The physiological origin of task-evoked systemic artefacts in functional near infrared spectroscopy

Gratitude enhances widespread dynamic cooperation and inter-brain synchronization in females

From both social and life perspectives, gratitude is essential for managing social relationships and fostering cooperation. This study investigated the dynamic influence of gratitude on two modalities of cooperative interactions and the associated interpersonal dynamic neural mechanism by integrating a dyadic ecological paradigm with functional near-infrared spectroscopy). Several critical findings emerged: the gratitude group exhibited better cooperative behaviors compared to the joy and neutral groups in both the Prisoner's Dilemma Game (PDG) and the Button-press Game (BPG). The dynamic cooperative behaviors further elucidated that gratitude dynamically facilitates cooperation by boosting inclusivity towards the benefactor's slight defect in the PDG and heightening action coordination in the BPG. Accordingly, higher inter-brain synchronization (IBS) was predominantly observed in the left and right middle frontal gyrus and the right sensorimotor cortex in the gratitude, compared to the joy and neutral groups. Moreover, the gratitude group exhibited increased IBS over time (across blocks) in the left and right middle frontal gyrus and the right superior temporal gyrus. These findings substantiate that gratitude facilitates widespread social cooperation and progressively enhances IBS among individuals. This work advances our understanding of gratitude-induced large-scale cooperative behaviors in societies.

Dynamic alterations in cortical activation during motor adaptation in table tennis using whole‑brain fNIRS

Human movements must constantly be adapted due to changing internal and external conditions in our environment. The underlying neuronal mechanisms that are responsible for motor adaptations have so far mainly been investigated in highly controlled laboratory scenarios using simple motor tasks. However, because motor adaptations in daily life and sports entail more complex processes involving several cognitive components and strategic adjustments, results from such highly controlled settings only allow restricted conclusions and do not capture neuronal processing in everyday life scenarios. Hence, we studied 56 participants using a table tennis paradigm to unravel cortical activation during motor adaptation in a sport-specific setting using functional NIRS. Furthermore, we wanted to investigate whether cortical activation during motor adaptation is influenced by the temporal order of perturbations (serial vs. randomized practice). Our findings revealed brain areas such as the dorsolateral prefrontal cortex and primary sensory cortex, left supplementary motor cortex and left primary motor cortex, as well as right superior parietal cortex and right inferior parietal cortex, exhibited dynamic alterations in their activation as motor adaptation progressed. Specifically, hemodynamic response alterations generally increased during early adaptation and decreased as motor adaptation progressed. On the other hand, no differential changes in cortical brain processing were observed with serial and randomized practice. Based on our findings, we can confirm and extent theoretical models and laboratory evidence of motor adaptation using a sport-specific motor task.

The emergence of moral alignment within human groups is facilitated by interbrain synchrony

Humans tend to align their behaviors and beliefs with their group peers. Establishing alignment between group members is crucial for group unity, yet the mechanisms underlying its emergence are under-explored. Here we examined the extent to which the brains of group members synchronize during deliberation on moral issues, and how interbrain synchrony supports alignment in their moral beliefs. We scanned 200 participants, who were divided into groups of four, using functional Near-Infrared Spectroscopy (fNIRS) during discussions on moral dilemmas. Behavioral results show that following group deliberations, members aligned their beliefs by adjusting their private beliefs towards the collective sentiment. Critically, neuroimaging results reveal that increased interbrain synchrony in the left inferior frontal gyrus (IFG) between group members predicts the degree of alignment post-deliberation. These findings indicate that the human tendency to align with group members extends to moral beliefs and reveal that regions related to mirroring and semantic sequence processing work across brains in coordination, to promote shared moral beliefs.

Capturing shared fNIRS responses to visual affective stimuli in young healthy women

Functional near-infrared spectroscopy (fNIRS) studies focusing on prefrontal cortex (PFC) have shown mixed results in relating hemodynamic changes to emotional processing, posing a challenge for clinical practice. Concerns related to instrumentation, recruited sample, task design, signal processing, and data analysis have been highlighted. To minimize some biasing factors, we proposed an experimental approach based on: (1) a homogeneous recruited sample, (2) an identical sequence of content-grouped affective pictures for emotion induction, (3) multi-distance forehead fNIRS recordings to separate cerebral from extra-cerebral components, and (4) a model-free frequency-based analysis to capture shared response patterns across individuals. We piloted a study to assess the feasibility of the approach in a sample of 20 young healthy women during an emotional task with affective pictures of neutral, sexual and violence content. We found coherent fNIRS responses to sexual and violence content located in slow fluctuations (0-0.019 Hz), characterized by positive and negative oxygenation patterns of extra-cerebral and cerebral origin, respectively. Additionally, we corroborated the strong interference of surface hemodynamics. This study proves the feasibility of our approach to identify frequency-specific fNIRS response patterns to affective visual stimuli, which holds promise for exploring functional biomarkers of healthy and altered emotional processing.

Deep multimodal representations and classification of first-episode psychosis via live face processing

Schizophrenia is a severe psychiatric disorder associated with a wide range of cognitive and neurophysiological dysfunctions and long-term social difficulties. Early detection is expected to reduce the burden of disease by initiating early treatment. In this paper, we test the hypothesis that integration of multiple simultaneous acquisitions of neuroimaging, behavioral, and clinical information will be better for prediction of early psychosis than unimodal recordings. We propose a novel framework to investigate the neural underpinnings of the early psychosis symptoms (that can develop into Schizophrenia with age) using multimodal acquisitions of neural and behavioral recordings including functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG), and facial features. Our data acquisition paradigm is based on live face-toface interaction in order to study the neural correlates of social cognition in first-episode psychosis (FEP). We propose a novel deep representation learning framework, Neural-PRISM, for learning joint multimodal compressed representations combining neural as well as behavioral recordings. These learned representations are subsequently used to describe, classify, and predict the severity of early psychosis in patients, as measured by the Positive and Negative Syndrome Scale (PANSS) and Global Assessment of Functioning (GAF) scores to evaluate the impact of symptomatology. We found that incorporating joint multimodal representations from fNIRS and EEG along with behavioral recordings enhances classification between typical controls and FEP individuals (significant improvements between 10 - 20%). Additionally, our results suggest that geometric and topological features such as curvatures and path signatures of the embedded trajectories of brain activity enable detection of discriminatory neural characteristics in early psychosis.

Timing of high-definition transcranial direct current stimulation to the nondominant primary motor cortex fails to modulate cortical hemodynamic activity and improve motor sequence learning

BACKGROUND

The relative timing of transcranial direct current stimulation (tDCS) and motor practice holds potential importance in modulating cortical activity and facilitating behavioral performance.

METHOD

A single-blind, randomized, cross-over experiment was conducted. Twenty healthy participants engaged in a sequential finger-tapping task with their left hand. High-definition anodal tDCS (1 mA, 20 min) was administered over the right primary motor cortex (M1) either during (concurrent-tDCS) or before the motor practice (prior-tDCS). A sham tDCS condition was also employed. The three tDCS conditions were separated by one-week intervals. Cortical hemodynamic activity in the prefrontal cortex (PFC), supplementary motor area (SMA), and M1 measured by functional near-infrared spectroscopy, as well as motor performance assessed by number of correct sequences were examined before (T1), immediately after (T2), and 24 h after the practice (T3). The data was subjected to a two-way repeated measures analysis of variance.

RESULTS

No significant interaction or main effect of condition were found on motor performance. Regarding cortical hemodynamic activity, none of the regions of interest or channels exhibited a significant interaction effect or main effect of condition. No significant correlation between cortical activity and motor performance was found.

CONCLUSION

Our results cannot support the timing effect of single-session anodal tDCS on facilitating brain activity or improving motor performance. These results contribute to the growing body of evidence challenging the efficacy of a single session of exogenous stimulation as an adjunct to motor practice for promoting motor acquisition. Further research should explore alternative tDCS parameters, multiple sessions and various age groups.

Reduced prefrontal hemodynamic responses measured using near-infrared spectroscopy in adults with autism spectrum disorder

Aim

Functional neuroimaging studies have suggested that prefrontal cortex dysfunction occurs in individuals with autism spectrum disorder (ASD). Near-infrared spectroscopy (NIRS) is a noninvasive optical tool used to investigate oxygenation and hemodynamic responses in the cerebral cortex by measuring changes in oxygenated hemoglobin. Previous studies using NIRS have suggested that male children with ASD exhibit reduced hemodynamic responses in the dorsolateral prefrontal cortex; however, only a few studies examined this response in adults with ASD.

