A systematic comparison of motion artifact correction techniques for functional near-infrared spectroscopy

Distinguishing motion artifacts during optical fiber-based in-vivo hemodynamics recordings from brain regions of freely moving rodents

Significance

Motion artifacts in the signals recorded during optical fiber-based measurements can lead to misinterpretation of data. In this work, we address this problem during in-vivo rodent experiments and develop a motion artifacts correction (MAC) algorithm for single-fiber system (SFS) hemodynamics measurements from the brains of rodents.

Aim

(i) To distinguish the effect of motion artifacts in the SFS signals. (ii) Develop a MAC algorithm by combining information from the experiments and simulations and validate it.

Approach

Monte-Carlo (MC) simulations were performed across 450 to 790 nm to identify wavelengths where the reflectance is least sensitive to blood absorption-based changes. This wavelength region is then used to develop a quantitative metric to measure motion artifacts, termed the dissimilarity metric (DM). We used MC simulations to mimic artifacts seen during experiments. Further, we developed a mathematical model describing light intensity at various optical interfaces. Finally, an MAC algorithm was formulated and validated using simulation and experimental data.

Results

We found that the 670 to 680 nm wavelength region is relatively less sensitive to blood absorption. The standard deviation of DM (σ D M ) can measure the relative magnitude of motion artifacts in the SFS signals. The artifacts cause rapid shifts in the reflectance data that can be modeled as transmission changes in the optical lightpath. The changes observed during the experiment were found to be in agreement to those obtained from MC simulations. The mathematical model developed to model transmission changes to represent motion artifacts was extended to an MAC algorithm. The MAC algorithm was validated using simulations and experimental data.

Conclusions

We distinguished motion artifacts from SFS signals during in vivo hemodynamic monitoring experiments. From simulation and experimental data, we showed that motion artifacts can be modeled as transmission changes. The developed MAC algorithm was shown to minimize artifactual variations in both simulation and experimental data.

Flexible circuit-based spatially aware modular optical brain imaging system for high-density measurements in natural settings

Significance

Functional near-infrared spectroscopy (fNIRS) presents an opportunity to study human brains in everyday activities and environments. However, achieving robust measurements under such dynamic conditions remains a significant challenge.

Aim

The modular optical brain imaging (MOBI) system is designed to enhance optode-to-scalp coupling and provide a real-time probe three-dimensional (3D) shape estimation to improve the use of fNIRS in everyday conditions.

Approach

The MOBI system utilizes a bendable and lightweight modular circuit-board design to enhance probe conformity to head surfaces and comfort for long-term wearability. Combined with automatic module connection recognition, the built-in orientation sensors on each module can be used to estimate optode 3D positions in real time to enable advanced tomographic data analysis and motion tracking.

Results

Optical characterization of the MOBI detector reports a noise equivalence power of 8.9 and 7.3    pW / Hz at 735 and 850 nm, respectively, with a dynamic range of 88 dB. The 3D optode shape acquisition yields an average error of 4.2 mm across 25 optodes in a phantom test compared with positions acquired from a digitizer. Results for initial in vivo validations, including a cuff occlusion and a finger-tapping test, are also provided.

Conclusions

To the best of our knowledge, the MOBI system is the first modular fNIRS system featuring fully flexible circuit boards. The self-organizing module sensor network and automatic 3D optode position acquisition, combined with lightweight modules ( 18    g / module ) and ergonomic designs, would greatly aid emerging explorations of brain function in naturalistic settings.

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

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

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.

Brain control of dual-task walking can be improved in aging and neurological disease

The peak prevalence of multiple sclerosis has shifted into older age groups, but co-occurring and possibly synergistic motoric and cognitive declines in this patient population are poorly understood. Dual-task-walking performance, subserved by the prefrontal cortex, and compromised in multiple sclerosis and aging, predicts health outcomes. Whether acute practice can improve dual-task walking performance and prefrontal cortex hemodynamic response efficiency in multiple sclerosis has not been reported. To address this gap in the literature, the current study examined task- and practice-related effects on dual-task-walking and associated brain activation in older adults with multiple sclerosis and controls. Multiple sclerosis (n = 94, mean age = 64.76 ± 4.19 years) and control (n = 104, mean age = 68.18 ± 7.01 years) participants were tested under three experimental conditions (dual-task-walk, single-task-walk, and single-task-alpha) administered over three repeated counterbalanced trials. Functional near-infrared-spectroscopy was used to evaluate task- and practice-related changes in prefrontal cortex oxygenated hemoglobin. Gait and cognitive performances declined, and prefrontal cortex oxygenated hemoglobin was higher in dual compared to both single task conditions in both groups. Gait and cognitive performances improved over trials in both groups. There were greater declines over trials in oxygenated hemoglobin in dual-task-walk compared to single-task-walk in both groups. Among controls, but not multiple sclerosis participants, declines over trials in oxygenated hemoglobin were greater in dual-task-walk compared to single-task-alpha. Dual-task walking and associated prefrontal cortex activation efficiency improved during a single session, but improvement in neural resource utilization, although significant, was attenuated in multiple sclerosis participants. These findings suggest encouraging brain adaptability in aging and neurological disease.

Flexible-circuit-based 3-D aware modular optical brain imaging system for high-density measurements in natural settings

Significance

Functional near-infrared spectroscopy (fNIRS) presents an opportunity to study human brains in everyday activities and environments. However, achieving robust measurements under such dynamic condition remains a significant challenge.

Aim

The modular optical brain imaging (MOBI) system is designed to enhance optode-to-scalp coupling and provide real-time probe 3-D shape estimation to improve the use of fNIRS in everyday conditions.

Approach

The MOBI system utilizes a bendable and lightweight modular circuit-board design to enhance probe conformity to head surfaces and comfort for long-term wearability. Combined with automatic module connection recognition, the built-in orientation sensors on each module can be used to estimate optode 3-D positions in real-time to enable advanced tomographic data analysis and motion tracking.

Results

Optical characterization of the MOBI detector reports a noise equivalence power (NEP) of 8.9 and 7.3 pW / H z at 735 nm and 850 nm, respectively, with a dynamic range of 88 dB. The 3-D optode shape acquisition yields an average error of 4.2 mm across 25 optodes in a phantom test compared to positions acquired from a digitizer. Results for initial in vivo validations, including a cuff occlusion and a finger-tapping test, are also provided.

Conclusions

To the best of our knowledge, the MOBI system is the first modular fNIRS system featuring fully flexible circuit boards. The self-organizing module sensor network and automatic 3-D optode position acquisition, combined with lightweight modules (18 g/module) and ergonomic designs, would greatly aid emerging explorations of brain function in naturalistic settings.

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

Background

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

Objective

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

Methods

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

Results

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

Conclusion

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

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

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

An Ultralow-Power Real-Time Machine Learning Based fNIRS Motion Artifacts Detection

Due to iterative matrix multiplications or gradient computations, machine learning modules often require a large amount of processing power and memory. As a result, they are often not feasible for use in wearable devices, which have limited processing power and memory. In this study, we propose an ultralow-power and real-time machine learning-based motion artifact detection module for functional near-infrared spectroscopy (fNIRS) systems. We achieved a high classification accuracy of 97.42%, low field-programmable gate array (FPGA) resource utilization of 38354 lookup tables and 6024 flip-flops, as well as low power consumption of 0.021 W in dynamic power. These results outperform conventional CPU support vector machine (SVM) methods and other state-of-the-art SVM implementations. This study has demonstrated that an FPGA-based fNIRS motion artifact classifier can be exploited while meeting low power and resource constraints, which are crucial in embedded hardware systems while keeping high classification accuracy.

