The present and future use of functional near-infrared spectroscopy (fNIRS) for cognitive neuroscience

Odor and taste characteristics, transduction mechanism, and perceptual interaction in fermented foods: a review

Fermentation is a critical technological process for flavor development in fermented foods. The combination of odor and taste, known as flavor, is crucial in enhancing people's perception and psychology toward fermented foods, thereby increasing their acceptance among consumers. This review summarized the determination and key flavor compound screening methods in fermented foods and analyzed the flavor perception, perceptual interactions, and evaluation methods. The flavor compounds in fermented foods could be separated, purified, and identified by instrument techniques, and a molecular sensory science approach could identify the key flavor compounds. How flavor compounds bind to their respective receptors determines flavor perception, which is influenced by their perceptual interactions, including odor-odor, taste-taste, and odor-taste. Evaluation methods of flavor perception mainly include human sensory evaluation, electronic sensors and biosensors, and neuroimaging techniques. Among them, the biosensor-based evaluation methods could facilitate the investigation of the flavor transduction mechanism and the neuroimaging technique could explain the brain's signals that relate to the perception of flavor and how they compare to signals from other senses. This review aims to elucidate the flavor profile of fermented foods and highlight the significance of comprehending the interactions between various flavor compounds, thus improving the healthiness and sensory attributes.

Awareness of embodiment enhances enjoyment and engages sensorimotor cortices

Whether in performing arts, sporting, or everyday contexts, when we watch others move, we tend to enjoy bodies moving in synchrony. Our enjoyment of body movements is further enhanced by our own prior experience with performing those movements, or our 'embodied experience'. The relationships between movement synchrony and enjoyment, as well as embodied experience and movement enjoyment, are well known. The interaction between enjoyment of movements, synchrony, and embodiment is less well understood, and may be central for developing new approaches for enriching social interaction. To examine the interplay between movement enjoyment, synchrony, and embodiment, we asked participants to copy another person's movements as accurately as possible, thereby gaining embodied experience of movement sequences. Participants then viewed other dyads performing the same or different sequences synchronously, and we assessed participants' recognition of having performed these sequences, as well as their enjoyment of each movement sequence. We used functional near-infrared spectroscopy to measure cortical activation over frontotemporal sensorimotor regions while participants performed and viewed movements. We found that enjoyment was greatest when participants had mirrored the sequence and recognised it, suggesting that awareness of embodiment may be central to enjoyment of synchronous movements. Exploratory analyses of relationships between cortical activation and enjoyment and recognition implicated the sensorimotor cortices, which subserve action observation and aesthetic processing. These findings hold implications for clinical research and therapies seeking to foster successful social interaction.

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

Background

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

Materials and Methods

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

Results

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

Conclusions

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

Association between neural prosody discrimination and language abilities in toddlers: a functional near-infrared spectroscopy study

BACKGROUND

Language delay affects near- and long-term social communication and learning in toddlers, and, an increasing number of experts pay attention to it. The development of prosody discrimination is one of the earliest stages of language development in which key skills for later stages are mastered. Therefore, analyzing the relationship between brain discrimination of speech prosody and language abilities may provide an objective basis for the diagnosis and intervention of language delay.

METHODS

In this study, all cases(n = 241) were enrolled from a tertiary women's hospital, from 2021 to 2022. We used functional near-infrared spectroscopy (fNIRS) to assess children's neural prosody discrimination abilities, and a Chinese communicative development inventory (CCDI) were used to evaluate their language abilities.

RESULTS

Ninety-eight full-term and 108 preterm toddlers were included in the final analysis in phase I and II studies, respectively. The total CCDI screening abnormality rate was 9.2% for full-term and 34.3% for preterm toddlers. Full-term toddlers showed prosody discrimination ability in all channels except channel 5, while preterm toddlers showed prosody discrimination ability in channel 6 only. Multifactorial logistic regression analyses showed that prosody discrimination of the right angular gyrus (channel 3) had a statistically significant effect on language delay (odd ratio = 0.301, P < 0.05) in full-term toddlers. Random forest (RF) regression model presented that prosody discrimination reflected by channels and brain regions based on fNIRS data was an important parameter for predicting language delay in preterm toddlers, among which the prosody discrimination reflected by the right angular gyrus (channel 4) was the most important parameter. The area under the model Receiver operating characteristic (ROC) curve was 0.687.

CONCLUSIONS

Neural prosody discrimination ability is positively associated with language development, assessment of brain prosody discrimination abilities through fNIRS could be used as an objective indicator for early identification of children with language delay in the future clinical application.

Event-related prefrontal activations during online video game playing are modulated by game mechanics, physiological arousal and the amount of daily playing

There is a trend to study human brain functions in ecological contexts and in relation to human factors. In this study, functional near-infrared spectroscopy (fNIRS) was used to record real-time prefrontal activities in 42 male university student habitual video game players when they played a round of multiplayer online battle arena game, League of Legends. A content-based event coding approach was used to analyze regional activations in relation to event type, physiological arousal indexed by heart rate (HR) change, and individual characteristics of the player. Game events Slay and Slain were found to be associated with similar HR and prefrontal responses before the event onset, but differential responses after the event onset. Ventrolateral prefrontal cortex (VLPFC) activation preceding the Slay onset correlated positively with HR change, whereas activations in dorsolateral prefrontal cortex (DLPFC) and rostral frontal pole area (FPAr) preceding the Slain onset were predicted by self-reported hours of weekly playing (HoWP). Together, these results provide empirical evidence to support the notion that event-related regional prefrontal activations during online video game playing are shaped by game mechanics, in-game dynamics of physiological arousal and individual characteristics the players.

Volleyball training improves working memory in children aged 7 to 12 years old: an fNIRS study

This study aimed to investigate the effect of a 12-wk extracurricular volleyball training on working memory from both behavioral and cerebral aspects. A total of 80 children were randomized assigned to (i) the experimental group, who engaged in extracurricular volleyball training for 60 min, thrice a week for 12 wk, and (ii) the control group, who maintained their regular daily routine. Working memory was evaluated in both groups using the N-back task before and after the intervention. Furthermore, functional near-infrared spectroscopy was employed to monitor the level of oxygenated hemoglobin in the prefrontal cortex. The experimental group performed better in the behavioral task than the control group, as evidenced by a shorter response time and a higher correct rate. The functional near-infrared spectroscopy results suggested that the activation of the left dorsolateral prefrontal cortex was significantly higher in the experimental group than in the control group. In addition, correlation analyses showed that the enhancement of left dorsolateral prefrontal cortex activation was significantly correlated with decreasing response time and improving response accuracy in the N-back task. These findings suggest that the left dorsolateral prefrontal cortex is likely the neural substrate for improved working memory performance elicited by 12-wk open skill exercise.

Effect of γ-tACS on prefrontal hemodynamics in bipolar disorder: A functional near-infrared study

OBJECTIVES

Transcranial alternating current stimulation (tACS) is a potential therapeutic psychiatric tool that has been shown to modulate clinical symptoms and brain function by inducing brain oscillations. However, direct evidence on the effects of gamma-tACS (γ-tACS) on Bipolar I Disorder (BD-I) is limited. In the present study we used functional near-infrared spectroscopy to explore prefrontal hemodynamic changes in BD-I patients receiving combined γ-tACS intervention in addition to pharmacological treatment.

METHODS

Only 39 male patients with BD-I in the acute manic phase were included, and they were randomly divided into an intervention group (n = 18) and a control group (n = 21). The intervention group received γ-tACS treatment on a weekday for a total of 10 sessions in the right prefrontal cortex and left prefrontal cortex. All participants were pretested (baseline) and posttested (2 weeks after) with questionnaires to assess clinical symptoms and cognitive abilities, and with functional near infrared spectroscopy (fNIRS) to assess spontaneous cortical hemodynamic activities.

RESULTS

Compared to the control group, the intervention group had greater increases in Montreal Cognitive Assessment (MoCA) scores, and greater decreases in Bech-Rafaelsen Mania Rating Scale (BRMS) scores. In the intervention group, functional connectivity (FC) was significantly greater in the left hemisphere. γ-tACS treatment resulted in a left hemispheric lateralization effect of resting state FC in BD-I patients, increasing the hemodynamic activity of the patient's left prefrontal cortex.

CONCLUSIONS

γ-tACS can improve cognitive impairment and mood symptoms with BD-I patients in an acute manic episode by enhancing FC in the patients' left prefrontal cortex.

