The present study aimed to examine the neural mechanisms underlying the ability to process the mental rotation with mirrored stimuli for different depressive tendencies with psychomotor retardation. Using functional near-infrared spectroscopy, we measured brain cortex activation of participants with higher and lower depressive tendencies while performing a left-right paradigm of object mental rotation or a same-different paradigm of subject mental rotation. Behavioral data revealed no differences in reaction time and rotation speed. The fNIRS data revealed (...) a higher deactivation of oxyhemoglobin change for the higher depression group in the perceptual stage of object mental rotation with mirrored stimuli in the superior external frontal cortex, inferior frontal gyrus, premotor cortex, and primary motor cortex. In addition, there existed a significant difference between the two groups in premotor cortex in subject mental rotation with mirrored stimuli. These results suggest that the neural mechanism of higher depression individuals connected with psychomotor retardation exists in the frontal and motor areas when processing object mental rotation with mirrored stimuli, and the motor cortex when processing subject mental rotation. (shrink)

This exploratory study assessed the use of functional Near Infrared Spectroscopy (fNIRS) to examine hemodynamic response patterns during sentence processing. Four groups of participants: monolingual English children, bilingual Chinese-English children, bilingual Chinese-English adults and monolingual English adults were given an agent selection syntactic processing task. Bilingual child participants were classified as simultaneous or sequential bilinguals to examine the impact of first language, age of second-language acquisition (AoL2A), and the length of second language experience on behavioral (...) performance and cortical activation. Participants were asked to select the agent of four types of sentences: subject-verb-object (SVO), passive (PAS), subject-extracted relative clause (SR), and object-extracted relative clause (OR) adopted from the “Whatdunit” task by Montgomery et al. (2016). Semantic cues were removed by using inanimate nouns for agents and patients, which constrained participants to make decisions based on syntactic knowledge. Behavioral results showed greater accuracy for canonical SVO and SR sentence types than for noncanonical OR and PAS sentence types, which aligns with prior studies. Neuroimaging results revealed greater hemodynamic responses to relative clauses (i.e., SR and OR sentences) than to simple sentences (SVO and PAS), especially for Chinese-English bilinguals suggesting first-language transfer influencing sentence processing in English. The effects AoL2A and the length of second language experience showed no significant differences between simultaneous and sequential bilinguals or between bilingual adults and children for identifying the correct agent in each sentence. However, neuroimaging results demonstrated greater hemodynamic responses in right dorsolateral prefrontal cortex (DLPFC) and left inferior parietal lobule (IPL) in simultaneous bilinguals compared to sequential bilinguals and greater hemodynamic responses in left and right DLPFC and left IPL among bilingual adults. Different behavioral and neural hemodynamic response patterns afford new insights into the effects of syntactic knowledge on sentence processing. (shrink)

Functional near-infrared spectroscopy has attracted increasing attention in the field of brain–computer interfaces owing to their advantages such as non-invasiveness, user safety, affordability, and portability. However, fNIRS signals are highly subject-specific and have low test-retest reliability. Therefore, individual calibration sessions need to be employed before each use of fNIRS-based BCI to achieve a sufficiently high performance for practical BCI applications. In this study, we propose a novel deep convolutional neural network -based approach for implementing (...) a subject-independent fNIRS-based BCI. A total of 18 participants performed the fNIRS-based BCI experiments, where the main goal of the experiments was to distinguish a mental arithmetic task from an idle state task. Leave-one-subject-out cross-validation was employed to evaluate the average classification accuracy of the proposed subject-independent fNIRS-based BCI. As a result, the average classification accuracy of the proposed method was reported to be 71.20 ± 8.74%, which was higher than the threshold accuracy for effective BCI communication as well as that obtained using conventional shrinkage linear discriminant analysis. To achieve a classification accuracy comparable to that of the proposed subject-independent fNIRS-based BCI, 24 training trials were necessary for the traditional subject-dependent fNIRS-based BCI. It is expected that our CNN-based approach would reduce the necessity of long-term individual calibration sessions, thereby enhancing the practicality of fNIRS-based BCIs significantly. (shrink)

Background Speech understanding may rely not only on auditory, but also on visual information. Non-invasive functional neuroimaging techniques can expose the neural processes underlying the integration of multisensory processes required for speech understanding in humans. Nevertheless, noise (from fMRI) limits the usefulness in auditory experiments, and electromagnetic artefacts caused by electronic implants worn by subjects can severely distort the scans (EEG, fMRI). Therefore, we assessed audio-visual activation of temporal cortex with a silent, optical neuroimaging technique: functional near- (...) class='Hi'>infrared spectroscopy (fNIRS). Methods We studied temporal cortical activation as represented by concentration changes of oxy- and deoxy-hemoglobin in four, easy-to-apply fNIRS optical channels of 33 normal-hearing adult subjects and 5 post-lingually deaf cochlear implant (CI) users in response to supra-threshold unisensory auditory and visual, as well as to congruent auditory-visual speech stimuli. Results Activation effects were not visible from single fNIRS channels. However, by discounting physiological noise through reference channel subtraction, auditory, visual and audiovisual speech stimuli evoked concentration changes for all sensory modalities in both cohorts (p<0.001). Auditory stimulation evoked larger concentration changes than visual stimuli (p<0.001). A saturation effect was observed for the audiovisual condition. Conclusions Physiological, systemic noise can be removed from fNIRS signals by reference channel subtraction. The observed multisensory enhancement of an auditory cortical channel can be plausibly described by a simple addition of the auditory and visual signals with saturation. (shrink)

There is growing interest for implementing tools to monitor cognitive performance in naturalistic work and everyday life settings. The emerging field of research, known as neuroergonomics, promotes the use of wearable and portable brain monitoring sensors such as functional near infrared spectroscopy (fNIRS) to investigate cortical activity in a variety of human tasks out of the laboratory. The objective of this study was to implement an on-line passive fNIRS-based brain computer interface to discriminate two (...) levels of working memory load during highly ecological aircraft piloting tasks. Twenty eight recruited pilots were equally split into two groups (flight simulator vs. real aircraft). In both cases, identical approaches and experimental stimuli were used (serial memorization task, consisting in repeating series of pre-recorded air traffic control instructions, easy vs. hard). The results show pilots in the real flight condition committed more errors and had higher anterior prefrontal cortex activation than pilots in the simulator, when completing cognitively demanding tasks. Nevertheless, evaluation of single trial working memory load classification showed high accuracy (>76%) across both experimental conditions. The contributions here are two-fold. First, we demonstrate the feasibility of passively monitoring cognitive load in a realistic and complex situation (live piloting of an aircraft). In addition, the differences in performance and brain activity between the two experimental conditions underscore the need for ecologically-valid investigations. (shrink)

Functional near-infrared spectroscopy is a neuroimaging technique that has undergone tremendous growth over the last decade due to methodological advantages over other measures of brain activation. The action-observation network, a system of brain structures proposed to have “mirroring” abilities, has been studied in humans through neural measures such as fMRI and electroencephalogram ; however, limitations of these methods are problematic for AON paradigms. For this reason, fNIRS is proposed as a solution to investigating the AON (...) in humans. The present review article briefly summarizes previous neural findings in the AON and examines the state of AON research using fNIRS in adults. A total of 14 fNIRS articles are discussed, paying particular attention to methodological choices and considerations while summarizing the general findings to aid in developing better protocols to study the AON through fNIRS. Additionally, future directions of this work are discussed, specifically in relation to researching AON development and potential multimodal imaging applications. (shrink)