A new perspective for evaluating the efficacy of tACS and tDCS in improving executive functions: A combined tES and fNIRS study

BACKGROUND

Executive function enhancement is considered necessary for improving the quality of life of patients with neurological or psychiatric disorders, such as attention-deficit/hyperactivity disorder, obsessive-compulsive disorder and Alzheimer's disease. Transcranial electrical stimulation (tES) has been shown to have some beneficial effects on executive functioning, but the quantification of these improvements remains controversial. We aimed to explore the potential beneficial effects on executive functioning induced by the use of transcranial alternating current stimulation (tACS)/transcranial direct current stimulation (tDCS) on the right inferior frontal gyrus (IFG) and the accompanying brain function variations in the resting state.

METHODS

We recruited 229 healthy adults to participate in Experiments 1 (105 participants) and 2 (124 participants). The participants in each experiment were randomly divided into tACS, tDCS, and sham groups. The participants completed cognitive tasks to assess behavior related to three core components of executive functions. Functional near-infrared spectroscopy (fNIRS) was used to monitor the hemodynamic changes in crucial cortical regions in the resting state.

RESULTS

Inhibition and cognitive flexibility (excluding working memory) were significantly increased after tACS/tDCS, but there were no significant behavioral differences between the tACS and tDCS groups. fNIRS revealed that tDCS induced decreases in the functional connectivity (increased neural efficiency) of the relevant cortices.

CONCLUSIONS

Enhancement of executive function was observed after tES, and the beneficial effects of tACS/tDCS may need to be precisely evaluated via brain imaging indicators at rest. tDCS revealed better neural benefits than tACS during the stimulation phase. These findings might provide new insights for selecting intervention methods in future studies and for evaluating the clinical efficacy of tES.

Inter-brain neural mechanism and influencing factors underlying different cooperative behaviors: a hyperscanning study

Cooperative behavior is a vital social interaction which plays a vital role in improving human survival and reproduction. However, few empirical studies have examined the differences between cooperative behaviors and the underlying neural substrates. In the present study, the brain activity of familiar dyads of the same sex was measured using functional near-infrared spectroscopy during three cooperative tasks (cooperative button-press, tangram, and Jenga tasks). We also measured the dyads' empathic abilities and personality traits to investigate the relationships between individual characteristics and neural markers. The results showed that first, there were significant differences in intra-brain activation and inter-brain synchronization among different cooperative tasks in three dimensions: social cognition, behavioral response, and cognitive processing. Second, male participants require stronger intra-brain activation to achieve the same inter-brain synchronization level as women in cooperative tasks. Third, when performing cooperative tasks involving high cognitive demands, Big Five Neuroticism may be an important predictor of neural activation in female participants. Inter-brain synchronization plays an important role in the frontal and temporoparietal junctions during interpersonal cooperation. Furthermore, this study demonstrates that mutual prediction theory is crucial for understanding the neural mechanisms of cooperative behavior.

Effective DBS treatment improves neural information transmission of patients with disorders of consciousness: an fNIRS study

Objective.Deep brain stimulation (DBS) is a potential treatment that promotes the recovery of patients with disorders of consciousness (DOC). This study quantified the changes in consciousness and the neuromodulation effect of DBS on patients with DOC.Approach.Eleven patients were recruited for this study which consists of three conditions: 'Pre' (two days before DBS surgery), 'Post-On' (one month after surgery with stimulation), and 'Post-Off' (one month after surgery without stimulation). Functional near-infrared spectroscopy (fNIRS) was recorded from the frontal lobe, parietal lobe, and occipital lobe of patients during the experiment of auditory stimuli paradigm, in parallel with the coma recovery scale-revised (CRS-R) assessment. The brain hemodynamic states were defined and state transition acceleration was taken to quantify the information transmission strength of the brain network. Linear regression analysis was conducted between the changes in regional and global indicators and the changes in the CRS-R index.Main results.Significant correlation was observed between the changes in the global transition acceleration indicator and the changes in the CRS-R index (slope = 55.910,p< 0.001,R2= 0.732). For the regional indicators, similar correlations were found between the changes in the frontal lobe and parietal lobe indicators and the changes in the CRS-R index (slope = 46.612,p< 0.01,R2= 0.694; slope = 47.491,p< 0.01,R2= 0.676).Significance.Our study suggests that fNIRS-based brain hemodynamics transition analysis can signify the neuromodulation effect of DBS treatment on patients with DOC, and the transition acceleration indicator is a promising brain functional marker for DOC.

Learning based motion artifacts processing in fNIRS: a mini review

This paper provides a concise review of learning-based motion artifacts (MA) processing methods in functional near-infrared spectroscopy (fNIRS), highlighting the challenges of maintaining optimal contact during subject movement, which can lead to MA and compromise data integrity. Traditional strategies often result in reduced reliability of the hemodynamic response and statistical power. Recognizing the limited number of studies focusing on learning-based MA removal, we examine 315 studies, identifying seven pertinent to our focus area. We discuss the current landscape of learning-based MA correction methods and highlight research gaps. Noting the absence of standard evaluation metrics for quality assessment of MA correction, we suggest a novel framework, integrating signal and model quality considerations and employing metrics like ΔSignal-to-Noise Ratio (ΔSNR), confusion matrix, and Mean Squared Error. This work aims to facilitate the application of learning-based methodologies to fNIRS and improve the accuracy and reliability of neurovascular studies.

Neurovascular coupling during auditory stimulation: event-related potentials and fNIRS hemodynamic

Intensity-dependent amplitude changes (IDAP) have been extensively studied using event-related potentials (ERPs) and have been linked to several psychiatric disorders. This study aims to explore the application of functional near-infrared spectroscopy (fNIRS) in IDAP paradigms, which related to ERPs could indicate the existence of neurovascular coupling. Thirty-three and thirty-one subjects participated in two experiments, respectively. The first experiment consisted of the presentation of three-tone intensities (77.9 dB, 84.5 dB, and 89.5 dB) lasting 500 ms, each type randomly presented 54 times, while the second experiment consisted of the presentation of five-tone intensities (70.9 dB, 77.9 dB, 84.5 dB, 89.5 dB, and 94.5 dB) in trains of 8 tones lasting 70 ms each tone, the trains were presented 20 times. EEG was used to measure ERP components: N1, P2, and N1-P2 peak-to-peak amplitude. fNIRS allowed the analysis of the hemodynamic activity in the auditory, visual, and prefrontal cortices. The results showed an increase in N1, P2, and N1-P2 peak-to-peak amplitude with auditory intensity. Similarly, oxyhemoglobin and deoxyhemoglobin concentrations showed amplitude increases and decreases, respectively, with auditory intensity in the auditory and prefrontal cortices. Spearman correlation analysis showed a relationship between the left auditory cortex with N1 amplitude, and the right dorsolateral cortex with P2 amplitude, specifically for deoxyhemoglobin concentrations. These findings suggest that there is a brain response to auditory intensity changes that can be obtained by EEG and fNIRS, supporting the neurovascular coupling process. Overall, this study enhances our understanding of fNIRS application in auditory paradigms and highlights its potential as a complementary technique to ERPs.

Self-calibrated pulse oximetry algorithm based on photon pathlength change and the application in human freedivers

Significance

Pulse oximetry estimates the arterial oxygen saturation of hemoglobin (SaO 2 ) based on relative changes in light intensity at the cardiac frequency. Commercial pulse oximeters require empirical calibration on healthy volunteers, resulting in limited accuracy at low oxygen levels. An accurate, self-calibrated method for estimating SaO 2 is needed to improve patient monitoring and diagnosis.