Methods

We examined the characteristics of prefrontal hemodynamic responses in 114 adults with ASD and 84 typically developing controls. Relative concentrations of oxygenated hemoglobin were measured with frontal probes every 0.1 s during the Stroop color-word task, using 24-channel NIRS.

Results

Our findings demonstrated that the oxygenated hemoglobin changes in the ASD group were significantly smaller than those in the control group at channels 19, 20, 23, and 24- located over the orbitofrontal cortex and frontal pole (p <0.05 for all three channels). The differences in oxygenated hemoglobin changes at Ch 20 were significantly correlated with the Autism-Spectrum Quotient Japanese version (AQ-J) total score and attention switching score, which is a symptom cluster of AQ-J (p = 0.043 and p = 0.009, respectively).

Conclusion

Adults with ASD have reduced prefrontal hemodynamic responses as measured using near-infrared spectroscopy and the reduced activity of the frontal pole in particular is related to reduced attentional function.

Synchronization of brain activity associated with eye contact: comparison of face-to-face and online communication

Online meetings have become increasingly prevalent, especially during the coronavirus disease 2019 pandemic. Although they offer convenience and effectiveness in various contexts, there is a pertinent question about whether they truly replicate the richness of in-person communication. This study delves into the distinctions between online and face-to-face interactions, with a particular focus on the synchronization of brain activity. Previous research has indicated a connection between synchronization and the quality of communication. Therefore, our hypothesis posits that face-to-face interactions lead to greater brain synchronization compared to online interactions, which often lack certain social cues. To investigate this, we conducted a study using functional near-infrared spectroscopy hyperscanning during an eye-contact task involving 28 male participants organized into 14 pairs. We assessed brain signal synchronization using wavelet coherence analysis. After comparing face-to-face and online conditions, our findings revealed significantly higher synchronization in face-to-face scenarios, particularly within the right temporoparietal region. These results align with the outcomes of other hyperscanning studies and suggest that face-to-face communication elicits a higher level of brain synchronization compared with online communication. In the future, this approach holds promise for evaluating the effectiveness of online meeting tools in achieving a more authentic virtual communication experience.

Evaluation of Neural, Systemic and Extracerebral Activations During Active Walking Tasks in Older Adults Using fNIRS

Functional near infrared spectroscopy (fNIRS) is being increasingly used to assess brain hemodynamic responses during active walking in older adults due to its wearability, and relative immunity to motion artifacts. Specifically, fNIRS allows for continuous monitoring of brain activations that vary in response to experimental manipulations of cognitive demands during active walking tasks. Studies using fNIRS highlighted increased involvement of the prefrontal cortex (PFC) in dual compared to single task walking, operationalized using oxygenated hemoglobin (HbO), due to increasing attention demands inherent in the former task condition in aging and clinical populations. However, current literature utilizing fNIRS in mobility research has not been uniform in terms of fNIRS instrumentation characteristics and the accompanying signal processing methods to separate various signal sources (i.e. neural activations, extracerebral signals, systemic responses) which can raise questions about prior research findings. In our previous studies, we have used a forehead fNIR sensor (fNIR Imager 1100 by fNIR Devices, LLC) with 2.5 cm source detector separation (SDS) at 2 Hz sampling rate which allowed us to reliably evaluate changes in brain activations in the PFC during active walking. However, there exists other fNIRS devices incorporating a number of different types of light sources and detectors allowing multiple channels of long (3 cm SDS) and short (0.8 cm SDS) distance measurements in complex configurations for the monitoring of cognitive activations on various head locations at different depths with higher sampling rates of ~5 Hz (i.e. NIRx sensor, NIR Sport2 by NIRx Medizintechnik GmbH). Such involved designs further allowed the implementation of advanced signal processing algorithms to separate and evaluate neural, systemic and extracerebral signal contributions on the overall measurements. In this study, we collected brain imaging data on a sample of healthy older adults (n =15, age ) under single (STW) and dual task walking (DTW) conditions; participants were evaluated twice during one study visit, once wearing fNIR sensor and a second time while wearing NIRx sensor. This study design allowed us to address critical gaps in the extant literature concerning fNIRS-derived brain activations during active walking. Specifically, we evaluated potential effects of penetration depth as defined by the SDS of the fNIRS device, extracerebral activations (i.e. skin blood flow) and systemic signals (i.e. heart rate) on the observed HbO increases from STW to DTW. Our findings suggested that PFC activation differences between STW and DTW conditions observed in older adults were consistent across fNIRS instrumentations and the observed differences in HbO between STW and DTW were not materially influenced by scalp activations or systemic changes. Nevertheless, efforts to optimize extraction of fNIRS-derived brain signal measurements should continue taking advantage of technological advancement.

Intra-subject test-retest reliability for auditory-evoked functional near-infrared spectroscopy responses: effects of systemic physiology correction

Significance

Functional near-infrared spectroscopy (fNIRS) is a valuable neuroimaging tool for non-invasively measuring hemodynamic changes in response to neural activity, particularly in auditory research. Although fNIRS shows strong test-retest reliability at the group level, individual-subject level reliability is often compromised by systemic noise.

Aim

We investigate how correcting for systemic-physiological signals affects reliability in single-subject fNIRS data.

Approach

fNIRS data were collected from one participant over 10 sessions during a passive auditory task. Using general linear modeling, six correction approaches were compared: no correction, physiology correction, short-channel correction, short-channel + physiology correction, short-channel + physiology + lag correction, and short-channel + tCCA correction.

Results

Intraclass correlation coefficient analysis revealed that physiology correction yielded the highest test-retest reliability score, whereas short-channel correction had the lowest. These results align with previous findings suggesting that global systemic artifacts bolster reliability, and regressing such artifacts enhances the clarity of the observed neuronal response, as supported by visual comparisons of raw and denoised signals.

Conclusions

We highlight the impact of correcting for extra-cerebral signals in single-subject auditory research and demonstrate that, while incorporating short channels in fNIRS data collection may reduce reliability, it offers a more accurate representation of the neuronal response.

Deep Multimodal Representations and Classification of First-Episode Psychosis via Live Face Processing

Schizophrenia is a severe psychiatric disorder associated with a wide range of cognitive and neurophysiological dysfunctions and long-term social difficulties. In this paper, we test the hypothesis that integration of multiple simultaneous acquisitions of neuroimaging, behavioral, and clinical information will be better for prediction of early psychosis than unimodal recordings. We propose a novel framework to investigate the neural underpinnings of the early psychosis symptoms (that can develop into Schizophrenia with age) using multimodal acquisitions of neural and behavioral recordings including functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG), and facial features. Our data acquisition paradigm is based on live face-to-face interaction in order to study the neural correlates of social cognition in first-episode psychosis (FEP). We propose a novel deep representation learning framework, Neural-PRISM, for learning joint multimodal compressed representations combining neural as well as behavioral recordings. These learned representations are subsequently used to describe, classify, and predict the severity of early psychosis in patients, as measured by the Positive and Negative Syndrome Scale (PANSS) and Global Assessment of Functioning (GAF) scores. We found that incorporating joint multimodal representations from fNIRS and EEG along with behavioral recordings enhances classification between typical controls and FEP individuals. Additionally, our results suggest that geometric and topological features such as curvatures and path signatures of the embedded trajectories of brain activity enable detection of discriminatory neural characteristics in early psychosis.

Ecological functional near-infrared spectroscopy in mobile children: using short separation channels to correct for systemic contamination during naturalistic neuroimaging

Significance

The advances and miniaturization in functional near-infrared spectroscopy (fNIRS) instrumentation offer the potential to move the classical laboratory-based cognitive neuroscience investigations into more naturalistic settings. Wearable and mobile fNIRS devices also provide a novel child-friendly means to image functional brain activity in freely moving toddlers and preschoolers. Measuring brain activity in more ecologically valid settings with fNIRS presents additional challenges, such as the increased impact of physiological interferences. One of the most popular methods for minimizing such interferences is to regress out short separation channels from the long separation channels [i.e., superficial signal regression (SSR)]. Although this has been extensively investigated in adults, little is known about the impact of systemic changes on the fNIRS signals recorded in children in either classical or novel naturalistic experiments.

Aim

We aim to investigate if extracerebral physiological changes occur in toddlers and preschoolers and whether SSR can help minimize these interferences.

Approach

We collected fNIRS data from 3- to 7-year-olds during a conventional computerized static task and in a dynamic naturalistic task in an immersive virtual reality (VR) cave automatic virtual environment.