Exaggerated sensitivity to threat and reduced medial prefrontal engagement during threat generalization in reactive aggressive adolescents

Aggressive adolescents tend to exhibit abnormal fear acquisition and extinction, and reactive aggressive adolescents are often more anxious. However, the relationship between fear generalization and reactive aggression (RA) remains unknown. According to Reactive-Proactive Aggression Questionnaire (RPQ) scores, 61 adolescents were divided into two groups, namely, a high RA group (N = 30) and a low aggression (LA) group (N = 31). All participants underwent three consecutive phases of the Pavlovian conditioning paradigm (i.e., habituation, acquisition, and generalization), and neural activation of the medial prefrontal cortex (mPFC) was assessed by functional near-infrared spectroscopy (fNIRS). The stimuli were ten circles with varying sizes, including two conditioned stimuli (CSs) and eight generalization stimuli (GSs). A scream at 85 dB served as the auditory unconditioned stimulus (US). The US expectancy ratings of both CSs and GSs were higher in the RA group than in the LA group. The fNIRS results showed that CSs and GSs evoked lower mPFC activation in the RA group compared to the LA group during fear generalization. These findings suggest that abnormalities in fear acquisition and generalization are prototypical dysregulations in adolescents with RA. They provide neurocognitive evidence for dysregulated fear learning in the mechanisms underlying adolescents with RA, highlighting the need to develop emotional regulation interventions for these individuals.

A scoping review of functional near-infrared spectroscopy biomarkers in late-life depression: Depressive symptoms, cognitive functioning, and social functioning

Late-life depression is one of the most damaging mental illnesses, disrupting the normal lives of older people by causing chronic illness and cognitive impairment. Patients with late-life depression, accompanied by changes in appetite, insomnia, fatigue and guilt, are more likely to experience irritability, anxiety and somatic symptoms. It increases the risk of suicide and dementia and is a major challenge for the public health systems. The current clinical assessment, identification and effectiveness assessment of late-life depression are primarily based on history taking, mental status examination and scale scoring, which lack subjectivity and precision. Functional near-infrared spectroscopy is a rapidly developing optical imaging technology that objectively reflects the oxygenation of hemoglobin in different cerebral regions during different tasks and assesses the functional status of the cerebral cortex. This article presents a comprehensive review of the assessment of functional near-infrared spectroscopy technology in assessing depressive symptoms, social functioning, and cognitive functioning in patients with late-life depression. The use of functional near-infrared spectroscopy provides greater insight into the neurobiological mechanisms underlying depression and helps to assess these three aspects of functionality in depressed patients. In addition, the study discusses the limitations of previous research and explores potential advances in the field.

Characteristics of oxyhemoglobin during the verbal fluency task in subthreshold depression: A multi-channel near-infrared spectroscopy study

OBJECTIVE

Subthreshold depression is an essential precursor and risk factor for major depressive disorder, and its accurate identification and timely intervention are important for reducing the prevalence of major depressive disorder. Therefore, we used functional near-infrared spectroscopic imaging (fNIRS) to explore the characteristics of the brain neural activity of college students with subthreshold depression in the verbal fluency task.

METHODS

A total of 72 subthreshold depressed college students (SDs) and 67 healthy college students (HCs) were recruited, and all subjects were subjected to a verbal fluency task (VFT) while a 53-channel fNIRS device was used to collect the subjects' cerebral blood oxygenation signals.

RESULTS

The results of the independent samples t-test showed that the mean oxyhemoglobin in the right dorsolateral prefrontal (ch34, ch42, ch45) and Broca's area (ch51, ch53) of SDs was lower than that of HCs. The peak oxygenated hemoglobin of SDs was lower in the right dorsolateral prefrontal (ch34) and Broca's area (ch51, ch53).The brain functional connectivity strength was lower than that of HCs. Correlation analysis showed that the left DLPFC and Broca's area were significantly negatively correlated with the depression level.

CONCLUSION

SDs showed abnormally low, inadequate levels of brain activation and weak frontotemporal brain functional connectivity. The right DLPFC has a higher sensitivity for the differentiation of depressive symptoms and is suitable as a biomarker for the presence of depressive symptoms. Dysfunction in Broca's area can be used both as a marker of depressive symptoms and as a biomarker, indicating the severity of depressive symptoms.

Exploring the dynamics of prefrontal cortex in the interaction between orienteering experience and cognitive performance by fNIRS

Sporting experience plays a pivotal role in shaping exercise habits, with a mutually reinforcing relationship that enhances cognitive performance. The acknowledged plasticity of cognition driven by sports necessitates a comprehensive examination. Hence, this study delves into the dynamic intricacies of the prefrontal cortex, exploring the impact of orienteering experience on cognitive performance. Our findings contribute empirical evidence regarding the functional activation of specific brain regions bridging the nexus between experiential factors and cognitive capabilities. In this cross-sectional study, a cohort of forty-nine athletes was enrolled to meticulously examine behavioral variances and prefrontal cortex dynamics among orienteering athletes of varying experience levels across diverse non-specialized scenarios. These investigations involved the utilization of functional near-infrared spectroscopy (fNIRS) to detect alterations in oxygenated hemoglobin (HbO2). The high-experience expert group exhibited neurological efficiency, demonstrating significantly diminished brain activation in the dorsolateral prefrontal, left ventral lateral prefrontal, and right orbitofrontal regions compared to the low-experience group. Within the low-experience novice group, superior performance in the spatial memory task was observed compared to the mental rotation task, with consistently lower reaction times across all conditions compared to the high-experience group. Notably, cerebral blood oxygenation activation exhibited a significant reduction in the high-experience expert group compared to the low-experience novice group, irrespective of task type. The dorsolateral prefrontal lobe exhibited activation upon task onset, irrespective of experience level. Correct rates in the spatial memory task were consistently higher than those in the mental rotation task, while brain region activation was significantly greater during the mental rotation task than the spatial memory task." This study elucidates disparities in prefrontal cortex dynamics between highly seasoned experts and neophyte novices, showcasing a cognitive edge within the highly experienced cohort and a spatial memory advantage in the inexperienced group. Our findings contribute to the comprehension of the neural mechanisms that underlie the observed cognitive advantage and provide insights into the forebrain resources mobilized by orienteering experience during spatial cognitive tasks."

Exploring Neural Correlates between Anxiety and Inhibitory Ability: Evidence from Task-Based fNIRS

Background

Cognitive control impairments in anxiety disorders are thought to be associated with deficiencies in the prefrontal network. However, a precise neural explanation for these impairments is still lacking. This study seeks to compare inhibitory ability between individuals with anxiety and healthy controls, as well as to explore the neural correlates of anxiety-related inhibitory deficits within a clinical context.

Materials and Methods

A total of 118 participants were recruited, including 59 patients with anxiety and 59 matched healthy controls (HCs). Anxiety and inhibitory ability were evaluated using Zung's Self-rating Anxiety Scale (SAS), the color word Stroop task, and verbal fluency task (VFT). Additionally, changes in oxyhemoglobin (Oxy-Hb) concentrations were measured using functional near-infrared spectroscopy (fNIRS).

Results

Compared to HCs, the anxiety group exhibited reduced cortical activation in prefrontal cortex (PFC) channels, prolonged inhibitory speed and lower inhibitory accuracy during Stroop task, and diminished VFT performance (all p < 0.05). Significant negative correlations were observed between SAS scores and inhibitory ability, as well as with PFC activation. Conversely, PFC activation showed positive correlations with inhibitory ability. Importantly, activation in the dorsolateral PFC during VFT partially mediated the association between anxiety and inhibitory performance.

Conclusions

This study reveals neural characteristics associated with inhibitory abilities in anxiety disorders and identifies neural correlations between anxiety and inhibitory performance. These findings illuminate the impact of anxiety on inhibitory abilities and propose intervention targets to enhance these abilities in individuals with anxiety disorders, thereby suggesting more effective therapeutic strategies.