Aim

Given the challenges of calibration at low SaO 2 levels, we pursued the creation of a self-calibrated algorithm that can effectively estimate SaO 2 across its full range. Our primary objective was to design and validate our calibration-free method using data collected from human subjects.

Approach

We developed an algorithm based on diffuse optical spectroscopy measurements of cardiac pulses and the modified Beer-Lambert law (mBLL). Recognizing that the photon mean pathlength (⟨ L ⟩ ) varies with SaO 2 related absorption changes, our algorithm aligns/fits the normalized ⟨ L ⟩ (across wavelengths) obtained from optical measurements with its analytical representation. We tested the algorithm with human freedivers performing breath-hold dives. A continuous-wave near-infrared spectroscopy probe was attached to their foreheads, and an arterial cannula was inserted in the radial artery to collect arterial blood samples at different stages of the dive. These samples provided ground-truth SaO 2 via a blood gas analyzer, enabling us to evaluate the accuracy of SaO 2 estimation derived from the NIRS measurement using our self-calibrated algorithm.

Results

The self-calibrated algorithm significantly outperformed the conventional method (mBLL with a constant ⟨ L ⟩ ratio) for SaO 2 estimation through the diving period. Analyzing 23 ground-truth SaO 2 data points ranging from 41% to 100%, the average absolute difference between the estimated SaO 2 and the ground truth SaO 2 is 4.23 % ± 5.16 % for our algorithm, significantly lower than the 11.25 % ± 13.74 % observed with the conventional approach.

Conclusions

By factoring in the variations in the spectral shape of ⟨ L ⟩ relative to SaO 2 , our self-calibrated algorithm enables accurate SaO 2 estimation, even in subjects with low SaO 2 levels.

From brain to worksite: the role of fNIRS in cognitive studies and worker safety

Effective hazard recognition and decision-making are crucial factors in ensuring workplace safety in the construction industry. Workers' cognition closely relates to that hazard-handling behavior. Functional near-infrared spectroscopy (fNIRS) is a neurotechique tool that can evaluate the concentration vibration of oxygenated hemoglobin [ H b O 2 ] and deoxygenated hemoglobin [H b R ] to reflect the cognition process. It is essential to monitor workers' brain activity by fNIRS to analyze their cognitive status and reveal the mechanism in hazard recognition and decision-making process, providing guidance for capability evaluation and management enhancement. This review offers a systematic assessment of fNIRS, encompassing the basic theory, experiment analysis, data analysis, and discussion. A literature search and content analysis are conducted to identify the application of fNIRS in construction safety research, the limitations of selected studies, and the prospects of fNIRS in future research. This article serves as a guide for researchers keen on harnessing fNIRS to bolster construction safety standards and forwards insightful recommendations for subsequent studies.

Development of Immersive Virtual Reality-Based Hand Rehabilitation System Using a Gesture-Controlled Rhythm Game With Vibrotactile Feedback: An fNIRS Pilot Study

Recently, virtua reality (VR) has been widely utilized with rehabilitation to promote user engagement, which has been shown to induce brain plasticity. In this study, we developed a VR-based hand rehabilitation system consisting of a personalized gesture-controlled rhythm game with vibrotactile feedback and investigated the cortical activation pattern induced by our system using functional near-infrared spectroscopy (fNIRS). Our system provides vibrotactile feedback as the user matches their hand gestures to VR targets customized to their pre-recorded hand gestures. Cortical activation was measured via fNIRS during 420 seconds of alternating gameplay and rest in 11 healthy subjects and one stroke survivor. Regions of interest (ROI) were the prefrontal cortex (PFC), the premotor cortex & the supplementary motor area (PMC&SMA), the primary sensorimotor cortex (SM1), and the somatosensory association cortex (SAC). The mean success rate of gesture matching among healthy subjects was 90 % with a standard deviation of 10.7 %, and the success rate of the stroke survivor was 79.6 %. The averaged cortical activation map for the 11 healthy subjects and the individual cortical activation map for the single stroke survivor showed increased hemodynamic responses of oxygenated hemoglobin (HbO) during the VR-based hand rehabilitation compared to the resting condition. Paired t-test analysis demonstrated a significant increase in HbO activation values in 19 out of 51 channels, corresponding to all ROIs except the left PFC and PMC&SMA, which exhibited high subject variability. The experimental results indicate that the proposed system successfully activated brain areas related to motor planning/execution, multisensory integration, and attention.

The different contributions of the eight prefrontal cortex subregions to reactive responses after unpredictable slip perturbations and vibrotactile cueing

Introduction

Recent advancements in functional near-infrared spectroscopy technology have offered a portable, wireless, wearable solution to measure the activity of the prefrontal cortex (PFC) in the human neuroscience field. This study is the first to validate the different contributions made by the PFC's eight subregions in healthy young adults to the reactive recovery responses following treadmill-induced unpredictable slip perturbations and vibrotactile cueing (i.e., precues).

Methods

Our fall-inducing technology platform equipped with a split-belt treadmill provided unpredictable slip perturbations to healthy young adults while walking at their self-selected walking speed. A portable, wireless, wearable, and multi-channel (48 channels) functional near-infrared spectroscopy system evaluated the activity of PFC's eight subregions [i.e., right and left dorsolateral prefrontal cortex (DLPFC), ventrolateral prefrontal cortex (VLPFC), frontopolar prefrontal cortex (FPFC), and orbitofrontal cortex (OFC)] as quantified by oxyhemoglobin and deoxyhemoglobin concentrations. A motion capture system and two force plates beneath the split-belt treadmill were used to quantify participants' kinematic and kinetic behavior. All participants completed 6 trials: 2 consecutive trials without vibrotactile cueing and with a slip perturbation (control trials); 3 trials with vibrotactile cueing [2 trials with the slip perturbation (cueing trial) and 1 trial without the slip perturbation (catch trial)], and 1 trial without vibrotactile cueing and with a slip perturbation (post-control trial). The PFC subregions' activity and kinematic behavior were assessed during the three periods (i.e., standing, walking, and recovery periods).

Results

Compared to the walkers' standing and walking periods, recovery periods showed significantly higher and lower levels of oxyhemoglobin and deoxyhemoglobin concentrations, respectively, in the right and left DLPFC, VLPFC, and FPFC, regardless of the presence of vibrotactile cueing. However, there was no significant difference in the right and left OFC between the three periods. Kinematic analyses confirmed that vibrotactile cueing significantly improved reactive recovery responses without requiring more involvement by the PFC subregions, which suggests that the sum of attentional resources is similar in cued and non-cued motor responses.

Discussion

The results could inform the design of wearable technologies that alert their users to the risks of falling and assist with the development of new gait perturbation paradigms that prompt reactive responses.

Prefrontal oxygenation varies as a function of response inhibition performance in healthy participants but not in youth with non-suicidal self-injury

Non-suicidal self-injury (NSSI), a highly prevalent symptom in adolescence, has been associated with impulsivity. Behavioral measures of response inhibition in combination with the recording of brain activity potentially improve the understanding of the etiology of the behavior. We therefore investigated prefrontal cortex (PFC) oxygenation during a response inhibition task using functional near-infrared spectroscopy (fNIRS) in n = 152 adolescents with NSSI and n = 47 healthy controls. We compared groups regarding behavioral performance and PFC oxygenation and tested whether the association between task performance and PFC oxygenation differed between groups. PFC oxygenation was slightly higher in adolescents with NSSI than in controls. Further, there was evidence for a group by performance interaction: In healthy controls, higher oxygenated hemoglobin was associated with better task performance, which was not the case in the NSSI group. We did not find evidence of associations between PFC oxygenation and clinical measures. Our study provides preliminary evidence of altered brain functional correlates of response inhibition in adolescents with NSSI potentially reflecting deficient top-down regulation of limbic regions through prefrontal regions. Due to methodological limitations of the current study, findings must be interpreted with caution and future studies should optimize task designs for fNIRS processing.

