Temporal Derivative Distribution Repair (TDDR): A motion correction method for fNIRS

Brain plasticity and adolescent HIV: A randomised controlled trial protocol investigating behavioural and hemodynamic responses in attention cognitive rehabilitation therapy

Despite advances in antiretroviral pharmacology, neuroHIV in the central nervous system (CNS), causes neuronal dysregulation, which is associated with compromised neurocognition. Non-pharmaceutical interventions such as HIV cognitive rehabilitation training (HIV-CRT), have shown potential to partially reverse cognitive deficits, sequent HIV neuroinvasion. Nonetheless, no studies exist pairing cognitive outcomes with objective neuroimaging biomarkers in adolescent HIV-CRT. This longitudinal pre-post-quasi-experimental protocol examined cognitive outcomes, paired with optimal neuroimaging outcomes following customised attention training in adolescent HIV. Twenty-six adolescents living with HIV were randomly assigned to either the treatment group, which received attention CRT using ACTIVATE™, (n = 13), or to the treatment as usual group (n = 13). Cognitive outcomes were examined using the NEPSY-II, and BRIEF; whilst neuroimaging outcomes were determined by changes in oxygenated haemoglobin (HbO), as determined by functional near-infrared spectrometry (fNIRS). Functional connectivity fNIRS measures were evaluated using seed-based correlation analysis, located in the central executive network (CEN). This study serves to guide the development and identification of objective biomarkers for adolescent neuroHIV, sequent CRT amongst children living with HIV in Sub-Saharan Africa.

Discriminative analysis of schizophrenia and major depressive disorder using fNIRS

BACKGROUND

Research into the shared and distinct brain dysfunctions in patients with schizophrenia (SCZ) and major depressive disorder (MDD) has been increasing. However, few studies have explored the application of functional near-infrared spectroscopy (fNIRS) in investigating brain dysfunction and enhancing diagnostic methodologies in these two conditions.

METHODS

A general linear model was used for analysis of brain activation following task-state fNIRS from 131 patients with SCZ, 132 patients with MDD and 130 healthy controls (HCs). Subsequently, seventy-seven time-frequency analysis methods were used to construct new features of fNIRS, followed by the implementation of five machine learning algorithms to develop a differential diagnosis model for the three groups. This model was evaluated by comparing it to both a diagnostic model relying on traditional fNIRS features and assessments made by two psychiatrists.

RESULTS

Brain activation analysis revealed significantly lower activation in Broca's area, the dorsolateral prefrontal cortex, and the middle temporal gyrus for both the SCZ and MDD groups compared to HCs. Additionally, the SCZ group exhibited notably lower activation in the superior temporal gyrus and the subcentral gyrus compared to the MDD group. When distinguishing among the three groups using independent validation datasets, the models utilizing new fNIRS features achieved an accuracy of 85.90 % (AUC = 0.95). In contrast, models based on traditional fNIRS features reached an accuracy of 52.56 % (AUC = 0.66). The accuracies of the two psychiatrists were 42.00 % (AUC = 0.60) and 38.00 % (AUC = 0.50), respectively.

CONCLUSION

This investigation brings to light the shared and distinct neurobiological abnormalities present in SCZ and MDD, offering potential enhancements for extant diagnostic systems.

Investigating the relationship between CSAT scores and prefrontal fNIRS signals during cognitive tasks using a quantum annealing algorithm

Academic achievement is a critical measure of intellectual ability, prompting extensive research into cognitive tasks as potential predictors. Neuroimaging technologies, such as functional near-infrared spectroscopy (fNIRS), offer insights into brain hemodynamics, allowing understanding of the link between cognitive performance and academic achievement. Herein, we explored the association between cognitive tasks and academic achievement by analyzing prefrontal fNIRS signals. A novel quantum annealer (QA) feature selection algorithm was applied to fNIRS data to identify cognitive tasks correlated with CSAT scores. Twelve features (signal mean, median, variance, peak, number of peaks, sum of peaks, range, minimum, kurtosis, skewness, standard deviation, and root mean square) were extracted from fNIRS signals at two time windows (10- and 60-s) to compare results from various feature variable conditions. The feature selection results from the QA-based and XGBoost regressor algorithms were compared to validate the former's performance. In a two-step validation process using multiple linear regression models, model fitness (adjusted R2) and model prediction error (RMSE) values were calculated. The quantum annealer demonstrated comparable performance to classical machine learning models, and specific cognitive tasks, including verbal fluency, recognition, and the Corsi block tapping task, were correlated with academic achievement. Group analyses revealed stronger associations between Tower of London and N-back tasks with higher CSAT scores. Quantum annealing algorithms have significant potential in feature selection using fNIRS data, and represents a novel research approach. Future studies should explore predictors of academic achievement and cognitive ability.

Children's oppositional defiant disorder symptoms and neural synchrony in mother-child interactions: An fNIRS study

Interpersonal neural synchrony (INS) between mothers and children responds to the temporal similarity of brain signals in joint behavior between dyadic partners and is considered an important neural indicator of the formation of adaptive social interaction bonds. Parent-child interactions are particularly important for the development and maintenance of oppositional defiant disorder (ODD) in children, but the underlying neurocognitive mechanisms are unknown. Therefore, in the current study we measured INS between mothers and children in interactions by using simultaneous functional Near-infrared Spectroscopy (fNIRS), and explored its association with ODD symptoms in children. Seventy-two mother-child dyads were recruited to participate in the study, including 35 children with ODD and 37 healthy children to be used as a control. Each mother-child dyad was measured for neural activity in frontal, parietal, and temporal lobe regions while completing free-play as well as positive, and negative topic discussion tasks. We used Phase-locked value to calculate the synchrony strength and then used the K-means algorithm and k-space based alignment tests to confirm the specific patterns of parent-child synchrony in different brain areas. The results showed that, in free-play (right MFG and bilateral SFG), positive (left TPJ and bilateral SFGdor), and negative (bilateral SFGmed, right ANG, and left MFG) topic discussions, the mother-child pairs showed different patterns of INS. These specific INS patterns were significantly lower in the ODD group compared to the control group and were negatively associated with ODD symptoms in children. Network analyses showed that these INS patterns were connected to different nodes in the ODD symptom network. Our findings suggest that ODD mother-child dyads exhibit lower neural synchrony across a wide range of parent-child interactions. Neural synchrony in the context of interpersonal interactions provides new insights into understanding the neural mechanisms of ODD and can be used as an indicator of neural and socio-environmental factors in the network of psychological disorder symptoms.

Examining the relationship between functional connectivity and broader autistic traits in non-autistic children

In the current study, we used functional near-infrared spectroscopy (fNIRS) to examine functional connectivity (FC) in relation to measures of cognitive flexibility and autistic features in non-autistic children. Previous research suggests that disruptions in FC between brain regions may underlie the cognitive and behavioral traits of autism. Moreover, research has identified a broader autistic phenotype (BAP), which refers to a set of behavioral traits that fall along a continuum of behaviors typical for autism but which do not cross a clinically relevant threshold. Thus, by examining FC in relation to the BAP in non-autistic children, we can better understand the spectrum of behaviors related to this condition and their neural basis. Results indicated age-related differences in performance across three measures of cognitive flexibility, as expected given the rapid development of this skill within this time period. Additionally, results showed that across the flexibility tasks, measures of autistic traits were associated with weaker FC along the executive control network, though task performance was not associated with FC. These results suggest that behavioral scores may be less sensitive than neural measures to autistic traits. Further, these results corroborate the use of broader autistic traits and the BAP to better understand disruptions to neural function associated with autism.

Real-time motion artifact suppression using convolution neural networks with penalty in fNIRS

Introduction

Removing motion artifacts (MAs) from functional near-infrared spectroscopy (fNIRS) signals is crucial in practical applications, but a standard procedure is not available yet. Artificial neural networks have found applications in diverse domains, such as voice and image processing, while their utility in signal processing remains limited.