This study decodes consumers' preference levels using a convolutional neural network in neuromarketing. The classification accuracy in neuromarketing is a critical factor in evaluating the intentions of the consumers. Functional near-infrared spectroscopy is utilized as a neuroimaging modality to measure the cerebral hemodynamic responses. In this study, a specific decoding structure, called CNN-based fNIRS-data analysis, was designed to achieve a high classification accuracy. Compared to other methods, the automated characteristics, constant training of the dataset, and (...) learning efficiency of the proposed method are the main advantages. The experimental procedure required eight healthy participants to view commercial advertisement videos of different durations. The cerebral hemodynamic responses of the participants were measured. To compare the preference classification performances, CNN was utilized to extract the most common features, including the mean, peak, variance, kurtosis, and skewness. Considering three video durations, the average classification accuracies of 15, 30, and 60 s videos were 84.3, 87.9, and 86.4%, respectively. Among them, the classification accuracy of 87.9% for 30 s videos was the highest. The average classification accuracies of three preferences in females and males were 86.2 and 86.3%, respectively, showing no difference in each group. By comparing the classification performances in three different combinations between two groups, male participants were observed to have targeted preferences for commercial advertising, and the classification performance 88.4% between “like” vs. “dislike” out of three categories was the highest. Finally, pairwise classification performance are shown as follows: For female, 86.1%, 87.4%, 85.2%, and for male 85.7, 88.4, 85.1%, respectively. (shrink)

The ability to learn sequential contingencies of actions for predicting future outcomes is indispensable for flexible behavior in many daily decision-making contexts. It remains open whether such ability may be enhanced by transcranial direct current stimulation. The present study combined tDCS with functional near-infrared spectroscopy to investigate potential tDCS-induced effects on sequential decision-making and the neural mechanisms underlying such modulations. Offline tDCS and sham stimulation were applied over the left and right dorsolateral prefrontal cortex in young (...) male adults in a double-blind between-subject design using a three-state Markov decision task. The results showed an enhanced dlPFC hemodynamic response during the acquisition of sequential state transitions that is consistent with the findings from a previous functional magnetic resonance imaging study; a tDCS-induced increase of the hemodynamic response in the dlPFC, but without accompanying performance-enhancing effects at the behavioral level; and a greater tDCS-induced upregulation of hemodynamic responses in the delayed reward condition that seems to be associated with faster decision speed. Taken together, these findings provide empirical evidence for fNIRS as a suitable method for investigating hemodynamic correlates of sequential decision-making as well as functional brain correlates underlying tDCS-induced modulation. Future research with larger sample sizes for carrying out subgroup analysis is necessary in order to decipher interindividual differences in tDCS-induced effects on sequential decision-making process at the behavioral and brain levels. (shrink)

A passive brain–computer interface based upon functional near-infrared spectroscopy brain signals is used for earlier detection of human drowsiness during driving tasks. This BCI modality acquired hemodynamic signals of 13 healthy subjects from the right dorsolateral prefrontal cortex of the brain. Drowsiness activity is recorded using a continuous-wave fNIRS system and eight channels over the right DPFC. During the experiment, sleep-deprived subjects drove a vehicle in a driving simulator while their cerebral oxygen regulation state was (...) continuously measured. Vector phase analysis was used as a classifier to detect drowsiness state along with sleep stage-based threshold criteria. Extensive training and testing with various feature sets and classifiers are done to justify the adaptation of threshold criteria for any subject without requiring recalibration. Three statistical features along with six VPA features were used. The average accuracies for the five classifiers are 90.9% for discriminant analysis, 92.5% for support vector machines, 92.3% for nearest neighbors, 92.4% for both decision trees, and ensembles over all subjects’ data. Trajectory slopes of CORE vector magnitude and angle: m and m are the best-performing features, along with ensemble classifier with the highest accuracy of 95.3% and minimum computation time of 40 ms. The statistical significance of the results is validated with a p-value of less than 0.05. The proposed passive BCI scheme demonstrates a promising technique for online drowsiness detection using VPA along with sleep stage classification. (shrink)

SignificanceElectrical burns can cause severe damage to the nervous system, resulting in autonomic dysfunction with reduced cerebral perfusion. However, few studies have investigated these consequences.AimTo elucidate changes in prefrontal cerebral hemodynamics using functional near-infrared spectroscopy (fNIRS) during the head-up tilt table test (HUT) for patients with electrical burns.ApproachWe recruited 17 patients with acute electrical burns within 1 week after their accidents and 10 healthy volunteers. The NIRS parameters acquired using an fNIRS device attached to (...) the forehead were analyzed in five distinct HUT phases.ResultsBased on their HUT response patterns, patients with electrical burns were classified into the group with abnormal HUT results (APG, n = 4) or normal HUT results (NPG, n = 13) and compared with the healthy control (HC, n = 10) participants. We found trends in hemodynamic changes during the HUT that distinguished HC, NPG, and APG. Reduced cerebral perfusion and decreased blood oxygenation during the HUT were found in both the NPG and APG groups. Patients with electrical burns had autonomic dysfunction compared to the HC participants.ConclusionsUsing fNIRS, we observed that acute-stage electrical burn injuries could affect cerebral perfusion. (shrink)

Functional near infrared spectroscopy 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. 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 and orbitofrontal cortex 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. (shrink)

Brain-computer interfaces (BCIs) are being investigated as an access pathway to communication for individuals with physical disabilities, as the technology obviates the need for voluntary motor control. However, to date, minimal research has investigated the use of BCIs for children. Traditional BCI communication paradigms may be suboptimal given that children with physical disabilities may face delays in cognitive development and acquisition of literacy skills. Instead, in this study we explored emotional state as an alternative access pathway to communication. We developed (...) a pediatric BCI to identify positive and negative emotional states from changes in hemodynamic activity of the prefrontal cortex (PFC). To train and test the BCI, 10 neurotypical children aged 8–14 underwent a series of emotion-induction trials over four experimental sessions (one offline, three online) while their brain activity was measured with functional near-infrared spectroscopy (fNIRS). Visual neurofeedback was used to assist participants in regulating their emotional states and modulating their hemodynamic activity in response to the affective stimuli. Child-specific linear discriminant classifiers were trained on cumulatively available data from previous sessions and adaptively updated throughout each session. Average online valence classification exceeded chance across participants by the last two online sessions (with 7 and 8 of the 10 participants performing better than chance, respectively, in Sessions 3 and 4). There was a small significant positive correlation with online BCI performance and age, suggesting older participants were more successful at regulating their emotional state and/or brain activity. Variability was seen across participants in regards to BCI performance, hemodynamic response, and discriminatory features and channels. Retrospective offline analyses yielded accuracies comparable to those reported in adult affective BCI studies using fNIRS. Affective fNIRS-BCIs appear to be feasible for school-aged children, but to further gauge the practical potential of this type of BCI, replication with more training sessions, larger sample sizes, and end-users with disabilities is necessary. (shrink)

