Mayer waves reduce the accuracy of estimated hemodynamic response functions in functional near-infrared spectroscopy

Cortical functional mechanisms in emotional cognitive tasks in first-episode, drug-naïve with major depressive disorder: A fNIRS study

BACKGROUND

Previous research has revealed that patients with major depressive disorder (MDD) have negative biases in various aspects of information processing, and these biases are mainly manifested in recognizing facial expressions. However, the link between this emotional cognitive inhibition and neural activation mechanisms in cortical brain regions remains poorly understood. Therefore, this study employed functional near-infrared spectroscopy (fNIRS) to explore the potential impaired regions and neural mechanisms associated with facial emotion cognition in MDD patients.

METHODS

37 MDD patients and 34 healthy controls (HC) were recruited to participate in three sets of cognitive tasks for emotion recognition, and the cortical activation in the brain was synchronously recorded using multi-channel fNIRS.

RESULTS

During tasks requiring the motions identification of sad versus happy emotional states, MDD patients exhibit altered activation in both the left frontopolar cortex (FPC) and the right dorsolateral prefrontal cortex (DLPFC). Notably, the FPC demonstrates a higher level of internal coherence and broader correlation with other cortical areas. Moreover, MDD patients showed lower accuracy in distinguishing emotional cues associated with sadness versus those associated with neutral and happy emotions.

LIMITATIONS

The study had a relatively small sample size, and it specifically examined only three prevalent facial expressions.

CONCLUSION

Facial expression recognition in MDD patients is characterized by negative cognitive interpretation of expressions, which are associated with various cortical altered activations. Neuroimaging further suggests that the cognitive inhibition of emotion signal recognition in everyday interpersonal interactions in MDD patients may primarily be influenced by activation in the left FPC.

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

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

Having a chat and then watching a movie: how social interaction synchronises our brains during co-watching

How does co-presence change our neural experience of the world? Can a conversation change how we synchronise with our partner during later events? Using fNIRS hyperscanning, we measured brain activity from 27 pairs of familiar adults simultaneously over frontal, temporal and parietal regions bilaterally, as they co-watched two different episodes of a short cartoon. In-between the two episodes, each pair engaged in a face-to-face conversation on topics unrelated to the cartoon episodes. Brain synchrony was calculated using wavelet transform coherence and computed separately for real pairs and shuffled pseudo) pairs. Findings reveal that real pairs showed increased brain synchrony over right Dorso-Lateral Pre-Frontal cortex (DLPFC) and right Superior Parietal Lobe (SPL), compared to pseudo pairs (who had never seen each other and watched the same movie at different times; uncorrected for multiple comparisons). In addition, co-watching after a conversation was associated with greater synchrony over right TPJ compared to co-watching before a conversation, and this effect was significantly higher in real pairs (who engaged in conversation with each other) compared to pseudo pairs (who had a conversation with someone else; uncorrected for multiple comparisons). The present study has shed the light on the role of social interaction in modulating brain synchrony across people not just during social interaction, but even for subsequent non-social activities. These results have implications in the growing domain of naturalistic neuroimaging and interactive neuroscience.

Post-interaction neuroplasticity of inter-brain networks underlies the development of social relationship

Inter-brain coupling has been increasingly recognized for its role in supporting connectedness during social communication. Here we investigate whether inter-brain coupling is plastic and persists beyond the offset of social interaction, facilitating the emergence of social closeness. Dyads were concurrently scanned using functional near infrared spectroscopy (fNIRS) while engaging in a task that involved movement synchronization. To assess post-interaction neuroplasticity, participants performed a baseline condition with no interaction before and after the interaction. The results reveal heightened inter-brain coupling in neural networks comprising the inferior frontal gyrus (IFG) and dorsomedial prefrontal cortex in the post-task compared to the pre-task baseline. Critically, the right IFG emerged as a highly connected hub, with post-task inter-brain coupling in this region predicting the levels of motivation to connect socially. We suggest that post-interactions inter-brain coupling may reflect consolidation of socially related cues, underscoring the role of inter-brain plasticity in fundamental aspects of relationship development.

Cognitive Effort during Visuospatial Problem Solving in Physical Real World, on Computer Screen, and in Virtual Reality

Spatial cognition plays a crucial role in academic achievement, particularly in science, technology, engineering, and mathematics (STEM) domains. Immersive virtual environments (VRs) have the growing potential to reduce cognitive load and improve spatial reasoning. However, traditional methods struggle to assess the mental effort required for visuospatial processes due to the difficulty in verbalizing actions and other limitations in self-reported evaluations. In this neuroergonomics study, we aimed to capture the neural activity associated with cognitive workload during visuospatial tasks and evaluate the impact of the visualization medium on visuospatial task performance. We utilized functional near-infrared spectroscopy (fNIRS) wearable neuroimaging to assess cognitive effort during spatial-reasoning-based problem-solving and compared a VR, a computer screen, and a physical real-world task presentation. Our results reveal a higher neural efficiency in the prefrontal cortex (PFC) during 3D geometry puzzles in VR settings compared to the settings in the physical world and on the computer screen. VR appears to reduce the visuospatial task load by facilitating spatial visualization and providing visual cues. This makes it a valuable tool for spatial cognition training, especially for beginners. Additionally, our multimodal approach allows for progressively increasing task complexity, maintaining a challenge throughout training. This study underscores the potential of VR in developing spatial skills and highlights the value of comparing brain data and human interaction across different training settings.

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.

Features of the speech processing network in post- and prelingually deaf cochlear implant users

The onset of hearing loss can lead to altered brain structure and functions. However, hearing restoration may also result in distinct cortical reorganization. A differential pattern of functional remodeling was observed between post- and prelingual cochlear implant users, but it remains unclear how these speech processing networks are reorganized after cochlear implantation. To explore the impact of language acquisition and hearing restoration on speech perception in cochlear implant users, we conducted assessments of brain activation, functional connectivity, and graph theory-based analysis using functional near-infrared spectroscopy. We examined the effects of speech-in-noise stimuli on three groups: postlingual cochlear implant users (n = 12), prelingual cochlear implant users (n = 10), and age-matched individuals with hearing controls (HC) (n = 22). The activation of auditory-related areas in cochlear implant users showed a lower response compared with the HC group. Wernicke's area and Broca's area demonstrated differences network attributes in speech processing networks in post- and prelingual cochlear implant users. In addition, cochlear implant users maintain a high efficiency of the speech processing network to process speech information. Taken together, our results characterize the speech processing networks, in varying noise environments, in post- and prelingual cochlear implant users and provide new insights for theories of how implantation modes impact remodeling of the speech processing functional networks.

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.

Risk, Trust, and Emotion in Online Pharmacy Medication Purchases: Multimethod Approach Incorporating Customer Self-Reports, Facial Expressions, and Neural Activation

BACKGROUND

Online pharmacies are used less than other e-commerce sites in Germany. Shopping behavior does not correspond to consumption behavior, as online purchases are predominantly made for over-the-counter (OTC) medications.

OBJECTIVE

The objective of this study was to understand the purchasing experiences of online pharmacy customers in terms of critical factors for online pharmacy adoption.