Method

In this work, we introduce an innovative neural network-based approach for online fNIRS signals processing, tailored to individual subjects and requiring minimal prior experimental data. Specifically, this approach employs one-dimensional convolutional neural networks with a penalty network (1DCNNwP), incorporating a moving window and an input data augmentation procedure. In the training process, the neural network is fed with simulated data derived from the balloon model for simulation validation and semi-simulated data for experimental validation, respectively.

Results

Visual validation underscores 1DCNNwP's capacity to effectively suppress MAs. Quantitative analysis reveals a remarkable improvement in signal-to-noise ratio by over 11.08 dB, surpassing the existing methods, including the spline-interpolation, wavelet-based, temporal derivative distribution repair with a 1 s moving window, and spline Savitzky-Goaly methods. Contrast-to-noise ratio (CNR) analysis further demonstrated 1DCNNwP's ability to restore or enhance CNRs for motionless signals. In the experiments of eight subjects, our method significantly outperformed the other approaches (except offline TDDR, t < -3.82, p < 0.01). With an average signal processing time of 0.53 ms per sample, 1DCNNwP exhibited strong potential for real-time fNIRS data processing.

Discussion

This novel univariate approach for fNIRS signal processing presents a promising avenue that requires minimal prior experimental data and adapts seamlessly to varying experimental paradigms.

Adaptive Changes in Neurovascular Properties With Binocular Accommodation Functions in Myopic Participants by 3D Visual Training: An EEG and fNIRS Study

Although three-dimensional visual training (3DVT) has been used for myopia intervention, its neural mechanisms remain largely unknown. In this study, visual function was examined before and after 3DVT, while resting-state EEG-fNIRS signals were recorded from 38 myopic participants. A graph theoretical analysis was applied to compute the neurovascular properties, including static brain networks (SBNs), dynamic brain networks (DBNs), and dynamic neurovascular coupling (DNC). Correlations between the changes in neurovascular properties and the changes in visual functions were calculated. After 3DVT, the local efficiency and node efficiency in the frontal lobes increased in the SBNs constructed from EEG δ -band; the global efficiency and node efficiency in the frontal-parietal lobes decreased in the DBNs variability constructed from EEG δ -band. For the DNC constructed with EEG α -band and oxyhemoglobin (HbO), the local efficiency decreased, for EEG α -band and deoxyhemoglobin (HbR), the node efficiency in the frontal-occipital lobes decreased. For the SBNs constructed from HbO, the functional connectivity (FC) between the frontal-occipital lobes increased. The DNC constructed between the FC of the frontal-parietal lobes from EEG β -band and the FC of the frontal-occipital lobes from HbO increased, and between the FC of the frontal-occipital lobes from EEG β -band and the FC of the inter-frontal lobes from HbR increased. The neurovascular properties were significantly correlated with the amplitude of accommodation and accommodative facility. The result indicated the positive effects of 3DVT on myopic participants, including improved efficiency of brain networks, increased FC of SBNs and DNC, and enhanced binocular accommodation functions.

Altered functional connectivity subserving expressed emotion environments in schizophrenia: An fNIRS study

Living in high-expressed emotion (EE) environments, characterized by critical, hostile, or over-involved family attitudes, has been linked to increased relapse rates among individuals with schizophrenia (SZ). In our previous work (Wang et al., 2023), we conducted the first feasibility study of using functional near-infrared spectroscopy (fNIRS) with our developed EE stimuli to examine cortical hemodynamics in SZ. To better understand the neural mechanisms underlying EE environmental factors in SZ, we extended our investigation by employing functional connectivity (FC) analysis with a graph theory approach to fNIRS signals. Relative to healthy controls (N=40), individuals with SZ (N=37) exhibited altered connectivity across the medial prefrontal cortex (mPFC), left ventrolateral prefrontal cortex (vlPFC), and left superior temporal gyrus (STG) while exposed to EE environments. Notably, while individuals with SZ were exposed to high-EE environments, (i) reduced connectivity was observed in these brain regions and (ii) the left vlPFC-STG coupling was found to be associated with the negative symptom severity. Taken together, our FC findings suggest individuals with SZ experience a more extensive disruption in neural functioning and coordination, particularly indicating an increased susceptibility to high-EE environments. This further supports the potential utility of integrating fNIRS with the created EE stimuli for assessing EE environmental influences, paving the way for more targeted therapeutic interventions.

Reliability of brain metrics derived from a Time-Domain Functional Near-Infrared Spectroscopy System

With the growing interest in establishing brain-based biomarkers for precision medicine, there is a need for noninvasive, scalable neuroimaging devices that yield valid and reliable metrics. Kernel's second-generation Flow2 Time-Domain Functional Near-Infrared Spectroscopy (TD-fNIRS) system meets the requirements of noninvasive and scalable neuroimaging, and uses a validated modality to measure brain function. In this work, we investigate the test-retest reliability (TRR) of a set of metrics derived from the Flow2 recordings. We adopted a repeated-measures design with 49 healthy participants, and quantified TRR over multiple time points and different headsets-in different experimental conditions including a resting state, a sensory, and a cognitive task. Results demonstrated high reliability in resting state features including hemoglobin concentrations, head tissue light attenuation, amplitude of low frequency fluctuations, and functional connectivity. Additionally, passive auditory and Go/No-Go inhibitory control tasks each exhibited similar activation patterns across days. Notably, areas with the highest reliability were in auditory regions during the auditory task, and right prefrontal regions during the Go/No-Go task, consistent with prior literature. This study underscores the reliability of Flow2-derived metrics, supporting its potential to actualize the vision of using brain-based biomarkers for diagnosis, treatment selection and treatment monitoring of neuropsychiatric and neurocognitive disorders.

The Time Course of Changes in Prefrontal Cortex Activity During Walking in People With Parkinson's Disease

BACKGROUND

Walking abnormalities in people with Parkinson's disease (PD) are characterized by a shift in locomotor control from healthy automaticity to compensatory, executive control, mainly located in the prefrontal cortex (PFC). Although PFC activity during walking increases in people with PD, the time course of PFC activity during walking and its relationship to clinical or gait characteristics is unknown.

OBJECTIVE

To identify the time course of PFC activity during walking in people with PD. To investigate whether clinical or gait variables would explain the PFC activity changes.

METHODS

Thirty-eight people with PD tested OFF medication wore a portable, functional near-infrared spectroscopy (fNIRS) system to record relative PFC activity while walking. Wearable inertial sensors recorded spatiotemporal gait characteristics. Based on the PFC activity (fNIRS) in the late phase of the walking task (final 40 seconds), compared to the early phase (initial 40 seconds), participants were separated into 2 groups: reduced or sustained PFC activity.

RESULTS

People with PD who reduced PFC activity during walking had less impaired gait (eg, faster gait speed) than those who had a sustained increase in PFC activity (P < .05). Cognitive set-shifting ability explained 18% of the PFC activation in the group with a sustained increase in PFC activity (P = .033).

CONCLUSIONS

The time course of reduction in PFC activity corresponds to less impaired gait performance in people with PD, while a sustained increase in PFC activity is related to worse cognitive flexibility. Reduction in PFC activity while walking may indicate a less impaired, automatic control of walking.

Hyperactivity in ADHD: Friend or Foe?

BACKGROUND

Hyperactivity may play a functional role in upregulating prefrontal cortical hypoarousal and executive functioning in ADHD. This study investigated the neurocognitive impact of movement during executive functioning on children with ADHD.

METHODS

Twenty-four children with and without ADHD completed a Stroop task and self-efficacy ratings while remaining stationary (Stationary condition) and while desk cycling (Movement condition). Simultaneous functional near-infrared spectroscopy (fNIRS) recorded oxygenated and deoxygenated changes in hemoglobin within the left dorsolateral prefrontal cortex (DLPFC).

RESULTS

Among children with ADHD, the Movement condition produced superior Stroop reaction time compared to the Stationary condition (p = 0.046, d = 1.00). Self-efficacy improved in the Movement condition (p = 0.033, d = 0.41), whereas it did not in the Stationary condition (p = 0.323). Seventy-eight percent of participants showed greater oxygenation in the left DLPFC during the Movement condition vs. the Stationary condition. Among children without ADHD, there were no differences in Stroop or self-efficacy outcomes between Stationary and Movement conditions (ps > 0.085, ts < 1.45); 60% of participants showed greater oxygenation in the left DLPFC during the Movement vs. the Stationary condition.