The brain-computer interface based on functional near-infrared spectroscopy has received more and more attention due to its vast application potential in emotion recognition. However, the relatively insufficient investigation of the feature extraction algorithms limits its use in practice. In this article, to improve the performance of fNIRS-based BCI, we proposed a method named R-CSP-E, which introduces EEG signals when computing fNIRS signals’ features based on transfer learning and ensemble learning theory. In detail, we used (...) the Independent Component Analysis algorithm for the correspondence between the sources of the two signals. We then introduced the EEG signals when computing the spatial filter based on a modified Common Spatial Pattern algorithm. Experimental results on public datasets show that the proposed method in this paper outperforms traditional methods without transfer. In general, the mean classification accuracy can be increased by up to 5%. To our knowledge, it is an innovation that we tried to apply transfer learning between EEG and fNIRS. Our study’s findings not only prove the potential of the transfer learning algorithm in cross-model brain-computer interface, but also offer a new and innovative perspective to research the hybrid brain-computer interface. (shrink)

Prospective memory is the ability to perform a planned action at an intended future time. This study examined the neural correlates of PM using functional near-infrared spectroscopy. This study employed a within-participants design. A laboratory PM task was adapted for use with fNIRS to investigate regions of interest and levels of brain activation during task performance in 32 participants. Participants first completed a working memory task followed by a WM plus PM task while neural activity (...) was measured using fNIRS. Behavioral results revealed an interference effect for reaction time on the WM task, whereby participants were significantly slower to respond in the WM plus PM task compared to the WM task. Ongoing task accuracies did not differ between the two conditions. fNIRS results revealed a higher level of neural activity in the fronto-polar prefrontal cortex and dorsolateral prefrontal cortex in the WM plus PM task compared to the WM Condition. These findings highlight that fNIRS is a suitable tool for studying and understanding the neural basis of PM. (shrink)

BackgroundExercise is one of the effective ways to improve cognition. Different forms of exercises, such as aerobic exercise, resistance exercise, and coordination exercise, have different effects on the improvement of cognitive impairment. In recent years, exergames based on Non-Immersive Virtual Reality have been widely used in entertainment and have gradually been applied to clinical rehabilitation. However, the mechanism of NIVR-Exergames on improving motor cognition has not been clarified. Therefore, the aim of this study is to find whether NIVR-Exergames result in (...) a better neural response mechanism to improve the area of the cerebral cortex related to motor cognition under functional near-infrared spectroscopy dynamic monitoring in comparison with resistance exercise.MethodsA cross-over study design was adopted in this study, and 15 healthy young subjects were randomly divided into group A and group B according to a computerized digital table method. Task 1 was an NIVR-Exergame task, and Task 2 was resistance band stretching. Group A first performed Task 1, rested for 30 min, and then performed Task 2. Group B had the reverse order. The fNIRS test was synchronized in real time during exercise tasks, and heart rate measurements, blood pressure measurements, and 2-back task synchronization fNIRS tests were performed at baseline, Post-task 1, and Post-task 2. The primary outcomes were beta values from the general linear model in different regions of interest, and the secondary outcomes were heart rate, blood pressure, reaction time of 2-back, and accuracy rate of 2-back.ResultsThe activation differences of Task 1 and Task 2 in the right premotor cortex and the left PMC were statistically significant. There were statistically significant differences in the activation of the right supplementary motor area, left dorsolateral prefrontal cortex, left and right PMC between baseline and Post-task 1. The differences in systolic pressure between the two groups at three time points among women were statistically significant.ConclusionIn this study, we found that NIVR-Exergames combined with motor and challenging cognitive tasks can promote the activation of SMA, PMC and DLPFC in healthy young people compared with resistance exercise alone, providing compelling preliminary evidence of the power for the rehabilitation of motor and cognitive function in patients with central nervous system diseases. (shrink)

Executive function is essential to child development, with associated skills beginning to emerge in the first few years of life and continuing to develop into adolescence and adulthood. The prefrontal cortex, which follows a neurodevelopmental timeline similar to EF, plays an important role in the development of EF. However, limited research has examined prefrontal function in young children due to limitations of currently available neuroimaging techniques such as functional resonance magnetic imaging. The current study developed and applied a multimodal (...) Go/NoGo task to examine the EF component of inhibitory control in children 4–10 years of age. Cortical activity was measured using a non-invasive and child-friendly neuroimaging technique – functional near-infrared spectroscopy. Children’s response accuracy and reaction times were captured during the fNIRS session and compared with responses obtained using the standardized assessments from NIH Toolbox cognition battery. Results showed significant correlations between the behavioral measures during the fNIRS session and the standardized EF assessments, in line with our expectations. Results from fNIRS measures demonstrated a significant, age-independent effect of inhibitory control in the right PFC, and an age-dependent effect in the left orbitofrontal cortex, consistent with results in previous studies using fNIRS and fMRI. Thus, the new task designed for fNIRS was suitable for examining IC in young children, and results showed that fNIRS measures can reveal prefrontal IC function. (shrink)

Training under high interference conditions through interleaved practice results in performance suppression during training but enhances long-term performance relative to repetitive practice involving low interference. Previous neuroimaging work addressing this contextual interference effect of motor learning has relied heavily on the blood-oxygen-level-dependent response using functional magnetic resonance imaging methodology resulting in mixed reports of prefrontal cortex recruitment under IP and RP conditions. We sought to clarify these equivocal findings by imaging bilateral PFC recruitment using functional near-infrared (...) spectroscopy while discrete key pressing sequences were trained under IP and RP schedules and subsequently tested following a 24-h delay. An advantage of fNIRS over the fMRI BOLD response is that the former measures oxygenated and deoxygenated hemoglobin changes independently allowing for assessment of cortical hemodynamics even when there is neurovascular decoupling. Despite slower sequence performance durations under IP, bilateral PFC oxygenated and deoxygenated hemoglobin values did not differ between practice conditions. During test, however, slower performance from those previously trained under RP coincided with hemispheric asymmetry in PFC recruitment. Specifically, following RP, test deoxygenated hemoglobin values were significantly lower in the right PFC. The present findings contrast with previous behavioral demonstrations of increased cognitive demand under IP to illustrate a more complex involvement of the PFC in the contextual interference effect. IP and RP incur similar levels of bilateral PFC recruitment, but the processes underlying the recruitment are dissimilar. PFC recruitment during IP supports action reconstruction and memory elaboration while RP relies on PFC recruitment to maintain task variation information in working memory from trial to trial. While PFC recruitment under RP serves to enhance immediate performance, it does not support long-term performance. (shrink)

In the midst of globalization, English is regarded as an international language, or Lingua Franca, but learning it as a second language (L2) remains still difficult to speakers of other languages. This is true especially for the speakers of languages distantly related to English such as Japanese. In this sense, exploring neural basis for translation between the first language (L1) and L2 is of great interest. There have been relatively many previous researches revealing brain activation patterns during translations between L1 (...) and English as L2. These studies, which focused on language translation with close or moderate linguistic distance (LD), have suggested that the Broca area (BA 44/45) and the dorsolateral prefrontal cortex (DLPFC; BA 46) may play an important role on translation. However, the neural mechanism of language translation between Japanese and English, having large LD, has not been clarified. Thus, we used functional near infrared spectroscopy (fNIRS) to investigate the brain activation patterns during word translation between Japanese and English. We also assessed the effects of translation directions and word familiarity. All participants’ first language was Japanese and they were learning English. Their English proficiency was advanced or elementary. We selected English and Japanese words as stimuli based on the familiarity for Japanese people. Our results showed that the brain activation patterns during word translation largely differed depending on their English proficiency. The advanced group elicited greater activation on the left prefrontal cortex around the Broca’s area while translating words with low familiarity, but no activation was observed while translating words with high familiarity. On the other hand, the elementary group evoked greater activation on the left temporal area including the superior temporal gyrus (STG) irrespective of the word familiarity. These results suggested that different cognitive process could be involved in word translation corresponding to English proficiency in Japanese learners of English. These difference on the brain activation patterns between the advanced and elementary group may reflect the difference on the cognitive loads depending on the levels of automatization in one’s language processing. (shrink)