METHODS

This study examined the perceived risk, perceived trust, and emotions related to purchasing medications online and, consequently, the purchase intention toward online pharmacies. In a within-subjects design (N=37 participants), 2 German online pharmacies with different perceptions of risk and trust were investigated for their main business, namely OTC and prescription drugs. The results of a preliminary study led to 1 online pharmacy with high and 1 with significantly low self-reported risk by the prestudy sample. Emotions were measured with a multimethod approach during and after the purchase situation as follows: (1) neural evaluation processes using functional near-infrared spectroscopy, (2) the automated direct motor response during the use of the online pharmacy via facial expression analysis (FaceReader), and (3) subjective evaluations through self-reports. Following the shopping experiences at both pharmacies for both product types, risk, trust, and purchase intention toward the pharmacies were assessed using self-assessments.

RESULTS

The 2 online pharmacies were rated differently in terms of risk, trust, emotions, and purchase intention. The high-risk pharmacy was also perceived as having lower trust and vice versa. Significantly stronger negative emotional expressions on customers' faces and different neural activations in the ventromedial prefrontal cortex and dorsomedial prefrontal cortex were measured when purchasing prescription drugs from the high-risk pharmacy than from the low-risk pharmacy, combined with OTC medications. In line with this, customers' self-ratings indicated higher negative emotions for the high-risk pharmacy and lower negative emotions for the low-risk pharmacy. Moreover, the ratings showed lower purchase intention for the high-risk pharmacy.

CONCLUSIONS

Using multimethod measurements, we showed that the preceding neural activation and subsequent verbal evaluation of online pharmacies are reflected in the customers' immediate emotional facial expressions. High-risk online pharmacies and prescription drugs lead to stronger negative emotional facial expressions and trigger neural evaluation processes that imply perceived loss. Low-risk online pharmacies and OTC medications lead to weaker negative emotional facial expressions and trigger neural evaluation processes that signify certainty and perceived reward. The results may provide an explanation for why OTC medications are purchased online more frequently than prescription medications.

Taste dysfunction after COVID-19: Analysis with functional near-infrared spectroscopy

<br><b>Introduction:</b> According to official data, COVID-19 emerged in China in December 2019 and has spread worldwide since then.</br> <br><b>Aim:</b> The aim of this study was to investigate differences in functional near-infrared spectroscopy (fNIRS) recordings between convalescent COVID-19 patients and a healthy control group, which could help to clarify the pathomechanism of dysgeusia in COVID-19.</br> <br><b>Material and methods:</b> The study included 16 participants, comprised of 8 convalescent COVID-19 patients and 8 healthy controls. All participants were examined with fNIRS. The amplitude of changes in oxyhemoglobin (oxyHb) concentration in the cerebral cortex was analyzed statistically (for the test and control groups after stimulation with a taste stimulus - citric acid solution).</br> <br><b>Results:</b> The differences in the amplitude of changes in oxyHb concentration in the cerebral cortex were not statistically significant between the groups. Discussion: Using fNIRS, a strong stimulation of the visual cortex was discovered in response to the taste stimulus, consisting of large, repetitive changes in oxyHb concentration occurring in parallel with stimulation of areas of the taste cortex. This phenomenon has not, to our knowledge, been described previously in the scientific literature. The exact location of the primary taste cortex is controversial, but to date the occipital cortex has not been considered to be involved.</br> <br><b>Conclusions: No difference was observed in the dynamics of changes in oxyHb in the examined areas of the cerebral cortex between convalescent COVID-19 patients and healthy controls. However, the determination of the role of the occipital cortex in the perception of taste requires further research.</br>.

Premotor and Posterior Parietal Cortex Activity is Increased for Slow, as well as Fast Walking Poststroke: An fNIRS Study

Methods

Twenty individuals in the chronic stage of stroke walked: (1) at their normal pace, (2) slower than normal, and (3) as fast as possible. Functional near-infrared spectroscopy was used to assess bilateral prefrontal, premotor, sensorimotor, and posterior parietal cortices during walking.

Results

No significant differences in laterality were observed between walking speeds. The ipsilesional prefrontal cortex was overall more active than the contralesional prefrontal cortex. Premotor and posterior parietal cortex activity were larger during slow and fast walking compared to normal-paced walking with no differences between slow and fast walking. Greater increases in brain activation in the ipsilesional prefrontal cortex during fast compared to normal-paced walking related to greater gait speed modulation.

Conclusions

Brain activation is not linearly related to gait speed. Ipsilesional prefrontal cortex, bilateral premotor, and bilateral posterior parietal cortices are important areas for gait speed modulation and could be an area of interest for neurostimulation.

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.

Test-retest reliability of fNIRS in resting-state cortical activity and brain network assessment in stroke patients

Resting-state functional near infrared spectroscopy (fNIRS) scanning has attracted considerable attention in stroke rehabilitation research in recent years. The aim of this study was to quantify the reliability of fNIRS in cortical activity intensity and brain network metrics among resting-state stroke patients, and to comprehensively evaluate the effects of frequency selection, scanning duration, analysis and preprocessing strategies on test-retest reliability. Nineteen patients with stroke underwent two resting fNIRS scanning sessions with an interval of 24 hours. The haemoglobin signals were preprocessed by principal component analysis, common average reference and haemodynamic modality separation (HMS) algorithm respectively. The cortical activity, functional connectivity level, local network metrics (degree, betweenness and local efficiency) and global network metrics were calculated at 25 frequency scales × 16 time windows. The test-retest reliability of each fNIRS metric was quantified by the intraclass correlation coefficient. The results show that (1) the high-frequency band has higher ICC values than the low-frequency band, and the fNIRS metric is more reliable than at the individual channel level when averaged within the brain region channel, (2) the ICC values of the low-frequency band above the 4-minute scan time are generally higher than 0.5, the local efficiency and global network metrics reach high and excellent reliability levels after 4 min (0.5 < ICC < 0.9), with moderate or even poor reliability for degree and betweenness (ICC < 0.5), (3) HMS algorithm performs best in improving the low-frequency band ICC values. The results indicate that a scanning duration of more than 4 minutes can lead to high reliability of most fNIRS metrics when assessing low-frequency resting brain function in stroke patients. It is recommended to use the global correction method of HMS, and the reporting of degree, betweenness and single channel level should be performed with caution. This paper provides the first comprehensive reference for resting-state experimental design and analysis strategies for fNIRS in stroke rehabilitation.

Synchronizing Motor Imagery Cue in fNIRS Brain-Computer Interface to reduce confounding effects of respiration

Functional near-infrared spectroscopy (fNIRS) is a neuroimaging method that measures oxygenated hemoglobin (HbO) levels in the brain to infer neural activity using near-infrared light. Measured HbO levels are directly affected by a person's respiration. Hence, respiration cycles tend to confound fNIRS readings in motor imagery-based fNIRS Brain-Computer Interfaces (BCI). To reduce this confounding effect, we propose a method of synchronizing the motor imagery cue timing with the subject's respiration cycle using a breathing sensor. We conducted an experiment to collect 160 single trials from 10 subjects performing motor imagery using an fNIRS-based BCI and the breathing sensor. We then compared the HbO levels in trials with and without respiration synchronization. The results showed that respiration synchronization yielded HbO levels that were less dispersed across trials, and a negative correlation between the dispersion index of HbO levels with MI decoding accuracies was found across the 10 subjects. This showed that synchronizing motor imagery cues to respiration can yield increased HbO level consistency leading to better MI performance. Hence, the proposed method holds promise to improve the decoding performance of fNIRS-BCI by reducing the confounding effects of respiration.