Results

Our results show that superficial signal contamination data are present in young children as in adults. Importantly, we find that SSR helps in improving the localization of functional brain activity, both in the computerized task and, to a larger extent, in the dynamic VR task.

Conclusions

Following these results, we formulate suggestions to advance the field of developmental neuroimaging with fNIRS, particularly in ecological settings.

Regional brain activity and neural network changes in cognitive-motor dual-task interference: A functional near-infrared spectroscopy study

Previous neuroimaging studies have reported dual-task interference (DTi) and deterioration of task performance in a cognitive-motor dual task (DT) compared to that in a single task (ST). Greater frontoparietal activity is a neural signature of DTi; nonetheless, the underlying mechanism of cortical network in DTi still remains unclear. This study aimed to investigate the regional brain activity and neural network changes during DTi induced by highly demanding cognitive-motor DT. Thirty-four right-handed healthy young adults performed the spiral-drawing task. They underwent a paced auditory serial addition test (PASAT) simultaneously or independently while their cortical activity was measured using functional near-infrared spectroscopy. Motor performance was determined using the balanced integration score (BIS), a balanced index of drawing speed and precision. The cognitive task of the PASAT was administered with two difficulty levels defined by 1 s (PASAT-1 s) and 2 s (PASAT-2 s) intervals, allowing for the serial addition of numbers. Cognitive performance was determined using the percentage of correct responses. These motor and cognitive performances were significantly reduced during DT, which combined a drawing and a cognitive task at either difficulty level, compared to those in the corresponding ST conditions. The DT conditions were also characterized by significantly increased activity in the right dorsolateral prefrontal cortex (DLPFC) compared to that in the ST conditions. Multivariate Granger causality (GC) analysis of cortical activity in the selected frontoparietal regions of interest further revealed selective top-down causal connectivity from the right DLPFC to the right inferior parietal cortex during DTs. Furthermore, changes in the frontoparietal GC connectivity strength between the PASAT-2 s DT and ST conditions significantly correlated negatively with changes in the percentage of correct responses. Therefore, DTi can occur even in cognitively proficient young adults, and the right DLPFC and frontoparietal network being crucial neural mechanisms underlying DTi. These findings provide new insights into DTi and its underlying neural mechanisms and have implications for the clinical utility of cognitive-motor DTs applied to clinical populations with cognitive decline, such as those with psychiatric and brain disorders.

Freezing of gait in Parkinson's disease is related to imbalanced stopping-related cortical activity

Freezing of gait, characterized by involuntary interruptions of walking, is a debilitating motor symptom of Parkinson's disease that restricts people's autonomy. Previous brain imaging studies investigating the mechanisms underlying freezing were restricted to scan people in supine positions and yielded conflicting theories regarding the role of the supplementary motor area and other cortical regions. We used functional near-infrared spectroscopy to investigate cortical haemodynamics related to freezing in freely moving people. We measured functional near-infrared spectroscopy activity over multiple motor-related cortical areas in 23 persons with Parkinson's disease who experienced daily freezing ('freezers') and 22 age-matched controls during freezing-provoking tasks including turning and doorway passing, voluntary stops and actual freezing. Crucially, we corrected the measured signals for confounds of walking. We first compared cortical activity between freezers and controls during freezing-provoking tasks without freezing (i.e. turning and doorway passing) and during stops. Secondly, within the freezers, we compared cortical activity between freezing, stopping and freezing-provoking tasks without freezing. First, we show that turning and doorway passing (without freezing) resemble cortical activity during stopping in both groups involving activation of the supplementary motor area and prefrontal cortex, areas known for their role in inhibiting actions. During these freezing-provoking tasks, the freezers displayed higher activity in the premotor areas than controls. Secondly, we show that, during actual freezing events, activity in the prefrontal cortex was lower than during voluntary stopping. The cortical relation between the freezing-provoking tasks (turning and doorway passing) and stopping may explain their susceptibility to trigger freezing by activating a stopping mechanism. Besides, the stopping-related activity of the supplementary motor area and prefrontal cortex seems to be out of balance in freezers. In this paper, we postulate that freezing results from a paroxysmal imbalance between the supplementary motor area and prefrontal cortex, thereby extending upon the current role of the supplementary motor area in freezing pathophysiology.

Effects of an online mindfulness-based intervention on brain haemodynamics: a pilot randomized controlled trial using functional near-infrared spectroscopy

Although many neuroimaging studies have evaluated changes in the prefrontal cortex during mindfulness-based interventions, most of these studies were cross-sectional studies of skilled participants or involved pre-post comparisons before and after a single session. While functional near-infrared spectroscopy is a useful tool to capture changes in the hemodynamic response of the prefrontal cortex during continuous mindfulness-based intervention, its ability to detect the accumulated effects of continuous mindfulness-based intervention is currently unclear. We investigated whether a 12-wk online mindfulness-based intervention changed the hemodynamic response of the prefrontal cortex during a verbal fluency task. Eighty-two healthy university students were randomly allocated to a 12-wk online mindfulness-based intervention group or a wait-list control group. The integral values of oxygenated hemoglobin measured using functional near-infrared spectroscopy before and after the intervention were compared to the values in the wait-list group. The intervention condition showed significantly greater functional near-infrared spectroscopy signal activation than the control condition; however, the effect sizes before and after the intervention were small. Thus, continuous mindfulness-based intervention could alter prefrontal cortex function, and functional near-infrared spectroscopy could be useful for measuring the accumulated effects of continuous mindfulness-based interventions. With a better understanding of the association between mindfulness and functional near-infrared spectroscopy signals, functional near-infrared spectroscopy can be used for biofeedback analyses.

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.

Mobile neuroimaging: What we have learned about the neural control of human walking, with an emphasis on EEG-based research

Our understanding of the neural control of human walking has changed significantly over the last twenty years and mobile brain imaging methods have contributed substantially to current knowledge. High-density electroencephalography (EEG) has the advantages of being lightweight and mobile while providing temporal resolution of brain changes within a gait cycle. Advances in EEG hardware and processing methods have led to a proliferation of research on the neural control of locomotion in neurologically intact adults. We provide a narrative review of the advantages and disadvantages of different mobile brain imaging methods, then summarize findings from mobile EEG studies quantifying electrocortical activity during human walking. Contrary to historical views on the neural control of locomotion, recent studies highlight the widespread involvement of many areas, such as the anterior cingulate, posterior parietal, prefrontal, premotor, sensorimotor, supplementary motor, and occipital cortices, that show active fluctuations in electrical power during walking. The electrocortical activity changes with speed, stability, perturbations, and gait adaptation. We end with a discussion on the next steps in mobile EEG research.

Adjusting effective multiplicity ( M eff ) for family-wise error rate in functional near-infrared spectroscopy data with a small sample size

Significance

The advancement of multichannel functional near-infrared spectroscopy (fNIRS) has enabled measurements across a wide range of brain regions. This increase in multiplicity necessitates the control of family-wise errors in statistical hypothesis testing. To address this issue, the effective multiplicity (M eff ) method designed for channel-wise analysis, which considers the correlation between fNIRS channels, was developed. However, this method loses reliability when the sample size is smaller than the number of channels, leading to a rank deficiency in the eigenvalues of the correlation matrix and hindering the accuracy ofM eff calculations.

Aim

We aimed to reevaluate the effectiveness of theM eff method for fNIRS data with a small sample size.

Approach

In experiment 1, we used resampling simulations to explore the relationship between sample size andM eff values. Based on these results, experiment 2 employed a typical exponential model to investigate whether validM eff could be predicted from a small sample size.

Results

Experiment 1 revealed that theM eff values were underestimated when the sample size was smaller than the number of channels. However, an exponential pattern was observed. Subsequently, in experiment 2, we found that validM eff values can be derived from sample sizes of 30 to 40 in datasets with 44 and 52 channels using a typical exponential model.

Conclusions

The findings from these two experiments indicate the potential for the effective application ofM eff correction in fNIRS studies with sample sizes smaller than the number of channels.

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.

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.