Intervention-Induced Changes in Balance and Task-Dependent Neural Activity in Adults with Acquired Brain Injury: A Pilot Randomized Control Trial

Advances in neuroimaging technology, like functional near-infrared spectroscopy (fNIRS), support the evaluation of task-dependent brain activity during functional tasks, like balance, in healthy and clinical populations. To date, there have been no studies examining how interventions, like yoga, impact task-dependent brain activity in adults with chronic acquired brain injury (ABI). This pilot study compared eight weeks of group yoga (active) to group exercise (control) on balance and task-dependent neural activity outcomes. Twenty-three participants were randomized to yoga (n = 13) or exercise groups (n = 10). Neuroimaging and balance performance data were collected simultaneously using a force plate and mobile fNIRS device before and after interventions. Linear mixed-effects models were used to evaluate the effect of time, time x group interactions, and simple (i.e., within-group) effects. Regardless of group, all participants had significant balance improvements after the interventions. Additionally, regardless of group, there were significant changes in task-dependent neural activity, as well as distinct changes in neural activity within each group. In summary, using advances in sensor technology, we were able to demonstrate preliminary evidence of intervention-induced changes in balance and neural activity in adults with ABI. These preliminary results may provide an important foundation for future neurorehabilitation studies that leverage neuroimaging methods, like fNIRS.

Neural dynamics of delayed feedback in robot teleoperation: insights from fNIRS analysis

Introduction

As robot teleoperation increasingly becomes integral in executing tasks in distant, hazardous, or inaccessible environments, operational delays remain a significant obstacle. These delays, inherent in signal transmission and processing, adversely affect operator performance, particularly in tasks requiring precision and timeliness. While current research has made strides in mitigating these delays through advanced control strategies and training methods, a crucial gap persists in understanding the neurofunctional impacts of these delays and the efficacy of countermeasures from a cognitive perspective.

Methods

This study addresses the gap by leveraging functional Near-Infrared Spectroscopy (fNIRS) to examine the neurofunctional implications of simulated haptic feedback on cognitive activity and motor coordination under delayed conditions. In a human-subject experiment (N = 41), sensory feedback was manipulated to observe its influences on various brain regions of interest (ROIs) during teleoperation tasks. The fNIRS data provided a detailed assessment of cerebral activity, particularly in ROIs implicated in time perception and the execution of precise movements.

Results

Our results reveal that the anchoring condition, which provided immediate simulated haptic feedback with a delayed visual cue, significantly optimized neural functions related to time perception and motor coordination. This condition also improved motor performance compared to the asynchronous condition, where visual and haptic feedback were misaligned.

Discussion

These findings provide empirical evidence about the neurofunctional basis of the enhanced motor performance with simulated synthetic force feedback in the presence of teleoperation delays. The study highlights the potential for immediate haptic feedback to mitigate the adverse effects of operational delays, thereby improving the efficacy of teleoperation in critical applications.

Applications of Functional Near-Infrared Spectroscopy (fNIRS) Neuroimaging During Rehabilitation Following Stroke: A Review

Stroke is a cerebrovascular disease that impairs blood supply to localized brain tissue regions due to various causes. This leads to ischemic and hypoxic lesions, necrosis of the brain tissue, and a variety of functional disorders. Abnormal cortical activation and functional connectivity occur in the brain after a stroke, but the activation patterns and functional reorganization are not well understood. Rehabilitation interventions can enhance functional recovery in stroke patients. However, clinicians require objective measures to support their practice, as outcome measures for functional recovery are based on scale scores. Furthermore, the most effective rehabilitation measures for treating patients are yet to be investigated. Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging method that detects changes in cerebral hemodynamics during task performance. It is widely used in neurological research and clinical practice due to its safety, portability, high motion tolerance, and low cost. This paper briefly introduces the imaging principle and the advantages and disadvantages of fNIRS to summarize the application of fNIRS in post-stroke rehabilitation.

Cortical processes of multisensory plausibility modulation of vibrotactile perception in virtual environments in middled-aged and older adults

Digital technologies, such as virtual or augmented reality, can potentially support neurocognitive functions of the aging populations worldwide and complement existing intervention methods. However, aging-related declines in the frontal-parietal network and dopaminergic modulation which progress gradually across the later periods of the adult lifespan may affect the processing of multisensory congruence and expectancy based contextual plausibility. We assessed hemodynamic brain responses while middle-aged and old adults experienced car-riding virtual-reality scenarios where the plausibility of vibrotactile stimulations was manipulated by delivering stimulus intensities that were either congruent or incongruent with the digitalized audio-visual contexts of the respective scenarios. Relative to previous findings observed in young adults, although highly plausible vibrotactile stimulations confirming with contextual expectations also elicited higher brain hemodynamic responses in middle-aged and old adults, this effect was limited to virtual scenarios with extreme expectancy violations. Moreover, individual differences in plausibility-related frontal activity did not correlate with plausibility violation costs in the sensorimotor cortex, indicating less systematic frontal context-based sensory filtering in older ages. These findings have practical implications for advancing digital technologies to support aging societies.

Modal Analysis of Cerebrovascular Effects for Digital Health Integration of Neurostimulation Therapies-A Review of Technology Concepts

Transcranial electrical stimulation (tES) is increasingly recognized for its potential to modulate cerebral blood flow (CBF) and evoke cerebrovascular reactivity (CVR), which are crucial in conditions like mild cognitive impairment (MCI) and dementia. This study explores the impact of tES on the neurovascular unit (NVU), employing a physiological modeling approach to simulate the vascular response to electric fields generated by tES. Utilizing the FitzHugh-Nagumo model for neuroelectrical activity, we demonstrate how tES can initiate vascular responses such as vasoconstriction followed by delayed vasodilation in cerebral arterioles, potentially modulated by a combination of local metabolic demands and autonomic regulation (pivotal locus coeruleus). Here, four distinct pathways within the NVU were modeled to reflect the complex interplay between synaptic activity, astrocytic influences, perivascular potassium dynamics, and smooth muscle cell responses. Modal analysis revealed characteristic dynamics of these pathways, suggesting that oscillatory tES may finely tune the vascular tone by modulating the stiffness and elasticity of blood vessel walls, possibly by also impacting endothelial glycocalyx function. The findings underscore the therapeutic potential vis-à-vis blood-brain barrier safety of tES in modulating neurovascular coupling and cognitive function needing the precise modulation of NVU dynamics. This technology review supports the human-in-the-loop integration of tES leveraging digital health technologies for the personalized management of cerebral blood flow, offering new avenues for treating vascular cognitive disorders. Future studies should aim to optimize tES parameters using computational modeling and validate these models in clinical settings, enhancing the understanding of tES in neurovascular health.

Optimizing spatial specificity and signal quality in fNIRS: an overview of potential challenges and possible options for improving the reliability of real-time applications

The optical brain imaging method functional near-infrared spectroscopy (fNIRS) is a promising tool for real-time applications such as neurofeedback and brain-computer interfaces. Its combination of spatial specificity and mobility makes it particularly attractive for clinical use, both at the bedside and in patients' homes. Despite these advantages, optimizing fNIRS for real-time use requires careful attention to two key aspects: ensuring good spatial specificity and maintaining high signal quality. While fNIRS detects superficial cortical brain regions, consistently and reliably targeting specific regions of interest can be challenging, particularly in studies that require repeated measurements. Variations in cap placement coupled with limited anatomical information may further reduce this accuracy. Furthermore, it is important to maintain good signal quality in real-time contexts to ensure that they reflect the true underlying brain activity. However, fNIRS signals are susceptible to contamination by cerebral and extracerebral systemic noise as well as motion artifacts. Insufficient real-time preprocessing can therefore cause the system to run on noise instead of brain activity. The aim of this review article is to help advance the progress of fNIRS-based real-time applications. It highlights the potential challenges in improving spatial specificity and signal quality, discusses possible options to overcome these challenges, and addresses further considerations relevant to real-time applications. By addressing these topics, the article aims to help improve the planning and execution of future real-time studies, thereby increasing their reliability and repeatability.

Disrupted hemodynamic response within dorsolateral prefrontal cortex during cognitive tasks among people with multiple sclerosis-related fatigue

INTRODUCTION

Mental fatigue is an early and enduring symptom in persons with autoimmune disease particularly multiple sclerosis (MS). Neuromodulation has emerged as a potential treatment although optimal cortical targets have yet to be determined. We aimed to examine cortical hemodynamic responses within bilateral dorsolateral prefrontal cortex (dlPFC) and frontopolar areas during single and dual cognitive tasks in persons with MS-related fatigue compared to matched controls.

METHODS

We recruited persons (15 MS and 12 age- and sex-matched controls) who did not have physical or cognitive impairment and were free from depressive symptoms. Functional near infrared spectroscopy (fNIRS) registered hemodynamic responses during the tasks. We calculated oxyhemoglobin peak, time-to-peak, coherence between channels (a potential marker of neurovascular coupling) and functional connectivity (z-score).