Comparison of the SenSmart™ and the INVOS™ neonatal cerebral near-infrared spectrometry devices

Objectives

To determine the correlation and agreement between the SenSmart™ and the INVOS™ devices of neonatal cerebral regional oxygen saturation (CrSO2) measurements using neonatal sensors. The secondary objective was to develop a regression model that predicts CrSO2-INVOS values using CrSO2-SenSmart indices and determine whether the values between the devices are interchangeable.

Methods

A prospective, cross-sectional study was conducted in infants during the first 4 weeks of life. Simultaneous, bilateral CrSO2 was measured using the SenSmart™X100 (CrSO2-SenSmart) or INVOS™ 5100C (CrSO2-INVOS) device in each frontoparietal area for 2 h. Five-minute CrSO2 values were extracted for analysis.

Results

Thirty infants were recruited with 720 pairwise measurements and 26 (84%) were evaluated in the first week of life. Mean gestational age of the preterm and term infants was [30.9 ± 2.8 (n = 14) and 38.8 ± 1.1 (n = 16)] weeks, respectively. Overall CrSO2- was 77.08 ± 9.70% and 71.45 ± 12.74% for the SenSmart and INVOS, respectively (p < 0.001). The correlation coefficient (r) between the CrSO2-SenSmart and INVOS was 0.20 (p < 0.001). The mean difference between the CrSO2-SenSmart and INVOS was 5.63 ± 13.87% with -21.6% to 32.8% limits of agreement. The r and mean difference was 0.39 (p < 0.001) and 8.87 ± 12.58% in preterm infants, and 0.06 (p = 0.27) and 2.79 ± 14.34 in term infants.

Conclusion

The CrSO2-SenSmart tended to read higher than the CrSO2-INVOS device. There was no correlation between the CrSO2-SenSmart and the CrSO2-INVOS in term infants and it was weak in preterms. Due to imprecise agreement, the CrSO2-SenSmart values are not interchangeable with those of the CrSO2-INVOS.

Facilitating or disturbing? An investigation about the effects of auditory frequencies on prefrontal cortex activation and postural sway

Auditory stimulation activates brain areas associated with higher cognitive processes, like the prefrontal cortex (PFC), and plays a role in postural control regulation. However, the effects of specific frequency stimuli on upright posture maintenance and PFC activation patterns remain unknown. Therefore, the study aims at filling this gap. Twenty healthy adults performed static double- and single-leg stance tasks of 60s each under four auditory conditions: 500, 1000, 1500, and 2000 Hz, binaurally delivered through headphones, and in quiet condition. Functional near-infrared spectroscopy was used to measure PFC activation through changes in oxygenated hemoglobin concentration, while an inertial sensor (sealed at the L5 vertebra level) quantified postural sway parameters. Perceived discomfort and pleasantness were rated through a 0-100 visual analogue scale (VAS). Results showed that in both motor tasks, different PFC activation patterns were displayed at the different auditory frequencies and the postural performance worsened with auditory stimuli, compared to quiet conditions. VAS results showed that higher frequencies were considered more discomfortable than lower ones. Present data prove that specific sound frequencies play a significant role in cognitive resources recruitment and in the regulation of postural control. Furthermore, it supports the importance of exploring the relationship among tones, cortical activity, and posture, also considering possible applications with neurological populations and people with hearing dysfunctions.

Cortical responses correlate with speech performance in pre-lingually deaf cochlear implant children

Introduction

Cochlear implantation is currently the most successful intervention for severe-to-profound sensorineural hearing loss, particularly in deaf infants and children. Nonetheless, there remains a significant degree of variability in the outcomes of CI post-implantation. The purpose of this study was to understand the cortical correlates of the variability in speech outcomes with a cochlear implant in pre-lingually deaf children using functional near-infrared spectroscopy (fNIRS), an emerging brain-imaging technique.

Methods

In this experiment, cortical activities when processing visual speech and two levels of auditory speech, including auditory speech in quiet and in noise with signal-to-noise ratios of 10 dB, were examined in 38 CI recipients with pre-lingual deafness and 36 normally hearing children whose age and sex matched CI users. The HOPE corpus (a corpus of Mandarin sentences) was used to generate speech stimuli. The regions of interest (ROIs) for the fNIRS measurements were fronto-temporal-parietal networks involved in language processing, including bilateral superior temporal gyrus, left inferior frontal gyrus, and bilateral inferior parietal lobes.

Results

The fNIRS results confirmed and extended findings previously reported in the neuroimaging literature. Firstly, cortical responses of superior temporal gyrus to both auditory and visual speech in CI users were directly correlated to auditory speech perception scores, with the strongest positive association between the levels of cross-modal reorganization and CI outcome. Secondly, compared to NH controls, CI users, particularly those with good speech perception, showed larger cortical activation in the left inferior frontal gyrus in response to all speech stimuli used in the experiment.

Discussion

In conclusion, cross-modal activation to visual speech in the auditory cortex of pre-lingually deaf CI children may be at least one of the neural bases of highly variable CI performance due to its beneficial effects for speech understanding, thus supporting the prediction and assessment of CI outcomes in clinic. Additionally, cortical activation of the left inferior frontal gyrus may be a cortical marker for effortful listening.

Between-sessions test-retest reliability of prefrontal cortical activity during usual walking in patients with Parkinson's Disease: A fNIRS study

BACKGROUND

Examining between-sessions test-retest reliability of functional near-infrared spectroscopy (fNIRS) data is crucial to better interpret rehabilitation-related changes in the hemodynamic response.

RESEARCH QUESTION

This study investigated test-retest reliability of prefrontal activity during usual walking in 14 patients with Parkinson's Disease with a fixed retest intervals of five weeks.

METHODS

Fourteen patients performed usual walking in two sessions (T0 and T1). Relative changes in cortical activity (oxy and deoxyhemoglobin: ∆HbO₂ and ∆HbR, respectively) in the dorsolateral prefrontal cortex (DLPFC) using fNIRS system and gait performance were measured. Test-retest reliability of mean ∆HbO₂ for the total DLPFC and for each hemisphere were measured using paired t-test, intraclass correlation coefficient (ICC), and Bland-Altman plots with 95% agreement. Pearson correlations between cortical activity and gait performance were also performed.

RESULTS

Moderate reliability was found for ∆HbO₂ in the total DLPFC (mean difference of ∆HbO₂ between T1 and T0 = -0.005 µmol, p = 0.93; ICC average = 0.72). However, test-retest reliability of ∆HbO₂ was poorer when considering each hemisphere.

SIGNIFICANCE

Findings suggest that fNIRS may be used as a reliable tool for rehabilitation studies in patients with PD. Test-retest reliability of fNIRS data between 2 sessions during walking tasks should be interpreted respectively of gait performance.