Cerebral, systemic physiological and behavioral responses to colored light exposure during a cognitive task: A SPA-fNIRS study

Colored light has important implications for human health and well-being, as well as for the aesthetics and function of various environments. In addition to its effects on visual function, colored light has significant effects on cognitive performance, behavior and systemic physiology. The aim of the current study was to comprehensively investigate how colored light exposure (CLE) combined with a cognitive task (2-back) affects performance, cerebral hemodynamics, oxygenation, and systemic physiology as assessed by systemic physiology augmented functional near-infrared spectroscopy (SPA-fNIRS). 36 healthy subjects (22 female, 14 male, age 26.3 ± 5.7 years) were measured twice on two different days. They were exposed to the sequence of blue and red light or vice versa in a randomized crossover design. During the CLE, the subjects were asked to perform a 2-back task. The 2-back task performance was correlated with changes in the concentration of oxygenated hemoglobin in the prefrontal cortex (red: r = -0.37, p = 0.001; blue: r = -0.33, p = 0.004) and the high-frequency component of the heart rate variability (red: r = 0.35, p = 0.003; blue: r = 0.25, p = 0.04). These changes were independent of the CLE. Sequence-dependent effects were observed for fNIRS signals at the visual cortex (VC) and for electrodermal activity (EDA). While both colors caused relatively similar changes in the VC and EDA at the position of the first exposure, blue and red light caused greater changes in the VC and EDA, respectively, in the second exposure. There was no significant difference in the subjects' 2-back task performance between the CLE (p = 0.46). The results of this study provide new insights into how human physiology and behavior respond to colored light exposure. Our findings are important for understanding the impact of colored light in our daily lives and its potential applications in a variety of settings, including education, the workplace and healthcare.

Unlocking the neural mechanisms of consumer loan evaluations: an fNIRS and ML-based consumer neuroscience study

Introduction

This study conducts a comprehensive exploration of the neurocognitive processes underlying consumer credit decision-making using cutting-edge techniques from neuroscience and machine learning (ML). Employing functional Near-Infrared Spectroscopy (fNIRS), the research examines the hemodynamic responses of participants while evaluating diverse credit offers.

Methods

The experimental phase of this study investigates the hemodynamic responses collected from 39 healthy participants with respect to different loan offers. This study integrates fNIRS data with advanced ML algorithms, specifically Extreme Gradient Boosting, CatBoost, Extra Tree Classifier, and Light Gradient Boosted Machine, to predict participants' credit decisions based on prefrontal cortex (PFC) activation patterns.

Results

Findings reveal distinctive PFC regions correlating with credit behaviors, including the dorsolateral prefrontal cortex (dlPFC) associated with strategic decision-making, the orbitofrontal cortex (OFC) linked to emotional valuations, and the ventromedial prefrontal cortex (vmPFC) reflecting brand integration and reward processing. Notably, the right dorsomedial prefrontal cortex (dmPFC) and the right vmPFC contribute to positive credit preferences.

Discussion

This interdisciplinary approach bridges neuroscience, machine learning and finance, offering unprecedented insights into the neural mechanisms guiding financial choices regarding different loan offers. The study's predictive model holds promise for refining financial services and illuminating human financial behavior within the burgeoning field of neurofinance. The work exemplifies the potential of interdisciplinary research to enhance our understanding of human financial decision-making.

Retrieval of chromophore concentration changes in a digital human head model using analytical mean partial pathlengths of photons

Significance

Continuous-wave functional near-infrared spectroscopy has proved to be a valuable tool for assessing hemodynamic activity in the human brain in a non-invasively and inexpensive way. However, most of the current processing/analysis methods assume the head is a homogeneous medium, and hence do not appropriately correct for the signal coming from the scalp. This effect can be reduced by considering light propagation in a layered model of the human head, being the Monte Carlo (MC) simulations the gold standard to this end. However, this implies large computation times and demanding hardware capabilities.

Aim

In this work, we study the feasibility of replacing the homogeneous model and the MC simulations by means of analytical multilayered models, combining in this way, the speed and simplicity of implementation of the former with the robustness and accuracy of the latter.

Approach

Oxy- and deoxyhemoglobin (HbO and HbR, respectively) concentration changes were proposed in two different layers of a magnetic resonance imaging (MRI)-based meshed model of the human head, and then these changes were retrieved by means of (i) a typical homogeneous reconstruction and (ii) a theoretical layered reconstruction.

Results

Results suggest that the use of analytical models of light propagation in layered models outperforms the results obtained using traditional homogeneous reconstruction algorithms, providing much more accurate results for both, the extra- and the cerebral tissues. We also compare the analytical layered reconstruction with MC-based reconstructions, achieving similar degrees of accuracy, especially in the gray matter layer, but much faster (between 4 and 5 orders of magnitude).

Conclusions

We have successfully developed, implemented, and validated a method for retrieving chromophore concentration changes in the human brain, combining the simplicity and speed of the traditional homogeneous reconstruction algorithms with robustness and accuracy much more similar to those provided by MC simulations.

Investigation of electro-vascular phase-amplitude coupling during an auditory task

Multimodal neuroimaging using electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) provides complementary views of cortical processes, including those related to auditory processing. However, current multimodal approaches often overlook potential insights that can be gained from nonlinear interactions between electrical and hemodynamic signals. Here, we explore electro-vascular phase-amplitude coupling (PAC) between low-frequency hemodynamic and high-frequency electrical oscillations during an auditory task. We further apply a temporally embedded canonical correlation analysis (tCCA)-general linear model (GLM)-based correction approach to reduce the possible effect of systemic physiology on fNIRS recordings. Before correction, we observed significant PAC between fNIRS and broadband EEG in the frontal region (p ≪ 0.05), β (p ≪ 0.05) and γ (p = 0.010) in the left temporal/temporoparietal (left auditory; LA) region, and γ (p = 0.032) in the right temporal/temporoparietal (right auditory; RA) region across the entire dataset. Significant differences in PAC across conditions (task versus silence) were observed in LA (p = 0.023) and RA (p = 0.049) γ sub-bands and in lower frequency (5-20 Hz) frontal activity (p = 0.005). After correction, significant fNIRS-γ-band PAC was observed in the frontal (p = 0.021) and LA (p = 0.025) regions, while fNIRS-α (p = 0.003) and fNIRS-β (p = 0.041) PAC were observed in RA. Decreased frontal γ-band (p = 0.008) and increased β-band (p ≪ 0.05) PAC were observed during the task. These outcomes represent the first characterization of electro-vascular PAC between fNIRS and EEG signals during an auditory task, providing insights into electro-vascular coupling in auditory processing.

fNIRS a novel neuroimaging tool to investigate olfaction, olfactory imagery, and crossmodal interactions: a systematic review

Olfaction is understudied in neuroimaging research compared to other senses, but there is growing evidence of its therapeutic benefits on mood and well-being. Olfactory imagery can provide similar health benefits as olfactory interventions. Harnessing crossmodal visual-olfactory interactions can facilitate olfactory imagery. Understanding and employing these cross-modal interactions between visual and olfactory stimuli could aid in the research and applications of olfaction and olfactory imagery interventions for health and wellbeing. This review examines current knowledge, debates, and research on olfaction, olfactive imagery, and crossmodal visual-olfactory integration. A total of 56 papers, identified using the PRISMA method, were evaluated to identify key brain regions, research themes and methods used to determine the suitability of fNIRS as a tool for studying these topics. The review identified fNIRS-compatible protocols and brain regions within the fNIRS recording depth of approximately 1.5 cm associated with olfactory imagery and crossmodal visual-olfactory integration. Commonly cited regions include the orbitofrontal cortex, inferior frontal gyrus and dorsolateral prefrontal cortex. The findings of this review indicate that fNIRS would be a suitable tool for research into these processes. Additionally, fNIRS suitability for use in naturalistic settings may lead to the development of new research approaches with greater ecological validity compared to existing neuroimaging techniques.

Prefrontal cortex hemodynamic activity during a test of lower extremity functional muscle strength in children with cerebral palsy: A functional near-infrared spectroscopy study

Children with cerebral palsy (CP) exhibit impaired motor control and significant muscle weakness due to a brain lesion. However, studies that assess the relationship between brain activity and performance on dynamic functional muscle strength assessments in CP are needed. The aim of this study was to determine the effect of a progressive lateral step-up test on prefrontal cortex (PFC) hemodynamic activity in children with CP. Fourteen ambulatory children with spastic CP (Gross Motor Function Classification System level I; 5-11 y) and 14 age- and sex-matched typically developing control children completed a progressive lateral step-up test at incremental step heights (0, 10, 15 and 20 cm) using their non-dominant lower limb. Hemodynamic activity in the PFC was assessed using non-invasive, portable functional neuroimaging (functional near-infrared spectroscopy). Children with CP completed fewer repetitions at each step height and exhibited lower PFC hemodynamic activity across step heights compared to controls. Lower PFC activation in CP was maintained after statistically controlling for the number of repetitions completed at each step height. PFC hemodynamic activity was not associated with LSUT task performance in children with CP, but a positive relationship was observed in controls at the most challenging 20 cm step height. The results suggest there is an altered PFC recruitment pattern in children with CP during a highly dynamic test of functional strength. Further studies are needed to explore the mechanisms underlying the suppressed PFC activation observed in children with CP compared to typically developing children.

