Imaging Brain Function with Functional Near-Infrared Spectroscopy in Unconstrained Environments

Affective Neurofeedback Under Naturalistic Conditions: A Mini-Review of Current Achievements and Open Challenges

Affective neurofeedback training allows for the self-regulation of the putative circuits of emotion regulation. This approach has recently been studied as a possible additional treatment for psychiatric disorders, presenting positive effects in symptoms and behaviors. After neurofeedback training, a critical aspect is the transference of the learned self-regulation strategies to outside the laboratory and how to continue reinforcing these strategies in non-controlled environments. In this mini-review, we discuss the current achievements of affective neurofeedback under naturalistic setups. For this, we first provide a brief overview of the state-of-the-art for affective neurofeedback protocols. We then discuss virtual reality as a transitional step toward the final goal of "in-the-wild" protocols and current advances using mobile neurotechnology. Finally, we provide a discussion of open challenges for affective neurofeedback protocols in-the-wild, including topics such as convenience and reliability, environmental effects in attention and workload, among others.

A New Statistical Approach for fNIRS Hyperscanning to Predict Brain Activity of Preschoolers' Using Teacher's

Hyperscanning studies using functional Near-Infrared Spectroscopy (fNIRS) 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 (SVR) 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 (OLS) 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 (18 channels 5 dyads = 90 channel-pairs) 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.

Evaluating a new generation of wearable high-density diffuse optical tomography technology via retinotopic mapping of the adult visual cortex

Significance: High-density diffuse optical tomography (HD-DOT) has been shown to approach the resolution and localization accuracy of blood oxygen level dependent-functional magnetic resonance imaging in the adult brain by exploiting densely spaced, overlapping samples of the probed tissue volume, but the technique has to date required large and cumbersome optical fiber arrays. Aim: To evaluate a wearable HD-DOT system that provides a comparable sampling density to large, fiber-based HD-DOT systems, but with vastly improved ergonomics. Approach: We investigated the performance of this system by replicating a series of classic visual stimulation paradigms, carried out in one highly sampled participant during 15 sessions to assess imaging performance and repeatability. Results: Hemodynamic response functions and cortical activation maps replicate the results obtained with larger fiber-based systems. Our results demonstrate focal activations in both oxyhemoglobin and deoxyhemoglobin with a high degree of repeatability observed across all sessions. A comparison with a simulated low-density array explicitly demonstrates the improvements in spatial localization, resolution, repeatability, and image contrast that can be obtained with this high-density technology. Conclusions: The system offers the possibility for minimally constrained, spatially resolved functional imaging of the human brain in almost any environment and holds particular promise in enabling neuroscience applications outside of the laboratory setting. It also opens up new opportunities to investigate populations unsuited to traditional imaging technologies.

Closed-loop neurostimulation for affective symptoms and disorders: An overview

Affective and anxiety disorders are the most prevalent and incident psychiatric disorders worldwide. Therapeutic approaches to these disorders using non-invasive brain stimulation (NIBS) and analogous techniques have been extensively investigated. In this paper, we discuss the combination of NIBS and neurofeedback in closed-loop setups and its application for affective symptoms and disorders. For this, we first provide a rationale for this combination by presenting some of the main original findings of NIBS, with a primary focus on transcranial magnetic stimulation (TMS), and neurofeedback, including protocols based on electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Then, we provide a scope review of studies combining real-time neurofeedback with NIBS protocols in the so-called closed-loop brain state-dependent neuromodulation (BSDS). Finally, we discuss the concomitant use of TMS and real-time functional near-infrared spectroscopy (fNIRS) as a possible solution to the current limitations of BSDS-based protocols for affective and anxiety disorders.

Measures of prefrontal functional near-infrared spectroscopy in visuomotor learning

Functional near-infrared spectroscopy (fNIRS) is a promising technique for non-invasively assessing cortical brain activity during learning. This technique is safe, portable, and, compared to other imaging techniques, relatively robust to head motion, ocular and muscular artifacts and environmental noise. Moreover, the spatial resolution of fNIRS is superior to electroencephalography (EEG), a more commonly applied technique for measuring brain activity non-invasively during learning. Outcomes from fNIRS measures during learning might therefore be both sensitive to learning and to feedback on learning, in a different way than EEG. However, few studies have examined fNIRS outcomes in learning and no study to date additionally examined the effects of feedback. To address this apparent gap in the literature, the current study examined prefrontal cortex activity measured through fNIRS during visuomotor learning and how this measure is affected by task feedback. Activity in the prefrontal cortex decreased over the course of learning while being unaffected by task feedback. The findings demonstrate that fNIRS in the prefrontal cortex is valuable for assessing visuomotor learning and that this measure is robust to task feedback. The current study highlights the potential of fNIRS in assessing learning even under different task feedback conditions.

Validating the use of functional Near-Infrared Spectroscopy in monkeys: The case of brain activation lateralization in Papio anubis

Hemispheric asymmetries have long been seen as characterizing the human brain; yet, an increasing number of reports suggest the presence of such brain asymmetries in our closest primate relatives. However, most available data in non-human primates have so far been acquired as part of neurostructural approaches such as MRI, while comparative data in humans are often dynamically acquired as part of neurofunctional studies. In the present exploratory study in baboons (Papio anubis), we tested whether brain lateralization could be recorded non-invasively using a functional Near-Infrared Spectroscopy (fNIRS) device in two contexts: motor and auditory passive stimulations. Under light propofol anaesthesia monitoring, three adult female baboons were exposed to a series of (1) left- versus right-arm passive movement stimulations; and (2) left- versus right-ear versus stereo auditory stimulations while recording fNIRS signals in the related brain areas (i.e., motor central sulcus and superior temporal cortices respectively). For the sensorimotor condition our results show that left-arm versus right-arm stimulations induced typical contralateral difference in hemispheric activation asymmetries in the three subjects. For the auditory condition, we also revealed typical human-like patterns of hemispheric asymmetries in one subject, namely a leftward lateralization for right ear stimulations for all three channels. Overall, our findings support the use of fNIRS to investigate brain processing in non-human primates from a functional perspective, opening the way for the development of non-invasive procedures in non-human primate brain research.