The aim of this study was to explain previous inconsistent results regarding the effects of positive affect on creative cognition based on the motivational dimensional model of affect theory and provide the underlying neural correlates of the effects of different approach-motivation intensities of positive affect on creative processes (creative idea generation and creative idea evaluation) using the functional near-infrared spectroscopy (fNIRS) technique. Sixty participants were randomly assigned to three groups (high-approach-motivated positive affect (HAM), low-approach-motivated positive (...) affect (LAM) and affectively neutral state (NS)) to complete corresponding tasks in creative idea generation and creative idea evaluation stages. In the creative idea generation stage, the results indicated that the LAM group achieved a higher performance in flexibility and originality than the NS group. However, compared with the NS group, the LAM group exhibited a lower sensitivity in the creative idea evaluation stage. The fNIRS technique provides an ideal approach with high ecological validity for exploring the issue of affect and creativity. In current study, fNIRS results showed that the HAM group exhibited significantly more activation in the bilateral frontal lobe than the LAM group and NS group in the creative idea generation stage. This result could reflect individuals attempting to overcome a narrowed attentional scope state through the activation of bilateral frontal cortical resources in the creative process. In the creative idea evaluation stage, compared with the NS group, the LAM group showed significant deactivation in the right dorsolateral prefrontal cortex, which is a brain area associated with executive, controlled processing. Moreover, the approach-motivation intensity altered the connectivity between the left prefrontal cortex and left superior temporal gyrus in the creative idea generation stage. Thus, the influences of positive affect on creative cognitive processes (both creative performance and hemodynamic responses) were modulated by the approach-motivation intensity in the creative idea generation and creative idea evaluation stages. (shrink)

Sensory feedback, which can be presented in different modalities - single and combined, aids task performance in human-robot interaction (HRI). However, combining feedback modalities does not always lead to optimal performance. Indeed, it is not known how feedback modalities affect operator performance under stress. Furthermore, there is limited information on how feedback affects neural processes differently for males and females and under stress. This is a critical gap in the literature, particularly in the domain of surgical robotics, where surgeons are (...) under challenging socio-technical environments that burden them physiologically. In the present study, we posited operator performance as the summation of task performance and neurophysiological cost of maintaining that performance. In a within-subject design, we used functional near-infrared spectroscopy (fNIRS) to assess cerebral activations of 12 participants who underwent a 3D manipulation task within a virtual environment with concurrent feedback (visual and visual + haptic) in the presence and absence of a cognitive stressor. Cognitive stress was induced with the serial-7 subtraction test. We found that while task performance was higher with visual than visual + haptic feedback, it degraded under stress. The two feedback modalities were found to be associated with varying neural activities and neural efficiencies, and these were stress- and gender-dependent. Our findings engender further investigation into effectiveness of feedback modalities on males and females under stressful conditions in HRI. (shrink)

This study aimed to reveal the characteristics of multi-circuit brain synergy between elite tai chi chuan athletes in resting and exercise states and to provide neuroimaging evidence of improvements in brain function by motor skill training. Functional near-infrared spectroscopy was used to compare the brain activity of professional tai chi chuan athletes and beginners in resting and exercise states, and to assess functional connectivity between the prefrontal lobe and the sensorimotor zone. In the resting state, (...) the FC between the left prefrontal lobe and the right sensorimotor area in the expert group was significantly lower than that in the novice group. In the exercise state, the patterns of FC between the left prefrontal lobe and right sensorimotor area, the right prefrontal lobe and left sensorimotor area, and the left and right sensorimotor areas in the expert group were significantly lower than that in the novice group. From the resting state to the locomotor state, the expert group experienced a greater absolute value of functional connection increment between the left prefrontal cortex and right sensorimotor area, and between the left sensorimotor area and right sensorimotor area. This was positively correlated with the self-evaluation results of motor performance behavior. Under sports conditions, professional athletes’ multi-circuit brain FC strength is significantly reduced, and their elite motor skill performance supports the neural efficiency hypothesis. This may be related to the high adaptation of the brain to specific tasks and the improvement of the integration of somatic perception processing and motor function. (shrink)

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

Hyperscanning studies using functional Near-Infrared Spectroscopy have been performed to understand the neural mechanisms underlying human-human interactions. In this study, we propose a novel methodological approach that is developed for fNIRS multi-brain analysis. Our method uses support vector regression to predict one brain activity time series using another as the predictor. We applied the proposed methodology to explore the teacher-student interaction, which plays a critical role in the formal learning process. In an illustrative application, we (...) collected fNIRS data of the teacher and preschoolers’ dyads performing an interaction task. The teacher explained to the child how to add two numbers in the context of a game. The Prefrontal cortex and temporal-parietal junction of both teacher and student were recorded. A multivariate regression model was built for each channel in each dyad, with the student’s signal as the response variable and the teacher’s ones as the predictors. We compared the predictions of SVR with the conventional ordinary least square predictor. The results predicted by the SVR model were statistically significantly correlated with the actual test data at least one channel-pair for all dyads. Overall, 29/90 channel-pairs across the five dyads presented significant signal predictions withthe SVR approach. The conventional OLS resulted in only 4 out of 90 valid predictions. These results demonstrated that the SVR could be used to perform channel-wise predictions across individuals, and the teachers’ cortical activity can be used to predict the student brain hemodynamic response. (shrink)

To further develop three-dimensional (3D) applications, it is important to elucidate the negative effects of 3D applications on the human body and mind. Thus, this study investigated differences in the effects of visual fatigue on cognition and brain activity using visual and auditory tasks induced by watching a 1-h movie in two dimensions (2D) and 3D. Eighteen young men participated in this study. Two conditions were randomly performed for each participant on different days, namely, watching the 1-h movie on television (...) in 2D (control condition) and 3D (3D condition). Before and after watching the 1-h movie on television, critical flicker fusion frequency (CFF: an index of visual fatigue), and response accuracy and reaction time for the cognitive tasks were determined. Brain activity during the cognitive tasks was evaluated using a multi-channel near-infrared spectroscopy system. In contrast to the control condition, the decreased CFF, and the lengthened reaction time and the decreased activity around the right primary somatosensory cortex during Go/NoGo blocks in the visual task at post-viewing in the 3D condition were significant, with significant repeated measures correlations among them. Meanwhile, in the auditory task, the changes in cognitive performance and brain activity during the Go/NoGo blocks were not significant in the 3D condition. These results suggest that the failure or delay in the transmission of visual information to the primary somatosensory cortex due to visual fatigue induced by watching a 3D movie reduced the brain activity around the primary somatosensory cortex, resulting in poor cognitive performance for the visual task. This suggests that performing tasks that require visual information, such as running in the dark or driving a car, immediately after using a 3D application, may create unexpected risks in our lives. Thus, the findings of this study will help outlining precautions for the use of 3D applications. (shrink)