The Benefit of Hearing Aids as Measured by Listening Accuracy, Subjective Listening Effort, and Functional Near Infrared Spectroscopy

There is broad consensus that listening effort is an important outcome for measuring hearing performance. However, there remains debate on the best ways to measure listening effort. This study sought to measure neural correlates of listening effort using functional near-infrared spectroscopy (fNIRS) in experienced adult hearing aid users. The study evaluated impacts of amplification and signal-to-noise ratio (SNR) on cerebral blood oxygenation, with the expectation that easier listening conditions would be associated with less oxygenation in the prefrontal cortex. Thirty experienced adult hearing aid users repeated sentence-final words from low-context Revised Speech Perception in Noise Test sentences. Participants repeated words at a hard SNR (individual SNR-50) or easy SNR (individual SNR-50 + 10 dB), while wearing hearing aids fit to prescriptive targets or without wearing hearing aids. In addition to assessing listening accuracy and subjective listening effort, prefrontal blood oxygenation was measured using fNIRS. As expected, easier listening conditions (i.e., easy SNR, with hearing aids) led to better listening accuracy, lower subjective listening effort, and lower oxygenation across the entire prefrontal cortex compared to harder listening conditions. Listening accuracy and subjective listening effort were also significant predictors of oxygenation.

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.

Workload-dependent hemispheric asymmetries during the emotion-cognition interaction: a close-to-naturalistic fNIRS study

Introduction

We investigated brain activation patterns of interacting emotional distractions and cognitive processes in a close-to-naturalistic functional near-infrared spectroscopy (fNIRS) study.

Methods

Eighteen participants engaged in a monitoring-control task, mimicking common air traffic controller requirements. The scenario entailed experiencing both low and high workload, while concurrently being exposed to emotional speech distractions of positive, negative, and neutral valence.

Results

Our investigation identified hemispheric asymmetries in prefrontal cortex (PFC) activity during the presentation of negative and positive emotional speech distractions at different workload levels. Thereby, in particular, activation in the left inferior frontal gyrus (IFG) and orbitofrontal cortex (OFC) seems to play a crucial role. Brain activation patterns revealed a cross-over interaction indicating workload-dependent left hemispheric inhibition processes during negative distractions and high workload. For positive emotional distractions under low workload, we observed left-hemispheric PFC recruitment potentially associated with speech-related processes. Furthermore, we found a workload-independent negativity bias for neutral distractions, showing brain activation patterns similar to those of negative distractions.

Discussion

In conclusion, lateralized hemispheric processing, regulating emotional speech distractions and integrating emotional and cognitive processes, is influenced by workload levels and stimulus characteristics. These findings advance our understanding of the factors modulating hemispheric asymmetries during the processing and inhibition of emotional distractions, as well as the interplay between emotion and cognition. Moreover, they emphasize the significance of exploring emotion-cognition interactions in more naturalistic settings to gain a deeper understanding of their implications in real-world application scenarios (e.g., working and learning environments).

Quantification of inter-brain coupling: A review of current methods used in haemodynamic and electrophysiological hyperscanning studies

Hyperscanning is a form of neuroimaging experiment where the brains of two or more participants are imaged simultaneously whilst they interact. Within the domain of social neuroscience, hyperscanning is increasingly used to measure inter-brain coupling (IBC) and explore how brain responses change in tandem during social interaction. In addition to cognitive research, some have suggested that quantification of the interplay between interacting participants can be used as a biomarker for a variety of cognitive mechanisms aswell as to investigate mental health and developmental conditions including schizophrenia, social anxiety and autism. However, many different methods have been used to quantify brain coupling and this can lead to questions about comparability across studies and reduce research reproducibility. Here, we review methods for quantifying IBC, and suggest some ways moving forward. Following the PRISMA guidelines, we reviewed 215 hyperscanning studies, across four different brain imaging modalities: functional near-infrared spectroscopy (fNIRS), functional magnetic resonance (fMRI), electroencephalography (EEG) and magnetoencephalography (MEG). Overall, the review identified a total of 27 different methods used to compute IBC. The most common hyperscanning modality is fNIRS, used by 119 studies, 89 of which adopted wavelet coherence. Based on the results of this literature survey, we first report summary statistics of the hyperscanning field, followed by a brief overview of each signal that is obtained from each neuroimaging modality used in hyperscanning. We then discuss the rationale, assumptions and suitability of each method to different modalities which can be used to investigate IBC. Finally, we discuss issues surrounding the interpretation of each method.

Deep Learning Based Walking Tasks Classification in Older Adults Using fNIRS

Decline in gait features is common in older adults and an indicator of increased risk of disability, morbidity, and mortality. Under dual task walking (DTW) conditions, further degradation in the performance of both the gait and the secondary cognitive task were found in older adults which were significantly correlated to falls history. Cortical control of gait, specifically in the pre-frontal cortex (PFC) as measured by functional near infrared spectroscopy (fNIRS), during DTW in older adults has recently been studied. However, the automatic classification of differences in cognitive activations under single and dual task gait conditions has not been extensively studied yet. In this paper, by considering single task walking (STW) as a lower attentional walking state and DTW as a higher attentional walking state, we aimed to formulate this as an automatic detection of low and high attentional walking states and leverage deep learning methods to perform their classification. We conduct analysis on the data samples which reveals the characteristics on the difference between HbO2 and Hb values that are subsequently used as additional features. We perform feature engineering to formulate the fNIRS features as a 3-channel image and apply various image processing techniques for data augmentation to enhance the performance of deep learning models. Experimental results show that pre-trained deep learning models that are fine-tuned using the collected fNIRS dataset together with gender and cognitive status information can achieve around 81% classification accuracy which is about 10% higher than the traditional machine learning algorithms. We present additional sensitivity metrics such as confusion matrix, precision and F1 score, as well as accuracy on two-way classification between condition pairings. We further performed an extensive ablation study to evaluate factors such as the voxel locations, channels of input images, zero-paddings and pre-training of deep learning model on their contribution or impact to the classification task. Results showed that using pre-trained model, all the voxel locations, and HbO2 - Hb as the third channel of the input image can achieve the best classification accuracy.

Subjective feeling of control during fNIRS-based neurofeedback targeting the DL-PFC is related to neural activation determined with short-channel correction

Neurofeedback (NF) training is a promising preventive and therapeutic approach for brain and behavioral impairments, the dorsolateral prefrontal cortex (DL-PFC) being a relevant region of interest. Functional near-infrared spectroscopy (NIRS) has recently been applied in NF training. However, this approach is highly sensitive to extra-cerebral vascularization, which could bias measurements of cortical activity. Here, we examined the feasibility of a NF training targeting the DL-PFC and its specificity by assessing the impact of physiological confounds on NF success via short-channel offline correction under different signal filtering conditions. We also explored whether the individual mental strategies affect the NF success. Thirty volunteers participated in a single 15-trial NF session in which they had to increase the oxy-hemoglobin (HbO2) level of their bilateral DL-PFC. We found that 0.01-0.09 Hz band-pass filtering was more suited than the 0.01-0.2 Hz band-pass filter to highlight brain activation restricted to the NF channels in the DL-PFC. Retaining the 10 out of 15 best trials, we found that 18 participants (60%) managed to control their DL-PFC. This number dropped to 13 (43%) with short-channel correction. Half of the participants reported a positive subjective feeling of control, and the "cheering" strategy appeared to be more effective in men (p<0.05). Our results showed successful DL-PFC fNIRS-NF in a single session and highlighted the value of accounting for extra cortical signals, which can profoundly affect the success and specificity of NF training.