Frontal Hemodynamic Response During Step Initiation Under Cognitive Conflict in Older and Young Healthy People

Gait initiation is a daily challenge even for healthy individuals as it requires the timely coupling between the automatic anticipatory postural adjustment (APA) and the voluntary step according to the context. Modulation of this motor event has been thought to involve higher level brain control, including cognitive inhibitory circuitries. Despite the known participation of the supplementary motor area (SMA) in the modulation of some parameters of APA, the participation of areas controlling inhibition during gait initiation still needs to be investigated. In this study, the hemodynamic responses of the SMA and dorsolateral prefrontal cortex (DLPFC) were assessed using functional near-infrared spectroscopy (fNIRS) during a gait initiation task under cognitive conflict to select the foot to step (congruent [CON] and incongruent [INC] conditions). The older group (OG) showed worse inhibitory control than the young group (YG) along with more impairments in APA parameters. OG also had a lower amplitude of hemodynamic responses in both areas than YG in the INC. The INC increased the correlation between SMA and DLPFC only in the YG. Aging seems to impair the interaction between the hemodynamic responses of SMA and DLPFC, which influences APA performance in gait initiation under cognitive conflict.

Subject-independent decoding of affective states using functional near-infrared spectroscopy

Affective decoding is the inference of human emotional states using brain signal measurements. This approach is crucial to develop new therapeutic approaches for psychiatric rehabilitation, such as affective neurofeedback protocols. To reduce the training duration and optimize the clinical outputs, an ideal clinical neurofeedback could be trained using data from an independent group of volunteers before being used by new patients. Here, we investigated if this subject-independent design of affective decoding can be achieved using functional near-infrared spectroscopy (fNIRS) signals from frontal and occipital areas. For this purpose, a linear discriminant analysis classifier was first trained in a dataset (49 participants, 24.65±3.23 years) and then tested in a completely independent one (20 participants, 24.00±3.92 years). Significant balanced accuracies between classes were found for positive vs. negative (64.50 ± 12.03%, p<0.01) and negative vs. neutral (68.25 ± 12.97%, p<0.01) affective states discrimination during a reactive block consisting in viewing affective-loaded images. For an active block, in which volunteers were instructed to recollect personal affective experiences, significant accuracy was found for positive vs. neutral affect classification (71.25 ± 18.02%, p<0.01). In this last case, only three fNIRS channels were enough to discriminate between neutral and positive affective states. Although more research is needed, for example focusing on better combinations of features and classifiers, our results highlight fNIRS as a possible technique for subject-independent affective decoding, reaching significant classification accuracies of emotional states using only a few but biologically relevant features.

NIRS measures in pain and analgesia: Fundamentals, features, and function

Current pain assessment techniques based only on clinical evaluation and self-reports are not objective and may lead to inadequate treatment. Having a functional biomarker will add to the clinical fidelity, diagnosis, and perhaps improve treatment efficacy in patients. While many approaches have been deployed in pain biomarker discovery, functional near-infrared spectroscopy (fNIRS) is a technology that allows for non-invasive measurement of cortical hemodynamics. The utility of fNIRS is especially attractive given its ability to detect specific changes in the somatosensory and high-order cortices as well as its ability to measure (1) brain function similar to functional magnetic resonance imaging, (2) graded responses to noxious and innocuous stimuli, (3) analgesia, and (4) nociception under anesthesia. In this review, we evaluate the utility of fNIRS in nociception/pain with particular focus on its sensitivity and specificity, methodological advantages and limitations, and the current and potential applications in various pain conditions. Everything considered, fNIRS technology could enhance our ability to evaluate evoked and persistent pain across different age groups and clinical populations.

Combining the intersubject correlation analysis and the multivariate distance matrix regression to evaluate associations between fNIRS signals and behavioral data from ecological experiments

The development of methods to analyze data acquired using functional near-infrared spectroscopy (fNIRS) in experiments similar to real-life situations is of great value in modern applied neuroscience. One of the most used methods to analyze fNIRS signals consists of the application of the general linear model on the observed hemodynamic signals. However, it implies limitations on the experimental design that must be constrained by triggers related to the stimuli protocols (such as block design or event related). In this work, a novel methodology is proposed to overcome such restrictions and allow more flexible protocols. The method combines the intersubject correlation analysis and the multivariate distance matrix regression to evaluate the brain-behavior relationship of subjects submitted to experiments with no trigger-based protocols. Its applicability is demonstrated throughout a naturalistic experiment about emotions conveyed by music. Thirty-two participants freely listened to instrumental excerpts from the operatic repertoire and reported the valences of the emotions conveyed by the musical segments. The method was able to find a statistically significant correlation between the subjects' fNIRS signals and valences of their emotional responses, for the excerpt that evoked the most negative valence. This result illustrates the potential of this approach as an alternative method to analyze fNIRS signals from experiments in which block design or task-related paradigms might not be suitable.

Characterizing hemodynamic response alterations during basketball dribbling

Knowledge on neural processing during complex non-stationary motion sequences of sport-specific movements still remains elusive. Hence, we aimed at investigating hemodynamic response alterations during a basketball slalom dribbling task (BSDT) using multi-distance functional near-infrared spectroscopy (fNIRS) in 23 participants (12 females). Additionally, we quantified how the brain adapts its processing as a function of altered hand use (dominant right hand (DH) vs. non-dominant left hand (NDH) vs. alternating hands (AH)) and pace of execution (slow vs. fast) in BSDT. We found that BSDT activated bilateral premotor cortex (PMC), supplementary motor cortex (SMA), primary motor cortex (M1) as well as inferior parietal cortex and somatosensory association cortex. Slow dominant hand dribbling (DH_slow) evoked lower contralateral hemodynamic responses in sensorimotor regions compared to fast dribbling (DH_fast). Furthermore, during DH_slow dribbling, we found lower hemodynamic responses in ipsilateral M1 as compared to dribbling with alternating hands (AH_slow). Hence, altered task complexity during BSDT induced differential hemodynamic response patterns. Furthermore, a correlation analysis revealed that lower levels of perceived task complexity are associated with lower hemodynamic responses in ipsilateral PMC-SMA, which is an indicator for neuronal efficiency in participants with better basketball dribbling skills. The present study extends previous findings by showing that varying levels of task complexity are reflected by specific hemodynamic response alterations even during sports-relevant motor behavior. Taken together, we suggest that quantifying brain activation during complex movements is a prerequisite for assessing brain-behavior relations and optimizing motor performance.