CONCLUSIONS

This work provides supportive evidence that hyperactivity in ADHD may be a compensatory mechanism to upregulate PFC hypoarousal to support executive functioning and self-efficacy.

Resting-State Functional Connectivity Predicts Cochlear-Implant Speech Outcomes

OBJECTIVES

Cochlear implants (CIs) have revolutionized hearing restoration for individuals with severe or profound hearing loss. However, a substantial and unexplained variability persists in CI outcomes, even when considering subject-specific factors such as age and the duration of deafness. In a pioneering study, we use resting-state functional near-infrared spectroscopy to predict speech-understanding outcomes before and after CI implantation. Our hypothesis centers on resting-state functional connectivity (FC) reflecting brain plasticity post-hearing loss and implantation, specifically targeting the average clustering coefficient in resting FC networks to capture variation among CI users.

DESIGN

Twenty-three CI candidates participated in this study. Resting-state functional near-infrared spectroscopy data were collected preimplantation and at 1 month, 3 months, and 1 year postimplantation. Speech understanding performance was assessed using consonant-nucleus-consonant words in quiet and Bamford-Kowal-Bench sentences in noise 1-year postimplantation. Resting-state FC networks were constructed using regularized partial correlation, and the average clustering coefficient was measured in the signed weighted networks as a predictive measure for implantation outcomes.

RESULTS

Our findings demonstrate a significant correlation between the average clustering coefficient in resting-state functional networks and speech understanding outcomes, both pre- and postimplantation.

CONCLUSIONS

This approach uses an easily deployable resting-state functional brain imaging metric to predict speech-understanding outcomes in implant recipients. The results indicate that the average clustering coefficient, both pre- and postimplantation, correlates with speech understanding outcomes.

Structural and functional abnormalities across clinical stages of psychosis: A multimodal neuroimaging investigation

BACKGROUND

Structural and functional neurobiological abnormalities have been observed in schizophrenia. Previous studies have concentrated on specific illness stages, obscuring relationships between functional/structural changes and disorder progression. The present study aimed to quantify structural and functional abnormalities across different clinical stages using functional near-infrared spectroscopy (fNIRS) and structural magnetic resonance imaging (sMRI).

METHODS

Fifty-four participants with first-episode schizophrenia (FES), 120 with clinically high risk of psychosis (CHR), and 111 healthy controls (HCs) underwent functional near-infrared spectroscopy (fNIRS) to measure oxyhemoglobin (Oxy-Hb) during the verbal fluency task. Among them, 28FES, 64CHR and 55HC also finished sMRI. Oxy-Hb and gray matter volume (GMV) were compared among the three groups while controlling for covariates, including age, sex, years of education, and task performance. Mediation analysis was utilized to determine the mediating effect of GMV on Oxy-Hb and cognition.

RESULTS

Compared with the HC group, CHR and FES groups showed significantly reduced brain activity. However, there were no significant differences between the FES and CHR. Pronounced GMV increase in the right frontal pole area (F = 4.234, p = 0.016) was identified in the CHR and FES groups. Mediation analysis showed a significant mediation effect of the right frontal pole GMV between Channel 31 Oxy-Hb and processing speed (z = 2.105, p = 0.035) and attention/vigilance (z = 1.992, p = 0.046).

CONCLUSIONS

Brain activation and anatomical deficits were observed in different brain regions, suggesting that anatomical and functional abnormalities are dissociated in the early stages of psychosis. The relationship between neural activity and anatomy may reflect a specific pathophysiology related to cognitive deterioration in schizophrenia.

Lateralization of cortical activity, networks, and hemodynamic lag after stroke: A resting-state fNIRS study

Focal damage due to stroke causes widespread abnormal changes in brain function and hemispheric asymmetry. In this study, functional near-infrared spectroscopy (fNIRS) was used to collect resting-state hemoglobin data from 85 patients with subacute stroke and 26 healthy controls, to comparatively analyze the characteristics of lateralization after stroke in terms of cortical activity, functional networks, and hemodynamic lags. Higher intensity of motor cortical activity, lower hemispheric autonomy, and more abnormal hemodynamic leads or lags were found in the affected hemisphere. Lateralization metrics of the three aspects were all associated with the Fugl-Meyer score. The results of this study prove that three lateralization metrics may provide clinical reference for stroke rehabilitation. Meanwhile, the present study piloted the use of resting-state fNIRS for analyzing hemodynamic lag, demonstrating the potential of fNIRS to assess hemodynamic abnormalities in addition to the study of cortical neurological function after stroke.

Differential effects of hypnotherapy and cognitive behavioral therapy on the default mode network of depressed patients

Hypnosis has been applied in healing procedures since the earliest of recorded history and today it is implemented in a wholesome concept Hypnotherapy (HT1). On a neurophysiological level, hypnosis has been associated with parts of the Default Mode Network (DMN2), but its effects on this network when induced in a treatment setting of a widespread disorder, namely depression, have never been investigated. Depression is associated with abnormal functional connectivity (FC3) of the DMN. Cognitive Behavioral Therapy (CBT4) has proven itself to be an effective treatment for depression; effects of CBT on DMN-related regions are heterogeneous. In the past years, HT was found to be a promising alternative or helpful adjunction. Yet, its underlying mechanisms remain to be unclear. In this original study 75 depressed patients receiving either CBT or HT were included and measured during resting-state before and after therapy with functional near-infrared-spectroscopy (fNIRS5). On symptom level, results show a significant reduction in both groups. On a neurophysiological level, first exploratory analyses hint toward treatment effects in two components of the DMN. However, these effects do not withstand correction for multiple testing. Still, our study is a first stepstone in the investigation of neural mechanisms of HT and offers first ideas about possible implications.

A Within-Subject Multimodal NIRS-EEG Classifier for Infant Data

Functional Near Infrared Spectroscopy (fNIRS) and Electroencephalography (EEG) are commonly employed neuroimaging methods in developmental neuroscience. Since they offer complementary strengths and their simultaneous recording is relatively easy, combining them is highly desirable. However, to date, very few infant studies have been conducted with NIRS-EEG, partly because analyzing and interpreting multimodal data is challenging. In this work, we propose a framework to carry out a multivariate pattern analysis that uses an NIRS-EEG feature matrix, obtained by selecting EEG trials presented within larger NIRS blocks, and combining the corresponding features. Importantly, this classifier is intended to be sensitive enough to apply to individual-level, and not group-level data. We tested the classifier on NIRS-EEG data acquired from five newborn infants who were listening to human speech and monkey vocalizations. We evaluated how accurately the model classified stimuli when applied to EEG data alone, NIRS data alone, or combined NIRS-EEG data. For three out of five infants, the classifier achieved high and statistically significant accuracy when using features from the NIRS data alone, but even higher accuracy when using combined EEG and NIRS data, particularly from both hemoglobin components. For the other two infants, accuracies were lower overall, but for one of them the highest accuracy was still achieved when using combined EEG and NIRS data with both hemoglobin components. We discuss how classification based on joint NIRS-EEG data could be modified to fit the needs of different experimental paradigms and needs.

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

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

Lights on music cognition: A systematic and critical review of fNIRS applications and future perspectives

Research investigating the neural processes related to music perception and production constitutes a well-established field within the cognitive neurosciences. While most neuroimaging tools have limitations in studying the complexity of musical experiences, functional Near-Infrared Spectroscopy (fNIRS) represents a promising, relatively new tool for studying music processes in both laboratory and ecological settings, which is also suitable for both typical and pathological populations across development. Here we systematically review fNIRS studies on music cognition, highlighting prospects and potentialities. We also include an overview of fNIRS basic theory, together with a brief comparison to characteristics of other neuroimaging tools. Fifty-nine studies meeting inclusion criteria (i.e., using fNIRS with music as the primary stimulus) are presented across five thematic sections. Critical discussion of methodology leads us to propose guidelines of good practices aiming for robust signal analyses and reproducibility. A continuously updated world map is proposed, including basic information from studies meeting the inclusion criteria. It provides an organized, accessible, and updatable reference database, which could serve as a catalyst for future collaborations within the community. In conclusion, fNIRS shows potential for investigating cognitive processes in music, particularly in ecological contexts and with special populations, aligning with current research priorities in music cognition.