RESULTS

In MS, dlPFC demonstrated disrupted hemodynamic coherence during both single and dual tasks, as evidenced by non-significant and negative correlations between fNIRS channels. In MS, reduced coherence occurred in left dorsolateral PFC during the single task but occurred bilaterally as the task became more challenging. Functional connectivity was lower during dual compared to single tasks in the right dorsolateral PFC in both groups. Lower z-score was related to greater feelings of fatigue. Peak and time-to-peak hemodynamic response did not differ between groups or tasks.

CONCLUSIONS

Hemodynamic responses were inconsistent and disrupted in people with MS experiencing mental fatigue, which worsened as the task became more challenging. Our findings point to dlPFC, but not frontopolar areas, as a potential target for neuromodulation to treat cognitive fatigue.

Functional near-infrared spectroscopy-based neurofeedback training regulates time-on-task effects and enhances sustained cognitive performance

Time-on-task effect is a common consequence of long-term cognitive demand work, which reflects reduced behavioral performance and increases the risk of accidents. Neurofeedback is a neuromodulation method that can guide individuals to regulate their brain activity and manifest as changes in related symptoms and cognitive behaviors. This study aimed to examine the effects of functional near-infrared spectroscopy-based neurofeedback training on time-on-task effects and sustained cognitive performance. A randomized, single-blind, sham-controlled study was performed: 17 participants received feedback signals of their own dorsolateral prefrontal cortex activity (neurofeedback group), and 16 participants received feedback signals of dorsolateral prefrontal cortex activity from the neurofeedback group (sham-neurofeedback group). All participants received 5 neurofeedback training sessions and completed 2 sustained cognitive tasks, including a 2-back task and a psychomotor vigilance task, to evaluate behavioral performance changes following neurofeedback training. Results showed that neurofeedback relative to the sham-neurofeedback group exhibited increased dorsolateral prefrontal cortex activation, increased accuracy in the 2-back task, and decreased mean response time in the psychomotor vigilance task after neurofeedback training. In addition, the neurofeedback group showed slower decline performance during the sustained 2-back task after neurofeedback training compared with sham-neurofeedback group. These findings demonstrate that neurofeedback training could regulate time-on-task effects on difficult task and enhance performance on sustained cognitive tasks by increasing dorsolateral prefrontal cortex activity.

Measurement of lung oxygenation by near-infrared spectroscopy in preterm infants with bronchopulmonary dysplasia

INTRODUCTION

It has recently been reported that it is possible to monitor lung oxygenation (rSO2L) by near-infrared spectroscopy (NIRS) in preterm infants with respiratory distress syndrome (RDS). Thus, our aim was to assess the possibility of monitoring rSO2L in infants with evolving and established bronchopulmonary dysplasia (BPD) and to evaluate if rSO2L correlates with BPD severity and other oxygenation indices.

METHODS

We studied 40 preterm infants with gestational age ≤30 weeks at risk for BPD. Patients were continuously studied for 2 h by NIRS at 28 ± 7 days of life and 36 weeks ± 7 days of postmenstrual age.

RESULTS

rSO2L was similar at the first and second NIRS recordings (71.8 ± 7.2 vs. 71.4 ± 4.2%) in the overall population, but it was higher in infants with mild than in those with moderate-to-severe BPD at both the first (73.3 ± 3.1 vs. 71.2 ± 3.2%, p = .042) and second (72.3 ± 2.8 vs. 70.5 ± 2.8, p = .049) NIRS recording. A rSO2L cutoff value of 71.6% in the first recording was associated with a risk for moderate-to-severe BPD with a sensitivity of 66% and a specificity of 60%. Linear regression analysis demonstrated a significant positive relationship between rSO2L and SpO2/FiO2 ratio (p = .013) and a/APO2 (p = .004).

CONCLUSIONS

Monitoring of rSO2L by NIRS in preterm infants with evolving and established BPD is feasible and safe. rSO2L was found to be higher in infants with mild BPD, and predicts the risk for developing moderate-to-severe BPD and correlates with other indices of oxygenation.

Functional near-infrared spectroscopy evidence of cognitive-motor interference in different dual tasks

Dual tasks (DTs) combining walking with a cognitive task can cause various levels of cognitive-motor interference, depending on which brain resources are recruited in each case. However, the brain activation and functional connectivity underlying cognitive-motor interferences remain to be elucidated. Therefore, this study investigated the neural correlation during different DT conditions in 40 healthy young adults (mean age: 27.53 years, 28 women). The DTs included walking during subtraction or N-Back tasks. Cognitive-motor interference was calculated, and brain activation and functional connectivity were analysed. Portable functional near-infrared spectroscopy was utilized to monitor haemodynamics in the prefrontal cortex (PFC), motor cortex and parietal cortex during each task. Walking interference (decrease in walking speed during DT) was greater than cognitive interference (decrease in cognitive performance during DT), regardless of the type of task. Brain activation in the bilateral PFC and parietal cortex was greater for walking during subtraction than for standing subtraction. Furthermore, brain activation was higher in the bilateral motor and parietal and PFCs for walking during subtraction than for walking alone, but only increased in the PFC for walking during N-Back. Coherence between the bilateral lateral PFC and between the left lateral PFC and left motor cortex was significantly greater for walking during 2-Back than for walking. The PFC, a critical brain region for organizing cognitive and motor functions, played a crucial role in integrating information coming from multiple brain networks required for completing DTs. Therefore, the PFC could be a potential target for the modulation and improvement of cognitive-motor functions during neurorehabilitation.

Shared and distinct prefrontal cortex alterations of implicit emotion regulation in depression and anxiety: An fNIRS investigation

BACKGROUND

Emotion regulation deficits, particularly in cognitive reappraisal, are crucial in depression and anxiety. However, research on the neural mechanisms of implicit emotion regulation is lacking, and it remains unclear whether these mechanisms are shared or distinct between the two disorders.

METHODS

We investigated the neural mechanisms of implicit cognitive reappraisal in 28 individuals with major depressive disorder (MDD), 25 with generalized anxiety disorder (GAD), and 30 healthy controls (HC) using functional near-infrared spectroscopy (fNIRS). Participants completed an implicit cognitive reappraisal task and underwent neuropsychological and clinical assessments.

RESULTS

We found that MDD patients reported higher levels of rumination and lower utilization of cognitive reappraisal, while GAD patients reported reduced use of perspective-taking. Notably, both MDD and GAD patients exhibited decreased activation in the dorsolateral prefrontal cortex (DLPFC) and orbitofrontal cortex (OFC) compared to HC participants during implicit cognitive reappraisal. Specifically, inadequate OFC activation was observed in MDD patients, while GAD patients demonstrated OFC deactivation during the task. Furthermore, DLPFC activation showed a negative correlation with depression severity in MDD patients, while OFC activation was positively correlated with perspective-taking in GAD patients.

LIMITATIONS

fNIRS has limited depth and spatial resolution.

CONCLUSION

Our fNIRS study is the first to reveal shared and distinct neurobiological profiles of depression and anxiety in implicit emotion regulation. These findings underscore the significance of reduced DLPFC/OFC activation in emotion regulation impairment and highlight unique OFC activation patterns in these disorders. These insights have potential implications for developing cognitive-behavioral therapy and transcranial magnetic stimulation as treatment approaches.

Why behaviour matters: Studying inter-brain coordination during child-caregiver interaction

Modern technology allows for simultaneous neuroimaging from interacting caregiver-child dyads. Whereas most analyses that examine the coordination between brain regions within an individual brain do so by measuring changes relative to observed events, studies that examine coordination between two interacting brains generally do this by measuring average intra-brain coordination across entire blocks or experimental conditions. In other words, they do not examine changes in inter-brain coordination relative to individual behavioural events. Here, we discuss the limitations of this approach. First, we present data suggesting that fine-grained temporal interdependencies in behaviour can leave residual artifact in neuroimaging data. We show how artifact can manifest as both power and (through that) phase synchrony effects in EEG and affect wavelet transform coherence in fNIRS analyses. Second, we discuss different possible mechanistic explanations of how inter-brain coordination is established and maintained. We argue that non-event-locked approaches struggle to differentiate between them. Instead, we contend that approaches which examine how interpersonal dynamics change around behavioural events have better potential for addressing possible artifactual confounds and for teasing apart the overlapping mechanisms that drive changes in inter-brain coordination.