Neural alignment during face-to-face spontaneous deception: Does gender make a difference?

This study investigated the gender differences in deception and their neural basis in the perspective of two‐person neuroscience. Both male and female dyads were asked to perform a face‐to‐face spontaneous sender–receiver deception task, while their neural activities in the prefrontal cortex (PFC) and right temporal parietal junction (rTPJ) were recorded simultaneously using functional near‐infrared spectroscopy (fNIRS)‐based hyperscanning. Male and female dyads displayed similar deception rate, successful deception rate, and eye contact in deception trials. Moreover, eye contact in deception trials was positively correlated with the success rate of deception in both genders. The fNIRS data showed that the interpersonal neural synchronization (INS) in PFC was significantly enhanced only in female dyads when performed the deception task, while INS in rTPJ was increased only in male dyads. Such INS was correlated with the success rate of deception in both dyads. Granger causality analysis showed that no significant directionality between time series of PFC (or rTPJ) in each dyad, which could indicate that sender and receiver played equally important role during deception task. Finally, enhanced INS in PFC in female dyads mediated the contribution of eye contact to the success rate of deception. All findings in this study suggest that differential patterns of INS are recruited when male and female dyads perform the face‐to‐face deception task. To our knowledge, this is the first interbrain evidence for gender difference of successful deception, which could make us a deeper understanding of spontaneous face‐to‐face deception.

EEG spectro-temporal amplitude modulation as a measurement of cortical hemodynamics: an EEG-fNIRS study

Neurovascular coupling provides valuable descriptive information about neural function and communication. In this work, we propose to objectively characterize EEG sub-band modulation in an attempt to compare with local variations of fNIRS hemoglobin concentration. First, full-band EEG signals are decomposed into five well-known frequency sub-bands: delta, theta, alpha, beta, and gamma. The temporal amplitude envelope of each sub-band is then computed via Hilbert transformation. The proposed EEG 'spectro-temporal amplitude modulation' (EEG-AM) feature measures the rate at which each sub-band is modulated. Similarities between EEG-AM features and fNIRS hemoglobin concentration are computed for four neighboring channels over the occipital area during resting-state. Experiments with a database of 29 participants show statistically significant similarities between the total hemoglobin concentration and the alpha band modulating the alpha, beta, and gamma frequencies. These results support the idea that the EEG-AM can carry hemodynamic properties.Clinical relevance- This shows that the EEG spectro-temporal amplitude modulation present similarities with the hemoglobin concentration in co-placed channels.

New Directions in Exercise Prescription: Is There a Role for Brain-Derived Parameters Obtained by Functional Near-Infrared Spectroscopy?

In the literature, it is well established that regular physical exercise is a powerful strategy to promote brain health and to improve cognitive performance. However, exact knowledge about which exercise prescription would be optimal in the setting of exercise–cognition science is lacking. While there is a strong theoretical rationale for using indicators of internal load (e.g., heart rate) in exercise prescription, the most suitable parameters have yet to be determined. In this perspective article, we discuss the role of brain-derived parameters (e.g., brain activity) as valuable indicators of internal load which can be beneficial for individualizing the exercise prescription in exercise–cognition research. Therefore, we focus on the application of functional near-infrared spectroscopy (fNIRS), since this neuroimaging modality provides specific advantages, making it well suited for monitoring cortical hemodynamics as a proxy of brain activity during physical exercise.

Brain-Based Binary Communication Using Spatiotemporal Features of fNIRS Responses

“Locked-in” patients lose their ability to communicate naturally due to motor system dysfunction. Brain-computer interfacing offers a solution for their inability to communicate by enabling motor-independent communication. Straightforward and convenient in-session communication is essential in clinical environments. The present study introduces a functional near-infrared spectroscopy (fNIRS)-based binary communication paradigm that requires limited preparation time and merely nine optodes. Eighteen healthy participants performed two mental imagery tasks, mental drawing and spatial navigation, to answer yes/no questions during one of two auditorily cued time windows. Each of the six questions was answered five times, resulting in five trials per answer. This communication paradigm thus combines both spatial (two different mental imagery tasks, here mental drawing for “yes” and spatial navigation for “no”) and temporal (distinct time windows for encoding a “yes” and “no” answer) fNIRS signal features for information encoding. Participants’ answers were decoded in simulated real-time using general linear model analysis. Joint analysis of all five encoding trials resulted in an average accuracy of 66.67 and 58.33% using the oxygenated (HbO) and deoxygenated (HbR) hemoglobin signal respectively. For half of the participants, an accuracy of 83.33% or higher was reached using either the HbO signal or the HbR signal. For four participants, effective communication with 100% accuracy was achieved using either the HbO or HbR signal. An explorative analysis investigated the differentiability of the two mental tasks based solely on spatial fNIRS signal features. Using multivariate pattern analysis (MVPA) group single-trial accuracies of 58.33% (using 20 training trials per task) and 60.56% (using 40 training trials per task) could be obtained. Combining the five trials per run using a majority voting approach heightened these MVPA accuracies to 62.04 and 75%. Additionally, an fNIRS suitability questionnaire capturing participants’ physical features was administered to explore its predictive value for evaluating general data quality. Obtained questionnaire scores correlated significantly (r = -0.499) with the signal-to-noise of the raw light intensities. While more work is needed to further increase decoding accuracy, this study shows the potential of answer encoding using spatiotemporal fNIRS signal features or spatial fNIRS signal features only.