Increased Cortical Activity in Novices Compared to Experts During Table Tennis: A Whole-Brain fNIRS Study Using Threshold-Free Cluster Enhancement Analysis

There is a growing interest to understand the neural underpinnings of high-level sports performance including expertise-related differences in sport-specific skills. Here, we aimed to investigate whether expertise level and task complexity modulate the cortical hemodynamics of table tennis players. 35 right-handed table tennis players (17 experts/18 novices) were recruited and performed two table tennis strokes (forehand and backhand) and a randomized combination of them. Cortical hemodynamics, as a proxy for cortical activity, were recorded using functional near-infrared spectroscopy, and the behavioral performance (i.e., target accuracy) was assessed via video recordings. Expertise- and task-related differences in cortical hemodynamics were analyzed using nonparametric threshold-free cluster enhancement. In all conditions, table tennis experts showed a higher target accuracy than novices. Furthermore, we observed expertise-related differences in widespread clusters compromising brain areas being associated with sensorimotor and multisensory integration. Novices exhibited, in general, higher activation in those areas as compared to experts. We also identified task-related differences in cortical activity including frontal, sensorimotor, and multisensory brain areas. The present findings provide empirical support for the neural efficiency hypothesis since table tennis experts as compared to novices utilized a lower amount of cortical resources to achieve superior behavioral performance. Furthermore, our findings suggest that the task complexity of different table tennis strokes is mirrored in distinct cortical activation patterns. Whether the latter findings can be useful to monitor or tailor sport-specific training interventions necessitates further investigations.

Short-separation regression incorporated diffuse optical tomography image reconstruction modeling for high-density functional near-infrared spectroscopy

Significance

Short-separation (SS) regression and diffuse optical tomography (DOT) image reconstruction, two widely adopted methods in functional near-infrared spectroscopy (fNIRS), were demonstrated to individually facilitate the separation of brain activation and physiological signals, with further improvement using both sequentially. We hypothesized that doing both simultaneously would further improve the performance.

Aim

Motivated by the success of these two approaches, we propose a method, SS-DOT, which applies SS and DOT simultaneously.

Approach

The method, which employs spatial and temporal basis functions to represent the hemoglobin concentration changes, enables us to incorporate SS regressors into the time series DOT model. To benchmark the performance of the SS-DOT model against conventional sequential models, we use fNIRS resting state data augmented with synthetic brain response as well as data acquired during a ball squeezing task. The conventional sequential models comprise performing SS regression and DOT.

Results

The results show that the SS-DOT model improves the image quality by increasing the contrast-to-background ratio by a threefold improvement. The benefits are marginal at small brain activation.

Conclusions

The SS-DOT model improves the fNIRS image reconstruction quality.

Functional near-infrared spectroscopy in pediatric clinical research: Different pathophysiologies and promising clinical applications

Over its 30 years of existence, functional near-infrared spectroscopy (fNIRS) has matured into a highly versatile tool to study brain function in infants and young children. Its advantages, amongst others, include its ease of application and portability, the option to combine it with electrophysiology, and its relatively good tolerance to movement. As shown by the impressive body of fNIRS literature in the field of cognitive developmental neuroscience, the method's strengths become even more relevant for (very) young individuals who suffer from neurological, behavioral, and/or cognitive impairment. Although a number of studies have been conducted with a clinical perspective, fNIRS cannot yet be considered as a truly clinical tool. The first step has been taken in this direction by studies exploring options in populations with well-defined clinical profiles. To foster further progress, here, we review several of these clinical approaches to identify the challenges and perspectives of fNIRS in the field of developmental disorders. We first outline the contributions of fNIRS in selected areas of pediatric clinical research: epilepsy, communicative and language disorders, and attention-deficit/hyperactivity disorder. We provide a scoping review as a framework to allow the highlighting of specific and general challenges of using fNIRS in pediatric research. We also discuss potential solutions and perspectives on the broader use of fNIRS in the clinical setting. This may be of use to future research, targeting clinical applications of fNIRS in children and adolescents.

fNIRS is sensitive to leg activity in the primary motor cortex after systemic artifact correction

BACKGROUND

functional near-infrared spectroscopy (fNIRS) is an increasingly popular tool to study cortical activity during movement and gait that requires further validation. This study aimed to assess (1) whether fNIRS can detect the difficult-to-measure leg area of the primary motor cortex (M1) and distinguish it from the hand area; and (2) whether fNIRS can differentiate between automatic (i.e., not requiring one's attention) and non-automatic movement processes. Special attention was attributed to systemic artifacts (i.e., changes in blood pressure, heart rate, breathing) which were assessed and corrected by short channels, i.e., fNIRS channels which are mainly sensitive to superficial scalp hemodynamics.

METHODS

Twenty-three seated, healthy participants tapped four fingers on a keyboard or tapped the right foot on four squares on the floor in a specific order given by a 12-digit sequence (e.g., 434141243212). Two different sequences were executed: a beforehand learned (i.e., automatic) version and a newly learned (i.e., non-automatic) version. A 36-channel fNIRS device including 12 short channels covered multiple motor-related cortical areas including M1. The fNIRS data were analyzed with a general linear model (GLM). Correlation between the expected functional hemodynamic responses (i.e. task regressor) and the short channels (i.e. nuisance regressors), necessitated performing a separate short channel regression instead of integrating them in the GLM.

RESULTS

Consistent with the M1 somatotopy, we found significant HbO increases of very large effect size in the lateral M1 channels during finger tapping (Cohen's d = 1.35, p<0.001) and significant HbO increases of moderate effect size in the medial M1 channels during foot tapping (Cohen's d = 0.8, p<0.05). The cortical activity differences between automatic and non-automatic tasks were not significantly different. Importantly, leg movements produced large systemic fluctuations, which were adequately removed by the use of all available short channels.

DISCUSSION

Our results indicate that fNIRS is sensitive to leg activity in M1, though the sensitivity is lower than for finger activity and requires rigorous correction for systemic fluctuations. We furthermore highlight that systemic artifacts may result in an unreliable GLM analysis when short channels show signals that are similar to the expected hemodynamic responses.

Using preregistration as a tool for transparent fNIRS study design

Significance

The expansion of functional near-infrared spectroscopy (fNIRS) methodology and analysis tools gives rise to various design and analytical decisions that researchers have to make. Several recent efforts have developed guidelines for preprocessing, analyzing, and reporting practices. For the planning stage of fNIRS studies, similar guidance is desirable. Study preregistration helps researchers to transparently document study protocols before conducting the study, including materials, methods, and analyses, and thus, others to verify, understand, and reproduce a study. Preregistration can thus serve as a useful tool for transparent, careful, and comprehensive fNIRS study design.

Aim

We aim to create a guide on the design and analysis steps involved in fNIRS studies and to provide a preregistration template specified for fNIRS studies.

Approach

The presented preregistration guide has a strong focus on fNIRS specific requirements, and the associated template provides examples based on continuous-wave (CW) fNIRS studies conducted in humans. These can, however, be extended to other types of fNIRS studies.

Results

On a step-by-step basis, we walk the fNIRS user through key methodological and analysis-related aspects central to a comprehensive fNIRS study design. These include items specific to the design of CW, task-based fNIRS studies, but also sections that are of general importance, including an in-depth elaboration on sample size planning.

Conclusions

Our guide introduces these open science tools to the fNIRS community, providing researchers with an overview of key design aspects and specification recommendations for comprehensive study planning. As such it can be used as a template to preregister fNIRS studies or merely as a tool for transparent fNIRS study design.

Assessing the development of mental fatigue during simulated flights with concurrent EEG-fNIRS measurement

Mental fatigue (MF) can impair pilots' performance and reactions to unforeseen events and is therefore an important concept within aviation. The physiological measurement of MF, especially with EEG and, in recent years, fNIRS, has gained much attention. However, a systematic investigation and comparison of the measurements is seldomly done. We induced MF via time on task during a 90-min simulated flight task and collected concurrent EEG-fNIRS, performance and self-report data from 31 participants. While their subjective MF increased linearly, the participants were able to keep their performance stable over the course of the experiment. EEG data showed an early increase and levelling in parietal alpha power and a slower, but steady increase in frontal theta power. No consistent trend could be observed in the fNIRS data. Thus, more research on fNIRS is needed to understand its possibilities and limits for MF assessment, and a combination with EEG is advisable to compare and validate results. Until then, EEG remains the better choice for continuous MF assessment in cockpit applications because of its high sensitivity to a transition from alert to fatigued, even before performance is impaired.

Optical neuroimaging and neurostimulation in surgical training and assessment: A state-of-the-art review

Introduction

Functional near-infrared spectroscopy (fNIRS) is a non-invasive optical neuroimaging technique used to assess surgeons' brain function. The aim of this narrative review is to outline the effect of expertise, stress, surgical technology, and neurostimulation on surgeons' neural activation patterns, and highlight key progress areas required in surgical neuroergonomics to modulate training and performance.

Methods

A literature search of PubMed and Embase was conducted to identify neuroimaging studies using fNIRS and neurostimulation in surgeons performing simulated tasks.