Improved Motion Artifact Correction in fNIRS Data by Combining Wavelet and Correlation-Based Signal Improvement

Functional near-infrared spectroscopy (fNIRS) is an optical non-invasive neuroimaging technique that allows participants to move relatively freely. However, head movements frequently cause optode movements relative to the head, leading to motion artifacts (MA) in the measured signal. Here, we propose an improved algorithmic approach for MA correction that combines wavelet and correlation-based signal improvement (WCBSI). We compare its MA correction accuracy to multiple established correction approaches (spline interpolation, spline-Savitzky-Golay filter, principal component analysis, targeted principal component analysis, robust locally weighted regression smoothing filter, wavelet filter, and correlation-based signal improvement) on real data. Therefore, we measured brain activity in 20 participants performing a hand-tapping task and simultaneously moving their head to produce MAs at different levels of severity. In order to obtain a "ground truth" brain activation, we added a condition in which only the tapping task was performed. We compared the MA correction performance among the algorithms on four predefined metrics (R, RMSE, MAPE, and ΔAUC) and ranked the performances. The suggested WCBSI algorithm was the only one exceeding average performance (p < 0.001), and it had the highest probability to be the best ranked algorithm (78.8% probability). Together, our results indicate that among all algorithms tested, our suggested WCBSI approach performed consistently favorably across all measures.

Evaluation of residual cognition in patients with disorders of consciousness based on functional near-infrared spectroscopy

SIGNIFICANCE

Accurate evaluation of consciousness in patients with prolonged disorders of consciousness (DOC) is critical for designing therapeutic plans, determining rehabilitative services, and predicting prognosis. Effective ways for detecting consciousness in patients with DOC are still needed.

AIM

Evaluation of the residual awareness in patients with DOC and investigation of the spatiotemporal differences in the hemodynamic responses between the minimally conscious state (MCS) and the unresponsive wakefulness syndrome (UWS) groups using active command-driven motor imagery (MI) tasks.

APPROACH

In this study, functional near-infrared spectroscopy (fNIRS) was used to measure the changes of hemodynamic responses in 19 patients with DOC (9 MCS and 10 UWS) using active command-driven MI tasks. The characteristics of the hemodynamic responses were extracted to compare the differences between the MCS and UWS groups. Moreover, the correlations between the hemodynamic responses and the clinical behavioral evaluations were also studied.

RESULTS

The results showed significant differences in the spatiotemporal distribution of the hemodynamic responses between the MCS and UWS groups. For the patients with MCS, significant increases in task-evoked hemodynamic responses occurred during the "YES" questions of the command-driven MI tasks. Importantly, these changes were significantly correlated with their coma-recovery scale-revised (CRS-R) scores. However, for the patients with UWS, no significant changes of the hemodynamic responses were found. Additionally, the results did not show any statistical correlation between the hemodynamic responses and their CRS-R scores.

CONCLUSIONS

The fNIRS-based command-driven MI tasks can be used as a promising tool for detecting residual awareness in patients with DOC. We hope that the findings and the active paradigm used in this study will provide useful insights into the diagnosis, therapy, and prognosis of this challenging patient population.

Using preregistration as a tool for transparent fNIRS study design

Significance

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

Aim

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

Approach

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

Results

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

Conclusions

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

Insomniacs show greater prefrontal activation during verbal fluency task compared to non-insomniacs: a functional near-infrared spectroscopy investigation of depression in patients

BACKGROUND

Previous studies have shown that insomnia affects human prefrontal function and that there are specific patterns of brain activation to counteract sleep and improve cognition. However, the effects of insomnia on the prefrontal cortex of MDD (major depressive disorder) patients and the patterns of activation to counteract sleep in MDD patients remain unclear. The aim of this study is to examine this using fNIRS (functional near-infrared spectroscopy).

METHODS

Eighty depressed patients and 44 healthy controls were recruited for this study. fNIRS was used to assess changes in the concentration of oxygenated hemoglobin ([oxy-Hb]) in the prefrontal cortex of all participants during the VFT (verbal fluency test) and to record the number of words created to assess cognitive ability. The Pittsburgh Sleep Quality Index was used to assess sleep quality, and the Hamilton Rating Scale for Depression (24-item) and Hamilton Rating Scale for Anxiety (14-item) were used to assess the severity of depression and anxiety.

RESULTS

When comparing patients, the healthy control group had significantly higher [oxy-Hb] values in the bilateral prefrontal cortex during VFT than the MDD group. In the MDD group, the [oxy-Hb] values in all brain regions except the right DLPFC were significantly higher in the group with insomnia than in the group without insomnia, but their VFT performance was significantly lower than in the group without insomnia and the healthy group. PSQI scores were positively correlated with [oxy-Hb] values in some left-brain regions, whereas HAMD and HAMA scores were not correlated with [oxy-Hb] values.

CONCLUSION

The PFC was significantly less active during VFT in those with MDD than in healthy controls. All brain regions, except the right DLPFC, were significantly more active in MDD patients with insomnia than in those without insomnia, suggesting that sleep quality needs to be an important indicator in fNIRS screening. In addition, there was a positive correlation between the severity of insomnia in the left VLPFC and the level of activation, suggesting a role for the left brain region in the neurophysiology of overcoming sleepiness in MDD patients. these findings may provide new ideas for the treatment of MDD patients in the future.

TRIAL REGISTRATION

Our experiment was registered in the China Clinical Trial Registry (registration number ChiCTR2200065622) on November 10.( The first patient was recruited in 10/11/2022.).

Simultaneous multimodal fNIRS-EEG recordings reveal new insights in neural activity during motor execution, observation, and imagery

Motor execution, observation, and imagery are important skills used in motor learning and rehabilitation. The neural mechanisms underlying these cognitive-motor processes are still poorly understood. We used a simultaneous recording of functional near-infrared spectroscopy (fNIRS) and electroencephalogram (EEG) to elucidate the differences in neural activity across three conditions requiring these processes. Additionally, we used a new method called structured sparse multiset Canonical Correlation Analysis (ssmCCA) to fuse the fNIRS and EEG data and determine the brain regions of neural activity consistently detected by both modalities. Unimodal analyses revealed differentiated activation between conditions; however, the activated regions did not fully overlap across the two modalities (fNIRS: left angular gyrus, right supramarginal gyrus, as well as right superior and inferior parietal lobes; EEG: bilateral central, right frontal, and parietal). These discrepancies might be because fNIRS and EEG detect different signals. Using fused fNIRS-EEG data, we consistently found activation over the left inferior parietal lobe, superior marginal gyrus, and post-central gyrus during all three conditions, suggesting that our multimodal approach identifies a shared neural region associated with the Action Observation Network (AON). This study highlights the strengths of using the multimodal fNIRS-EEG fusion technique for studying AON. Neural researchers should consider using the multimodal approach to validate their findings.

Involvement of the prefrontal cortex in motor sequence learning: A functional near-infrared spectroscopy (fNIRS) study

Our previous functional near-infrared spectroscopy (fNIRS) study on motor sequence learning (Polskaia et al., 2020) did not detect the same decrease in activity in the left dorsolateral prefrontal cortex (DLPFC) associated with movement automaticity, as reported by Wu et al. (2004). This was partly attributed to insufficient practice time to reach neural efficiency. Therefore, we sought to expand on our previous work to better understand the contribution of the prefrontal cortex (PFC) to motor sequence learning by examining learning across a longer period of time. Participants were randomly assigned to one of two groups: control or trained. fNIRS was acquired at three time points: pre-test, post-test, and retention. Participants performed four sequences (S1, S2, S3, and S4) of right-hand finger tapping. The trained group also underwent four days of practice of S1 and S2. No group differences in the left DLPFC and ventrolateral (VLPFC) were found between sessions for S1 and S2. Our findings revealed increased contribution from the right VLPFC in post-test for the trained group, which may reflect the active retrieval of explicit information from long-term memory. Our results suggest that despite additional practice time, explicit motor sequence learning requires the continued involvement of the PFC.