A case for hybrid BCIs: combining optical and electrical modalities improves accuracy

Near-infrared spectroscopy (NIRS) is a promising research tool that found its way into the field of brain-computer interfacing (BCI). BCI is crucially dependent on maximized usability thus demanding lightweight, compact, and low-cost hardware. We designed, built, and validated a hybrid BCI system incorporating one optical and two electrical modalities ameliorating usability issues. The novel hardware consisted of a NIRS device integrated with an electroencephalography (EEG) system that used two different types of electrodes: Regular gelled gold disk electrodes and tri-polar concentric ring electrodes (TCRE). BCI experiments with 16 volunteers implemented a two-dimensional motor imagery paradigm in off- and online sessions. Various non-canonical signal processing methods were used to extract and classify useful features from EEG, tEEG (EEG through TCRE electrodes), and NIRS. Our analysis demonstrated evidence of improvement in classification accuracy when using the TCRE electrodes compared to disk electrodes and the NIRS system. Based on our synchronous hybrid recording system, we could show that the combination of NIRS-EEG-tEEG performed significantly better than either single modality only.

Measuring cognitively demanding activities in pediatric out-of-hospital cardiac arrest

BACKGROUND

This methodological intersection article demonstrates a method to measure cognitive load in clinical simulations. Researchers have hypothesized that high levels of cognitive load reduce performance and increase errors. This phenomenon has been studied primarily by experimental designs that measure responses to predetermined stimuli and self-reports that reduce the experience to a summative value. Our goal was to develop a method to identify clinical activities with high cognitive burden using physiologic measures.

METHODS

Teams of emergency medical responders were recruited from local fire departments to participate in a scenario with a shockable pediatric out-of-hospital cardiac arrest (POHCA) patient. The scenario was standardized with the patient being resuscitated after receiving high-quality CPR and 3 defibrillations. Each team had a person in charge (PIC) who wore a functional near-infrared spectroscopy (fNIRS) device that recorded changes in oxygenated and deoxygenated hemoglobin concentration in their prefrontal cortex (PFC), which was interpreted as cognitive activity. We developed a data processing pipeline to remove nonneural noise (e.g., motion artifacts, heart rate, respiration, and blood pressure) and detect statistically significant changes in cognitive activity. Two researchers independently watched videos and coded clinical tasks corresponding to detected events. Disagreements were resolved through consensus, and results were validated by clinicians.

RESULTS

We conducted 18 simulations with 122 participants. Participants arrived in teams of 4 to 7 members, including one PIC. We recorded the PIC's fNIRS signals and identified 173 events associated with increased cognitive activity. [Defibrillation] (N = 34); [medication] dosing (N = 33); and [rhythm checks] (N = 28) coincided most frequently with detected elevations in cognitive activity. [Defibrillations] had affinity with the right PFC, while [medication] dosing and [rhythm checks] had affinity with the left PFC.

CONCLUSIONS

FNIRS is a promising tool for physiologically measuring cognitive load. We describe a novel approach to scan the signal for statistically significant events with no a priori assumptions of when they occur. The events corresponded to key resuscitation tasks and appeared to be specific to the type of task based on activated regions in the PFC. Identifying and understanding the clinical tasks that require high cognitive load can suggest targets for interventions to decrease cognitive load and errors in care.

Cortical hemodynamic response and networks in children with cerebral palsy during upper limb bilateral motor training

Understanding the characteristics of functional brain activity is important for motor rehabilitation of children with cerebral palsy (CP). Using the functional near-infrared spectroscopy (fNIRS) technology, the cortical response and networks of prefrontal (PFC) and motor cortices (MC) were analyzed for children with CP and typical development (CTD). Compared with CTD, the resting cortical response of dominant MC in children with CP increased, and the functional connectivity between cerebral areas decreased. In the motor state of children with CP, the coupling strength started from dominant MC increased compared with resting state, and the hemispherical autonomy index (HAI) of the dominant MC was higher than that in the CTD, which reflected the leading role of dominant MC in brain regulation during motor. The functional connectivity between bilateral MC was positively correlated with motor performance. This study provided effective indices for evaluating the motor function and real-time impact of motor on brain networks.

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.

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.

Connections between spatially distant primary language regions strengthen with age during infancy, as revealed by resting-state fNIRS

Objective.Hearing is an important sensory function that plays a key role in how children learn to speak and develop language skills. Although previous neuroimaging studies have established that much of brain network maturation happens in early childhood, our understanding of the developmental trajectory of language areas is still very limited. We hypothesized that typical development trajectory of language areas in early childhood could be established by analyzing the changes of functional connectivity in normal hearing infants at different ages using functional near-infrared spectroscopy.Approach.Resting-state data were recorded from two bilateral temporal and prefrontal regions associated with language processing by measuring the relative changes of oxy-hemoglobin (HbO) and deoxy-hemoglobin (HbR) concentrations. Connectivity was calculated using magnitude-squared coherence of channel pairs located in (a) inter-hemispheric homologous and (b) intra-hemispheric brain regions to assess connectivity between homologous regions across hemispheres and two regions of interest in the same hemisphere, respectively.Main results.A linear regression model fitted to the age vs coherence of inter-hemispheric homologous test group revealed a significant coefficient of determination for both HbO (R²= 0.216,p= 0.0169) and HbR (R²= 0.206,p= 0.0198). A significant coefficient of determination was also found for intra-hemispheric test group for HbO (R²= 0.237,p= 0.0117) but not for HbR (R²= 0.111,p= 0.0956).Significance.The findings from HbO data suggest that both inter-hemispheric homologous and intra-hemispheric connectivity between primary language regions significantly strengthen with age in the first year of life. Mapping out the developmental trajectory of primary language areas of normal hearing infants as measured by functional connectivity could potentially allow us to better understand the altered connectivity and its effects on language delays in infants with hearing impairments.

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

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

Confounding effects of heart rate, breathing rate, and frontal fNIRS on interoception

Recent studies have established that cardiac and respiratory phases can modulate perception and related neural dynamics. While heart rate and respiratory sinus arrhythmia possibly affect interoception biomarkers, such as heartbeat-evoked potentials, the relative changes in heart rate and cardiorespiratory dynamics in interoceptive processes have not yet been investigated. In this study, we investigated the variation in heart and breathing rates, as well as higher functional dynamics including cardiorespiratory correlation and frontal hemodynamics measured with fNIRS, during a heartbeat counting task. To further investigate the functional physiology linked to changes in vagal activity caused by specific breathing rates, we performed the heartbeat counting task together with a controlled breathing rate task. The results demonstrate that focusing on heartbeats decreases breathing and heart rates in comparison, which may be part of the physiological mechanisms related to "listening" to the heart, the focus of attention, and self-awareness. Focusing on heartbeats was also observed to increase frontal connectivity, supporting the role of frontal structures in the neural monitoring of visceral inputs. However, cardiorespiratory correlation is affected by both heartbeats counting and controlled breathing tasks. Based on these results, we concluded that variations in heart and breathing rates are confounding factors in the assessment of interoceptive abilities and relative fluctuations in breathing and heart rates should be considered to be a mode of covariate measurement of interoceptive processes.