Processing False Beliefs in Preschool Children and Adults: Developing a Set of Custom Tasks to Test the Theory of Mind in Neuroimaging and Behavioral Research

The theory of mind (ToM) is the ability to attribute mental states to others and is extremely important for social functioning. It has been widely examined in both behavioral and neuroimaging research, usually with the use of the many versions of the false-belief (FB) task. However, there is still not enough evidence from studies on the neurodevelopmental mechanisms of ToM mostly because of methodological limitations: lack of selectivity, mismatch of experimental and control tasks, and focusing on participants older than 6 years old. In the current study, we attempted to develop a computerized tool for ToM assessment suitable for both behavioral and neuriomaging testing in preschoolers. We designed a version of the classic change-of-location task with custom visuals and three fine-tuned conditions: FB, true-belief, and no-belief (NB). The usability of the task for further application in neurodevelopmental research was tested with three methods: first, behaviorally, with the use of a touch screen on a group of 75 children, followed by a functional MRI (fMRI) study on 13 adults, and a functional near-infrared spectroscopy (fNIRS) study on 19 preschool children. In line with our expectations, on the behavioral level, our task elicited the all-or-none performance in preschoolers. There was also a progression of performance with age in the FB condition. On the neural level, we observed the activation of structures involved in the ToM brain network in response to our task in both adults and children. The results therefore suggest that our task can be a useful tool for studying ToM development and its neural underpinnings.

Neurodiagnostics in Sports: Investigating the Athlete's Brain to Augment Performance and Sport-Specific Skills

Enhancing performance levels of athletes during training and competition is a desired goal in sports. Quantifying training success is typically accompanied by performance diagnostics including the assessment of sports-relevant behavioral and physiological parameters. Even though optimal brain processing is a key factor for augmented motor performance and skill learning, neurodiagnostics is typically not implemented in performance diagnostics of athletes. We propose, that neurodiagnostics via non-invasive brain imaging techniques such as functional near-infrared spectroscopy (fNIRS) will offer novel perspectives to quantify training-induced neuroplasticity and its relation to motor behavior. A better understanding of such a brain-behavior relationship during the execution of sport-specific movements might help to guide training processes and to optimize training outcomes. Furthermore, targeted non-invasive brain stimulation such as transcranial direct current stimulation (tDCS) might help to further enhance training outcomes by modulating brain areas that show training-induced neuroplasticity. However, we strongly suggest that ethical aspects in the use of non-invasive brain stimulation during training and/or competition need to be addressed before neuromodulation can be considered as a performance enhancer in sports.

The present and future use of functional near-infrared spectroscopy (fNIRS) for cognitive neuroscience

The past few decades have seen a rapid increase in the use of functional near-infrared spectroscopy (fNIRS) in cognitive neuroscience. This fast growth is due to the several advances that fNIRS offers over the other neuroimaging modalities such as functional magnetic resonance imaging and electroencephalography/magnetoencephalography. In particular, fNIRS is harmless, tolerant to bodily movements, and highly portable, being suitable for all possible participant populations, from newborns to the elderly and experimental settings, both inside and outside the laboratory. In this review we aim to provide a comprehensive and state-of-the-art review of fNIRS basics, technical developments, and applications. In particular, we discuss some of the open challenges and the potential of fNIRS for cognitive neuroscience research, with a particular focus on neuroimaging in naturalistic environments and social cognitive neuroscience.

An EEG-fNIRS hybridization technique in the four-class classification of alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is projected to become one of the most expensive diseases in modern history, and yet diagnostic uncertainties exist that can only be confirmed by postmortem brain examination. Machine Learning (ML) algorithms have been proposed as a feasible alternative to the diagnosis of several neurological diseases and disorders, such as AD. An ideal ML-derived diagnosis should be inexpensive and noninvasive while retaining the accuracy and versatility that make ML techniques desirable for medical applications.

NEW METHODS

Two portable modalities, Electroencephalography (EEG) and functional Near-Infrared Spectroscopy (fNIRS) have been widely employed in constructing hybrid classification models to compensate for each other's weaknesses. In this study, we present a hybrid EEG-fNIRS model for classifying four classes of subjects including one healthy control (HC) group, one mild cognitive impairment (MCI) group, and, two AD patient groups. A concurrent EEG-fNIRS setup was used to record data from 29 subjects during a random digit encoding-retrieval task. EEG-derived and fNIRS-derived features were sorted using a Pearson correlation coefficient-based feature selection (PCCFS) strategy and then fed into a linear discriminant analysis (LDA) classifier to evaluate their performance.

RESULTS

The hybrid EEG-fNIRS feature set was able to achieve a higher accuracy (79.31 %) by integrating their complementary properties, compared to using EEG (65.52 %) or fNIRS alone (58.62 %). Moreover, our results indicate that the right prefrontal and left parietal regions are associated with the progression of AD.

COMPARISON WITH EXISTING METHODS

Our hybrid and portable system provided enhanced classification performance in multi-class classification of AD population.

CONCLUSIONS

These findings suggest that hybrid EEG-fNIRS systems are a promising tool that may enhance the AD diagnosis and assessment process.

Effect of English learning experience on young children's prefrontal cortex functioning for attentional control: An fNIRS study

The exploration concerning effect of bilingualism on cognitive performance has been enriched in recently studies. However, scarce research focused on its impact on the brain function, especially in non-proficient bilingual children. In the present study, both Chinese monolingual and English as a foreign language (EFL) bilingual children were conducted to a non-verbal attentional network task (ANT) by functional near-infrared spectroscopy (fNIRS) technique for exploring the consequence of English learning experience on young children's prefrontal regions of functioning attentional control. The behavior results showed that young EFL bilinguals outperformed monolinguals on the accuracy of ANT conflict condition. Furthermore, EFL bilingual children had higher activation in the left prefrontal cortex (inferior frontal gyrus and dorsal lateral prefrontal cortex) than counterpart monolinguals. More interestingly, the degree of bilingual language balance positively correlated with that behavior accuracy and brain activation in bilingual group. These findings provided additional support for the bilingual advantage hypothesis and illustrated implications for understanding how foreign language learning impact children's brain development.