Investigation of hemispheric asymmetry in Alzheimer's disease patients during resting state revealed BY fNIRS

Alzheimer's disease (AD) is characterized by the gradual deterioration of brain structures and changes in hemispheric asymmetry. Meanwhile, healthy aging is associated with a decrease in functional hemispheric asymmetry. In this study, functional connectivity analysis was used to compare the functional hemispheric asymmetry in eyes-open resting-state fNIRS data of 16 healthy elderly controls (mean age: 60.4 years, MMSE (Mini-Mental State Examination): 27.3 ± 2.52) and 14 Alzheimer's patients (mean age: 73.8 years, MMSE: 22 ± 4.32). Increased interhemispheric functional connectivity was found in the premotor cortex, supplementary motor cortex, primary motor cortex, inferior parietal cortex, primary somatosensory cortex, and supramarginal gyrus in the control group compared to the AD group. The study revealed that the control group had stronger interhemispheric connectivity, leading to a more significant decrease in hemispheric asymmetry than the AD group. The results show that there is a difference in interhemispheric functional connections at rest between the Alzheimer's group and the control group, suggesting that functional hemispheric asymmetry continues in Alzheimer's patients.

A brief real-time fNIRS-informed neurofeedback training of the prefrontal cortex changes brain activity and connectivity during subsequent working memory challenge

Working memory (WM) represents a building-block of higher cognitive functions and a wide range of mental disorders are associated with WM impairments. Initial studies have shown that several sessions of functional near-infrared spectroscopy (fNIRS) informed real-time neurofeedback (NF) allow healthy individuals to volitionally increase activity in the dorsolateral prefrontal cortex (DLPFC), a region critically involved in WM. For the translation to therapeutic or neuroenhancement applications, however, it is critical to assess whether fNIRS-NF success transfers into neural and behavioral WM enhancement in the absence of feedback. We therefore combined single-session fNIRS-NF of the left DLPFC with a randomized sham-controlled design (N = 62 participants) and a subsequent WM challenge with concomitant functional MRI. Over four runs of fNIRS-NF, the left DLPFC NF training group demonstrated enhanced neural activity in this region, reflecting successful acquisition of neural self-regulation. During the subsequent WM challenge, we observed no evidence for performance differences between the training and the sham group. Importantly, however, examination of the fMRI data revealed that - compared to the sham group - the training group exhibited significantly increased regional activity in the bilateral DLPFC and decreased left DLPFC - left anterior insula functional connectivity during the WM challenge. Exploratory analyses revealed a negative association between DLPFC activity and WM reaction times in the NF group. Together, these findings indicate that healthy individuals can learn to volitionally increase left DLPFC activity in a single training session and that the training success translates into WM-related neural activation and connectivity changes in the absence of feedback. This renders fNIRS-NF as a promising and scalable WM intervention approach that could be applied to various mental disorders.

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.

Cerebral hemodynamics underlying ankle force sense modulated by high-definition transcranial direct current stimulation

This study aimed to investigate the effects of high-definition transcranial direct current stimulation on ankle force sense and underlying cerebral hemodynamics. Sixteen healthy adults (8 males and 8 females) were recruited in the study. Each participant received either real or sham high-definition transcranial direct current stimulation interventions in a randomly assigned order on 2 visits. An isokinetic dynamometer was used to assess the force sense of the dominant ankle; while the functional near-infrared spectroscopy was employed to monitor the hemodynamics of the sensorimotor cortex. Two-way analyses of variance with repeated measures and Pearson correlation analyses were performed. The results showed that the absolute error and root mean square error of ankle force sense dropped more after real stimulation than after sham stimulation (dropped by 23.4% vs. 14.9% for absolute error, and 20.0% vs. 10.2% for root mean square error). The supplementary motor area activation significantly increased after real high-definition transcranial direct current stimulation. The decrease in interhemispheric functional connectivity within the Brodmann's areas 6 was significantly correlated with ankle force sense improvement after real high-definition transcranial direct current stimulation. In conclusion, high-definition transcranial direct current stimulation can be used as a potential intervention for improving ankle force sense. Changes in cerebral hemodynamics could be one of the explanations for the energetic effect of high-definition transcranial direct current stimulation.

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

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

A feasibility study investigating cortical hemodynamic changes during infinity walk with fNIRS

This study seeks to explore the correlation between cortical activation and the Infinity Walk pattern, examining how the influence of foot overpronation and footwear may impact motor control. Functional near-infrared spectroscopy (fNIRS), a portable and user-friendly neuroimaging technique, was used to measure hemodynamical changes in six individuals with non-critical pronation degrees. Participants perform the Infinity Walk under various footwear conditions while wearing an fNIRS portable imaging device. Results indicate a consistent hemodynamic pattern in both hemispheres during the Infinity Walk, with no significant differences observed across subjects and footwear conditions in the prefrontal cortex (PFC), pre-motor area, the supplementary motor cortex (PMA & SMC), the primary motor cortex (PMC), and Wernicke's area (WA). The impact of pronation and footwear on motor control remains inconclusive due to inconsistent hemodynamic patterns. Notably, the activation patterns in Broca's area (BA) and the temporal gyrus (TG) differ significantly from other brain regions. The balanced hemodynamic responses in the bilateral hemispheres may be attributed to the Infinity Walk's inherent walking pattern. These findings indicate a need for further investigation into the Infinity Walk to examine the similarities and distinctions in activation patterns within specific brain regions. Additionally, the impact of pronation necessitates more substantial experimental research to establish a correlation between pronation and cortical hemodynamics.

Effects of age on the interactions of attentional and emotional processes: a prefrontal fNIRS study

The aging of attentional and emotional functions has been extensively studied but relatively independently. Therefore, the relationships between aging and the interactions of attentional and emotional processes remain elusive. This study aimed to determine how age affected the interactions between attentional and emotional processes during adulthood. One-hundred forty adults aged 18-79 performed the emotional variant of the Attention Network Test, which probed alerting, orienting, and executive control in the presence and absence of threatening faces. During this task, contexts with varying levels of task preparatory processes were created to modulate the effect of threatening faces on attention, and functional near-infrared spectroscopy (fNIRS) was used to examine the neural underpinnings of the behavioural effects. The behavioural results showed that aging was associated with a significant decline in alerting efficiency, and there was a statistical trend for age-related deficits in executive control. Despite these age differences, age did not significantly moderate the interactions among attentional networks or between attention and emotion. Additionally, the fNIRS results showed that decreased frontal cortex functioning might underlie the age-related decline in executive control. Therefore, while aging has varying effects on different attentional networks, the interactions of attentional and emotional processes remain relatively unaffected by age.

FNIRS based study of brain network characteristics in children with cerebral palsy during bilateral lower limb movement

BACKGROUND

Motor dysfunctions in children with cerebral palsy (CP) are caused by nonprogressive brain damage. Understanding the functional characteristics of the brain is important for rehabilitation.

PURPOSE

This paper aimed to study the brain networks of children with CP during bilateral lower limb movement using functional near-infrared spectroscopy (fNIRS) and to explore effective fNIRS indices for reflecting functional brain activity.

METHODS

Using fNIRS, cerebral oxygenation signals in the bilateral prefrontal cortex (LPFC/RPFC) and motor cortex (LMC/RMC) were recorded from fifteen children with spastic CP and seventeen children with typical development (CTDs) in the resting state and during bilateral lower limb movement. Functional connectivity matrices based on phase-locking values (PLVs) were calculated using Hilbert transformation, and binary networks were constructed at different sparsity levels. Network metrics such as the clustering coefficient, global efficiency, local efficiency, and transitivity were calculated. Furthermore, the time-varying curves of network metrics during movement were obtained by dividing the time window and using sparse inverse covariance matrices. Finally, conditional Granger causality (GC) was used to explore the causal relationships between different brain regions.