Results

Novice surgeons exhibit greater haemodynamic responses across the pre-frontal cortex than experts during simple surgical tasks, whilst expert surgical performance is characterized by relative prefrontal attenuation and upregulation of activation foci across other regions such as the supplementary motor area. The association between PFC activation and mental workload follows an inverted-U shaped curve, activation increasing then attenuating past a critical inflection point at which demands outstrip cognitive capacity Neuroimages are sensitive to the impact of laparoscopic and robotic tools on cognitive workload, helping inform the development of training programs which target neural learning curves. FNIRS differs in comparison to current tools to assess proficiency by depicting a cognitive state during surgery, enabling the development of cognitive benchmarks of expertise. Finally, neurostimulation using transcranial direct-current-stimulation may accelerate skill acquisition and enhance technical performance.

Conclusion

FNIRS can inform the development of surgical training programs which modulate stress responses, cognitive learning curves, and motor skill performance. Improved data processing with machine learning offers the possibility of live feedback regarding surgeons' cognitive states during operative procedures.

Stress estimation by the prefrontal cortex asymmetry: Study on fNIRS signals

BACKGROUND

Functional near-infrared spectroscopy (fNIRS) is a non-invasive technique frequently used to measure the brain hemodynamic activity in applications to evaluate affective disorders and stress. Using two wavelengths of light, it is possible to monitor relative changes in the concentrations of oxyhemoglobin and deoxyhemoglobin. Besides, the spatial asymmetry in the prefrontal cortex activity has been correlated with the brain response to stressful situations.

METHODS

We measured prefrontal cortex activity with a NIRS multi-distance device during a baseline period, under stressful conditions (e.g., social stress), and after a recovery phase. We calculated a laterality index for the contaminated brain signal and for the brain signal where we removed the influence of extracerebral hemodynamic activity by using a short channel.

RESULTS

There was a significant right lateralization during stress when using the contaminated signals, consistent with previous investigations, but this significant difference disappeared using the corrected signals. Indeed, exploration of the susceptibility to contamination of the different channels showed non-homogeneous spatial patterns, which would hint at detection of stress from extracerebral activity from the forehead.

LIMITATIONS

There was no recovery phase between the social and the arithmetic stressor, a cumulative effect was not considered.

CONCLUSIONS

Extracerebral hemodynamic activity provided insights into the pertinence of short channel corrections in fNIRS studies dealing with emotions. It is important to consider this issue in clinical applications including modern monitoring systems based on fNIRS technique to assess emotional states in affective disorders.

The identification of interacting brain networks during robot-assisted training with multimodal stimulation

Objective.Robot-assisted rehabilitation training is an effective way to assist rehabilitation therapy. So far, various robotic devices have been developed for automatic training of central nervous system following injury. Multimodal stimulation such as visual and auditory stimulus and even virtual reality technology were usually introduced in these robotic devices to improve the effect of rehabilitation training. This may need to be explained from a neurological perspective, but there are few relevant studies.Approach.In this study, ten participants performed right arm rehabilitation training tasks using an upper limb rehabilitation robotic device. The tasks were completed under four different feedback conditions including multiple combinations of visual and auditory components: auditory feedback; visual feedback; visual and auditory feedback (VAF); non-feedback. The functional near-infrared spectroscopy devices record blood oxygen signals in bilateral motor, visual and auditory areas. Using hemoglobin concentration as an indicator of cortical activation, the effective connectivity of these regions was then calculated through Granger causality.Main results.We found that overall stronger activation and effective connectivity between related brain regions were associated with VAF. When participants completed the training task without VAF, the trends in activation and connectivity were diminished.Significance.This study revealed cerebral cortex activation and interacting networks of brain regions in robot-assisted rehabilitation training with multimodal stimulation, which is expected to provide indicators for further evaluation of the effect of rehabilitation training, and promote further exploration of the interaction network in the brain during a variety of external stimuli, and to explore the best sensory combination.

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.

Hotspots and trends in fNIRS disease research: A bibliometric analysis

Objective

To summarize the general information and hotspots of functional near-infrared spectroscopy (fNIRS)-based clinical disease research over the past 10 years and provide some references for future research.

Methods

The related literature published between 1 January 2011 and 31 January 2022 was retrieved from the Web of Science core database (WoS). Bibliometric visualization analysis of countries/regions, institutions, authors, journals, keywords and references were conducted by using CiteSpace 6.1.R3.

Results

A total of 467 articles were included, and the annual number of articles published over nearly a decade showed an upward trend year-by-year. These articles mainly come from 39 countries/regions and 280 institutions. The representative country and institution were the USA and the University of Tubingen. We identified 266 authors, among which Andreas J Fallgatter and Ann-Christine Ehlis were the influential authors. Neuroimage was the most co-cited journal. The major topics in fNIRS disease research included activation, prefrontal cortex, working memory, cortex, and functional magnetic resonance imaging (fMRI). In recent years, the Frontier topics were executive function, functional connectivity, performance, diagnosis, Alzheimer's disease, children, and adolescents. Based on the burst of co-cited references, gait research has received much attention.

Conclusion

This study conducted a comprehensive, objective, and visual analysis of publications, and revealed the status of relevant studies, hot topics, and trends concerning fNIRS disease research from 2011 to 2022. It is hoped that this work would help researchers to identify new perspectives on potential collaborators, important topics, and research Frontiers.

Revealing the spatiotemporal requirements for accurate subject identification with resting-state functional connectivity: a simultaneous fNIRS-fMRI study

SIGNIFICANCE

Brain fingerprinting refers to identifying participants based on their functional patterns. Despite its success with functional magnetic resonance imaging (fMRI), brain fingerprinting with functional near-infrared spectroscopy (fNIRS) still lacks adequate validation.

AIM

We investigated how fNIRS-specific acquisition features (limited spatial information and nonneural contributions) influence resting-state functional connectivity (rsFC) patterns at the intra-subject level and, therefore, brain fingerprinting.

APPROACH

We performed multiple simultaneous fNIRS and fMRI measurements in 29 healthy participants at rest. Data were preprocessed following the best practices, including the removal of motion artifacts and global physiology. The rsFC maps were extracted with the Pearson correlation coefficient. Brain fingerprinting was tested with pairwise metrics and a simple linear classifier.

RESULTS

Our results show that average classification accuracy with fNIRS ranges from 75% to 98%, depending on the number of runs and brain regions used for classification. Under the right conditions, brain fingerprinting with fNIRS is close to the 99.9% accuracy found with fMRI. Overall, the classification accuracy is more impacted by the number of runs and the spatial coverage than the choice of the classification algorithm.

CONCLUSIONS

This work provides evidence that brain fingerprinting with fNIRS is robust and reliable for extracting unique individual features at the intra-subject level once relevant spatiotemporal constraints are correctly employed.

Cot-side imaging of functional connectivity in the developing brain during sleep using wearable high-density diffuse optical tomography

Studies of cortical function in newborn infants in clinical settings are extremely challenging to undertake with traditional neuroimaging approaches. Partly in response to this challenge, functional near-infrared spectroscopy (fNIRS) has become an increasingly common clinical research tool but has significant limitations including a low spatial resolution and poor depth specificity. Moreover, the bulky optical fibres required in traditional fNIRS approaches present significant mechanical challenges, particularly for the study of vulnerable newborn infants. A new generation of wearable, modular, high-density diffuse optical tomography (HD-DOT) technologies has recently emerged that overcomes many of the limitations of traditional, fibre-based and low-density fNIRS measurements. Driven by the development of this new technology, we have undertaken the first cot-side study of newborn infants using wearable HD-DOT in a clinical setting. We use this technology to study functional brain connectivity (FC) in newborn infants during sleep and assess the effect of neonatal sleep states, active sleep (AS) and quiet sleep (QS), on resting state FC. Our results demonstrate that it is now possible to obtain high-quality functional images of the neonatal brain in the clinical setting with few constraints. Our results also suggest that sleep states differentially affect FC in the neonatal brain, consistent with prior reports.

Dual-task related frontal cerebral blood flow changes in older adults with mild cognitive impairment: A functional diffuse correlation spectroscopy study

Introduction

In a worldwide aging population with a high prevalence of motor and cognitive impairment, it is paramount to improve knowledge about underlying mechanisms of motor and cognitive function and their interplay in the aging processes.