Oxygenation of the Prefrontal Cortex during Memory Interference

BACKGROUND

Memory interference occurs when information (or memory) to be retrieved is interrupted by competing stimuli. Proactive interference (PI) occurs when previously acquired information interferes with newly acquired information, whereas retroactive interference (RI) occurs when newly acquired information interferes with previously acquired information. In animal paradigms, the prefrontal cortex (PFC) has been shown to help facilitate pattern separation, and ultimately, attenuate memory interference. Research evaluating the role of the PFC on memory interference among humans is, however, limited. The present study evaluated the relationship between PFC oxygenation on memory interference among humans, with the null hypothesis being that there is no association between PFC oxygenation and memory interference.

METHODS

A total of 74 participants (Mage = 20.8 years) completed the study. Participants completed a computerized memory interference task using the AB-DE AC-FG paradigm, with PFC oxyhemoglobin levels measured via functional near-infrared spectroscopy.

RESULTS

For PI, the change in oxygenated hemoglobin for encoding list 1 and retrieval of list 1 showed moderate evidence for the null hypothesis (BF01 = 4.05 and 3.28, respectively). For RI, the Bayesian analysis also established moderate evidence for the null hypothesis across all memory task time points.

CONCLUSION

Our study demonstrates evidence of the null hypothesis regarding the relationship between PFC oxygenation and memory interference. Future work should continue to investigate this topic to identify mechanistic correlates of memory interference.

Characterizing cortical hemodynamic changes during climbing and its relation to climbing expertise

Bouldering is a special form of climbing without rope that requires coordinated whole-body movements. While physical performance parameters such as condition have been well studied, the knowledge on neural activity during climbing still remains sparse. Functional near-infrared spectroscopy (fNIRS) allows to measure brain activation while performing sportive actions due to its relative robustness against motion artefacts. In the current study, hemodynamic response alterations of 13 advanced climbers were investigated during boulder performance using fNIRS measurements. Simple and moderate climbing routes were compared regarding their level of cortical activation mainly in the sensorimotor area. Our results show that repetitively climbing a set of boulders activates almost all areas of the sensorimotor system including the bilateral premotor and supplementary motor cortex, bilateral primary motor cortex as well as the bilateral gyrus supramarginalis and somatosensory cortex. This result was found in both simple and moderate climbing routes with no effect of task complexity on the level of cortical activity. Correlation analysis (uncorrected for multiple comparisons) revealed a negative association between the level of expertise and the hemodynamic response in the supplementary-motor region, suggesting that gaining expertise in climbing is associated with a decrease in secondary motor areas, which is an indicator of motor automaticity. In summary, the present study provides first proof of concept that fNIRS is capable of assessing hemodynamic response alterations within the human motor system during the execution of complex whole-body climbing movements.

Changes in neurovascular coupling during cycling exercise measured by multi-distance fNIRS: a comparison between endurance athletes and physically active controls

It is well known that endurance exercise modulates the cardiovascular, pulmonary, and musculoskeletal system. However, knowledge about its effects on brain function and structure is rather sparse. Hence, the present study aimed to investigate exercise-dependent adaptations in neurovascular coupling to different intensity levels in motor-related brain regions. Moreover, expertise effects between trained endurance athletes (EA) and active control participants (ACP) during a cycling test were investigated using multi-distance functional near-infrared spectroscopy (fNIRS). Initially, participants performed an incremental cycling test (ICT) to assess peak values of power output (PPO) and cardiorespiratory parameters such as oxygen consumption volume (VO2max) and heart rate (HRmax). In a second session, participants cycled individual intensity levels of 20, 40, and 60% of PPO while measuring cardiorespiratory responses and neurovascular coupling. Our results revealed exercise-induced decreases of deoxygenated hemoglobin (HHb), indicating an increased activation in motor-related brain areas such as primary motor cortex (M1) and premotor cortex (PMC). However, we could not find any differential effects in brain activation between EA and ACP. Future studies should extend this approach using whole-brain configurations and systemic physiological augmented fNIRS measurements, which seems to be of pivotal interest in studies aiming to assess neural activation in a sports-related context.

Neural Activity and Decoding of Action Observation Using Combined EEG and fNIRS Measurement

In a social world, observing the actions of others is fundamental to understanding what they are doing, as well as their intentions and feelings. Studies of the neural basis and decoding of action observation are important for understanding action-related processes and have implications for cognitive, social neuroscience, and human-machine interaction (HMI). In the current study, we first investigated temporal-spatial dynamics during action observation using a combined 64-channel electroencephalography (EEG) and 48-channel functional near-infrared spectroscopy (fNIRS) system. We measured brain activation while 16 healthy participants observed three action tasks: (1) grasping a cup with the intention of drinking; (2) grasping a cup with the intention of moving it; and (3) touching a cup with an unclear intention. The EEG and fNIRS source analysis results revealed the dynamic involvement of both the mirror neuron system (MNS) and the theory of mind (ToM)/mentalizing network during action observation. The source analysis results suggested that the extent to which these two systems were engaged was determined by the clarity of the intention of the observed action. Based on the difference in neural activity observed among different action-observation tasks in the first experiment, we conducted a second experiment to classify the neural processes underlying action observation using a feature classification method. We constructed complex brain networks based on the EEG and fNIRS data. Fusing features from both EEG and fNIRS complex brain networks resulted in a classification accuracy of 72.7% for the three action observation tasks. This study provides a theoretical and empirical basis for elucidating the neural mechanisms of action observation and intention understanding, and a feasible method for decoding the underlying neural processes.