Whole-Head Functional Near-Infrared Spectroscopy as an Ecological Monitoring Tool for Assessing Cortical Activity in Parkinson's Disease Patients at Different Stages

Functional near-infrared spectroscopy (fNIRS) is increasingly employed as an ecological neuroimaging technique in assessing age-related chronic neurological disorders, such as Parkinson's disease (PD), mainly providing a cross-sectional characterization of clinical phenotypes in ecological settings. Current fNIRS studies in PD have investigated the effects of motor and non-motor impairment on cortical activity during gait and postural stability tasks, but no study has employed fNIRS as an ecological neuroimaging tool to assess PD at different stages. Therefore, in this work, we sought to investigate the cortical activity of PD patients during a motor grasping task and its relationship with both the staging of the pathology and its clinical variables. This study considered 39 PD patients (age 69.0 ± 7.64, 38 right-handed), subdivided into two groups at different stages by the Hoehn and Yahr (HY) scale: early PD (ePD; N = 13, HY = [1; 1.5]) and moderate PD (mPD; N = 26, HY = [2; 2.5; 3]). We employed a whole-head fNIRS system with 102 measurement channels to monitor brain activity. Group-level activation maps and region of interest (ROI) analysis were computed for ePD, mPD, and ePD vs. mPD contrasts. A ROI-based correlation analysis was also performed with respect to contrasted subject-level fNIRS data, focusing on age, a Cognitive Reserve Index questionnaire (CRIQ), disease duration, the Unified Parkinson's Disease Rating Scale (UPDRS), and performances in the Stroop Color and Word (SCW) test. We observed group differences in age, disease duration, and the UPDRS, while no significant differences were found for CRIQ or SCW scores. Group-level activation maps revealed that the ePD group presented higher activation in motor and occipital areas than the mPD group, while the inverse trend was found in frontal areas. Significant correlations with CRIQ, disease duration, the UPDRS, and the SCW were mostly found in non-motor areas. The results are in line with current fNIRS and functional and anatomical MRI scientific literature suggesting that non-motor areas-primarily the prefrontal cortex area-provide a compensation mechanism for PD motor impairment. fNIRS may serve as a viable support for the longitudinal assessment of therapeutic and rehabilitation procedures, and define new prodromal, low-cost, and ecological biomarkers of disease progression.

Individual-Specific Characterization of Event-Related Hemodynamic Responses during an Auditory Task: An Exploratory Study

Functional near-infrared spectroscopy (fNIRS) has been established as an informative modality for understanding the hemodynamic-metabolic correlates of cortical auditory processing. To date, such knowledge has shown broad clinical applications in the diagnosis, treatment, and intervention procedures in disorders affecting auditory processing; however, exploration of the hemodynamic response to auditory tasks is yet incomplete. This holds particularly true in the context of auditory event-related fNIRS experiments, where preliminary work has shown the presence of valid responses while leaving the need for more comprehensive explorations of the hemodynamic correlates of event-related auditory processing. In this study, we apply an individual-specific approach to characterize fNIRS-based hemodynamic changes during an auditory task in healthy adults. Oxygenated hemoglobin (HbO₂) concentration change time courses were acquired from eight participants. Independent component analysis (ICA) was then applied to isolate individual-specific class discriminative spatial filters, which were then applied to HbO₂ time courses to extract auditory-related hemodynamic features. While six of eight participants produced significant class discriminative features before ICA-based spatial filtering, the proposed method identified significant auditory hemodynamic features in all participants. Furthermore, ICA-based filtering improved correlation between trial labels and extracted features in every participant. For the first time, this study demonstrates hemodynamic features important in experiments exploring auditory processing as well as the utility of individual-specific ICA-based spatial filtering in fNIRS-based feature extraction techniques in auditory experiments. These outcomes provide insights for future studies exploring auditory hemodynamic characteristics and may eventually provide a baseline framework for better understanding auditory response dysfunctions in clinical populations.

Cross-modal functional connectivity supports speech understanding in cochlear implant users

Sensory deprivation can lead to cross-modal cortical changes, whereby sensory brain regions deprived of input may be recruited to perform atypical function. Enhanced cross-modal responses to visual stimuli observed in auditory cortex of postlingually deaf cochlear implant (CI) users are hypothesized to reflect increased activation of cortical language regions, but it is unclear if this cross-modal activity is "adaptive" or "mal-adaptive" for speech understanding. To determine if increased activation of language regions is correlated with better speech understanding in CI users, we assessed task-related activation and functional connectivity of auditory and visual cortices to auditory and visual speech and non-speech stimuli in CI users (n = 14) and normal-hearing listeners (n = 17) and used functional near-infrared spectroscopy to measure hemodynamic responses. We used visually presented speech and non-speech to investigate neural processes related to linguistic content and observed that CI users show beneficial cross-modal effects. Specifically, an increase in connectivity between the left auditory and visual cortices-presumed primary sites of cortical language processing-was positively correlated with CI users' abilities to understand speech in background noise. Cross-modal activity in auditory cortex of postlingually deaf CI users may reflect adaptive activity of a distributed, multimodal speech network, recruited to enhance speech understanding.

Concurrent fNIRS and EEG for Brain Function Investigation: A Systematic, Methodology-Focused Review

Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) stand as state-of-the-art techniques for non-invasive functional neuroimaging. On a unimodal basis, EEG has poor spatial resolution while presenting high temporal resolution. In contrast, fNIRS offers better spatial resolution, though it is constrained by its poor temporal resolution. One important merit shared by the EEG and fNIRS is that both modalities have favorable portability and could be integrated into a compatible experimental setup, providing a compelling ground for the development of a multimodal fNIRS-EEG integration analysis approach. Despite a growing number of studies using concurrent fNIRS-EEG designs reported in recent years, the methodological reference of past studies remains unclear. To fill this knowledge gap, this review critically summarizes the status of analysis methods currently used in concurrent fNIRS-EEG studies, providing an up-to-date overview and guideline for future projects to conduct concurrent fNIRS-EEG studies. A literature search was conducted using PubMed and Web of Science through 31 August 2021. After screening and qualification assessment, 92 studies involving concurrent fNIRS-EEG data recordings and analyses were included in the final methodological review. Specifically, three methodological categories of concurrent fNIRS-EEG data analyses, including EEG-informed fNIRS analyses, fNIRS-informed EEG analyses, and parallel fNIRS-EEG analyses, were identified and explained with detailed description. Finally, we highlighted current challenges and potential directions in concurrent fNIRS-EEG data analyses in future research.

The presence of adjacent others facilitates interpersonal neural synchronization in the left prefrontal cortex during a simple addition task

The hyperscanning technique, that is, simultaneous measurement of neural signals in more than one person, is a powerful research tool for understanding humans' social interactions. In recent years, many studies have investigated interpersonal neural synchronization during various types of communication processes. However, there has been little focus on the impact of the presence of others without explicit social interaction, despite the mere presence of others having been suggested as influencing behavior. In this study, we clarify whether neural signals during a self-paced, repeated, addition task are synchronized when another individual is adjacent without direct interaction. Twenty pairs of participants were measured using a hyperscanning approach with near-infrared spectroscopy. The results show that interpersonal neural synchronization of the task-related signal in the left forehead region was enhanced under the condition of being adjacent to another participant. By contrast, a significant decrease in neural synchronization in the center of the forehead region, where increased neural synchronization is often reported in explicit communication, was observed. Thus, the results indicate that the adjacency of others modulates interpersonal neural synchronization in the task-related signal, and the effect on cognitive processing is different from that of explicit social interaction.