Children with autism spectrum disorder show marked difficulties in reading comprehension, a complex cognitive skill fundamental to successful daily functioning that is associated with core executive functions. However, the neurophysiological mechanisms underlying reading comprehension deficits in these children remain elusive. Twenty-one right-handed males with high-functioning ASD and 23 age-, IQ-, educational level-, sex- and handedness-matched typically developing individuals underwent a reading comprehension test and the semantic verbal fluency test that tapped core executive functions underlying reading comprehension during concurrent prefrontal (...) class='Hi'>functional near-infrared spectroscopy measurement. Participants’ information processing efficiency was also assessed. High-functioning ASD children exhibited general reading comprehension [main effect of group: F = 7.58, p = 0.009], selective verbal fluency deficits [Group × category interaction: F = 4.90, p = 0.032] and slower processing speed. Regarding the hemodynamics of the prefrontal cortex, although ASD individuals showed comparable patterns of PFC brain activation to their healthy counterparts, lower PFC intrahemispheric [main effect of group: F = 11.36, p = 0.002] and interhemispheric [main effect of group: F = 7.79, p = 0.008] functional connectivity were evident during the semantic verbal fluency test. At the whole-group level, poorer reading comprehension performance was associated with poorer performance in the semantic verbal fluency test. Moreover, poorer semantic verbal fluency test performance was associated with slower information processing speed, which is associated with reduced left medial PFC functional connectivity. Abnormal intrahemispheric and interhemispheric prefrontal hypoconnectivity is associated with deficits in executive processes essential for reading comprehension in ASD. Our study has provided important implications for the neuropsychological and neurophysiological mechanisms underlying reading comprehension deficits in ASD. (shrink)

Electroencephalography and functional near-infrared spectroscopy have potentially complementary characteristics that reflect the electrical and hemodynamic characteristics of neural responses, so EEG-fNIRS-based hybrid brain-computer interface is the research hotspots in recent years. However, current studies lack a comprehensive systematic approach to properly fuse EEG and fNIRS data and exploit their complementary potential, which is critical for improving BCI performance. To address this issue, this study proposes a novel multimodal fusion framework based on multi-level progressive learning (...) with multi-domain features. The framework consists of a multi-domain feature extraction process for EEG and fNIRS, a feature selection process based on atomic search optimization, and a multi-domain feature fusion process based on multi-level progressive machine learning. The proposed method was validated on EEG-fNIRS-based motor imagery and mental arithmetic tasks involving 29 subjects, and the experimental results show that multi-domain features provide better classification performance than single-domain features, and multi-modality provides better classification performance than single-modality. Furthermore, the experimental results and comparison with other methods demonstrated the effectiveness and superiority of the proposed method in EEG and fNIRS information fusion, it can achieve an average classification accuracy of 96.74% in the MI task and 98.42% in the MA task. Our proposed method may provide a general framework for future fusion processing of multimodal brain signals based on EEG-fNIRS. (shrink)

Acute exercise consistently benefits both emotion and cognition, particularly cognitive control. We evaluated acute endurance exercise influences on emotion, domain-general cognitive control, and the cognitive control of emotion, specifically cognitive reappraisal. Thirty-six endurance runners, defined as running at least 30 miles per week with one weekly run of at least 9 miles (21 female, age 18-30 years) participated. In a repeated measures design, participants walked at 57% age-adjusted maximum heart rate (HRmax) (range 51-63%) and ran at 70% HRmax (range 64-76%) (...) for 90 minutes on two separate days. Participants completed measures of emotional state and the Stroop test of domain-general cognitive control before, every 30 minutes during, and 30 minutes after exercise. Participants also completed a cognitive reappraisal task after exercise. Functional near-infrared spectroscopy tracked changes in oxygenated and deoxygenated hemoglobin levels in the prefrontal cortex (PFC). Endurance exercise elevated positive emotion and cognitive reappraisal success. Endurance exercise reduced Stroop response time and test-evoked PFC oxygenation during exercise. Results suggest that even at relatively moderate intensities, endurance athletes benefit emotionally from running both during and after exercise, and task-related prefrontal cortex oxygenation reductions do not appear to hinder prefrontal-dependent cognitive control. (shrink)

As automobile manufacturers have begun to design, engineer, and test autonomous driving systems of the future, brain imaging with functional near-infrared spectroscopy can provide unique insights about cognitive processes associated with evolving levels of autonomy implemented in the automobile. Modern fNIRS devices provide a portable, relatively affordable, and robust form of functional neuroimaging that allows researchers to investigate brain function in real-world environments. The trend toward “naturalistic neuroscience” is evident in the growing number of (...) studies that leverage the methodological flexibility of fNIRS, and in doing so, significantly expand the scope of cognitive function that is accessible to observation via functional brain imaging. While more than a decade’s worth of study in this field of fNIRS driving research has led to many interesting findings, the number of studies applying fNIRS during autonomous modes of operation is limited. To support future research that directly addresses this lack in autonomous driving research with fNIRS, we argue that a cogent distillation of the methods used to date will help facilitate and streamline this research of tomorrow. To that end, here we provide a methodological review of the existing fNIRS driving research, with the overarching goal of highlighting the current diversity in methodological approaches. We argue that standardization of these approaches will facilitate greater overlap of methods by researchers from all disciplines, which will, in-turn, allow for meta-analysis of future results. We conclude by providing recommendations for advancing the use of such fNIRS technology in furthering understanding the adoption of safe autonomous vehicle technology. (shrink)

This abstract presents a novel brain-computer interface (BCI) framework to control a prosthetic leg, for the rehabilitation of patients suffering from locomotive disorders, using functional near-infrared spectroscopy (fNIRS). fNIRS signals corresponding to walking intention and rest are used to initiate and stop the gait cycle and a nonlinear proportional derivative computed torque controller (PD-CTC) with gravity compensation is used to control torques of hip and knee joints for minimization of position error. The brain signals (...) of walking intention and rest tasks are acquired from primary motor cortex in the left hemisphere for nine subjects. After acquiring brain signals, in order to remove motion artifacts and physiological noises, the performance of six different filters i.e. Kalman, Wiener, Gaussian, hemodynamic response filter (hrf), Band-pass and finite impulse response, is evaluated. Afterwards, six different features are extracted from oxygenated hemoglobin signals and their different combinations were used for classification. The classification performance of five different classifiers i.e. artificial neural network, quadratic discriminant analysis, linear discriminant analysis (LDA), Naïve Bayes and support vector machine (SVM) is used. The classification accuracies obtained from SVM using hrf filter are significantly higher (p < 0.005) than the other combinations of classifier and filters. These accuracies are 77.5%, 72.5%, 68.3%, 74.2%, 73.3%, 80.8%, 65%, 76.7%, and 86.7% for all nine subjects. The control commands generated using classifier initiate and stop the gait cycle of the prosthetic leg whose knee and hip torques are controlled using PD-CTC to minimize position error. The proposed scheme can be effectively used for neurofeedback training and rehabilitation of lower limb amputation of paralyzed patients. (shrink)