RESULTS

Compared to CTDs, the connectivity between RMC-RPFC (p = 0.017) and RMC-LMC (p = 0.002) in the brain network was decreased in children with CP, and the clustering coefficient (p = 0.003), global efficiency (p = 0.034), local efficiency (p = 0.015), and transitivity (p = 0.009) were significantly lower. The standard deviation of the changes in global efficiency of children with CP during motion was also greater than that of CTDs. Using GC, it was found that there was a significant increase in causal strength from the RMC to the RPFC (p = 0.04) and from the RMC to the LMC (p = 0.042) in children with CP during motion. Additionally, there were significant negative correlations between the PLV of LMC-RMC (p = 0.002) and the Gross Motor Function Classification System (GMFCS) and between the GMFCS and the clustering coefficient (p = 0.01).

CONCLUSIONS

During rehabilitation training of the lower limbs, there were significant differences in brain network indices between children with CP and CTDs. The indicators proposed in this paper are effective at evaluating motor function and the real-time impact of rehabilitation training on the brain network and have great potential for application in guiding clinical motor function assessment and planning rehabilitation strategies.

An fNIRS dataset for driving risk cognition of passengers in highly automated driving scenarios

For highly autonomous vehicles, human does not need to operate continuously vehicles. The brain-computer interface system in autonomous vehicles will highly depend on the brain states of passengers rather than those of human drivers. It is a meaningful and vital choice to translate the mental activities of human beings, essentially playing the role of advanced sensors, into safe driving. Quantifying the driving risk cognition of passengers is a basic step toward this end. This study reports the creation of an fNIRS dataset focusing on the prefrontal cortex activity in fourteen types of highly automated driving scenarios. This dataset considers age, sex and driving experience factors and contains the data collected from an 8-channel fNIRS device and the data of driving scenarios. The dataset provides data support for distinguishing the driving risk in highly automated driving scenarios via brain-computer interface systems, and it also provides the possibility of preventing potential hazards in some scenarios, in which risk remains at a high value for an extended period, before hazard occurs.

The neurocognitive mechanism linking temperature and humidity with miners' alertness: an fNIRS study

As the depth of coal mining increases, the temperature and humidity of the underground environment also rise, which can negatively impact the physiological health of miners, and may even pose a threat to their safety and lives. However, studies on the neurocognitive mechanisms underlying the relationship between temperature, humidity, and miners' alertness are scant. This study investigates several research objectives: (A) the differences in reaction time and error rate in different temperature and humidity conditions, which factor has a greater impact; (B) the differences in the levels of Oxy-Hb in different conditions and which factor has a greater impact; (C) the differences of activation degree between different regions of interest; and (D) the differences in the shape of Oxy-Hb time course between different conditions between different regions of interests. The fNIRS was used to measure the activity in 100 participants' prefrontal cortex in this study. The results showed that both temperature and humidity would lead to decreased alertness of miners, which would not only prolong the reaction time, increase the error rate, and increase the Oxy-Hb concentration, but also lead to increased activation of the prefrontal cortex and greater activation of the right side than that of the left side, the Oxy-Hb time course was different on both sides, and temperature has a greater effect on alertness than humidity.

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

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

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

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

Cortical activity in patients with high-functioning ischemic stroke during the Purdue Pegboard Test: insights into bimanual coordinated fine motor skills with functional near-infrared spectroscopy

After stroke, even high-functioning individuals may experience compromised bimanual coordination and fine motor dexterity, leading to reduced functional independence. Bilateral arm training has been proposed as a promising intervention to address these deficits. However, the neural basis of the impairment of functional fine motor skills and their relationship to bimanual coordination performance in stroke patients remains unclear, limiting the development of more targeted interventions. To address this gap, our study employed functional near-infrared spectroscopy to investigate cortical responses in patients after stroke as they perform functional tasks that engage fine motor control and coordination. Twenty-four high-functioning patients with ischemic stroke (7 women, 17 men; mean age 64.75 ± 10.84 years) participated in this cross-sectional observational study and completed four subtasks from the Purdue Pegboard Test, which measures unimanual and bimanual finger and hand dexterity. We found significant bilateral activation of the sensorimotor cortices during all Purdue Pegboard Test subtasks, with bimanual tasks inducing higher cortical activation than the assembly subtask. Importantly, patients with better bimanual coordination exhibited lower cortical activation during the other three Purdue Pegboard Test subtasks. Notably, the observed neural response patterns varied depending on the specific subtask. In the unaffected hand task, the differences were primarily observed in the ipsilesional hemisphere. In contrast, the bilateral sensorimotor cortices and the contralesional hemisphere played a more prominent role in the bimanual task and assembly task, respectively. While significant correlations were found between cortical activation and unimanual tasks, no significant correlations were observed with bimanual tasks. This study provides insights into the neural basis of bimanual coordination and fine motor skills in high-functioning patients after stroke, highlighting task-dependent neural responses. The findings also suggest that patients who exhibit better bimanual performance demonstrate more efficient cortical activation. Therefore, incorporating bilateral arm training in post-stroke rehabilitation is important for better outcomes. The combination of functional near-infrared spectroscopy with functional motor paradigms is valuable for assessing skills and developing targeted interventions in stroke rehabilitation.

Spatial correspondence of cortical activity measured with whole head fNIRS and fMRI: Toward clinical use within subject

Functional near infrared spectroscopy (fNIRS) and functional magnetic resonance imaging (fMRI) both measure the hemodynamic response, and so both imaging modalities are expected to have a strong correspondence in regions of cortex adjacent to the scalp. To assess whether fNIRS can be used clinically in a manner similar to fMRI, 22 healthy adult participants underwent same-day fMRI and whole-head fNIRS testing while they performed separate motor (finger tapping) and visual (flashing checkerboard) tasks. Analyses were conducted within and across subjects for each imaging approach, and regions of significant task-related activity were compared on the cortical surface. The spatial correspondence between fNIRS and fMRI detection of task-related activity was good in terms of true positive rate, with fNIRS overlap of up to 68 % of the fMRI for analyses across subjects (group analysis) and an average overlap of up to 47.25 % for individual analyses within subject. At the group level, the positive predictive value of fNIRS was 51 % relative to fMRI. The positive predictive value for within subject analyses was lower (41.5 %), reflecting the presence of significant fNIRS activity in regions without significant fMRI activity. This could reflect task-correlated sources of physiologic noise and/or differences in the sensitivity of fNIRS and fMRI measures to changes in separate (vs. combined) measures of oxy and de-oxyhemoglobin. The results suggest whole-head fNIRS as a noninvasive imaging modality with promising clinical utility for the functional assessment of brain activity in superficial regions of cortex physically adjacent to the skull.

The convergence of naturalistic paradigms and cognitive neuroscience methods to investigate memory and its development

Studies that involve lab-based stimuli (e.g., words, pictures) are fundamental in the memory literature. At the same time, there is growing acknowledgment that memory processes assessed in the lab may not be analogous to how memory operates in the real world. Naturalistic paradigms can bridge this gap and over the decades a growing proportion of memory research has involved more naturalistic events. However, there is significant variation in the types of naturalistic studies used to study memory and its development, each with various advantages and limitations. Further, there are notable gaps in how often different types of naturalistic approaches have been combined with cognitive neuroscience methods (e.g., fMRI, EEG) to elucidate the neural processes and substrates involved in memory encoding and retrieval in the real world. Here we summarize and discuss what we identify as progressively more naturalistic methodologies used in the memory literature (movie, virtual reality, staged-events inside and outside of the lab, photo-taking, and naturally occurring event studies). Our goal is to describe each approach's benefits (e.g., naturalistic quality, feasibility), limitations (e.g., viability of neuroimaging method for event encoding versus event retrieval), and discuss possible future directions with each approach. We focus on child studies, when available, but also highlight past adult studies. Although there is a growing body of child memory research, naturalistic approaches combined with cognitive neuroscience methodologies in this domain remain sparse. Overall, this viewpoint article reviews how we can study memory through the lens of developmental cognitive neuroscience, while utilizing naturalistic and real-world events.