Consumer Behaviour through the Eyes of Neurophysiological Measures: State-of-the-Art and Future Trends

The new technological advances achieved during the last decade allowed the scientific community to investigate and employ neurophysiological measures not only for research purposes but also for the study of human behaviour in real and daily life situations. The aim of this review is to understand how and whether neuroscientific technologies can be effectively employed to better understand the human behaviour in real decision-making contexts. To do so, firstly, we will describe the historical development of neuromarketing and its main applications in assessing the sensory perceptions of some marketing and advertising stimuli. Then, we will describe the main neuroscientific tools available for such kind of investigations (e.g., measuring the cerebral electrical or hemodynamic activity, the eye movements, and the psychometric responses). Also, this review will present different brain measurement techniques, along with their pros and cons, and the main cerebral indexes linked to the specific mental states of interest (used in most of the neuromarketing research). Such indexes have been supported by adequate validations from the scientific community and are largely employed in neuromarketing research. This review will also discuss a series of papers that present different neuromarketing applications, such us in-store choices and retail, services, pricing, brand perception, web usability, neuropolitics, evaluation of the food and wine taste, and aesthetic perception of artworks. Furthermore, this work will face the ethical issues arisen on the use of these tools for the evaluation of the human behaviour during decision-making tasks. In conclusion, the main challenges that neuromarketing is going to face, as well as future directions and possible scenarios that could be derived by the use of neuroscience in the marketing field, will be identified and discussed.

A Brief Review of the Application of Neuroergonomics in Skilled Cognition During Expert Sports Performance

The elite sports environment provides a unique setting for studying human performance, where both cognitive and physical demands are high. Successful performance in sport is contingent upon key cognitive skills such as attention, perception, working memory and decision-making. The demands of competitive sport also increase loading on the central nervous system (CNS). Neuroimaging methods such as functional magnetic resonance imaging (fMRI), functional near infrared spectroscopy (fNIRS) and electroencephalography (EEG) offer the potential to investigate the cognitive demands of sport, neuroplasticity of athletes, and biofeedback training. However, practical and technical limitations of these methods have generally limited their use to laboratory-based studies of athletes during simulated sporting tasks. This review article, provides a brief overview of research that has applied neuroimaging technology to study various aspects of cognitive function during sports performance in athletes, alternative methods for measuring CNS loading [e.g., direct current (DC) potential], possible solutions and avenues of focus for future neuroergonomics research in sport.

Identifying individuals using fNIRS-based cortical connectomes

The fMRI-based functional connectome was shown to be sufficiently unique to allow individual identification (fingerprinting). We aimed to test whether a fNIRS-based connectome could also be used to identify individuals. Forty-four participants performed experimental protocols that consisted of two periods of resting-state interleaved by a cognitive task period. Connectome identification was performed for all possible pairwise combinations of the three periods. The influence of hemodynamic global variation was tested using global signal regression and principal component analysis. High identification accuracies well-above chance level (2.3%) were observed overall, being particularly high (93%) to the oxyhemoglobin signal between resting conditions. Our results suggest that fNIRS is a suitable technique to assess connectome fingerprints.

Mental Fatigue and Functional Near-Infrared Spectroscopy (fNIRS) - Based Assessment of Cognitive Performance After Mild Traumatic Brain Injury

Pathological mental fatigue after mild traumatic brain injury (TBI-MF) is characterized by pronounced mental fatigue after cognitive activity. The neurological origin is unknown, and we aimed in the present study to investigate how prolonged mental activity affects cognitive performance and its neural correlates in individuals with TBI-MF. We recruited individuals with TBI-MF (n = 20) at least 5 months after injury, and age-matched healthy controls (n = 20). We used functional near-infrared spectroscopy (fNIRS) to assess hemodynamic changes in the frontal cortex. The self-assessed mental energy level was measured with a visual analog scale (VAS) before and after the experimental procedure. A battery of six neuropsychological tests including Stroop–Simon, Symbol Search, Digit Span, Parallel Serial Mental Operation (PaSMO), Sustained Attention and Working Memory test, and Digit Symbol Coding (DSC) were used. The sequence was repeated once after an 8 min sustained-attention test. The test procedure lasted 2½ h. The experimental procedure resulted in a decrease in mental energy in the TBI-MF group, compared to controls (interaction, p < 0.001, η_p² = 0.331). The TBI-MF group performed at a similar level on both DSC tests, whereas the controls improved their performance in the second session (interaction, p < 0.01, η_p² = 0.268). During the Stroop–Simon test, the fNIRS event-related response showed no time effect. However, the TBI-MF group exhibited lower oxygenated hemoglobin (oxy-Hb) concentrations in the frontal polar area (FPA), ventrolateral motor cortex, and dorsolateral prefrontal cortex (DLPFC) from the beginning of the test session. A Stroop and Group interaction was found in the left ventrolateral prefrontal cortex showing that the TBI-MF group did have the same oxy-Hb concentration for both congruent and incongruent trials, whereas the controls had more oxy-Hb in the incongruent trial compared to the congruent trial (interaction, p < 0.01, η_p² = 0.227). In sum these results indicate that individuals with TBI-MF have a reduced ability to recruit the frontal cortex, which is correlated with self-reported mental fatigue. This may result both in deterioration of cognitive function and the experience of a mental fatigue after extended mental activity.

Contrast Agents Delivery: An Up-to-Date Review of Nanodiagnostics in Neuroimaging

Neuroimaging is a highly important field of neuroscience, with direct implications for the early diagnosis and progression monitoring of brain-associated diseases. Neuroimaging techniques are categorized into structural, functional and molecular neuroimaging, each possessing advantages and disadvantages in terms of resolution, invasiveness, toxicity of contrast agents and costs. Nanotechnology-based approaches for neuroimaging mostly involve the development of nanocarriers for incorporating contrast agents or the use of nanomaterials as imaging agents. Inorganic and organic nanoparticles, liposomes, micelles, nanobodies and quantum dots are some of the most studied candidates for the delivery of contrast agents for neuroimaging. This paper focuses on describing the conventional modalities used for imaging and the applications of nanotechnology for developing novel strategies for neuroimaging. The aim is to highlight the roles of nanocarriers for enhancing and/or overcome the limitations associated with the most commonly utilized neuroimaging modalities. For future directions, several techniques that could benefit from the increased contrast induced by using imaging probes are presented.

Use of a Portable Functional Near-Infrared Spectroscopy (fNIRS) System to Examine Team Experience During Crisis Event Management in Clinical Simulations

Objective: The aim of this study was to investigate the utilization of a portable functional near-infrared spectroscopy (fNIRS) system, the fNIRS Pioneer^TM, to examine team experience in high-fidelity simulation-based crisis event management (CEM) training for anesthesiologists in operating rooms.