Effect of 12-week head-down strong abdominal breathing on cognitive function in patients with stable chronic obstructive pulmonary disease: a single-centre randomised controlled trial protocol

BACKGROUND

Patients with chronic obstructive pulmonary disease (COPD) often suffer from a combination of mild cognitive impairment (MCI) and a significant reduction in their quality of life. In the exercise programme of pulmonary rehabilitation (PR), pulmonary rehabilitation intervention is often carried out by enhancing respiratory function. Strong abdominal breathing is a kind of breathing method, through which the diaphragm can be exercised, thereby enhancing the deflection distance of the diaphragm during breathing and improving respiratory function. The inversion trainer can meet the different angles of head-down training and also has the characteristics of low cost, easy to operate, and use a wide range of scenarios. According to currently available data, strong abdominal breathing in combination with head-down position has not yet been used in pulmonary rehabilitation in this type of rehabilitation programme. It is valuable to use this device to study PR of cognitive function in patients with COPD.

METHODS

This study was a 12-week single-centre randomised controlled trial and blinding the assessors and data processors of the test. Recruitment is planned for January 1, 2024. It is expected that 81 patients with stable COPD combined with MCI will be recruited and randomly assigned to the head-down strong abdominal breathing group (HG), the fitness qigong eight-duanjin group (BDJ), and the control group (CG) in a 1:1:1 ratio. Using fNIRS (functional near-infrared spectroscopy) to assess brain oxygen availability before and after pulmonary rehabilitation in three periods: before, during and after the intervention. Cognitive functioning is also assessed using the Overall Cognitive Assessment Scale, the Specific Cognitive Functioning Assessment Scale and the Cognitive Behavioural Ability Test.

TRIAL REGISTRATION

The Specialised Committee on Scientific Research and Academic Ethics of the Academic Committee of Anqing Normal University approved the project (ANU2023001). China Clinical Trial Registry approved the study (ChiCTR2300075400) with a registration date of 2023/09/04.

DISCUSSION

The aim of this study was to explore novel exercise rehabilitation methods to improve cognitive function in COPD patients. It results in a lower financial burden and higher participation in pulmonary rehabilitation and improves the quality of survival of patients with COPD.

The neural mechanism of communication between graduate students and advisers in different adviser-advisee relationships

Communication is crucial in constructing the relationship between students and advisers, ultimately bridging interpersonal interactions. Only a few studies however explore the communication between postgraduate students and advisers. To fill the gaps in the empirical researches, this study uses functional near-infrared spectroscopy (FNIRS) techniques to explore the neurophysiology differences in brain activation of postgraduates with different adviser-advise relationships during simulated communication with their advisers. Results showed significant differences in the activation of the prefrontal cortex between high-quality and the low-quality students during simulating and when communicating with advisers, specifically in the Broca's areas, the frontal pole, and the orbitofrontal and dorsolateral prefrontal cortices. This further elucidated the complex cognitive process of communication between graduate students and advisers.

Cross-modal plasticity in children with cochlear implant: converging evidence from EEG and functional near-infrared spectroscopy

Over the first years of life, the brain undergoes substantial organization in response to environmental stimulation. In a silent world, it may promote vision by (i) recruiting resources from the auditory cortex and (ii) making the visual cortex more efficient. It is unclear when such changes occur and how adaptive they are, questions that children with cochlear implants can help address. Here, we examined 7-18 years old children: 50 had cochlear implants, with delayed or age-appropriate language abilities, and 25 had typical hearing and language. High-density electroencephalography and functional near-infrared spectroscopy were used to evaluate cortical responses to a low-level visual task. Evidence for a 'weaker visual cortex response' and 'less synchronized or less inhibitory activity of auditory association areas' in the implanted children with language delays suggests that cross-modal reorganization can be maladaptive and does not necessarily strengthen the dominant visual sense.

Bringing together multimodal and multilevel approaches to study the emergence of social bonds between children and improve social AI

This protocol paper outlines an innovative multimodal and multilevel approach to studying the emergence and evolution of how children build social bonds with their peers, and its potential application to improving social artificial intelligence (AI). We detail a unique hyperscanning experimental framework utilizing functional near-infrared spectroscopy (fNIRS) to observe inter-brain synchrony in child dyads during collaborative tasks and social interactions. Our proposed longitudinal study spans middle childhood, aiming to capture the dynamic development of social connections and cognitive engagement in naturalistic settings. To do so we bring together four kinds of data: the multimodal conversational behaviors that dyads of children engage in, evidence of their state of interpersonal rapport, collaborative performance on educational tasks, and inter-brain synchrony. Preliminary pilot data provide foundational support for our approach, indicating promising directions for identifying neural patterns associated with productive social interactions. The planned research will explore the neural correlates of social bond formation, informing the creation of a virtual peer learning partner in the field of Social Neuroergonomics. This protocol promises significant contributions to understanding the neural basis of social connectivity in children, while also offering a blueprint for designing empathetic and effective social AI tools, particularly for educational contexts.

A Demographic-Conditioned Variational Autoencoder for fMRI Distribution Sampling and Removal of Confounds

Objective

fMRI and derived measures such as functional connectivity (FC) have been used to predict brain age, general fluid intelligence, psychiatric disease status, and preclinical neurodegenerative disease. However, it is not always clear that all demographic confounds, such as age, sex, and race, have been removed from fMRI data. Additionally, many fMRI datasets are restricted to authorized researchers, making dissemination of these valuable data sources challenging.

Methods

We create a variational autoencoder (VAE)-based model, DemoVAE, to decorrelate fMRI features from demographics and generate high-quality synthetic fMRI data based on user-supplied demographics. We train and validate our model using two large, widely used datasets, the Philadelphia Neurodevel-opmental Cohort (PNC) and Bipolar and Schizophrenia Network for Intermediate Phenotypes (BSNIP).

Results

We find that DemoVAE recapitulates group differences in fMRI data while capturing the full breadth of individual variations. Significantly, we also find that most clinical and computerized battery fields that are correlated with fMRI data are not correlated with DemoVAE latents. An exception are several fields related to schizophrenia medication and symptom severity.

Conclusion

Our model generates fMRI data that captures the full distribution of FC better than traditional VAE or GAN models. We also find that most prediction using fMRI data is dependent on correlation with, and prediction of, demographics.

Significance

Our DemoVAE model allows for generation of high quality synthetic data conditioned on subject demographics as well as the removal of the confounding effects of demographics. We identify that FC-based prediction tasks are highly influenced by demographic confounds.

Frontal and parietal cortices activation during walking is repeatable in older adults based on fNIRS

Purpose

This study aimed to explore the test-retest reliability of fNIRS in measuring frontal and parietal cortices activation during straight walking and turning walking in older adults, in order to provide a theoretical foundation for selecting assessment tools for clinical research on motor control and some diseases such as Parkinson's disease in older adults.

Methods

18 healthy older participants (69.1 ± 0.7 years) were included in this study. The participants completed straight walking and figure-of-eight turning walking tasks at self-selected speeds. Intra-class correlation coefficients (ICCs) and Bland-Altman scatter plots were used to assess the test-retest reliability of oxyhemoglobin (HbO2) changes derived from fNIRS. p < 0.05 was considered statistically significant.

Results

The test-retest reliability of HbO2 in prefrontal cortex (ICC, 0.67-0.78) was good and excellent, in frontal motor cortex (ICC, 0.51-0.61) and parietal sensory cortex (ICC, 0.53-0.62) is fair and good when the older adults performed straight and turning walking tasks. Bland-Altman diagram shows that the data consistency is fair and good.

Conclusion

fNIRS can be used as a clinical measurement method to evaluate the brain activation of the older adults when walking in a straight line and turning, and the results are acceptable repeatability and consistency. However, it is necessary to strictly control the testing process and consider the possible changes in the repeated measurements.

A Demographic-Conditioned Variational Autoencoder for fMRI Distribution Sampling and Removal of Confounds

Objective

fMRI and derived measures such as functional connectivity (FC) have been used to predict brain age, general fluid intelligence, psychiatric disease status, and preclinical neurodegenerative disease. However, it is not always clear that all demographic confounds, such as age, sex, and race, have been removed from fMRI data. Additionally, many fMRI datasets are restricted to authorized researchers, making dissemination of these valuable data sources challenging.