Methods

We measured prefrontal cerebral blood flow (CBF) using functional diffuse correlation spectroscopy during motor and dual-task. We aimed to compare CBF changes among 49 older adults with and without mild cognitive impairment (MCI) during a dual-task paradigm (normal walk, 2- forward count walk, 3-backward count walk, obstacle negotiation, and heel tapping). Participants with MCI walked slower during the normal walk and obstacle negotiation compared to participants with normal cognition (NC), while gait speed during counting conditions was not different between the groups, therefore the dual-task cost was higher for participants with NC. We built a linear mixed effects model with CBF measures from the right and left prefrontal cortex.

Results

MCI (n = 34) showed a higher increase in CBF from the normal walk to the 2-forward count walk (estimate = 0.34, 95% CI [0.02, 0.66], p = 0.03) compared to participants with NC, related to a right- sided activation. Both groups showed a higher CBF during the 3-backward count walk compared to the normal walk, while only among MCI, CFB was higher during the 2-forward count walk.

Discussion

Our findings suggest a differential prefrontal hemodynamic pattern in older adults with MCI compared to their NC counterparts during the dual-task performance, possibly as a response to increasing attentional demand.

Tai Chi practice enables prefrontal cortex bilateral activation and gait performance prioritization during dual-task negotiating obstacle in older adults

BACKGROUND

With aging, the cognitive function of the prefrontal cortex (PFC) declined, postural control weakened, and fall risk increased. As a mind-body exercise, regular Tai Chi practice could improve postural control and effectively prevent falls; however, underlying brain mechanisms remained unclear, which were shed light on by analyzing the effect of Tai Chi on the PFC in older adults by means of functional near-infrared spectroscopy (fNIRS).

METHODS

36 healthy older adults without Tai Chi experience were divided randomly into Tai Chi group and Control group. The experiment was conducted four times per week for 16 weeks; 27 participants remained and completed the experiment. Negotiating obstacle task (NOT) and negotiating obstacle with cognitive task (NOCT) were performed pre- and post-intervention, and Brodmann area 10 (BA10) was detected using fNIRS for hemodynamic response. A three-dimensional motion capture system measured walking speed.

RESULTS

After intervention in the Tai Chi group under NOCT, the HbO2 concentration change value (ΔHbO2) in BA10 was significantly greater (right BA10: p = 0.002, left BA10: p = 0.001), walking speed was significantly faster (p = 0.040), and dual-task cost was significantly lower than pre-intervention (p = 0.047). ΔHbO2 in BA10 under NOCT was negatively correlated with dual-task cost (right BA10: r = -0.443, p = 0.021, left BA10: r = -0.448, p = 0.019). There were strong negative correlations between ΔHbO2 and ΔHbR under NOCT either pre-intervention (left PFC r = -0.841, p < 0.001; right PFC r = -0.795, p < 0.001) or post-intervention (left PFC r = -0.842, p < 0.001; right PFC r = -0.744, p < 0.001).

CONCLUSION

Tai Chi practice might increase the cognitive resources in older adults through the PFC bilateral activation to prioritize gait performance during negotiating obstacles under a dual-task condition.

The Role of Sleep Quality and Physical Activity Level on Gait Speed and Brain Hemodynamics Changes in Young Adults-A Dual-Task Study

Walking requires attentional resources, and the studies using neuroimage techniques have grown to understand the interaction between cortical activity and motor performance. Previous studies reported a decline in gait performance and changes in the prefrontal cortex (PFC) activity during a dual-task performance compared to walking only. Some lifestyle factors, such as sleep and physical activity (PA) levels, can compromise walking performance and brain activity. Nonetheless, the studies are scarce. This study aimed to assess gait speed and hemodynamic response in the PFC during a cognitive dual-task (cog-DT) compared to walking only, and to analyze the correlation between PA and sleep quality (SQ) with gait performance and hemodynamic response in the PFC during a single task (ST) and cog-DT performance in young adults. A total of 18 healthy young adults (mean age ± SD = 24.11 ± 4.11 years) participated in this study. They performed a single motor task (mot-ST)—normal walking—and a cog-DT—walking while performing a cognitive task on a smartphone. Gait speed was collected using a motion capture system coupled with two force plates. The hemoglobin differences (Hb-diff), oxyhemoglobin ([oxy-Hb]) and deoxyhemoglobin ([deoxy-Hb]) concentrations in the PFC were obtained using functional near-infrared spectroscopy. The SQ and PA were assessed through the Pittsburg Sleep Quality Index and International Physical Activity Questionnaire-Short Form questionnaires, respectively. The results show a decrease in gait speed (p < 0.05), a decrease in [deoxy-Hb] (p < 0.05), and an increase in Hb-diff (p < 0.05) and [oxy-Hb] (p > 0.05) in the prefrontal cortex during the cog-DT compared to the single task. A positive correlation between SQ and Hb-diff during the cog-DT performance was found. In conclusion, the PFC’s hemodynamic response during the cog-DT suggests that young adults prioritize cognitive tasks over motor performance. SQ only correlates with the Hb-diff during the cog-DT, showing that poor sleep quality was associated with increased Hb-diff in the PFC. The gait performance and hemodynamic response do not correlate with physical activity level.

Distinct neural couplings to shared goal and action coordination in joint action: evidence based on fNIRS hyperscanning

Joint action is central to human nature, enabling individuals to coordinate in time and space to achieve a joint outcome. Such interaction typically involves two key elements: shared goal and action coordination. Yet, the substrates entrained to these two components in joint action remained unclear. In the current study, dyads performed two tasks involving both sharing goal and action coordination, i.e. complementary joint action and imitative joint action, a task only involving shared goal and a task only involving action coordination, while their brain activities were recorded by the functional near-infrared spectroscopy hyperscanning technique. The results showed that both complementary and imitative joint action (i.e. involving shared goal and action coordination) elicited better behavioral performance than the task only involving shared goal/action coordination. We observed that the interbrain synchronization (IBS) at the right inferior frontal cortex (IFC) entrained more to shared goal, while left-IFC IBS entrained more to action coordination. We also observed that the right-IFC IBS was greater during completing a complementary action than an imitative action. Our results suggest that IFC plays an important role in joint action, with distinct lateralization for the sub-components of joint action.

Functional quantification of oral motor cortex at rest and during tasks using activity phase ratio: A zero-setting vector functional near-infrared spectroscopy study

Oral frailty associated with oral hypokinesia may cause dementia. Functional near-infrared spectroscopy (fNIRS) can be used while the participants are in seating position with few restrictions. Thus, it is useful for assessing brain function, particularly oral motor activity. However, methods for identifying oral motor cortex (OMC) activation via the scalp have not been established. The current study aimed to detect OMC activation, an indicator of activity phase ratio (APR), which reflects increased oxygen consumption (0 &lt; [deoxyhemoglobin (ΔDeoxyHb) or 0 &lt; {[ΔDeoxyHb- oxyhemoglobin (ΔOxyHb)/√2]}, via fNIRS to accurately identify local brain activity. The APR, calculated via zero-set vector analysis, is a novel index for quantifying brain function both temporally and spatially at rest and during tasks. In total, 14 healthy participants performed bite tasks for 3 s per side for 10 times while in the sitting position. Then, time-series data on concentration changes in ΔOxyHb and ΔDeoxyHb were obtained via fNIRS. The anatomical location of the OMC was determined using a pooled data set of three-dimensional magnetic resonance images collected in advance from 40 healthy adults. In the zero-set vector analysis, the average change in ΔOxyHb and ΔDeoxyHb concentrations was utilized to calculate the APR percentage in 140 trials. The significant regions (z-score of ≥2.0) of the APR and ΔOxyHb in the task were compared. During the bite task, the APR significantly increased within the estimated OMC region (56–84 mm lateral to Cz and 4–20 mm anterior to Cz) in both the right and left hemispheres. By contrast, the ΔOxyHb concentrations increased on the bite side alone beyond the OMC region. The mean APR at rest for 2 s before the task showed 59.5%–62.2% in the left and right OMCs. The average APR for 3 s during the task showed 75.3% for the left OMC and 75.7% for the right OMC during the left bite task, and 65.9% for the left OMC and 80.9% for the right OMC during the right bite task. Interestingly, the average increase in APR for the left and right OMCs for the left bite task and the right bite task was 13.9% and 13.7%, respectively, showing almost a close match. The time course of the APR was more limited to the bite task segment than that of ΔOxyHb or ΔDexyHb concentration, and it increased in the OMC. Hence, the APR can quantitatively monitor both the resting and active states of the OMC in the left and right hemispheres. Using the zero-set vector-based fNIRS, the APR can be a valid indicator of oral motor function and bite force.