Functional near-infrared spectroscopy shows that object relative clauses are more difficult to process than subject relative clauses in Turkish

It was suggested that processing subject relative clauses (SRCs) is universally easier than processing object relative clauses (ORCs) based on the studies carried out in head-initial languages such as English and German. However, studies in head-final languages such as Chinese and Basque contradicted this claim. Turkish is also a head-final language. Existing relative clause processing literature in Turkish is based solely on behavioural metrics. Even though an ORC processing disadvantage was suggested for Turkish, the results were not conclusive. Therefore, we aimed to investigate the neural dynamics of relative clause processing in Turkish. We asked 14 native Turkish speakers to answer yes/no questions about 24 sentences each containing either a SRC or ORC while their prefrontal hemodynamic activity was recorded with functional near-infrared spectroscopy. Our findings revealed hemodynamic activity in the lateral portions of the left prefrontal cortex for both conditions. However, hemodynamic activity was more widespread in prefrontal regions in ORC compared to SRC condition. Even though the behavioural metrics failed to produce a significant difference between the conditions, direct ORC > SRC contrast revealed significant activity in the left inferior frontal cortex, a region heavily involved in language processing, as well as in left and right dorsolateral prefrontal cortices, which are also known to be involved in language processing-related and conflict monitoring-related processes, respectively. Our findings indicate that processing ORCs is more difficult and requires further prefrontal resources than processing SRCs in Turkish, thus refuting the head-directionality-based explanations of relative clause processing asymmetries.

fNIRS-based functional connectivity signifies recovery in patients with disorders of consciousness after DBS treatment

OBJECTIVE

While deep brain stimulation (DBS) has proved effective for certain patients with disorders of consciousness (DOC), the working neural mechanism is not clear, the response varies for patients, and the assessment is inadequate. This paper aims to quantify the DBS-induced changes of consciousness in DOC patients at the neural functional level.

METHODS

Ten DOC patients were included for DBS surgery. The DBS target was the right centromedian-parafascicular (CM-pf) nuclei for four patients and the bilateral CM-pf nuclei for six patients. Functional near-infrared spectroscopy (fNIRS) was taken to measure the neural activation of patients, in parallel with Coma Recovery Scale-Revised (CRS-R), before the DBS surgery and one month after. The fNIRS signals were recorded from the frontal, parietal, and occipital lobes. Functional connectivity analysis quantified the communication between brain regions, area communication strength, and global communication efficiency. Linear regression analysis was conducted between the changes of indices based on functional connectivity analysis and the changes of the CRS-R index.

RESULTS

Patients with trauma (n = 4) exhibited a greater increase of CRS-R scores after DBS treatment compared with patients with hemorrhage (n = 4) and brainstem infarction (n = 2). Global communication efficiency changed consistently with the CRS-R index (slope = 57.384, p < 0.05, R²=0.483). No significant relationship was found between the changes of area communication strength of six brain lobes and the changes of the CRS-R index.

CONCLUSIONS

The cause of DOC is essential for the outcome of DBS treatment, and brain communication efficiency is a promising functional marker for DOC recovery.

SIGNIFICANCE

fNIRS-based functional connectivity analysis on brain network signifies changes of consciousness in DOC patients after DBS treatment.

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

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

Using Cognitive-Motor Dual-Tasks and Functional Near-Infrared Spectroscopy to Characterize Older Adults with and without Subjective Cognitive Decline

BACKGROUND

Subjective cognitive decline (SCD) refers to individuals who report persistent cognitive deficits but perform normally on neuropsychological tests. Performance may be facilitated by increased prefrontal cortex activation, known as neural compensation, and could be used to differentiate between older adults with and without SCD.

OBJECTIVE

This cross-sectional pilot study measured changes in the hemodynamic response (ΔHbO2) using functional near-infrared spectroscopy (fNIRS) as well as cognitive and motor performance during fine and gross motor dual-tasks in older adults with and without SCD.

METHODS

Twenty older adults over 60 years old with (n = 10) and without (n = 10) SCD were recruited. Two experiments were conducted using 1) gross motor walking and 2) fine motor finger tapping tasks that were paired with an n-back working memory task. Participants also completed neuropsychological assessments and questionnaires on everyday functioning.

RESULTS

Repeated measures ANOVAs demonstrated slower response times during dual-task gait compared to the single task (p = 0.032) and in the non-SCD group, slower gait speed was also observed in the dual compared to single task (p = 0.044). Response times during dual-task finger tapping were slower than the single task (p = 0.049) and greater ΔHbO2 was observed overall in the SCD compared to non-SCD group (p = 0.002).

CONCLUSIONS

Examining neural and performance outcomes revealed differences between SCD and non-SCD groups and single and dual-tasks. Greater brain activation during dual-task finger tapping may reflect neural compensation, which should be examined in a larger sample and longitudinally to better characterize SCD.

Prefrontal activation in preschool children is associated with maternal adversity and child temperament: A preliminary fNIRS study of inhibitory control

Exposure to adversity is a well-documented risk factor for cognitive, behavioral, and mental health problems. In fact, the consequences of adversity may be intergenerational. A growing body of research suggests that maternal exposures to adversity, including those prior to childbirth, are associated with offspring biobehavioral development. In a sample of 36 mothers and their preschool-age children (mean child age = 4.21 ± 0.92 years), we used functional near-infrared spectroscopy to replicate and extend this work to include brain activation during inhibitory control in young children. We found that measures of maternal exposure to adversity, including cumulative, childhood, and preconception exposures, were significantly and positively associated with activation in the right frontopolar prefrontal cortex (PFC) and in the left temporal and parietal clusters during inhibitory control. In addition, and consistent with previous findings, children's increased negative affect and decreased effortful control were associated with increased right PFC activation during inhibitory control. These findings provide preliminary evidence that maternal and dispositional risk factors are linked to alterations in PFC functioning during the preschool years. Children of mothers with a history of exposure to adversity, as well as children who are less temperamentally regulated, may require increased neural resources to meet the cognitive demands of inhibitory control.

Congruence-based contextual plausibility modulates cortical activity during vibrotactile perception in virtual multisensory environments

How congruence cues and congruence-based expectations may together shape perception in virtual reality (VR) still need to be unravelled. We linked the concept of plausibility used in VR research with congruence-based modulation by assessing brain responses while participants experienced vehicle riding experiences in VR scenarios. Perceptual plausibility was manipulated by sensory congruence, with multisensory stimulations confirming with common expectations of road scenes being plausible. We hypothesized that plausible scenarios would elicit greater cortical responses. The results showed that: (i) vibrotactile stimulations at expected intensities, given embedded audio-visual information, engaged greater cortical activities in frontal and sensorimotor regions; (ii) weaker plausible stimulations resulted in greater responses in the sensorimotor cortex than stronger but implausible stimulations; (iii) frontal activities under plausible scenarios negatively correlated with plausibility violation costs in the sensorimotor cortex. These results potentially indicate frontal regulation of sensory processing and extend previous evidence of contextual modulation to the tactile sense.

Reliability and similarity of resting state functional connectivity networks imaged using wearable, high-density diffuse optical tomography in the home setting

BACKGROUND

When characterizing the brain's resting state functional connectivity (RSFC) networks, demonstrating networks' similarity across sessions and reliability across different scan durations is essential for validating results and possibly minimizing the scanning time needed to obtain stable measures of RSFC. Recent advances in optical functional neuroimaging technologies have resulted in fully wearable devices that may serve as a complimentary tool to functional magnetic resonance imaging (fMRI) and allow for investigations of RSFC networks repeatedly and easily in non-traditional scanning environments.

