pattern in depression through the use of near-Infrared Spectroscopy (NIRS). We hypothesized that, through use of NIRS during the FTT, motor retardation in depression would generate a distinct PFC activation pattern, allowing for differentiation between patients with MDD and healthy controls (HCs).

METHODS

Thirty-five patients with MDD and thirty-nine HCs underwent NIRS evaluation during performance of the FTT. The FTT included both left-finger tapping and right-finger tapping performed by a computer screen. Each participant was assessed using a 45-channel NIRS and various clinical scales.

FINDINGS

During the left-FTT, the left orbitofrontal cortex (OFC) showed higher oxy-hemoglobin (Oxy-Hb) activation in the MDD group when compared to the HCs. During the right-FTT, the right dorsolateral prefrontal cortex (DLPFC) demonstrated lower Oxy-Hb activation, and the dorsomedial prefrontal cortex (DMPFC) showed higher Oxy-Hb activation in the MDD group versus the HC group.

CONCLUSION

Our results demonstrated different activation patterns of the PFC between the MDD and HC groups, using FTT as a motor performance task. In particular, the OFC, the DLPFC and the DMPFC areas hold promise as new useful sites for such differentiation in future investigations.

Programming ability prediction: Applying an attention-based convolutional neural network to functional near-infrared spectroscopy analyses of working memory

Although theoretical studies have suggested that working-memory capacity is crucial for academic achievement, few empirical studies have directly investigated the relationship between working-memory capacity and programming ability, and no direct neural evidence has been reported to support this relationship. The present study aimed to fill this gap in the literature. Using a between-subject design, 17 programming novices and 18 advanced students performed an n-back working-memory task. During the experiment, their prefrontal hemodynamic responses were measured using a 48-channel functional near-infrared spectroscopy (fNIRS) device. The results indicated that the advanced students had a higher working-memory capacity than the novice students, validating the relationship between programming ability and working memory. The analysis results also showed that the hemodynamic responses in the prefrontal cortex can be used to discriminate between novices and advanced students. Additionally, we utilized an attention-based convolutional neural network to analyze the spatial domains of the fNIRS signals and demonstrated that the left prefrontal cortex was more important than other brain regions for programming ability prediction. This result was consistent with the results of statistical analysis, which in turn improved the interpretability of neural networks.

Decoding lexical tones and vowels in imagined tonal monosyllables using fNIRS signals

Objective.Speech is a common way of communication. Decoding verbal intent could provide a naturalistic communication way for people with severe motor disabilities. Active brain computer interaction (BCI) speller is one of the most commonly used speech BCIs. To reduce the spelling time of Chinese words, identifying vowels and tones that are embedded in imagined Chinese words is essential. Functional near-infrared spectroscopy (fNIRS) has been widely used in BCI because it is portable, non-invasive, safe, low cost, and has a relatively high spatial resolution.Approach.In this study, an active BCI speller based on fNIRS is presented by covertly rehearsing tonal monosyllables with vowels (i.e. /a/, /i/, /o/, and /u/) and four lexical tones in Mandarin Chinese (i.e. tones 1, 2, 3, and 4) for 10 s.Main results.fNIRS results showed significant differences in the right superior temporal gyrus between imagined vowels with tone 2/3/4 and those with tone 1 (i.e. more activations and stronger connections to other brain regions for imagined vowels with tones 2/3/4 than for those with tone 1). Speech-related areas for tone imagery (i.e. the right hemisphere) provided majority of information for identifying tones, while the left hemisphere had advantages in vowel identification. Having decoded both vowels and tones during the post-stimulus 15 s period, the average classification accuracies exceeded 40% and 70% in multiclass (i.e. four classes) and binary settings, respectively. To spell words more quickly, the time window size for decoding was reduced from 15 s to 2.5 s while the classification accuracies were not significantly reduced.Significance.For the first time, this work demonstrated the possibility of discriminating lexical tones and vowels in imagined tonal syllables simultaneously. In addition, the reduced time window for decoding indicated that the spelling time of Chinese words could be significantly reduced in the fNIRS-based BCIs.