Methods

We create a variational autoencoder (VAE)-based model, DemoVAE, to decorrelate fMRI features from demographics and generate high-quality synthetic fMRI data based on user-supplied demographics. We train and validate our model using two large, widely used datasets, the Philadelphia Neurodevelopmental Cohort (PNC) and Bipolar and Schizophrenia Network for Intermediate Phenotypes (BSNIP).

Results

We find that DemoVAE recapitulates group differences in fMRI data while capturing the full breadth of individual variations. Significantly, we also find that most clinical and computerized battery fields that are correlated with fMRI data are not correlated with DemoVAE latents. An exception are several fields related to schizophrenia medication and symptom severity.

Conclusion

Our model generates fMRI data that captures the full distribution of FC better than traditional VAE or GAN models. We also find that most prediction using fMRI data is dependent on correlation with, and prediction of, demographics.

Significance

Our DemoVAE model allows for generation of high quality synthetic data conditioned on subject demographics as well as the removal of the confounding effects of demographics. We identify that FC-based prediction tasks are highly influenced by demographic confounds.

Exploratory insights into prefrontal cortex activity in continuous glucose monitoring: findings from a portable wearable functional near-infrared spectroscopy system

The escalating global prevalence of diabetes highlights an urgent need for advancements in continuous glucose monitoring (CGM) technologies that are non-invasive, accurate, and user-friendly. Here, we introduce a groundbreaking portable wearable functional near-infrared spectroscopy (fNIRS) system designed to monitor glucose levels by assessing prefrontal cortex (PFC) activity. Our study delineates the development and application of this novel fNIRS system, emphasizing its potential to revolutionize diabetes management by providing a non-invasive, real-time monitoring solution. Fifteen healthy university students participated in a controlled study, where we monitored their PFC activity and blood glucose levels under fasting and glucose-loaded conditions. Our findings reveal a significant correlation between PFC activity, as measured by our fNIRS system, and blood glucose levels, suggesting the feasibility of fNIRS technology for CGM. The portable nature of our system overcomes the mobility limitations of traditional setups, enabling continuous, real-time monitoring in everyday settings. We identified 10 critical features related to blood glucose levels from extensive fNIRS data and successfully correlated PFC function with blood glucose levels by constructing predictive models. Results show a positive association between fNIRS data and blood glucose levels, with the PFC exhibiting a clear response to blood glucose. Furthermore, the improved regressive rule principal component analysis (PCA) method outperforms traditional PCA in model prediction. We propose a model validation approach based on leave-one-out cross-validation, demonstrating the unique advantages of K-nearest neighbor (KNN) models. Comparative analysis with existing CGM methods reveals that our paper's KNN model exhibits lower RMSE and MARD at 0.11 and 8.96%, respectively, and the fNIRS data were highly significant positive correlation with actual blood glucose levels (r = 0.995, p < 0.000). This study provides valuable insights into the relationship between metabolic states and brain activity, laying the foundation for innovative CGM solutions. Our portable wearable fNIRS system represents a significant advancement in effective diabetes management, offering a promising alternative to current technologies and paving the way for future advancements in health monitoring and personalized medicine.

The most fundamental and popular literature on functional near-infrared spectroscopy: a bibliometric analysis of the top 100 most cited articles

Background

Functional near infrared spectroscopy (fNIRS) has developed rapidly in recent years, and there are more and more studies on fNIRS. At present, there is no bibliometric analysis of the top 100 most cited articles on fNIRS research.

Objective

To identify the top 100 most cited articles on fNIRS and analyze those most fundamental and popular articles through bibliometric research methods.

Methods

The literature on fNIRS of web of science from 1990 to 2023 was searched and the top 100 most cited articles were identified by citations. Use the bibliometrix package in R studio and VOSviewer for data analysis and plotting to obtain the output characteristics and citation status of these 100 most cited articles, and analyze research trends in this field through keywords.

Results

A total of 9,424 articles were retrieved from web of science since 1990. The average citation number of the 100 articles was 457.4 (range from 260 to 1,366). Neuroimage published the most articles (n = 31). Villringer, A. from Leipzig University had the largest number of top 100 papers. Harvard University (n = 22) conducted most cited articles. The United States, Germany, Japan, and the United Kingdom had most cited articles, respectively. The most common keywords were near-infrared spectroscopy, activation, cerebral-blood-flow, brain, newborn-infants, oxygenation, cortex, fMRI, spectroscopy. The fund sources mostly came from National Institutes of Health Unitd States (NIH) and United States Department of Health Human Services (n = 28).

Conclusion

Neuroimage was the most popular journal. The top countries, institutions, and authors were the United States, Harvard University, and Villringer, A., respectively. Researchers and institutions from North America and Europe contributed the most. Near-infrared spectroscopy, activation, cerebral-blood-flow, brain, newborn-infants, oxygenation, cortex, fmri, spectroscopy, stimulation, blood-flow, light-propagation, infants, tissue comprise the future research directions and potential topic hotspots for fNIRS.

Prefrontal cortex activity and functional organisation in dual-task ocular pursuit is affected by concurrent upper limb movement

Tracking a moving object with the eyes seems like a simple task but involves areas of prefrontal cortex (PFC) associated with attention, working memory and prediction. Increasing the demand on these processes with secondary tasks can affect eye movements and/or perceptual judgments. This is particularly evident in chronic or acute neurological conditions such as Alzheimer's disease or mild traumatic brain injury. Here, we combined near infrared spectroscopy and video-oculography to examine the effects of concurrent upper limb movement, which provides additional afference and efference that facilitates tracking of a moving object, in a novel dual-task pursuit protocol. We confirmed the expected effects on judgement accuracy in the primary and secondary tasks, as well as a reduction in eye velocity when the moving object was occluded. Although there was limited evidence of oculo-manual facilitation on behavioural measures, performing concurrent upper limb movement did result in lower activity in left medial PFC, as well as a change in PFC network organisation, which was shown by Graph analysis to be locally and globally more efficient. These findings extend upon previous work by showing how PFC is functionally organised to support eye-hand coordination when task demands more closely replicate daily activities.

Mapping brain function in adults and young children during naturalistic viewing with high-density diffuse optical tomography

Human studies of early brain development have been limited by extant neuroimaging methods. MRI scanners present logistical challenges for imaging young children, while alternative modalities like functional near-infrared spectroscopy have traditionally been limited by image quality due to sparse sampling. In addition, conventional tasks for brain mapping elicit low task engagement, high head motion, and considerable participant attrition in pediatric populations. As a result, typical and atypical developmental trajectories of processes such as language acquisition remain understudied during sensitive periods over the first years of life. We evaluate high-density diffuse optical tomography (HD-DOT) imaging combined with movie stimuli for high resolution optical neuroimaging in awake children ranging from 1 to 7 years of age. We built an HD-DOT system with design features geared towards enhancing both image quality and child comfort. Furthermore, we characterized a library of animated movie clips as a stimulus set for brain mapping and we optimized associated data analysis pipelines. Together, these tools could map cortical responses to movies and contained features such as speech in both adults and awake young children. This study lays the groundwork for future research to investigate response variability in larger pediatric samples and atypical trajectories of early brain development in clinical populations.

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.

A dynamic brain network decomposition method discovers effective brain hemodynamic sub-networks for Parkinson's disease

Objective.Dopaminergic treatment is effective for Parkinson's disease (PD). Nevertheless, the conventional treatment assessment mainly focuses on human-administered behavior examination while the underlying functional improvements have not been well explored. This paper aims to investigate brain functional variations of PD patients after dopaminergic therapy.Approach.This paper proposed a dynamic brain network decomposition method and discovered brain hemodynamic sub-networks that well characterized the efficacy of dopaminergic treatment in PD. Firstly, a clinical walking procedure with functional near-infrared spectroscopy was developed, and brain activations during the procedure from fifty PD patients under the OFF and ON states (without and with dopaminergic medication) were captured. Then, dynamic brain networks were constructed with sliding-window analysis of phase lag index and integrated time-varying functional networks across all patients. Afterwards, an aggregated network decomposition algorithm was formulated based on aggregated effectiveness optimization of functional networks in spanning network topology and cross-validation network variations, and utilized to unveil effective brain hemodynamic sub-networks for PD patients. Further, dynamic sub-network features were constructed to characterize the brain flexibility and dynamics according to the temporal switching and activation variations of discovered sub-networks, and their correlations with differential treatment-induced gait alterations were analyzed.Results.The results demonstrated that PD patients exhibited significantly enhanced flexibility after dopaminergic therapy within a sub-network related to the improvement of motor functions. Other sub-networks were significantly correlated with trunk-related axial symptoms and exhibited no significant treatment-induced dynamic interactions.Significance.The proposed method promises a quantified and objective approach for dopaminergic treatment evaluation. Moreover, the findings suggest that the gait of PD patients comprises distinct motor domains, and the corresponding neural controls are selectively responsive to dopaminergic treatment.