METHODS

Resting-state cortical hemodynamic activity was repeatedly measured in a single individual in the home environment during COVID-19 lockdown conditions using the first ever application of a 24-module (72 sources, 96 detectors) wearable high-density diffuse optical tomography (HD-DOT) system. Twelve-minute recordings of resting-state data were acquired over the pre-frontal and occipital regions in fourteen experimental sessions over three weeks. As an initial validation of the data, spatial independent component analysis was used to identify RSFC networks. Reliability and similarity scores were computed using metrics adapted from the fMRI literature.

RESULTS

We observed RSFC networks over visual regions (visual peripheral, visual central networks) and higher-order association regions (control, salience and default mode network), consistent with previous fMRI literature. High similarity was observed across testing sessions and across chromophores (oxygenated and deoxygenated haemoglobin, HbO and HbR) for all functional networks, and for each network considered separately. Stable reliability values (described here as a <10% change between time windows) were obtained for HbO and HbR with differences in required scanning time observed on a network-by-network basis.

DISCUSSION

Using RSFC data from a highly sampled individual, the present work demonstrates that wearable HD-DOT can be used to obtain RSFC measurements with high similarity across imaging sessions and reliability across recording durations in the home environment. Wearable HD-DOT may serve as a complimentary tool to fMRI for studying RSFC networks outside of the traditional scanning environment and in vulnerable populations for whom fMRI is not feasible.

Neural Correlates of Dual-Task Processing following Motor Sequence Learning: A Functional Near-Infrared Spectroscopy (fNIRS) Study

The current study used functional near-infrared spectroscopy (fNIRS) to examine cerebral oxygenation changes in the prefrontal cortex (PFC) associated with dual-task processing before and after motor sequence learning. Participants performed self-initiated sequential finger movements that were 4 and 12 units in length with a visual letter-counting task. After practice, dual-task sequence-4 performance revealed decreased activity in the right dorsolateral PFC, medial PFC, and orbitofrontal cortex. However, dual-task sequence-12 performance revealed increased activity in the right ventrolateral PFC when compared to the left hemisphere. The findings suggest that dual-task interference was reduced following practice for dual-task sequence-4. The results also suggest that increased right hemisphere activation is needed to maintain performance when the primary sequential task (e.g., dual-task sequence-12) has a high level of difficulty.

Motion artifacts removal and evaluation techniques for functional near-infrared spectroscopy signals: A review

With the emergence of an increasing number of functional near-infrared spectroscopy (fNIRS) devices, the significant deterioration in measurement caused by motion artifacts has become an essential research topic for fNIRS applications. However, a high requirement for mathematics and programming limits the number of related researches. Therefore, here we provide the first comprehensive review for motion artifact removal in fNIRS aiming to (i) summarize the latest achievements, (ii) present the significant solutions and evaluation metrics from the perspective of application and reproduction, and (iii) predict future topics in the field. The present review synthesizes information from fifty-one journal articles (screened according to three criteria). Three hardware-based solutions and nine algorithmic solutions are summarized, and their application requirements (compatible signal types, the availability for online applications, and limitations) and extensions are discussed. Five metrics for noise suppression and two metrics for signal distortion were synthesized to evaluate the motion artifact removal methods. Moreover, we highlight three deficiencies in the existing research: (i) The balance between the use of auxiliary hardware and that of an algorithmic solution is not clarified; (ii) few studies mention the filtering delay of the solutions, and (iii) the robustness and stability of the solution under extreme application conditions are not discussed.

Parallel factor analysis for multidimensional decomposition of functional near-infrared spectroscopy data

SIGNIFICANCE

Current techniques for data analysis in functional near-infrared spectroscopy (fNIRS), such as artifact correction, do not allow to integrate the information originating from both wavelengths, considering only temporal and spatial dimensions of the signal's structure. Parallel factor analysis (PARAFAC) has previously been validated as a multidimensional decomposition technique in other neuroimaging fields.

AIM

We aimed to introduce and validate the use of PARAFAC for the analysis of fNIRS data, which is inherently multidimensional (time, space, and wavelength).

APPROACH

We used data acquired in 17 healthy adults during a verbal fluency task to compare the efficacy of PARAFAC for motion artifact correction to traditional two-dimensional decomposition techniques, i.e., target principal (tPCA) and independent component analysis (ICA). Correction performance was further evaluated under controlled conditions with simulated artifacts and hemodynamic response functions.

RESULTS

PARAFAC achieved significantly higher improvement in data quality as compared to tPCA and ICA. Correction in several simulated signals further validated its use and promoted it as a robust method independent of the artifact's characteristics.

CONCLUSIONS

This study describes the first implementation of PARAFAC in fNIRS and provides validation for its use to correct artifacts. PARAFAC is a promising data-driven alternative for multidimensional data analyses in fNIRS and this study paves the way for further applications.

Deep learning-based motion artifact removal in functional near-infrared spectroscopy

Significance: Functional near-infrared spectroscopy (fNIRS), a well-established neuroimaging technique, enables monitoring cortical activation while subjects are unconstrained. However, motion artifact is a common type of noise that can hamper the interpretation of fNIRS data. Current methods that have been proposed to mitigate motion artifacts in fNIRS data are still dependent on expert-based knowledge and the post hoc tuning of parameters. Aim: Here, we report a deep learning method that aims at motion artifact removal from fNIRS data while being assumption free. To the best of our knowledge, this is the first investigation to report on the use of a denoising autoencoder (DAE) architecture for motion artifact removal. Approach: To facilitate the training of this deep learning architecture, we (i) designed a specific loss function and (ii) generated data to mimic the properties of recorded fNIRS sequences. Results: The DAE model outperformed conventional methods in lowering residual motion artifacts, decreasing mean squared error, and increasing computational efficiency. Conclusion: Overall, this work demonstrates the potential of deep learning models for accurate and fast motion artifact removal in fNIRS data.

Motion artifact correction for resting-state neonatal functional near-infrared spectroscopy through adaptive estimation of physiological oscillation denoising

SIGNIFICANCE

Functional near-infrared spectroscopy (fNIRS) for resting-state neonatal brain function evaluation provides assistance for pediatricians in diagnosis and monitoring treatment outcomes. Artifact contamination is an important challenge in the application of fNIRS in the neonatal population.

AIM

Our study aims to develop a correction algorithm that can effectively remove different types of artifacts from neonatal data.

APPROACH

In the study, we estimate the recognition threshold based on the amplitude characteristics of the signal and artifacts. After artifact recognition, Spline and Gaussian replacements are used separately to correct the artifacts. Various correction method recovery effects on simulated artifact and actual neonatal data are compared using the Pearson correlation ( R ) and root mean square error (RMSE). Simulated data connectivity recovery is used to compare various method performances.

RESULTS

The neonatal resting-state data corrected by our method showed better agreement with results by visual recognition and correction, and significant improvements ( R = 0.732 ± 0.155 , RMSE = 0.536 ± 0.339 ; paired t -test, ** p < 0.01 ). Moreover, the method showed a higher degree of recovery of connectivity in simulated data.

CONCLUSIONS

The proposed algorithm corrects artifacts such as baseline shifts, spikes, and serial disturbances in neonatal fNIRS data quickly and more effectively. It can be used for preprocessing in clinical applications of neonatal fNIRS brain function detection.