Multi-modal integration, which combines multiple neurophysiological signals, is gaining more attention for its potential to supplement single modality’s drawbacks and yield reliable results by extracting complementary features. In particular, integration of electroencephalography and functional near-infrared spectroscopy is cost-effective and portable, and therefore is a fascinating approach to brain-computer interface. However, outcomes from the integration of these two modalities have yielded only modest improvement in BCI performance because of the lack of approaches to integrate the two different (...) features. In addition, mismatch of recording locations may hinder further improvement. In this literature review, we surveyed studies of the integration of EEG/fNIRS in BCI thoroughly and discussed its current limitations. We also suggested future directions for efficient and successful multi-modal integration of EEG/fNIRS in BCI systems. (shrink)

Brain-computer interface multi-modal fusion has the potential to generate multiple commands in a highly reliable manner by alleviating the drawbacks associated with single modality. In the present work, a hybrid EEG-fNIRS BCI system—achieved through a fusion of concurrently recorded electroencephalography and functional near-infrared spectroscopy signals—is used to overcome the limitations of uni-modality and to achieve higher tasks classification. Although the hybrid approach enhances the performance of the system, the improvements are still modest due to the (...) lack of availability of computational approaches to fuse the two modalities. To overcome this, a novel approach is proposed using Multi-resolution singular value decomposition to achieve system- and feature-based fusion. The two approaches based up different features set are compared using the KNN and Tree classifiers. The results obtained through multiple datasets show that the proposed approach can effectively fuse both modalities with improvement in the classification accuracy. (shrink)

Executive functions are of vital importance in the process of active cognition, which is thought to be associated with the dorsolateral prefrontal cortex. As a valid brain stimulation technology, high-definition transcranial direct current stimulation has been used to optimize cognitive function in healthy adults. Substantial evidence indicates that short-term or single anodal tDCS sessions over the left DLPFC will enhance the performance of executive functions. However, the changes in performance and cortical activation of executive functions after modulation by repeated anodal (...) HD-tDCS is as yet unexplored. This study aims to examine changes in three core components of executive functions produced by nine HD-tDCS sessions, and to use functional near-infrared spectroscopy to bilaterally record DLPFC neural activity. A total of 43 participants were divided randomly into two study groups to complete nine interventions. Our results demonstrate that the enhancement of cognitive flexibility in the anodal group was significantly better than that in the sham group. Additionally, a Stroop effect-related decrease in oxygenated hemoglobin concentration in the DLPFC was observed in the anodal group but not the sham group. In conclusion, our study found that repeated anodal HD-tDCS sessions can significantly promote cognitive flexibility, one of the core components of executive function, and that alterations in DLPFC activation can enhance our understanding of the neuroplastic modifications modulated by HD-tDCS. (shrink)

Human gait is a complex activity that requires high coordination between the central nervous system, the limb, and the musculoskeletal system. More research is needed to understand the latter coordination's complexity in designing better and more effective rehabilitation strategies for gait disorders. Electroencephalogram and functional near-infrared spectroscopy are among the most used technologies for monitoring brain activities due to portability, non-invasiveness, and relatively low cost compared to others. Fusing EEG and fNIRS is a well-known and (...) established methodology proven to enhance brain–computer interface performance in terms of classification accuracy, number of control commands, and response time. Although there has been significant research exploring hybrid BCI involving both EEG and fNIRS for different types of tasks and human activities, human gait remains still underinvestigated. In this article, we aim to shed light on the recent development in the analysis of human gait using a hybrid EEG-fNIRS-based BCI system. The current review has followed guidelines of preferred reporting items for systematic reviews and meta-Analyses during the data collection and selection phase. In this review, we put a particular focus on the commonly used signal processing and machine learning algorithms, as well as survey the potential applications of gait analysis. We distill some of the critical findings of this survey as follows. First, hardware specifications and experimental paradigms should be carefully considered because of their direct impact on the quality of gait assessment. Second, since both modalities, EEG and fNIRS, are sensitive to motion artifacts, instrumental, and physiological noises, there is a quest for more robust and sophisticated signal processing algorithms. Third, hybrid temporal and spatial features, obtained by virtue of fusing EEG and fNIRS and associated with cortical activation, can help better identify the correlation between brain activation and gait. In conclusion, hBCI system is not yet much explored for the lower limb due to its complexity compared to the higher limb. Existing BCI systems for gait monitoring tend to only focus on one modality. We foresee a vast potential in adopting hBCI in gait analysis. Imminent technical breakthroughs are expected using hybrid EEG-fNIRS-based BCI for gait to control assistive devices and Monitor neuro-plasticity in neuro-rehabilitation. However, although those hybrid systems perform well in a controlled experimental environment when it comes to adopting them as a certified medical device in real-life clinical applications, there is still a long way to go. (shrink)

Over the last few decades, neuroimaging techniques have transformed our understanding of the brain and the effect of neurological conditions on brain function. More recently, light-based modalities such as functional near-infrared spectroscopy have gained popularity as tools to study brain function at the bedside. A recent application is to assess residual awareness in patients with disorders of consciousness, as some patients retain awareness albeit lacking all behavioural response to commands. Functional near-infrared spectroscopy (...) can play a vital role in identifying these patients by assessing command-driven brain activity. The goal of this review is to summarise the studies reported on this topic, to discuss the technical and ethical challenges of working with patients with disorders of consciousness, and to outline promising future directions in this field. (shrink)

This study explored the differentiated neural correlates of mental rotation in preschoolers with high and low working memory capacity using functional near-infrared spectroscopy. Altogether 38 Chinese preschoolers completed the Working Memory Capacity test, the Mental Rotation, and its Control tasks. They were divided into High-WMC and Low-WMC groups based on the WMC scores. The behavioral and fNIRS results indicated that: there were no significant differences in MR task performance between the High-WMC and Low-WMC group ; (...) the Low-WMC group activated BA6, BA8, BA 9, and BA 44, whereas the High-WMC group activated BA8, BA10 and BA 44 during mental rotation; significant differences were found in the activation of BA44 and BA9 between the High-WMC and Low-WMC groups during mental rotation; and the High-WMC and Low-WMC groups differed significantly in the activation of BA 9 and BA10 during the control tasks, indicating that both areas might be responsible for the group differences in working memory. (shrink)

Neuroimaging technologies have improved our understanding of deception and also exhibit their potential in revealing the origins of its neural mechanism. In this study, a quantitative power analysis method that uses the Welch power spectrum estimation of functional near-infrared spectroscopy signals was proposed to examine the brain activation difference between the spontaneous deceptive behavior and controlled behavior. The power value produced by the model was applied to quantify the activity energy of brain regions, which can serve (...) as a neuromarker for deception detection. Interestingly, the power analysis results generated from the Welch spectrum estimation method demonstrated that the spontaneous deceptive behavior elicited significantly higher power than that from the controlled behavior in the prefrontal cortex. Meanwhile, the power findings also showed significant difference between the spontaneous deceptive behavior and controlled behavior, indicating that the reward system was only involved in the deception. The proposed power analysis method for processing fNIRS data provides us an additional insight to understand the cognitive mechanism of deception. (shrink)