Exploring Social Impairment in Those with Opioid Use Disorder: Linking Impulsivity, Childhood Trauma, and the Prefrontal Cortex

Background

Challenges with social functioning, which is a hallmark of opioid use disorder (OUD), are a drawback in treatment adherence and maintenance. Yet, little research has explored the underlying mechanisms of this impairment. Impulsivity, a known risk factor for OUD, and corresponding neural alterations may be at the center of this issue. Childhood adversity, which has been linked to both impulsivity and poorer treatment outcomes, could also affect this relationship. This study aims to understand the relationship between impulsivity and social functioning in those recovering from OUD. Differences in the prefrontal cortex will be analyzed, as well as potential moderating effects of childhood trauma.

Methods

Participants with (N = 16) and without (N = 19) social impairment completed a survey (e.g., social functioning, Barrat's Impulsivity Scale, Adverse Childhood Experiences (ACEs) and cognitive tasks while undergoing neuroimaging. Functional near infrared spectroscopy (fNIRS), a modern, portable, wearable and low-cost neuroimaging technology, was used to measure prefrontal cortex activity during a behavioral inhibition task (Go/No-Go task).

Results

Those who social functioning survey scores indicated social impairment (n = 16) scored significantly higher on impulsivity scale (t(33)= -3.4, p < 0.01) and reported more depressive symptoms (t(33) = -2.8, p < 0.01) than those reporting no social impairment (n = 19). Social functioning was negatively correlated with impulsivity (r=-0.7, p < 0.001), such that increased impulsivity corresponded to decreased social functioning. Childhood trauma emerged as a moderator of this relationship, but only when controlling for the effects of depression, B=-0.11, p = 0.023. Although both groups had comparable Go/No-Go task performance, the socially impaired group displayed greater activation in the dorsolateral (F(1,100.8) = 7.89, p < 0.01), ventrolateral (F(1,88.8) = 7.33, p < 0.01), and ventromedial (F(1,95.6) = 7.56, p < 0.01) prefrontal cortex during impulse control.

Conclusion

In addition to being more impulsive, individuals with social impairment exhibited differential activation in the prefrontal cortex when controlling responses. Furthermore, the impact of impulsivity on social functioning varies depending on ACEs demonstrating that it must be considered in treatment approaches. These findings have implications for addressing social needs and impulsivity of those in recovery, highlighting the importance of a more personalized, integrative, and trauma-informed approach to intervention.

Neuronal Control of Posture in Blind Individuals

The control of posture is guided by the integration of sensory information. Because blind individuals cannot apply visual information to control posture as sighted individuals do they must compensate by the remaining senses. We therefore hypothesize that blind individuals alter their brain activation in the sensorimotor cortex during postural control to compensate for balance control without vision by the increased integration of somatosensory information. Ten blind and ten sighted (matched) individuals controlled posture during conditions with (I) eyes closed / open, and (II) stable / unstable surface conditions. Postural sway was recorded by applying a pressure distribution measuring plate. Brain activation was collected by functional Near InfraRed Spectroscopy (fNIRS) above motor-sensory cortices of the right and left hemispheres. Blind individuals showed significantly increased postural sway when balancing with open eyes on an unstable surface and when compared to sighted individuals. Whereas blind individuals showed significantly increased brain activation when balancing with open eyes on stable and unstable surface conditions, sighted individuals increased their brain oxygenation only during closed eyes and unstable surface conditions. Overall conditions, blind individuals presented significantly increased brain activation in two channels of the left and right hemispheric motor-sensory cortex when compared to sighted individuals. We therefore conclude that sighted individuals increase their brain oxygenation in the sensorimotor cortex during postural control tasks that demand sensory integration processes. Blind individuals are characterized by increased brain activation overall conditions indicating additional sensory integration during postural control. Thus, the sensorimotor cortex of blind individuals adapts to control posture without vision.

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

Introduction

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

Methods

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

Results

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

Discussion

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

Evaluation of the learning state of online video courses based on functional near infrared spectroscopy

Studying brain activity during online learning will help to improve research on brain function based on real online learning situations, and will also promote the scientific evaluation of online education. Existing research focuses on enhancing learning effects and evaluating the learning process associated with online learning from an attentional perspective. We aimed to comparatively analyze the differences in prefrontal cortex (PFC) activity during resting, studying, and question-answering states in online learning and to establish a classification model of the learning state that would be useful for the evaluation of online learning. Nineteen university students performed experiments using functional near-infrared spectroscopy (fNIRS) to monitor the prefrontal lobes. The resting time at the start of the experiment was the resting state, watching 13 videos was the learning state, and answering questions after the video was the answering state. Differences in student activity between these three states were analyzed using a general linear model, 1s fNIRS data clips, and features, including averages from the three states, were classified using machine learning classification models such as support vector machines and k-nearest neighbor. The results show that the resting state is more active than learning in the dorsolateral prefrontal cortex, while answering questions is the most active of the three states in the entire PFC, and k-nearest neighbor achieves 98.5% classification accuracy for 1s fNIRS data. The results clarify the differences in PFC activity between resting, learning, and question-answering states in online learning scenarios and support the feasibility of developing an online learning assessment system using fNIRS and machine learning techniques.

Mothers and fathers show different neural synchrony with their children during shared experiences

Parent-child shared experiences has an important influence on social development in children although contributions of mothers and fathers may differ. Neural synchronicity occurs between mothers and fathers and their children during social interactions but it is unclear whether they differ in this respect. We used data from simultaneous fNIRS hyperscanning in mothers (n = 33) and fathers (n = 29) and their children (3-4 years) to determine different patterns and strengths of neural synchronization in the frontal cortex during co-viewing of videos or free-play. Mothers showed greater synchrony with child than fathers during passive viewing of videos and the synchronization was positively associated with video complexity and negatively associated with parental stress. During play interactions, mothers showed more controlling behaviors over their child and greater evidence for joint gaze and joint imitation play with child whereas fathers spent more time gazing at other things. In addition, different aspects of child communication promoted neural synchrony between mothers and fathers and child during active play interactions. Overall, our findings indicate greater neural and behavioral synchrony between mothers than fathers and young children during passive or active shared experiences, although for both it was weakened by parental distress and child difficulty.

Unleashing the potential of fNIRS with machine learning: classification of fine anatomical movements to empower future brain-computer interface

In this study, we explore the potential of using functional near-infrared spectroscopy (fNIRS) signals in conjunction with modern machine-learning techniques to classify specific anatomical movements to increase the number of control commands for a possible fNIRS-based brain-computer interface (BCI) applications. The study focuses on novel individual finger-tapping, a well-known task in fNIRS and fMRI studies, but limited to left/right or few fingers. Twenty-four right-handed participants performed the individual finger-tapping task. Data were recorded by using sixteen sources and detectors placed over the motor cortex according to the 10-10 international system. The event's average oxygenated Δ HbO and deoxygenated Δ HbR hemoglobin data were utilized as features to assess the performance of diverse machine learning (ML) models in a challenging multi-class classification setting. These methods include LDA, QDA, MNLR, XGBoost, and RF. A new DL-based model named "Hemo-Net" has been proposed which consists of multiple parallel convolution layers with different filters to extract the features. This paper aims to explore the efficacy of using fNRIS along with ML/DL methods in a multi-class classification task. Complex models like RF, XGBoost, and Hemo-Net produce relatively higher test set accuracy when compared to LDA, MNLR, and QDA. Hemo-Net has depicted a superior performance achieving the highest test set accuracy of 76%, however, in this work, we do not aim at improving the accuracies of models rather we are interested in exploring if fNIRS has the neural signatures to help modern ML/DL methods in multi-class classification which can lead to applications like brain-computer interfaces. Multi-class classification of fine anatomical movements, such as individual finger movements, is difficult to classify with fNIRS data. Traditional ML models like MNLR and LDA show inferior performance compared to the ensemble-based methods of RF and XGBoost. DL-based method Hemo-Net outperforms all methods evaluated in this study and demonstrates a promising future for fNIRS-based BCI applications.