Background: Effective evaluation of team performance and experience in CEM simulations is essential for healthcare training and research. Neurophysiological measures with wearable devices can provide useful indicators of team experience to compliment traditional self-report, observer ratings, and behavioral performance measures. fNIRS measured brain blood oxygenation levels and neural synchrony can be used as indicators of workload and team engagement, which is vital for optimal team performance.

Methods: Thirty-three anesthesiologists, who were attending CEM training in two-person teams, participated in this study. The participants varied in their expertise level and the simulation scenarios varied in difficulty level. The oxygenated and de-oxygenated hemoglobin (HbO and HbR) levels in the participants’ prefrontal cortex were derived from data recorded by a portable one-channel fNIRS system worn by all participants throughout CEM training. Team neural synchrony was measured by HbO/HbR wavelet transformation coherence (WTC). Observer-rated workload and self-reported workload and mood were also collected.

Results: At the individual level, the pattern of HbR level corresponded to changes of workload for the individuals in different roles during different phases of a scenario; but this was not the case for HbO level. Thus, HbR level may be a better indicator for individual workload in the studied setting. However, HbR level was insensitive to differences in scenario difficulty and did not correlate with observer-rated or self-reported workload. At the team level, high levels of HbO and HbR WTC were observed during active teamwork. Furthermore, HbO WTC was sensitive to levels of scenario difficulty.

Conclusion: This study showed that it was feasible to use a portable fNIRS system to study workload and team engagement in high-fidelity clinical simulations. However, more work is needed to establish the sensitivity, reliability, and validity of fNIRS measures as indicators of team experience.

Muscle oxygenation dynamics in response to electrical stimulation as measured with near-infrared spectroscopy: A pilot study

Neuromuscular electrical stimulation (NMES) is used for preventing muscle atrophy and improving muscle strength in patients and healthy people. However, the current intensity of NMES is usually set at a level that causes the stimulated muscles to contract. This typically causes pain. Quantifying the instantaneous changes in muscle microcirculation and metabolism during NMES before muscle contraction occurs is crucial, because it enables the current intensity to be optimally tuned, thereby reducing the NMES-induced muscle pain and fatigue. We applied near-infrared spectroscopy (NIRS) to measure instantaneous tissue oxygenation and deoxygenation changes in 43 healthy young adults during NMES at 10, 15, 20, 25, 30, and 35 mA. Having been stabilized at the NIRS signal baseline, the tissue oxygenation and total hemoglobin concentration increased immediately after stimulation in a dose-dependent manner (P < 0.05) until stimulation was stopped at the level causing muscle contraction without pain. Tissue deoxygenation appeared relatively unchanged during NMES. We conclude that NIRS can be used to determine the optimal NMES current intensity by monitoring oxygenation changes.

fNIRS Responses in Professional Violinists While Playing Duets: Evidence for Distinct Leader and Follower Roles at the Brain Level

Music played in ensembles is a naturalistic model to study joint action and leader-follower relationships. Recently, the investigation of the brain underpinnings of joint musical actions has gained attention; however, the cerebral correlates underlying the roles of leader and follower in music performance remain elusive. The present study addressed this question by simultaneously measuring the hemodynamic correlates of functional neural activity elicited during naturalistic violin duet performance using fNIRS. Findings revealed distinct patterns of functional brain activation when musicians played the Violin 2 (follower) than the Violin 1 part (leader) in duets, both compared to solo performance. More specifically, results indicated that musicians playing the Violin 2 part had greater oxy-Hb activation in temporo-parietal (p = 0.02) and somatomotor (p = 0.04) regions during the duo condition in relation to the solo. On the other hand, there were no significant differences in the activation of these areas between duo/solo conditions during the execution of the Violin 1 part (p's > 0.05). These findings suggest that ensemble cohesion during a musical performance may impose particular demands when musicians play the follower position, especially in brain areas associated with the processing of dynamic social information and motor simulation. This study is the first to use fNIRS hyperscanning technology to simultaneously measure the brain activity of two musicians during naturalistic music ensemble performance, opening new avenues for the investigation of brain correlates underlying joint musical actions with multiple subjects in a naturalistic environment.

Demonstrating Brain-Level Interactions Between Visuospatial Attentional Demands and Working Memory Load While Driving Using Functional Near-Infrared Spectroscopy

Driving is a complex task concurrently drawing on multiple cognitive resources. Yet, there is a lack of studies investigating interactions at the brain-level among different driving subtasks in dual-tasking. This study investigates how visuospatial attentional demands related to increased driving difficulty interacts with different working memory load (WML) levels at the brain level. Using multichannel whole-head high density functional near-infrared spectroscopy (fNIRS) brain activation measurements, we aimed to predict driving difficulty level, both separate for each WML level and with a combined model. Participants drove for approximately 60 min on a highway with concurrent traffic in a virtual reality driving simulator. In half of the time, the course led through a construction site with reduced lane width, increasing visuospatial attentional demands. Concurrently, participants performed a modified version of the n-back task with five different WML levels (from 0-back up to 4-back), forcing them to continuously update, memorize, and recall the sequence of the previous 'n' speed signs and adjust their speed accordingly. Using multivariate logistic ridge regression, we were able to correctly predict driving difficulty in 75.0% of the signal samples (1.955 Hz sampling rate) across 15 participants in an out-of-sample cross-validation of classifiers trained on fNIRS data separately for each WML level. There was a significant effect of the WML level on the driving difficulty prediction accuracies [range 62.2-87.1%; χ2(4) = 19.9, p < 0.001, Kruskal-Wallis H test] with highest prediction rates at intermediate WML levels. On the contrary, training one classifier on fNIRS data across all WML levels severely degraded prediction performance (mean accuracy of 46.8%). Activation changes in the bilateral dorsal frontal (putative BA46), bilateral inferior parietal (putative BA39), and left superior parietal (putative BA7) areas were most predictive to increased driving difficulty. These discriminative patterns diminished at higher WML levels indicating that visuospatial attentional demands and WML involve interacting underlying brain processes. The changing pattern of driving difficulty related brain areas across WML levels could indicate potential changes in the multitasking strategy with level of WML demand, in line with the multiple resource theory.