Phase-dependent Brain Activation of the Frontal and Parietal Regions During Walking After Stroke - An fNIRS Study

Background

Recovery of walking post-stroke is highly variable. Accurately measuring and documenting functional brain activation characteristics during walking can help guide rehabilitation. Previous work in this area has been limited to investigations of frontal brain regions and have not utilized recent technological and analytical advances for more accurate measurements. There were three aims for this study: to characterize the hemodynamic profile during walking post-stroke, to investigate regional changes in brain activation during different phases of walking, and to related brain changes to clinical measures.

Methods

Functional near-infrared spectroscopy (fNIRS) along the pre-frontal, premotor, sensorimotor, and posterior parietal cortices was used on twenty individuals greater than six months post-stroke. Individual fNIRS optodes were digitized and used to estimate channel locations on each participant and short separation channels were used to control for extracerebral hemodynamic changes. Participants walked at their comfortable pace several times along a hallway while brain activation was recorded. Exploratory cluster analysis was conducted to determine if there was a link between brain activation and clinical measures.

Results

Sustained activation was observed in the pre-frontal cortex with the ipsilesional hemisphere showing greater activation compared to the contralesional side. Sensorimotor cortex was active during the early, acceleration stage of walking only. Posterior parietal cortex showed changes in activation during the later, steady-state stage of walking. Faster gait speeds also related to increased activation in contralesional sensorimotor and posterior parietal cortices. Exploratory analysis clustered participants into two distinct groups based on their brain activation profiles and generally showed that individuals with greater activation tended to have better physical outcomes.

Conclusions

These findings can guide future research for obtaining adequate power and determining factors that can be used as effect modifiers to reduce inter-subject variability. Overall, this is the first study to report specific oxygenated and deoxygenated hemoglobin changes in frontal to parietal regions during walking in the stroke population. Our results shed light on the importance of measuring brain activation across the cortex and show the importance of pre-frontal, sensorimotor, and posterior parietal cortices in walking after a stroke.

An Exploratory Analysis of the Neural Correlates of Human-Robot Interactions With Functional Near Infrared Spectroscopy

Functional near infrared spectroscopy (fNIRS) has been gaining increasing interest as a practical mobile functional brain imaging technology for understanding the neural correlates of social cognition and emotional processing in the human prefrontal cortex (PFC). Considering the cognitive complexity of human-robot interactions, the aim of this study was to explore the neural correlates of emotional processing of congruent and incongruent pairs of human and robot audio-visual stimuli in the human PFC with fNIRS methodology. Hemodynamic responses from the PFC region of 29 subjects were recorded with fNIRS during an experimental paradigm which consisted of auditory and visual presentation of human and robot stimuli. Distinct neural responses to human and robot stimuli were detected at the dorsolateral prefrontal cortex (DLPFC) and orbitofrontal cortex (OFC) regions. Presentation of robot voice elicited significantly less hemodynamic response than presentation of human voice in a left OFC channel. Meanwhile, processing of human faces elicited significantly higher hemodynamic activity when compared to processing of robot faces in two left DLPFC channels and a left OFC channel. Significant correlation between the hemodynamic and behavioral responses for the face-voice mismatch effect was found in the left OFC. Our results highlight the potential of fNIRS for unraveling the neural processing of human and robot audio-visual stimuli, which might enable optimization of social robot designs and contribute to elucidation of the neural processing of human and robot stimuli in the PFC in naturalistic conditions.

Frontal, Sensorimotor, and Posterior Parietal Regions Are Involved in Dual-Task Walking After Stroke

Background

Walking within the community requires the ability to walk while simultaneously completing other tasks. After a stroke, completing an additional task while walking is significantly impaired, and it is unclear how the functional activity of the brain may impact this.

Methods

Twenty individual in the chronic stage post-stroke participated in this study. Functional near-infrared spectroscopy (fNIRS) was used to measure prefrontal, pre-motor, sensorimotor, and posterior parietal cortices during walking and walking while completing secondary verbal tasks of varying difficulty. Changes in brain activity during these tasks were measured and relationships were accessed between brain activation changes and cognitive or motor abilities.

Results

Significantly larger activations were found for prefrontal, pre-motor, and posterior parietal cortices during dual-task walking. Increasing dual-task walking challenge did not result in an increase in brain activation in these regions. Higher general cognition related to lower increases in activation during the easier dual-task. With the harder dual-task, a trend was also found for higher activation and less motor impairment.

Conclusions

This is the first study to show that executive function, motor preparation/planning, and sensorimotor integration areas are all important for dual-task walking post-stroke. A lack of further brain activation increase with increasing challenge suggests a point at which a trade-off between brain activation and performance occurs. Further research is needed to determine if training would result in further increases in brain activity or improved performance.

Frequency-domain analysis of fNIRS fluctuations induced by rhythmic mental arithmetic

Functional near‐infrared spectroscopy (fNIRS) is an increasingly used technology for imaging neural correlates of cognitive processes. However, fNIRS signals are commonly impaired by task‐evoked and spontaneous hemodynamic oscillations of non‐cerebral origin, a major challenge in fNIRS research. In an attempt to isolate the task‐evoked cortical response, we investigated the coupling between hemodynamic changes arising from superficial and deep layers during mental effort. For this aim, we applied a rhythmic mental arithmetic task to induce cyclic hemodynamic fluctuations suitable for effective frequency‐resolved measurements. Twenty university students aged 18–25 years (eight males) underwent the task while hemodynamic changes were monitored in the forehead using a newly developed NIRS device, capable of multi‐channel and multi‐distance recordings. We found significant task‐related fluctuations for oxy‐ and deoxy‐hemoglobin, highly coherent across shallow and deep tissue layers, corroborating the strong influence of surface hemodynamics on deep fNIRS signals. Importantly, after removing such surface contamination by linear regression, we show that the frontopolar cortex response to a mental math task follows an unusual inverse oxygenation pattern. We confirm this finding by applying for the first time an alternative method to estimate the neural signal, based on transfer function analysis and phasor algebra. Altogether, our results demonstrate the feasibility of using a rhythmic mental task to impose an oscillatory state useful to separate true brain functional responses from those of non‐cerebral origin. This separation appears to be essential for a better understanding of fNIRS data and to assess more precisely the dynamics of the neuro‐visceral link.

We proposed the use of rhythmic mental arithmetic tasks to induce cyclic oscillations in multi‐distance fNIRS signals measured on the forehead, suitable for effective frequency‐domain analysis to better identify the actual neural functional response. We confirm the impairment of deep signals by task‐evoked non‐cerebral confounds, while providing evidence for an inverse oxygenation response in the frontopolar cortex.