Altered Functional Connectivity of Temporoparietal Lobe in Obstructive Sleep Apnea: A Resting-State fNIRS Study

Obstructive Sleep Apnea (OSA), a sleep disorder with high prevalence, is normally accompanied by affective, autonomic, and cognitive abnormalities, and is deemed to be linked to functional brain alterations. To investigate alterations in brain functional connectivity properties in patients with OSA, a comparative analysis of global and local topological properties of brain networks was conducted between patients with OSA and healthy controls (HCs), utilizing functional near-infrared spectroscopy (fNIRS) imaging. A total of 148 patients with OSA and 150 healthy individuals were involved. Firstly, quantitative alterations in blood oxygen concentration, changes in functional connectivity, and variations in graph theory-based network topological characteristics were assessed. Then, with Mann-Whitney statistics, this study compared whether there are significant differences in the above characteristics between patients with OSA and HCs. Lastly, the study further examined the correlation between the altered characteristics and the apnea hypopnea index (AHI) using linear regression. Results revealed a higher mean and standard deviation of hemoglobin concentration in the superior temporal gyrus among patients with OSA compared to HCs. Resting-state functional connectivity (RSFC) exhibited a slight increase between the superior temporal gyrus and other specific areas in patients with OSA. Notably, neither patients with OSA nor HCs demonstrated significant small-world network properties. Patients with OSA displayed an elevated clustering coefficient (p < 0.05) and local efficiency (p < 0.05). Additionally, patients with OSA exhibited a tendency towards increased nodal betweenness centrality (p < 0.05) and degree centrality (p < 0.05) in the right supramarginal gyrus, as well as a trend towards higher betweenness centrality (p < 0.05) in the right precentral gyrus. The results of multiple linear regressions indicate that the influence of the AHI on RSFC between the right precentral gyrus and right superior temporal gyrus (p < 0.05), as well as between the right precentral gyrus and right supramarginal gyrus (p < 0.05), are statistically significant. These findings suggest that OSA may compromise functional brain connectivity and network topological properties in affected individuals, serving as a potential neurological mechanism underlying the observed abnormalities in brain function associated with OSA.

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

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

Experience-dependent neurodevelopment of self-regulation in adolescence

Adolescence is a period of rapid biobehavioral change, characterized in part by increased neural maturation and sensitivity to one's environment. In this review, we aim to demonstrate that self-regulation skills are tuned by adolescents' social, cultural, and socioeconomic contexts. We discuss adjacent literatures that demonstrate the importance of experience-dependent learning for adolescent development: environmental contextual influences and training paradigms that aim to improve regulation skills. We first highlight changes in prominent limbic and cortical regions-like the amygdala and medial prefrontal cortex-as well as structural and functional connectivity between these areas that are associated with adolescents' regulation skills. Next, we consider how puberty, the hallmark developmental milestone in adolescence, helps instantiate these biobehavioral adaptations. We then survey the existing literature demonstrating the ways in which cultural, socioeconomic, and interpersonal contexts drive behavioral and neural adaptation for self-regulation. Finally, we highlight promising results from regulation training paradigms that suggest training may be especially efficacious for adolescent samples. In our conclusion, we highlight some exciting frontiers in human self-regulation research as well as recommendations for improving the methodological implementation of developmental neuroimaging studies and training paradigms.

Using interbrain synchrony to study teamwork: A systematic review and meta-analysis

It has been proposed that interbrain synchrony (IBS) may help to elucidate the neural mechanisms underpinning teamwork. As hyperscanning studies have provided abundant findings on IBS in team environments, the current review aims to synthesize the findings of hyperscanning studies in a way that is relevant to the teamwork research. A systematic review was conducted. Included studies were classified according to the IPO (i.e. input, process, output) model of teamwork. Three multi-level meta-analyses were performed to quantify the associations between IBS and the three IPO variables. The methodology followed PRISMA guidelines and the protocol was pre-registered (https://osf.io/7h8sa/). Of the 229 studies, 41 were included, representing 1326 teams. The three meta-analyses found statistically significant positive effects, indicating a positive association between IBS and the three IPO teamwork variables. This study provides evidence that IBS is a relevant measure of the teamwork process and argues for the continued use of IBS to study teamwork.

Alterations in brain functional connectivity in patients with mild cognitive impairment: A systematic review and meta-analysis of functional near-infrared spectroscopy studies

Emerging evidences suggest that cognitive deficits in individuals with mild cognitive impairment (MCI) are associated with disruptions in brain functional connectivity (FC). This systematic review and meta-analysis aimed to comprehensively evaluate alterations in FC between MCI individuals and healthy control (HC) using functional near-infrared spectroscopy (fNIRS). Thirteen studies were included in qualitative analysis, with two studies synthesized for quantitative meta-analysis. Overall, MCI patients exhibited reduced resting-state FC, predominantly in the prefrontal, parietal, and occipital cortex. Meta-analysis of two studies revealed a significant reduction in resting-state FC from the right prefrontal to right occipital cortex (standardized mean difference [SMD] = -.56; p < .001), left prefrontal to left occipital cortex (SMD = -.68; p < .001), and right prefrontal to left occipital cortex (SMD = -.53; p < .001) in MCI patients compared to HC. During naming animal-walking task, MCI patients exhibited enhanced FC in the prefrontal, motor, and occipital cortex, whereas a decrease in FC was observed in the right prefrontal to left prefrontal cortex during calculating-walking task. In working memory tasks, MCI predominantly showed increased FC in the medial and left prefrontal cortex. However, a decreased in prefrontal FC and a shifted in distribution from the left to the right prefrontal cortex were noted in MCI patients during a verbal frequency task. In conclusion, fNIRS effectively identified abnormalities in FC between MCI and HC, indicating disrupted FC as potential markers for the early detection of MCI. Future studies should investigate the use of task- and region-specific FC alterations as a sensitive biomarker for MCI.

Classification Algorithm for fNIRS-based Brain Signals Using Convolutional Neural Network with Spatiotemporal Feature Extraction Mechanism

Brain Computer Interface (BCI) is a highly promising human-computer interaction method that can utilize brain signals to control external devices. BCI based on functional near-infrared spectroscopy (fNIRS) is considered a relatively new and promising paradigm. fNIRS is a technique of measuring functional changes in cerebral hemodynamics. It detects changes in the hemodynamic activity of the cerebral cortex by measuring oxyhemoglobin and deoxyhemoglobin (HbR) concentrations and inversely predicts the neural activity of the brain. At the present time, Deep learning (DL) methods have not been widely used in fNIRS decoding, and there are fewer studies considering both spatial and temporal dimensions for fNIRS classification. To solve these problems, we proposed an end-to-end hybrid neural network for feature extraction of fNIRS. The method utilizes a spatial-temporal convolutional layer for automatic extraction of temporally valid information and uses a spatial attention mechanism to extract spatially localized information. A temporal convolutional network (TCN) is used to further utilize the temporal information of fNIRS before the fully connected layer. We validated our approach on a publicly available dataset including 29 subjects, including left-hand and right-hand motor imagery (MI), mental arithmetic (MA), and a baseline task. The results show that the method has few training parameters and high accuracy, providing a meaningful reference for BCI development.

Reliability Evaluation for Continuous-Wave Functional Near-Infrared Spectroscopy Systems: Comprehensive Testing from Bench Characterization to Human Test

In recent years, biomedical optics technology has developed rapidly. The current widespread use of biomedical optics was made possible by the invention of optical instruments. The advantages of being non-invasive, portable, effective, low cost, and less susceptible to system noise have led to the rapid development of functional near-infrared spectroscopy (fNIRS) technology for hemodynamics detection, especially in the field of functional brain imaging. At the same time, laboratories and companies have developed various fNIRS-based systems. The safety, stability, and efficacy of fNIRS systems are key performance indicators. However, there is still a lack of comprehensive and systematic evaluation methods for fNIRS instruments. This study uses the fNIRS system developed in our laboratory as the test object. The test method established in this study includes system validation and performance testing to comprehensively assess fNIRS systems' reliability. These methods feature low cost and high practicality. Based on this study, existing or newly developed systems can be comprehensively and easily evaluated in the laboratory or workspace.