Motor Processing in Children With Cochlear Implants as Assessed by Functional Near-Infrared Spectroscopy

Auditory-motor and visual-motor networks are often coupled in daily activities, such as when listening to music and dancing; but these networks are known to be highly malleable as a function of sensory input. Thus, congenital deafness may modify neural activities within the connections between the motor, auditory, and visual cortices. Here, we investigated whether the cortical responses of children with cochlear implants (CI) to a simple and repetitive motor task would differ from that of children with typical hearing (TH) and we sought to understand whether this response related to their language development. Participants were 75 school-aged children, including 50 with CI (with varying language abilities) and 25 controls with TH. We used functional near-infrared spectroscopy (fNIRS) to record cortical responses over the whole brain, as children squeezed the back triggers of a joystick that vibrated or not with the squeeze. Motor cortex activity was reflected by an increase in oxygenated hemoglobin concentration (HbO) and a decrease in deoxygenated hemoglobin concentration (HbR) in all children, irrespective of their hearing status. Unexpectedly, the visual cortex (supposedly an irrelevant region) was deactivated in this task, particularly for children with CI who had good language skills when compared to those with CI who had language delays. Presence or absence of vibrotactile feedback made no difference in cortical activation. These findings support the potential of fNIRS to examine cognitive functions related to language in children with CI.

How a pilot's brain copes with stress and mental load? Insights from the executive control network

In aviation, mental workload and stress are two major factors that can considerably impact a pilot's flight performance and decisions. Their consequences can be even more dramatic in single-pilot aircraft or with the forthcoming single-pilot operations where the pilot will fly alone and will not be able to be assisted in case of difficulty. An accurate and automatic monitoring of the pilot's mental state could help to prevent the potentially dangerous effects of an excess mental workload and stress. For example, some tasks could be allocated to automation or to a ground-based flight crew if a mental overload or significant stress is detected. In the current study, the brain activity of 20 private pilots was recorded with a fNIRS device during two realistic flight simulator scenarios. The mental workload was manipulated with the added difficulty of a secondary task and stress was induced by a social stressor. Our results confirmed the sensitivity of the fNIRS readings to variations in the mental workload, with increased HbO2 concentration in regions of the executive control network (ECN), in particular in the dorsolateral prefrontal cortex and in lateral parietal regions, when the difficulty of the secondary task was high. The social stressor also triggered an HbO2 increase in the ECN, especially when it was combined with high mental workload. This latter result suggests that mental workload and stress together can have cumulative effects, and coping with both factors is possible at the expense of an extra recruitment of the ECN. Finally, results also revealed a time-on-task effect, with a progressive reduction of the HbO2 signal in the ECN during the flight scenario, suggesting that these regions are sensitive to short term habituation to the tasks. Overall, fNIRS efficiently indexed mental load, stress, and practice effects.

Differential cortical activation patterns: pioneering sub-classification of tinnitus with and without hyperacusis by combining audiometry, gamma oscillations, and hemodynamics

The ongoing controversies about the neural basis of tinnitus, whether linked with central neural gain or not, may hamper efforts to develop therapies. We asked to what extent measurable audiometric characteristics of tinnitus without (T) or with co-occurrence of hyperacusis (TH) are distinguishable on the level of cortical responses. To accomplish this, electroencephalography (EEG) and concurrent functional near-infrared spectroscopy (fNIRS) were measured while patients performed an attentionally demanding auditory discrimination task using stimuli within the individual tinnitus frequency (fTin) and a reference frequency (fRef). Resting-state-fMRI-based functional connectivity (rs-fMRI-bfc) in ascending auditory nuclei (AAN), the primary auditory cortex (AC-I), and four other regions relevant for directing attention or regulating distress in temporal, parietal, and prefrontal cortex was compiled and compared to EEG and concurrent fNIRS activity in the same brain areas. We observed no group differences in pure-tone audiometry (PTA) between 10 and 16 kHz. However, the PTA threshold around the tinnitus pitch was positively correlated with the self-rated tinnitus loudness and also correlated with distress in T-groups, while TH experienced their tinnitus loudness at minimal loudness levels already with maximal suffering scores. The T-group exhibited prolonged auditory brain stem (ABR) wave I latency and reduced ABR wave V amplitudes (indicating reduced neural synchrony in the brainstem), which were associated with lower rs-fMRI-bfc between AAN and the AC-I, as observed in previous studies. In T-subjects, these features were linked with elevated spontaneous and reduced evoked gamma oscillations and with reduced deoxygenated hemoglobin (deoxy-Hb) concentrations in response to stimulation with lower frequencies in temporal cortex (Brodmann area (BA) 41, 42, 22), implying less synchronous auditory responses during active auditory discrimination of reference frequencies. In contrast, in the TH-group gamma oscillations and hemodynamic responses in temporoparietal regions were reversed during active discrimination of tinnitus frequencies. Our findings suggest that T and TH differ in auditory discrimination and memory-dependent directed attention during active discrimination at either tinnitus or reference frequencies, offering a test paradigm that may allow for more precise sub-classification of tinnitus and future improved treatment approaches.

Mobile fNIRS for exploring inter-brain synchrony across generations and time

While still relatively rare, longitudinal hyperscanning studies are exceptionally valuable for documenting changes in inter-brain synchrony, which may in turn underpin how behaviors develop and evolve in social settings. The generalizability and ecological validity of this experimental approach hinges on the selected imaging technique being mobile-a requirement met by functional near-infrared spectroscopy (fNIRS). fNIRS has most frequently been used to examine the development of inter-brain synchrony and behavior in child-parent dyads. In this position paper, we contend that dedicating attention to longitudinal and intergenerational hyperscanning stands to benefit the fields of social and cognitive neuroscience more broadly. We argue that this approach is particularly relevant for understanding the neural mechanisms underpinning intergenerational social dynamics, and potentially for benchmarking progress in psychological and social interventions, many of which are situated in intergenerational contexts. In line with our position, we highlight areas of intergenerational research that stand to be enhanced by longitudinal hyperscanning with mobile devices, describe challenges that may arise from measuring across generations in the real world, and offer potential solutions.

Neuroimaging evidence of visual-vestibular interaction accounting for perceptual mislocalization induced by head rotation

Significance

A fleeting flash aligned vertically with an object remaining stationary in the head-centered space would be perceived as lagging behind the object during the observer's horizontal head rotation. This perceptual mislocalization is an illusion named head-rotation-induced flash-lag effect (hFLE). While many studies have investigated the neural mechanism of the classical visual FLE, the hFLE has been hardly investigated.

Aim

We measured the cortical activity corresponding to the hFLE on participants experiencing passive head rotations using functional near-infrared spectroscopy.

Approach

Participants were asked to judge the relative position of a flash to a fixed reference while being horizontally rotated or staying static in a swivel chair. Meanwhile, functional near-infrared spectroscopy signals were recorded in temporal-parietal areas. The flash duration was manipulated to provide control conditions.

Results

Brain activity specific to the hFLE was found around the right middle/inferior temporal gyri, and bilateral supramarginal gyri and superior temporal gyri areas. The activation was positively correlated with the rotation velocity of the participant around the supramarginal gyrus and negatively related to the hFLE intensity around the middle temporal gyrus.

Conclusions

These results suggest that the mechanism underlying the hFLE involves multiple aspects of visual-vestibular interactions including the processing of multisensory conflicts mediated by the temporoparietal junction and the modulation of vestibular signals on object position perception in the human middle temporal complex.

Effect of the VR-guided grasping task on the brain functional network

Virtual reality (VR) technology has been demonstrated to be effective in rehabilitation training with the assistance of VR games, but its impact on brain functional networks remains unclear. In this study, we used functional near-infrared spectroscopy imaging to examine the brain hemodynamic signals from 18 healthy participants during rest and grasping tasks with and without VR game intervention. We calculated and compared the graph theory-based topological properties of the brain networks using phase locking values (PLV). The results revealed significant differences in the brain network properties when VR games were introduced compared to the resting state. Specifically, for the VR-guided grasping task, the modularity of the brain network was significantly higher than the resting state, and the average clustering coefficient of the motor cortex was significantly lower compared to that of the resting state and the simple grasping task. Correlation analyses showed that a higher clustering coefficient, local efficiency, and modularity were associated with better game performance during VR game participation. This study demonstrates that a VR game task intervention can better modulate the brain functional network compared to simple grasping movements and may be more beneficial for the recovery of grasping abilities in post-stroke patients with hand paralysis.