Individual differences in skill acquisition and transfer assessed by dual task training performance and brain activity

Assessment of expertise development during training program primarily consists of evaluating interactions between task characteristics, performance, and mental load. Such a traditional assessment framework may lack consideration of individual characteristics when evaluating training on complex tasks, such as driving and piloting, where operators are typically required to execute multiple tasks simultaneously. Studies have already identified individual characteristics arising from intrinsic, context, strategy, personality, and preference as common predictors of performance and mental load. Therefore, this study aims to investigate the effect of individual difference in skill acquisition and transfer using an ecologically valid dual task, behavioral, and brain activity measures. Specifically, we implemented a search and surveillance task (scanning and identifying targets) using a high-fidelity training simulator for the unmanned aircraft sensor operator, acquired behavioral measures (scan, not scan, over scan, and adaptive target find scores) using simulator-based analysis module, and measured brain activity changes (oxyhemoglobin and deoxyhemoglobin) from the prefrontal cortex (PFC) using a portable functional near-infrared spectroscopy (fNIRS) sensor array. The experimental protocol recruited 13 novice participants and had them undergo three easy and two hard sessions to investigate skill acquisition and transfer, respectively. Our results from skill acquisition sessions indicated that performance on both tasks did not change when individual differences were not accounted for. However inclusion of individual differences indicated that some individuals improved only their scan performance (Attention-focused group), while others improved only their target find performance (Accuracy-focused group). Brain activity changes during skill acquisition sessions showed that mental load decreased in the right anterior medial PFC (RAMPFC) in both groups regardless of individual differences. However, mental load increased in the left anterior medial PFC (LAMPFC) of Attention-focused group and decreased in the Accuracy-focused group only when individual differences were included. Transfer results showed no changes in performance regardless of grouping based on individual differences; however, mental load increased in RAMPFC of Attention-focused group and left dorsolateral PFC (LDLPFC) of Accuracy-focused group. Efficiency and involvement results suggest that the Attention-focused group prioritized the scan task, while the Accuracy-focused group prioritized the target find task. In conclusion, training on multitasks results in individual differences. These differences may potentially be due to individual preference. Future studies should incorporate individual differences while assessing skill acquisition and transfer during multitask training.

Oscillator decomposition of infant fNIRS data

The functional near-infrared spectroscopy (fNIRS) can detect hemodynamic responses in the brain and the data consist of bivariate time series of oxygenated hemoglobin (oxy-Hb) and deoxygenated hemoglobin (deoxy-Hb) on each channel. In this study, we investigate oscillatory changes in infant fNIRS signals by using the oscillator decompisition method (OSC-DECOMP), which is a statistical method for extracting oscillators from time series data based on Gaussian linear state space models. OSC-DECOMP provides a natural decomposition of fNIRS data into oscillation components in a data-driven manner and does not require the arbitrary selection of band-pass filters. We analyzed 18-ch fNIRS data (3 minutes) acquired from 21 sleeping 3-month-old infants. Five to seven oscillators were extracted on most channels, and their frequency distribution had three peaks in the vicinity of 0.01-0.1 Hz, 1.6-2.4 Hz and 3.6-4.4 Hz. The first peak was considered to reflect hemodynamic changes in response to the brain activity, and the phase difference between oxy-Hb and deoxy-Hb for the associated oscillators was at approximately 230 degrees. The second peak was attributed to cardiac pulse waves and mirroring noise. Although these oscillators have close frequencies, OSC-DECOMP can separate them through estimating their different projection patterns on oxy-Hb and deoxy-Hb. The third peak was regarded as the harmonic of the second peak. By comparing the Akaike Information Criterion (AIC) of two state space models, we determined that the time series of oxy-Hb and deoxy-Hb on each channel originate from common oscillatory activity. We also utilized the result of OSC-DECOMP to investigate the frequency-specific functional connectivity. Whereas the brain oscillator exhibited functional connectivity, the pulse waves and mirroring noise oscillators showed spatially homogeneous and independent changes. OSC-DECOMP is a promising tool for data-driven extraction of oscillation components from biological time series data.

Effective brain network analysis in unilateral and bilateral upper limb exercise training in subjects with stroke

PURPOSE

Knowing the patterns of brain activation that occur and networks involved under different interventions is important for motor recovery in subjects with stroke. This study aimed to study the patterns of brain activation and networks in two interventions, affected upper limb side and bilateral exercise training, using concurrent functional near-infrared spectroscopy (fNIRS) imaging.

METHODS

Thirty-two patients in the early subacute stage were randomly divided into two groups: unilateral and bilateral groups. The patients in the unilateral group underwent isokinetic muscle strength training on the affected upper limb side and patients in the bilateral group underwent bilateral upper limb training. Oxyhemoglobin and deoxyhemoglobin concentration changes (ΔHbO₂ and ΔHbR, respectively) were recorded in the ipsilateral and contralateral prefrontal cortex (IPFC and CPFC, respectively) and ipsilateral and contralateral motor cortex (IMC and CMC, respectively) by fNIRS equipment in the resting state and training conditions. The phase information of a 0.01-0.08 Hz fNIRS signal was extracted by the wavelet transform method. Dynamic Bayesian inference was adopted to calculate the coupling strength and direction of effective connectivity. The network threshold was determined by surrogate signal method, the global (weighted clustering coefficient, global efficiency and small-worldness) and local (degree, betweenness centrality and local efficiency) network metrics were calculated. The degree of cerebral lateralization was also compared between the two groups.

RESULTS

The results of covariance analysis showed that, compared with bilateral training, the coupling effect of CMC→IMC was significantly enhanced (p = 0.03); also, the local efficiency of the IMC (p = 0.01), IPFC (p<0.001), and CPFC (p = 0.006) and the hemispheric autonomy index of IPFC (p = 0.007) were significantly increased in unilateral training. In addition, there was a significant positive correlation between the coupling intensity of the inter-hemispheric motor area and the shifted local efficiency.

CONCLUSIONS

The results indicated that unilateral upper limb training could more effectively promote the interaction and balance of bilateral motor hemispheres and help brain reorganization in the IMC and prefrontal cortex in stroke patients. The method provided in this study could be used to evaluate dynamic brain activation and network reorganization under different interventions, thus improving the strategy of rehabilitation intervention in a timely manner and resulting in better motor recovery. This article is protected by copyright. All rights reserved.

Effects of Systemic Physiology on Mapping Resting-State Networks Using Functional Near-Infrared Spectroscopy

Resting-state functional connectivity (rsFC) has gained popularity mainly due to its simplicity and potential for providing insights into various brain disorders. In this vein, functional near-infrared spectroscopy (fNIRS) is an attractive choice due to its portability, flexibility, and low cost, allowing for bedside imaging of brain function. While promising, fNIRS suffers from non-neural signal contaminations (i.e., systemic physiological noise), which can increase correlation across fNIRS channels, leading to spurious rsFC networks. In the present work, we hypothesized that additional measurements with short channels, heart rate, mean arterial pressure, and end-tidal CO2 could provide a better understanding of the effects of systemic physiology on fNIRS-based resting-state networks. To test our hypothesis, we acquired 12 min of resting-state data from 10 healthy participants. Unlike previous studies, we investigated the efficacy of different pre-processing approaches in extracting resting-state networks. Our results are in agreement with previous studies and reinforce the fact that systemic physiology can overestimate rsFC. We expanded on previous work by showing that removal of systemic physiology decreases intra- and inter-subject variability, increasing the ability to detect neural changes in rsFC across groups and over longitudinal studies. Our results show that by removing systemic physiology, fNIRS can reproduce resting-state networks often reported with functional magnetic resonance imaging (fMRI). Finally, the present work details the effects of systemic physiology and outlines how to remove (or at least ameliorate) their contributions to fNIRS signals acquired at rest.