Although the neural systems that underlie spoken language are well-known, how they adapt to evolving social cues during natural conversations remains an unanswered question. In this work we investigate the neural correlates of face-to-face conversations between two individuals using functional near infrared spectroscopy and acoustical analyses of concurrent audio recordings. Nineteen pairs of healthy adults engaged in live discussions on two controversial topics where their opinions were either in agreement or disagreement. Participants were matched according to (...) their a priori opinions on these topics as assessed by questionnaire. Acoustic measures of the recorded speech including the fundamental frequency range, median fundamental frequency, syllable rate, and acoustic energy were elevated during disagreement relative to agreement. Consistent with both the a priori opinion ratings and the acoustic findings, neural activity associated with long-range functional networks, rather than the canonical language areas, was also differentiated by the two conditions. Specifically, the frontoparietal system including bilateral dorsolateral prefrontal cortex, left supramarginal gyrus, angular gyrus, and superior temporal gyrus showed increased activity while talking during disagreement. In contrast, talking during agreement was characterized by increased activity in a social and attention network including right supramarginal gyrus, bilateral frontal eye-fields, and left frontopolar regions. Further, these social and visual attention networks were more synchronous across brains during agreement than disagreement. Rather than localized modulation of the canonical language system, these findings are most consistent with a model of distributed and adaptive language-related processes including cross-brain neural coupling that serves dynamic verbal exchanges. (shrink)

Robots are increasingly envisaged as our future cohabitants. However, while considerable progress has been made in recent years in terms of their technological realization, the ability of robots to inter-act with humans in an intuitive and social way is still quite limited. An important challenge for social robotics is to determine how to design robots that can perceive the user’s needs, feelings, and intentions, and adapt to users over a broad range of cognitive abilities. It is conceivable that if robots (...) were able to adequately demonstrate this, humans would eventually accept them as social companions. We argue that the best way to achieve this is using a systematic experimental approach based on behavioral and physiological neuroscience methods such as motion/eye tracking, electroencephalography (EEG), or functional near-infrared spectroscopy (fNIRS) embedded in interactive human-robot paradigms. This approach requires understanding how humans interact with each other, how they perform tasks together and how they develop feelings of social connection over time, and using these insights to formulate design principles that make social robots attuned to the workings of the human brain. In this review, we put forward the argument that the likelihood of artificial agents being perceived as social companions can be increased by designing them in a way that they are perceived as intentional agents that activate areas in the human brain involved in social-cognitive processing. We first review literature related to social-cognitive mechanisms involved in human-human interactions, and high-light the importance of perceiving others as intentional agents to activate these brain areas. We then discuss how attribution of intentionality can positively affect human-robot interaction by (a) fostering feelings of social connection, empathy and prosociality, and by (b) enhancing performance on joint human-robot tasks. Lastly, we describe circumstances under which attribution of intentionality to robot agents might be disadvantageous, and discuss challenges associated with designing social robots that are inspired by neuroscientific principles. (shrink)

It has long been hypothesized that pretend play is beneficial to social and cognitive development. However, there is little evidence regarding the neural regions that are active while children engage in pretend play. We examined activation of prefrontal and posterior superior temporal sulcus (pSTS) regions using near-infrared spectroscopy while 42 four- to eight-year-old children freely played with dolls or tablet games with a social partner or by themselves. Social play activated right prefrontal regions more than solo play. (...) Children engaged the pSTS during solo doll play but not during solo tablet play, suggesting they were rehearsing social cognitive skills more with dolls. These findings suggest social play utilizes multiple neural regions and highlight how doll play can achieve similar patterns of activation, even when children play by themselves. Doll play may provide a unique opportunity for children to practice social interactions important for developing social emotional skills, such as empathy. (shrink)

The term ‘locked-in’ syndrome (LIS) describes a medical condition in which persons concerned are severely paralyzed and at the same time fully conscious and awake. The resulting anarthria makes it impossible for these patients to naturally communicate, which results in diagnostic as well as serious practical and ethical problems. Therefore, developing alternative, muscle-independent communication means is of prime importance. Such communication means can be realized via brain–computer interfaces (BCIs) circumventing the muscular system by using brain signals associated with preserved cognitive, (...) sensory, and emotional brain functions. Primarily, BCIs based on electrophysiological measures have been developed and applied with remarkable success. Recently, also blood flow–based neuroimaging methods, such as functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRS), have been explored in this context. After reviewing recent literature on the development of especially hemodynamically based BCIs, we introduce a highly reliable and easy-to-apply communication procedure that enables untrained participants to motor-independently and relatively effortlessly answer multiple-choice questions based on intentionally generated single-trial fMRI signals that can be decoded online. Our technique takes advantage of the participants’ capability to voluntarily influence certain spatio-temporal aspects of the blood oxygenation level–dependent (BOLD) signal: source location (by using different mental tasks), signal onset and offset. We show that healthy participants are capable of hemodynamically encoding at least four distinct information units on a single-trial level without extensive pretraining and with little effort. Moreover, realtime data analysis based on simple multi-filter correlations allows for automated answer decoding with a high accuracy (94.9%) demonstrating the robustness of the presented method.. (shrink)

Increasing student involvement in classes has always been a challenge for teachers and school managers. In online learning, some interactivity mechanisms like quizzes are increasingly used to engage students during classes and tasks. However, there is a high demand for tools that evaluate the efficiency of these mechanisms. In order to distinguish between high and low levels of engagement in tasks, it is possible to monitor brain activity through functional near-infrared spectroscopy. The main advantages of this (...) technique are portability, low cost, and a comfortable way for students to concentrate and perform their tasks. This setup provides more natural conditions for the experiments if compared to the other acquisition tools. In this study, we investigated levels of task involvement through the identification of correct and wrong answers of typical quizzes used in virtual environments. We collected data from the prefrontal cortex region of 18 students while watching a video lecture. This data was modeled with supervised learning algorithms. We used random forests and penalized logistic regression to classify correct answers as a function of oxyhemoglobin and deoxyhemoglobin concentration. These models identify which regions best predict student performance. The random forest and penalized logistic regression obtained, respectively, 0.67 and 0.65 area of the ROC curve. Both models indicate that channels F4-F6 and AF3-AFz are the most relevant for the prediction. The statistical significance of these models was confirmed through cross-validation and a permutation test. This methodology can be useful to better understand the teaching and learning processes in a video lecture and also provide improvements in the methodologies used in order to better adapt the presentation content. (shrink)

Neurofeedback has been suggested as a potential complementary therapy to different psychiatric disorders. Of interest for this approach is the prediction of individual performance and outcomes. In this study, we applied functional connectivity-based modeling using electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) modalities to (i) investigate whether resting-state connectivity predicts performance during an affective neurofeedback task and (ii) evaluate the extent to which predictive connectivity profiles are correlated across EEG and fNIRS techniques. The (...) fNIRS oxyhemoglobin and deoxyhemoglobin concentrations and the EEG beta and gamma bands modulated by the alpha frequency band (beta-m-alpha and gamma-m-alpha, respectively) recorded over the frontal cortex of healthy subjects were used to estimate functional connectivity from each neuroimaging modality. For each connectivity matrix, relevant edges were selected in a leave-one-subject-out procedure, summed into “connectivity summary scores” (CSS), and submitted as inputs to a support vector regressor (SVR). Then, the performance of the left-out-subject was predicted using the trained SVR model. Linear relationships between the CSS across both modalities were evaluated using Pearson’s correlation. The predictive model showed a mean absolute error smaller than 20%, and the fNIRS oxyhemoglobin CSS was significantly correlated with the EEG gamma-m-alpha CSS (r = −0.456, p = 0.030). These results support that pre-task electrophysiological and hemodynamic resting-state connectivity are potential predictors of neurofeedback performance and are meaningfully coupled. This investigation motivates the use of joint EEG-fNIRS connectivity as outcome predictors, as well as a tool for functional connectivity coupling investigation. (shrink)