Functional near-infrared spectroscopy imaging of the prefrontal cortex during a naturalistic comedy movie

Naturalistic stimulation (i.e., movies and auditory narratives of some minutes' length) has been a powerful approach to bringing more real-life experiences into laboratory experiments. Data-driven, intersubject correlation (ISC) analysis permits examining to what extent activity in a specific brain region correlates across participants during exposure to a naturalistic stimulus, as well as testing whether neural activity correlates with behavioral measures. Notably, most of the previous research with naturalistic stimuli was conducted using functional fMRI (fMRI). Here, we tested whether a naturalistic approach and the ISC are feasible using functional near-infrared spectroscopy (fNIRS) - the imaging method particularly suited for populations of patients and children. Fifty-three healthy adult participants watched twice a 3-min segment of a Charlie Chaplin movie while we recorded the brain activity on the surface of their prefrontal cortex using fNIRS. In addition, an independent group of 18 participants used a continuous scoring procedure to rate the extent to which they felt that different parts of the movie fragment were funny. Our two findings were as follows. First, we found higher-than-zero ISC in fNIRS signals in the prefrontal cortex lobes, a result that was particularly high in the oxygenated channels during the first repetition of the movie. Second, we found a significant negative correlation between oxygenated brain signals and ratings of the movie's humorousness. In a series of control analyses we demonstrated that this latter correlation could not be explained by various non-humor-related movie sensory properties (e.g., auditory volume and image brightness). The key overall outcome of the present study is that fNIRS in combination with the naturalistic paradigms and the ISC might be a sensitive and powerful research method to explore cognitive processing. Our results also suggest a potential role of the prefrontal cortex in humor appreciation.

Prefrontal cortex oxygenation and autonomic nervous system activity under transcutaneous auricular vagus nerve stimulation in adolescents

INTRODUCTION

The Neurovisceral Integration Model (NIM) proposes a complex interplay of visceral and neural structures that are crucial for adaptive responses to environmental demands. The aim of the present study was to investigate this circuitry using experimental manipulation via transcutaneous auricular vagus nerve stimulation (tVNS), measures of peripheral autonomic nervous system (ANS) activity and prefrontal cortex (PFC) oxygenation, quantified using functional near-infrared spectroscopy (fNIRS).

METHODS

In a sample of n = 30 adolescents (age 14-17 years), tVNS versus sham stimulation was applied each during a 15-minute stimulation phase in a within-subject-cross-randomized-design. Mean oxygenation of the PFC and functional connectivity were assessed using fNIRS. Additionally, heart rate variability (HRV), heart rate (HR), electrodermal activity (EDA), and saliva alpha-amylase (sAA) were assessed to quantify peripheral ANS activity.

RESULTS

Using linear mixed-effects models, HRV increased (p < .0001) and HR (p < .0001) decreased during tVNS compared to sham. No effect on EDA or sAA was observed. PFC oxygenation increased over time under tVNS compared to sham (p = .017). The relative increase in HRV and decrease in HR was associated with increased oxygenation of the PFC (HR: p < .0001; HRV: p = .007). Exploratory analyses illustrated, that under tVNS, PFC connectivity increased compared to sham.

CONCLUSION

The present study supports the NIM by showing that tVNS influences ANS activity and that relative changes in PFC oxygenation contribute to these effects. Implications of these findings and directions for further research are discussed.

Lawrence K, Tachtsidis I, Tong Y, Torricelli A, Urner T, Wabnitz H, Wolf M, Wolf U, Xu S, Yang C, Yodh AG, Yücel MA, Zhou W. Optical imaging and spectroscopy for the study of the human brain: status report

This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function. While the first report focused on neurophotonic tools mostly applicable to animal studies, here, we highlight optical spectroscopy and imaging methods relevant to noninvasive human brain studies. We outline current state-of-the-art technologies and software advances, explore the most recent impact of these technologies on neuroscience and clinical applications, identify the areas where innovation is needed, and provide an outlook for the future directions.

Interpersonal neural synchrony when predicting others' actions during a game of rock-paper-scissors

As members of a social species, we spend most of our time interacting with others. In interactions, we tend to mutually align our behavior and brain responses to communicate more effectively. In a semi-computerized version of the Rock-Paper-Scissors game, we investigated whether people show enhanced interpersonal neural synchronization when making explicit predictions about others' actions. Across four experimental conditions, we measured the dynamic brain activity using the functional near-infrared spectroscopy (fNIRS) hyperscanning method. Results showed that interpersonal neural synchrony was enhanced when participants played the game together as they would do in real life in comparison to when they played the game on their own. We found no evidence of increased neural synchrony when participants made explicit predictions about others' actions. Hence, neural synchrony may depend on mutual natural interaction rather than an explicit prediction strategy. This study is important, as it examines one of the presumed functions of neural synchronization namely facilitating predictions.

Comparing fixed-array and functionally-defined channel of interest approaches to infant functional near-infrared spectroscopy data

Functional near-infrared spectroscopy (fNIRS) is increasingly used to study brain function in infants, but the development and standardization of analysis techniques for use with infant fNIRS data have not paced other technical advances. Here we quantify and compare the effects of different methods of analysis of infant fNIRS data on two independent fNIRS datasets involving 6–9-month-old infants and a third simulated infant fNIRS dataset. With each, we contrast results from a traditional, fixed-array analysis with several functional channel of interest (fCOI) analysis approaches. In addition, we tested the effects of varying the number and anatomical location of potential data channels to be included in the fCOI definition. Over three studies we find that fCOI approaches are more sensitive than fixed-array analyses, especially when channels of interests were defined within-subjects. Applying anatomical restriction and/or including multiple channels in the fCOI definition does not decrease and in some cases increases sensitivity of fCOI methods. Based on these results, we recommend that researchers consider employing fCOI approaches to the analysis of infant fNIRS data and provide some guidelines for choosing between particular fCOI approaches and settings for the study of infant brain function and development.

Influence of the Somatic Rubber Hand Illusion on Maximum Grip Aperture

The classic rubber hand illusion (RHI), based on visual, proprioceptive, and tactile feedback, can affect actions. However, it is not known whether these effects still occur if the paradigm is administered without visual feedback. In this study, we used the somatic RHI to test in thirty-two healthy individuals whether the incorporation of the rubber hand based on proprioceptive and tactile information only is sufficient to generate changes in actions. We measured maximum grip aperture (GA) changes towards a target and associated brain activations within the dorsal stream before and after the somatic RHI. Behavioural and neuroimaging data do not support an effect on maximum GA when the RHI is based on proprioceptive and tactile information only.

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.

Head hemodynamics and systemic responses during auditory stimulation

The present study aims to analyze the systemic response to auditory stimulation by means of hemodynamic (cephalic and peripheral) and autonomic responses in a broad range of auditory intensities (70.9, 77.9, 84.5, 89.5, 94.5 dBA). This approach could help to understand the possible influence of the autonomic nervous system on the cephalic blood flow. Twenty-five subjects were exposed to auditory stimulation while electrodermal activity (EDA), photoplethysmography (PPG), electrocardiogram, and functional near-infrared spectroscopy signals were recorded. Seven trials with 20 individual tones, each for the five intensities, were presented. The results showed a differentiated response to the higher intensity (94.5 dBA) with a decrease in some peripheral signals such as the heart rate (HR), the pulse signal, the pulse transit time (PTT), an increase of the LFnu power in PPG, and at the head level a decrease in oxygenated and total hemoglobin concentration. After the regression of the visual channel activity from the auditory channels, a decrease in deoxyhemoglobin in the auditory cortex was obtained, indicating a likely active response at the highest intensity. Nevertheless, other measures, such as EDA (Phasic and Tonic), and heart rate variability (Frequency and time domain) showed no significant differences between intensities. Altogether, these results suggest a systemic and complex response to high-intensity auditory stimuli. The results obtained in the decrease of the PTT and the increase in LFnu power of PPG suggest a possible vasoconstriction reflex by a sympathetic control of vascular tone, which could be related to the decrease in blood oxygenation at the head level.