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

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

fNIRS brain measures of ongoing nociception during surgical incisions under anesthesia

Significance: Functional near-infrared spectroscopy (fNIRS) has evaluated pain in awake and anesthetized states. Aim: We evaluated fNIRS signals under general anesthesia in patients undergoing knee surgery for anterior cruciate ligament repair. Approach: Patients were split into groups: those with regional nerve block (NB) and those without (non-NB). Continuous fNIRS measures came from three regions: the primary somatosensory cortex (S1), known to be involved in evaluation of nociception, the lateral prefrontal cortex (BA9), and the polar frontal cortex (BA10), both involved in higher cortical functions (such as cognition and emotion). Results: Our results show three significant differences in fNIRS signals to incision procedures between groups: (1) NB compared with non-NB was associated with a greater net positive hemodynamic response to pain procedures in S1; (2) dynamic correlation between the prefrontal cortex (PreFC) and S1 within 1 min of painful procedures are anticorrelated in NB while positively correlated in non-NB; and (3) hemodynamic measures of activation were similar at two separate time points during surgery (i.e., first and last incisions) in PreFC and S1 but showed significant differences in their overlap. Comparing pain levels immediately after surgery and during discharge from postoperative care revealed no significant differences in the pain levels between NB and non-NB. Conclusion: Our data suggest multiple pain events that occur during surgery using devised algorithms could potentially give a measure of "pain load." This may allow for evaluation of central sensitization (i.e., a heightened state of the nervous system where noxious and non-noxious stimuli is perceived as painful) to postoperative pain levels and the resulting analgesic consumption. This evaluation could potentially predict postsurgical chronic neuropathic pain.

Multimodal Autoencoder Predicts fNIRS Resting State From EEG Signals

In this work, we introduce a deep learning architecture for evaluation on multimodal electroencephalographic (EEG) and functional near-infrared spectroscopy (fNIRS) recordings from 40 epileptic patients. Long short-term memory units and convolutional neural networks are integrated within a multimodal sequence-to-sequence autoencoder. The trained neural network predicts fNIRS signals from EEG, sans a priori, by hierarchically extracting deep features from EEG full spectra and specific EEG frequency bands. Results show that higher frequency EEG ranges are predictive of fNIRS signals with the gamma band inputs dominating fNIRS prediction as compared to other frequency envelopes. Seed based functional connectivity validates similar patterns between experimental fNIRS and our model's fNIRS reconstructions. This is the first study that shows it is possible to predict brain hemodynamics (fNIRS) from encoded neural data (EEG) in the resting human epileptic brain based on power spectrum amplitude modulation of frequency oscillations in the context of specific hypotheses about how EEG frequency bands decode fNIRS signals.

Evaluation of fNIRS signal components elicited by cognitive and hypercapnic stimuli

Functional near infrared spectroscopy (fNIRS) measurements are confounded by signal components originating from multiple physiological causes, whose activities may vary temporally and spatially (across tissue layers, and regions of the cortex). Furthermore, the stimuli can induce evoked effects, which may lead to over or underestimation of the actual effect of interest. Here, we conducted a temporal, spectral, and spatial analysis of fNIRS signals collected during cognitive and hypercapnic stimuli to characterize effects of functional versus systemic responses. We utilized wavelet analysis to discriminate physiological causes and employed long and short source-detector separation (SDS) channels to differentiate tissue layers. Multi-channel measures were analyzed further to distinguish hemispheric differences. The results highlight cardiac, respiratory, myogenic, and very low frequency (VLF) activities within fNIRS signals. Regardless of stimuli, activity within the VLF band had the largest contribution to the overall signal. The systemic activities dominated the measurements from the short SDS channels during cognitive stimulus, but not hypercapnic stimulus. Importantly, results indicate that characteristics of fNIRS signals vary with type of the stimuli administered as cognitive stimulus elicited variable responses between hemispheres in VLF band and task-evoked temporal effect in VLF, myogenic and respiratory bands, while hypercapnic stimulus induced a global response across both hemispheres.

Characterization of Mayer-wave oscillations in functional near-infrared spectroscopy using a physiologically informed model of the neural power spectra

Significance: Mayer waves are spontaneous oscillations in arterial blood pressure that can mask cortical hemodynamic responses associated with neural activity of interest. Aim: We aim to characterize the properties of oscillations in the functional near-infrared spectroscopy (fNIRS) signal generated by Mayer waves in a large sample of fNIRS recordings. Further, we aim to determine the impact of short-channel correction for the attenuation of these unwanted signal components. Approach: Mayer-wave oscillation parameters were extracted from 310 fNIRS measurements using the fitting oscillations and one-over-f method to compute normative values. The effect of short-channel correction on Mayer-wave oscillation power was quantified on 222 measurements. The practical benefit of the short-channel correction approach for reducing Mayer waves and improving response detection was also evaluated on a subgroup of 17 fNIRS measurements collected during a passive auditory speech detection experiment. Results: Mayer-wave oscillations had a mean frequency of 0.108 Hz, bandwidth of 0.04 Hz, and power of 3.5    μ M 2 / Hz . The distribution of oscillation signal power was positively skewed, with some measurements containing large Mayer waves. Short-channel correction significantly reduced the amplitude of these undesired signals; greater attenuation was observed for measurements containing larger Mayer-wave oscillations. Conclusions: A robust method for quantifying Mayer-wave oscillations in the fNIRS signal spectrum was presented and used to provide normative parameterization. Short-channel correction is recommended as an approach for attenuating Mayer waves, particularly in participants with large oscillations.

fNIRS Evidence for Distinguishing Patients With Major Depression and Healthy Controls

In recent years, major depressive disorder (MDD) has been shown to negatively impact physical recovery in a variety of patients. Functional near-infrared spectroscopy (fNIRS) is a tool that can potentially supplement clinical interviews and mental state examinations to establish a psychiatric diagnosis and monitor treatment progress. Thirty-two subjects, including 16 patients clinically diagnosed with MDD and 16 healthy controls (HCs), participated in the study. Brain oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) responses were recorded using a 22-channel continuous-wave fNIRS device while the subjects performed the emotional sound test. This study evaluated the difference between MDD patients and HCs using a variety of methods. In a comparison of the Pearson correlation coefficients between the HbO/HbR responses of each fNIRS channel and four scores, MDD patients and HCs had significantly different Athens Insomnia Scale (AIS) scores. By quantitative evaluation of the functional association, we found that MDD patients had aberrant functional connectivity compared with HCs. Furthermore, we concluded that compared with HCs, there were marked abnormalities in blood oxygen in the bilateral ventrolateral prefrontal cortex (VLPFC) and bilateral dorsolateral prefrontal cortex (DLPFC). Four statistical-based features extracted from HbO signals and four vector-based features from both HbO and HbR served as inputs to four simple neural networks (multilayer neural network (MNN), feedforward neural network (FNN), cascade forward neural network (CFNN) and recurrent neural network (RNN)). Through an analysis of combinations of different features, the combination of 4 common features (mean, STD, area under the receiver operating characteristic curve (AUC) and slope) yielded the highest classification accuracy of 89.74% for fear emotion. The combination of four novel feature (CBV, COE, |L | and K) resulted in a classification accuracy of 99.94% for fear emotion. The top 10 common and novel features were selected by the ReliefF feature selection algorithm, resulting in classification accuracies of 83.52% and 91.99%, respectively. This study identified the AUC and angle K as specific neuromarkers for predicting MDD across specific depression-related regions of the prefrontal cortex (PFC). These findings suggest that the fNIRS measurement of the PFC may serve as a supplementary test in routine clinical practice to further support a diagnosis of MDD.