The Contribution of Functional Near-Infrared Spectroscopy (fNIRS) to the Study of Neurodegenerative Disorders: A Narrative Review

Functional near-infrared spectroscopy (fNIRS) is an innovative neuroimaging method that offers several advantages over other commonly used modalities. This narrative review investigated the potential contribution of this method to the study of neurodegenerative disorders. Thirty-four studies involving patients with Alzheimer's disease (AD), mild cognitive impairment (MCI), frontotemporal dementia (FTD), Parkinson's disease (PD), or amyotrophic lateral sclerosis (ALS) and healthy controls were reviewed. Overall, it was revealed that the prefrontal cortex of individuals with MCI may engage compensatory mechanisms to support declining brain functions. A rightward shift was suggested to compensate for the loss of the left prefrontal capacity in the course of cognitive decline. In parallel, some studies reported the failure of compensatory mechanisms in MCI and early AD; this lack of appropriate hemodynamic responses may serve as an early biomarker of neurodegeneration. One article assessing FTD demonstrated a heterogeneous cortical activation pattern compared to AD, indicating that fNIRS may contribute to the challenging distinction of these conditions. Regarding PD, there was evidence that cognitive resources (especially executive function) were recruited to compensate for locomotor impairments. As for ALS, fNIRS data support the involvement of extra-motor networks in ALS, even in the absence of measurable cognitive impairment.

Prefrontal Cortex Activity During Gait in People With Persistent Symptoms After Concussion

BACKGROUND

Concussions result in transient symptoms stemming from a cortical metabolic energy crisis. Though this metabolic energy crisis typically resolves in a month, symptoms can persist for years. The symptomatic period is associated with gait dysfunction, the cortical underpinnings of which are poorly understood. Quantifying prefrontal cortex (PFC) activity during gait may provide insight into post-concussion gait dysfunction. The purpose of this study was to explore the effects of persisting concussion symptoms on PFC activity during gait. We hypothesized that adults with persisting concussion symptoms would have greater PFC activity during gait than controls. Within the concussed group, we hypothesized that worse symptoms would relate to increased PFC activity during gait, and that increased PFC activity would relate to worse gait characteristics.

METHODS

The Neurobehavior Symptom Inventory (NSI) characterized concussion symptoms. Functional near-infrared spectroscopy quantified PFC activity (relative concentration changes of oxygenated hemoglobin [HbO2]) in 14 people with a concussion and 25 controls. Gait was assessed using six inertial sensors in the concussion group.

RESULTS

Average NSI total score was 26.4 (13.2). HbO2 was significantly higher (P = .007) for the concussed group (0.058 [0.108]) compared to the control group (-0.016 [0.057]). Within the concussion group, HbO2 correlated with NSI total symptom score (ρ = .62; P = .02), sagittal range of motion (r = .79; P = .001), and stride time variability (r = -.54; P = .046).

CONCLUSION

These data suggest PFC activity relates to symptom severity and some gait characteristics in people with persistent concussion symptoms. Identifying the neurophysiological underpinnings to gait deficits post-concussion expands our knowledge of motor behavior deficits in people with persistent concussion symptoms.

Interpersonal eye-tracking reveals the dynamics of interacting minds

The human eye is a rich source of information about where, when, and how we attend. Our gaze paths indicate where and what captures our attention, while changes in pupil size can signal surprise, revealing our expectations. Similarly, the pattern of our blinks suggests levels of alertness and when our attention shifts between external engagement and internal thought. During interactions with others, these cues reveal how we coordinate and share our mental states. To leverage these insights effectively, we need accurate, timely methods to observe these cues as they naturally unfold. Advances in eye-tracking technology now enable real-time observation of these cues, shedding light on mutual cognitive processes that foster shared understanding, collaborative thought, and social connection. This brief review highlights these advances and the new opportunities they present for future research.

Interpersonal neural synchrony and mental disorders: unlocking potential pathways for clinical interventions

Introduction

Interpersonal synchronization involves the alignment of behavioral, affective, physiological, and brain states during social interactions. It facilitates empathy, emotion regulation, and prosocial commitment. Mental disorders characterized by social interaction dysfunction, such as Autism Spectrum Disorder (ASD), Reactive Attachment Disorder (RAD), and Social Anxiety Disorder (SAD), often exhibit atypical synchronization with others across multiple levels. With the introduction of the "second-person" neuroscience perspective, our understanding of interpersonal neural synchronization (INS) has improved, however, so far, it has hardly impacted the development of novel therapeutic interventions.

Methods

To evaluate the potential of INS-based treatments for mental disorders, we performed two systematic literature searches identifying studies that directly target INS through neurofeedback (12 publications; 9 independent studies) or brain stimulation techniques (7 studies), following PRISMA guidelines. In addition, we narratively review indirect INS manipulations through behavioral, biofeedback, or hormonal interventions. We discuss the potential of such treatments for ASD, RAD, and SAD and using a systematic database search assess the acceptability of neurofeedback (4 studies) and neurostimulation (4 studies) in patients with social dysfunction.

Results

Although behavioral approaches, such as engaging in eye contact or cooperative actions, have been shown to be associated with increased INS, little is known about potential long-term consequences of such interventions. Few proof-of-concept studies have utilized brain stimulation techniques, like transcranial direct current stimulation or INS-based neurofeedback, showing feasibility and preliminary evidence that such interventions can boost behavioral synchrony and social connectedness. Yet, optimal brain stimulation protocols and neurofeedback parameters are still undefined. For ASD, RAD, or SAD, so far no randomized controlled trial has proven the efficacy of direct INS-based intervention techniques, although in general brain stimulation and neurofeedback methods seem to be well accepted in these patient groups.

Discussion

Significant work remains to translate INS-based manipulations into effective treatments for social interaction disorders. Future research should focus on mechanistic insights into INS, technological advancements, and rigorous design standards. Furthermore, it will be key to compare interventions directly targeting INS to those targeting other modalities of synchrony as well as to define optimal target dyads and target synchrony states in clinical interventions.

Transcutaneous auricular vagus nerve stimulation with task-oriented training improves upper extremity function in patients with subacute stroke: a randomized clinical trial

Background

Transcutaneous auricular vagus nerve stimulation (taVNS) has emerged as a promising brain stimulation modality in poststroke upper extremity rehabilitation. Although several studies have examined the safety and reliability of taVNS, the mechanisms underlying motor recovery in stroke patients remain unclear.

Objectives

This study aimed to investigate the effects of taVNS paired with task-oriented training (TOT) on upper extremity function in patients with subacute stroke and explore the potential underlying mechanisms.

Methods

In this double-blinded, randomized, controlled pilot trial, 40 patients with subacute stroke were randomly assigned to two groups: the VNS group (VG), receiving taVNS during TOT, and the Sham group (SG), receiving sham taVNS during TOT. The intervention was delivered 5 days per week for 4 weeks. Upper extremity function was measured using the Fugl-Meyer Assessment-Upper Extremity (FMA-UE), the Action Research Arm Test (ARAT). Activities of daily living were measured by the modified Barthel Index (MBI). Motor-evoked potentials (MEPs) were measured to evaluate cortical excitability. Assessments were administered at baseline and post-intervention. Additionally, the immediate effect of taVNS was detected using functional near-infrared spectroscopy (fNIRS) and heart rate variability (HRV) before intervention.

Results

The VG showed significant improvements in upper extremity function (FMA-UE, ARAT) and activities of daily living (MBI) compared to the SG at post-intervention. Furthermore, the VG demonstrated a higher rate of elicited ipsilesional MEPs and a shorter latency of MEPs in the contralesional M1. In the VG, improvements in FMA-UE were significantly associated with reduced latency of contralesional MEPs. Additionally, fNIRS revealed increased activation in the contralesional prefrontal cortex and ipsilesional sensorimotor cortex in the VG in contrast to the SG. However, no significant between-group differences were found in HRV.

Conclusion

The combination of taVNS with TOT effectively improves upper extremity function in patients with subacute stroke, potentially through modulating the bilateral cortex excitability to facilitate task-specific functional recovery.