Exposure Therapy (ET) has demonstrated its efficacy in the treatment of phobias, anxiety and Post-traumatic Stress Disorder (PTSD), however, it suffers a high drop-out rate because of too low or too high patient engagement in treatment. Virtual Reality Exposure Therapy (VRET) is comparably effective regarding symptom reduction and offers an alternative tool to facilitate engagement for avoidant participants. Neuroimaging studies have demonstrated that both ET and VRET normalize brain activity within a fear circuit. However, previous studies have employed brain imaging (...) technology which restricts people’s movement and hides their body, surroundings and therapist from view. This is at odds with the way engagement is typically controlled. We used a novel combination of neural imaging and VR technology—Functional Near-Infrared Spectroscopy (fNIRS) and Immersive Projection Technology (IPT), to avoid these limitations. Although there are a few studies that have investigated the effect of VRET on a brain function after the treatment, the present study utilized technologies which promote ecological validity to measure brain changes after VRET treatment. Furthermore, there are no studies that have measured brain activity within VRET session. In this study brain activity within the prefrontal cortex (PFC) was measured during three consecutive exposure sessions. N = 13 acrophobic volunteers were asked to walk on a virtual plank with a 6 m drop below. Changes in oxygenated (HbO) hemogl... (shrink)

This study aims to decode the hemodynamic responses evoked by multiple sound-categories using functional near-infrared spectroscopy. The six different sounds were given as stimuli. The oxy-hemoglobin concentration changes are measured in both hemispheres of the auditory cortex while 18 healthy subjects listen to 10-s blocks of six sound-categories. Long short-term memory networks were used as a classifier. The classification accuracy was 20.38 ± 4.63% with six class classification. Though LSTM networks’ performance was a little higher than (...) chance levels, it is noteworthy that we could classify the data subject-wise without feature selections. (shrink)

Background: There is increasing evidence to support the efficacy of transcranial direct current stimulation applications in cognitive augmentation and rehabilitation. Neuromodulation achieved with tDCS may further regulate regional cerebral perfusion affiliated through the neurovascular unit; however, components of cerebral perfusion decrease across aging. A novel neuroimaging approach, functional near-infrared spectroscopy, can aid in quantifying these regional perfusional changes. To date, the interaction of the effects of tDCS on cognitive performance across the lifespan and obtained fNIRS (...) hemodynamic responses remain unknown.Objective: This review aims to examine the effects of tDCS on cognitive performance and fNIRS hemodynamic responses within the context of cognitive aging.Methods: Six databases were searched for studies. Quality appraisal and data extraction were conducted by two independent reviewers. Meta-analysis was carried out to determine overall and subgroup effect sizes.Results: Eight studies met inclusion criteria. The overall effect size demonstrates that tDCS can alter cognitive performance and fNIRS signals, with aging being a potential intermediary in tDCS efficacy.Conclusion: From the studies included, the effects of tDCS on cognitive performance and fNIRS metrics are most prominent in young healthy adults and appear to become less robust with increasing age. Given the small number of studies included in this review further investigation is recommended. (shrink)

The simultaneous recording of brain activity in two or more people, termed hyperscanning, is an emerging field of research investigating the neural basis of social interaction. Hyperscanning studies of adult–infant dyads have great potential to provide insights into how social functions develop. In particular, taking advantage of functional near-infrared spectroscopy for its spatial resolution and invulnerability to motion artifacts, adult–infant fNIRS may play a major role in this field. However, there remains a problem in analyzing (...) hyperscanning data between adult and young populations. Namely, there are intrinsic differences in hemodynamic time latencies depending on age, and the peak latency of the hemodynamic response function is longer in younger populations. Despite this fact, the effects of such differences on quantified synchrony have not yet been examined. Consequently, the present study investigated the influence of intrinsic hemodynamic differences on wavelet coherence for assessing brain synchrony, and further examined the statistical removal of these effects through simulation experiments. First, we assumed a social signal model, where one counterpart of the dyad sends a social signal to the other, which eventually results in simultaneous brain activation. Based on this model, simulated fNIRS activation sequences were synthesized by convolving boxcar event sequences with HRFs. We set two conditions for the event: synchronized and asynchronized event conditions. We also modeled the HRFs of adults and infants by referring to previous studies. After preprocessing with additional statistical processing, we calculated the wavelet coherence for each synthesized fNIRS activation sequence pair. The simulation results showed that the wavelet coherence in the synchronized event condition was attenuated for the combination of different HRFs. We also confirmed that prewhitening via an autoregressive filter could recover the attenuation of wavelet coherence in the 0.03–0.1 Hz frequency band, which was regarded as being associated with synchronous neural activity. Our results showed that variability in hemodynamics affected the analysis of inter-brain synchrony, and that the application of prewhitening is critical for such evaluations between adult and young populations. (shrink)

This study examined whether 8-month-old infants’ hemodynamic responses in the temporal region were modulated by repeated presentation of “Peekaboo” by using functional near-infrared spectroscopy. Previous studies have shown that infants’ temporal region responds to faces. A recent electroencephalography study showed that the neural activity of infants was modulated by repeated presentation of “Peekaboo.” Some fNIRS studies also revealed that the movie of “Peekaboo” activated the hemodynamic response of the temporal region in infancy. However, no studies (...) have shown the hemodynamic modulation of the temporal region according to the repeated presentation of “Peekaboo” in infants. In order to examine whether the hemodynamic responses of the temporal region were modulated by repeated presentation of “Peekaboo,” we compared the activity of the temporal region between the early and late trials. We set long and short delays before face-presentation. The results showed that the concentration of oxy-hemoglobin in the right occipitotemporal region in both conditions increased after the presentation of “Peekaboo” relative to the baseline. Moreover, in the long delay condition, the hemodynamic modulation of the right occipitotemporal region was induced according to the repeated presentation of “Peekaboo” in infants. (shrink)

While many publications have reported brain hemodynamic responses to decision-making under various conditions of risk, no inventory management scenarios, such as the newsvendor problem, have been investigated in conjunction with neuroimaging. In this study, we hypothesized that NP stimulates the dorsolateral prefrontal cortex and the orbitofrontal cortex joined with frontal polar area significantly in the human brain, and that local brain network properties are increased when a person transits from rest to the NP decision-making phase. A 77-channel functional (...) class='Hi'>near infrared spectroscopy system with wide field-of-view was employed to measure frontal cerebral hemodynamics in response to NP in 27 healthy human subjects. NP-induced changes in oxy-hemoglobin concentration, Δ[HbO], were investigated using a general linear model and graph theory analysis. Significant activation induced by NP was shown in both DLPFC and OFC+FPA across all subjects. Specifically, higher risk NP with low-profit margins activated left-DLPFC but deactivated right-DLPFC in 14 subjects, while lower risk NP with high-profit margins stimulated both DLPFC and OFC+FPA in 13 subjects. The local efficiency, clustering coefficient, and path length of the network metrics were significantly enhanced under NP decision making. In summary, multi-channel fNIRS enabled us to identify DLPFC and OFC+FPA as key cortical regions of brain activations when subjects were making inventory-management risk decisions. We demonstrated that challenging NP resulted in the deactivation within right-DLPFC due to higher levels of stress. Also, local brain network properties were increased when a person transitioned from the rest phase to the NP decision-making phase. (shrink)