Acupuncture With deqi Modulates the Hemodynamic Response and Functional Connectivity of the Prefrontal-Motor Cortical Network

As a world intangible cultural heritage, acupuncture is considered an essential modality of complementary and alternative therapy to Western medicine. Despite acupuncture’s long history and public acceptance, how the cortical network is modulated by acupuncture remains largely unclear. Moreover, as the basic acupuncture unit for regulating the central nervous system, how the cortical network is modulated during acupuncture at the Hegu acupoint is mostly unclear. Here, multi-channel functional near-infrared spectroscopy (fNIRS) data were recorded from twenty healthy subjects for acupuncture manipulation, pre- and post-manipulation tactile controls, and pre- and post-acupuncture rest controls. Results showed that: (1) acupuncture manipulation caused significantly increased acupuncture behavioral deqi performance compared with tactile controls. (2) The bilateral prefrontal cortex (PFC) and motor cortex were significantly inhibited during acupuncture manipulation than controls, which was evidenced by the decreased power of oxygenated hemoglobin (HbO) concentration. (3) The bilateral PFC’s hemodynamic responses showed a positive correlation trend with acupuncture behavioral performance. (4) The network connections with bilateral PFC as nodes showed significantly increased functional connectivity during acupuncture manipulation compared with controls. (5) Meanwhile, the network’s efficiency was improved by acupuncture manipulation, evidenced by the increased global efficiency and decreased shortest path length. Taken together, these results reveal that a cooperative PFC-Motor functional network could be modulated by acupuncture manipulation at the Hegu acupoint. This study provides neuroimaging evidence that explains acupuncture’s neuromodulation effects on the cortical network.

Changes in Sensorimotor Cortical Activation in Children Using Prostheses and Prosthetic Simulators

This study aimed to examine the neural responses of children using prostheses and prosthetic simulators to better elucidate the emulation abilities of the simulators. We utilized functional near-infrared spectroscopy (fNIRS) to evaluate the neural response in five children with a congenital upper limb reduction (ULR) using a body-powered prosthesis to complete a 60 s gross motor dexterity task. The ULR group was matched with five typically developing children (TD) using their non-preferred hand and a prosthetic simulator on the same hand. The ULR group had lower activation within the primary motor cortex (M1) and supplementary motor area (SMA) compared to the TD group, but nonsignificant differences in the primary somatosensory area (S1). Compared to using their non-preferred hand, the TD group exhibited significantly higher action in S1 when using the simulator, but nonsignificant differences in M1 and SMA. The non-significant differences in S1 activation between groups and the increased activation evoked by the simulator's use may suggest rapid changes in feedback prioritization during tool use. We suggest that prosthetic simulators may elicit increased reliance on proprioceptive and tactile feedback during motor tasks. This knowledge may help to develop future prosthesis rehabilitative training or the improvement of tool-based skills.

The role of anterior prefrontal cortex (area 10) in face-to-face deception measured with fNIRS

Anterior prefrontal cortex (PFC, Brodmann area 10) activations are often, but not always, found in neuroimaging studies investigating deception, and the precise role of this area remains unclear. To explore the role of the PFC in face-to-face deception, we invited pairs of participants to play a card game involving lying and lie detection while we used functional near infrared spectroscopy (fNIRS) to record brain activity in the PFC. Participants could win points for successfully lying about the value of their cards or for detecting lies. We contrasted patterns of brain activation when the participants either told the truth or lied, when they were either forced into this or did so voluntarily and when they either succeeded or failed to detect a lie. Activation in the anterior PFC was found in both lie production and detection, unrelated to reward. Analysis of cross-brain activation patterns between participants identified areas of the PFC where the lead player’s brain activity synchronized their partner’s later brain activity. These results suggest that during situations that involve close interpersonal interaction, the anterior PFC supports processing widely involved in deception, possibly relating to the demands of monitoring one’s own and other people’s behaviour.

Compromised Brain Activity With Age During a Game-Like Dynamic Balance Task: Single- vs. Dual-Task Performance

Background: Postural control and cognition are affected by aging. We investigated whether cognitive distraction influenced neural activity differently in young and older adults during a game-like mediolateral weight-shifting task with a personalized task load.

Methods: Seventeen healthy young and 17 older adults performed a balance game, involving hitting virtual wasps, serial subtractions and a combination of both (dual-task). A motion analysis system estimated each subject's center of mass position. Cortical activity in five regions was assessed by measuring oxygenated hemoglobin (HbO₂) with a functional Near-Infrared Spectroscopy system.

Results: When adding cognitive load to the game, weight-shifting speed decreased irrespective of age, but older adults reduced the wasp-hits more than young adults. Accompanying these changes, older adults decreased HbO₂ in the left pre-frontal cortex (PFC) and frontal eye fields (FEF) compared to single-tasking, a finding not seen in young adults. Additionally, lower HbO₂ levels were found during dual-tasking compared to the summed activation of the two single tasks in all regions except for the right PFC. These relative reductions were specific for the older age group in the left premotor cortex (PMC), the right supplementary motor area (SMA), and the left FEF.

Conclusion: Older adults showed more compromised neural activity than young adults when adding a distraction to a challenging balance game. We interpret these changes as competitive downgrading of neural activity underpinning the age-related deterioration of game performance during dual-tasking. Future work needs to ascertain if older adults can train their neural flexibility to withstand balance challenges during daily life activities.

Cortical thinning is associated with brain pulsatility in older adults: An MRI and NIRS study

Aging is accompanied by global brain atrophy occurring unequally across the brain. Cortical thinning is seen with aging with a larger loss in the frontal and temporal subregions. We explored the link between regional cortical thickness and regional cerebral pulsatility. Sixty healthy individuals were divided into two age groups, young (aged 19-31) and older (aged 65-75) adults. Each participant underwent a near-infrared spectroscopy (NIRS) scan to index regional brain pulsatility from cerebral pulse-transit-time-to-the peak-of-the-pulse (PTTp), an anatomical magnetic resonance imaging (MRI) and a phase-contrast MRI (PC-MRI) scan to measure arterial and cerebrospinal fluid (CSF) pulsatility. In older adults, the greatest association between cerebral pulsatility and cortical thickness was found in superior and middle temporal and superior, middle and inferior frontal areas, which are the regions perfused first by the internal carotid arteries. This association dropped in the postcentral and superior parietal regions. These findings suggest higher brain pulsatility as a potential risk factor contributing to cortical thinning for some brain regions more than others.