Effects of endurance exercise on physiologic complexity of the hemodynamics in prefrontal cortex

Significance

Prefrontal cortex (PFC) hemodynamics are regulated by numerous underlying neurophysiological components over multiple temporal scales. The pattern of output signals, such as functional near-infrared spectroscopy fluctuations (i.e., fNIRS), is thus complex. We demonstrate first-of-its-kind evidence that this fNIRS complexity is a marker that captures the influence of endurance capacity and the effects of hydrogen gas (H 2 ) on PFC regulation.

Aim

We aim to explore the effects of different physical loads of exercise as well as the intaking of hydrogen gas on the fNIRS complexity of the PFC.

Approach

Twenty-four healthy young men completed endurance cycling exercise from 0 (i.e., baseline) to 100% of their physical loads after intaking 20 min of either H 2 or placebo gas (i.e., control) on each of two separate visits. The fNIRS measuring the PFC hemodynamics and heart rate (HR) was continuously recorded throughout the exercise. The fNIRS complexity was quantified using multiscale entropy.

Results

The fNIRS complexity was significantly greater in the conditions from 25% to 100% of the physical load (p < 0.0005 ) compared with the baseline and after intaking H 2 before exercise; this increase of fNIRS complexity was significantly greater compared with the control (p = 0.001 ∼ 0.01 ). At the baseline, participants with a greater fNIRS complexity had a lower HR (β = - 0.35 ∼ - 0.33 , p = 0.008 ∼ 0.02 ). Those with a greater increase of complexity had a lower increase of the HR (β = - 0.30 ∼ - 0.28 , p = 0.001 ∼ 0.002 ) during exercise.

Conclusions

These observations suggest that fNIRS complexity would be a marker that captures the adaptive capacity of PFC to endurance exercise and to the effects of interventions on PFC hemodynamics.

Feasibility study of functional near-infrared spectroscopy in the ventral visual pathway for real-life applications

Significance

fNIRS-based neuroenhancement depends on the feasible detection of hemodynamic responses in target brain regions. Using the lateral occipital complex (LOC) and the fusiform face area (FFA) in the ventral visual pathway as neurofeedback targets boosts performance in visual recognition. However, the feasibility of utilizing fNIRS to detect LOC and FFA activity in adults remains to be validated as the depth of these regions may exceed the detection limit of fNIRS.

Aim

This study aims to investigate the feasibility of using fNIRS to measure hemodynamic responses in the ventral visual pathway, specifically in the LOC and FFA, in adults.

Approach

We recorded the hemodynamic activities of the LOC and FFA regions in 35 subjects using a portable eight-channel fNIRS instrument. A standard one-back object and face recognition task was employed to elicit selective brain responses in the LOC and FFA regions. The placement of fNIRS optodes for LOC and FFA detection was guided by our group's transcranial brain atlas (TBA).

Results

Our findings revealed selective activation of the LOC target channel (CH2) in response to objects, whereas the FFA target channel (CH7) did not exhibit selective activation in response to faces.

Conclusions

Our findings indicate that, although fNIRS detection has limitations in capturing FFA activity, the LOC region emerges as a viable target for fNIRS-based detection. Furthermore, our results advocate for the adoption of the TBA-based method for setting the LOC target channel, offering a promising solution for optrode placement. This feasibility study stands as the inaugural validation of fNIRS for detecting cortical activity in the ventral visual pathway, underscoring its ecological validity. We suggest that our findings establish a pivotal technical groundwork for prospective real-life applications of fNIRS-based research.

Two Independent Response Mechanisms to Auditory Stimuli Measured with Functional Near-Infrared Spectroscopy in Sleeping Infants

This study investigated the morphology of the functional near-infrared spectroscopy (fNIRS) response to speech sounds measured from 16 sleeping infants and how it changes with repeated stimulus presentation. We observed a positive peak followed by a wide negative trough, with the latter being most evident in early epochs. We argue that the overall response morphology captures the effects of two simultaneous, but independent, response mechanisms that are both activated at the stimulus onset: one being the obligatory response to a sound stimulus by the auditory system, and the other being a neural suppression effect induced by the arousal system. Because the two effects behave differently with repeated epochs, it is possible to mathematically separate them and use fNIRS to study factors that affect the development and activation of the arousal system in infants. The results also imply that standard fNIRS analysis techniques need to be adjusted to take into account the possibilities of multiple simultaneous brain systems being activated and that the response to a stimulus is not necessarily stationary.

Aging effects on dual-route speech processing networks during speech perception in noise

Healthy aging leads to complex changes in the functional network of speech processing in a noisy environment. The dual-route neural architecture has been applied to the study of speech processing. Although evidence suggests that senescent increases activity in the brain regions across the dorsal and ventral stream regions to offset reduced periphery, the regulatory mechanism of dual-route functional networks underlying such compensation remains largely unknown. Here, by utilizing functional near-infrared spectroscopy (fNIRS), we investigated the compensatory mechanism of the dual-route functional connectivity, and its relationship with healthy aging by using a speech perception task at varying signal-to-noise ratios (SNR) in healthy individuals (young adults, middle-aged adults, and older adults). Results showed that the speech perception scores showed a significant age-related decrease with the reduction of the SNR. The analysis results of dual-route speech processing networks showed that the functional connection of Wernicke's area and homolog Wernicke's area were age-related increases. Further to clarify the age-related characteristics of the dual-route speech processing networks, graph-theoretical network analysis revealed an age-related increase in the efficiency of the networks, and the age-related differences in nodal characteristics were found both in Wernicke's area and homolog Wernicke's area under noise environment. Thus, Wernicke's area might be a key network hub to maintain efficient information transfer across the speech process network with healthy aging. Moreover, older adults would recruit more resources from the homologous Wernicke's area in a noisy environment. The recruitment of the homolog of Wernicke's area might provide a means of compensation for older adults for decoding speech in an adverse listening environment. Together, our results characterized dual-route speech processing networks at varying noise environments and provided new insight for the compensatory theories of how aging modulates the dual-route speech processing functional networks.

Intravesical Electrical Stimulation Improves Abnormal Prefrontal Brain Activity in Patients With Underactive Bladder: A Possible Central Mechanism

PURPOSE

The aim of this study was to explore the mechanisms of central brain action in patients with neurogenic underactive bladder (UAB) treated with intravesical electrical stimulation (IVES).

METHODS

We prospectively recruited patients with neurogenic UAB who chose to receive IVES treatment and healthy subjects (HS). At baseline, the following data were obtained: a 72-hour voiding diary; measurements of postvoid residual urine (PVR), voiding efficiency (VE) and first sensation of bladder filling (FS); American Urological Association Symptom Index Quality of Life (AUA-SI-QOL) scores, and functional near-infrared spectroscopy scans of the prefrontal cortex in the voiding stage. All UAB patients were re-evaluated for these indices after completing 4 weeks of IVES. A >50% improvement in PVR was defined as successful IVES treatment. Prefrontal activity was analyzed using the NIRS_KIT software, corrected with the false discovery rate (P<0.05). Statistical analysis was performed using IBM SPSS Statistics ver. 22.0, and P<0.05 was considered statistically significant.

RESULTS

Eighteen UAB patients and 16 HS were included. IVES treatment was successful in 11 UAB patients and failed in 7. The PVR, VE, 24-hour clean intermittent catheterization, FS volume, and AUA-SI-QOL scores of the UAB group significantly improved after successful IVES treatment. BA9 (right dorsolateral prefrontal cortex [DLPFC]) and BA10 (right frontal pole) were significantly activated after successful IVES, and no significant difference was found between the successful group and HS group after IVES. Before IVES, BA10 (right frontal pole) was significantly deactivated in the failed group compared with the successful group.

CONCLUSION

The possible central mechanism of IVES treatment for neurogenic UAB is that IVES reactivates the right DLPFC and right frontal pole.