Endurance Exercise Enhances Emotional Valence and Emotion Regulation

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 min on two separate days. Participants completed measures of emotional state and the Stroop test of domain-general cognitive control before, every 30 min during and 30 min after exercise. Participants also completed a cognitive reappraisal task (CRT) after exercise. Functional near-infrared spectroscopy (fNIRS) tracked changes in oxygenated and deoxygenated hemoglobin (O2Hb and dHb) levels in the prefrontal cortex (PFC). Results suggest that even at relatively moderate intensities, endurance athletes benefit emotionally from running both during and after exercise and task-related PFC oxygenation reductions do not appear to hinder prefrontal-dependent cognitive control.

From the Laboratory to the Classroom: The Potential of Functional Near-Infrared Spectroscopy in Educational Neuroscience

Paralleling two decades of growth in the emergent field known as educational neuroscience is an increasing concern that educational practices and programs should be evidence-based, however, the idea that neuroscience could potentially influence education is controversial. One of the criticisms, regarding applications of the findings produced in this discipline, concerns the artificiality of neuroscientific experiments and the oversimplified nature of the tests used to investigate cognitive processes in educational contexts. The simulations may not account for all of the variables present in real classroom activities. In this study, we aim to get a step closer to the formation of data-supported classroom methodologies by employing functional near-infrared spectroscopy in various experimental paradigms. First, we present two hyperscanning scenarios designed to explore realistic interdisciplinary contexts, i.e., the classroom. In a third paradigm, we present a case study of a single student evaluated with functional near-infrared spectroscopy and mobile eye-tracking glasses. These three experiments are performed to provide proofs of concept for the application of functional near-infrared spectroscopy in scenarios that more closely resemble authentic classroom routines and daily activities. The goal of our study is to explore the potential of this technique in hopes that it offers insights in experimental design to investigate teaching-learning processes during teacher-student interactions.

A Review on the Use of Wearable Functional Near-Infrared Spectroscopy in Naturalistic Environments. JAPANESE PSYCHOLOGICAL RESEARCH 2018;60:347-373. [PMID: 30643322 PMCID: PMC6329605 DOI: 10.1111/jpr.12206]

The development of novel miniaturized wireless and wearable functional Near-Infrared Spectroscopy (fNIRS) devices have paved the way to new functional brain imaging that can revolutionize the cognitive research fields. Over the past few decades, several studies have been conducted with conventional fNIRS systems that have demonstrated the suitability of this technology for a wide variety of populations and applications, to investigate both the healthy brain and the diseased brain. However, what makes wearable fNIRS even more appealing is its capability to allow measurements in everyday life scenarios that are not possible with other gold-standard neuroimaging modalities, such as functional Magnetic Resonance Imaging. This can have a huge impact on the way we explore the neural bases and mechanisms underpinning human brain functioning. The aim of this review is to provide an overview of studies conducted with wearable fNIRS in naturalistic settings in the field of cognitive neuroscience. In addition, we present the challenges associated with the use of wearable fNIRS in unrestrained contexts, discussing solutions that will allow accurate inference of functional brain activity. Finally, we provide an overview of the future perspectives in cognitive neuroscience that we believe would benefit the most by using wearable fNIRS.

Studying brain activity in sports performance: Contributions and issues

Understanding the interactions between brain activity and behavior comprehensively in achieving optimal exercise performance in sports is still lacking. The existent research in this area has been limited by the constraints of sports environments and the robustness of the most suitable non-invasive functional neuroimaging methods (electroencephalography, EEG and functional near-infrared spectroscopy, fNIRS) to motion artifacts and noise. However, recent advances in brain mapping technology should improve the capabilities of the future brain imaging devices to assess and monitor the level of adaptive cognitive-motor performance during exercise in sports environments. The purpose of this position manuscript is to discuss the contributions and issues in behavioral neuroscience related to brain activity measured during exercise and in various sports. A first part aims to give an overview of EEG and fNIRS neuroimaging methods assessing electrophysiological activity and hemodynamic responses of the acute and chronic relation of physical exercise on the human brain. Then, methodological issues, such as the reliability of brain data during physical exertion, key limitations and possible prospects of fNIRS and EEG methods are provided. While the use of such methods in sports environments remains scarce and limited to controlled cycling task, new generation of wearable, whole-scalp EEG and fNIRS technologies could open up a range of new applications in sports sciences for providing neuroimaging-based biomarkers (hemodynamic and/or neural electrical signals) to various types of exercise and innovative training.

Functional near-infrared spectroscopy-based affective neurofeedback: feedback effect, illiteracy phenomena, and whole-connectivity profiles

Background: Affective neurofeedback constitutes a suitable approach to control abnormal neural activities associated with psychiatric disorders and might consequently relief symptom severity. However, different aspects of neurofeedback remain unclear, such as its neural basis, the performance variation, the feedback effect, among others. Aim: First, we aimed to propose a functional near-infrared spectroscopy (fNIRS)-based affective neurofeedback based on the self-regulation of frontal and occipital networks. Second, we evaluated three different feedback approaches on performance: real, fixed, and random feedback. Third, we investigated different demographic, psychological, and physiological predictors of performance. Approach: Thirty-three healthy participants performed a task whereby an amorphous figure changed its shape according to the elicited affect (positive or neutral). During the task, the participants randomly received three different feedback approaches: real feedback, with no change of the classifier output; fixed feedback, keeping the feedback figure unmodified; and random feedback, where the classifier output was multiplied by an arbitrary value, causing a feedback different than expected by the subject. Then, we applied a multivariate comparison of the whole-connectivity profiles according to the affective states and feedback approaches, as well as during a pretask resting-state block, to predict performance. Results: Participants were able to control this feedback system with 70.00 % ± 24.43 % ( p < 0.01 ) of performance during the real feedback trials. No significant differences were found when comparing the average performances of the feedback approaches. However, the whole functional connectivity profiles presented significant Mahalanobis distances ( p ≪ 0.001 ) when comparing both affective states and all feedback approaches. Finally, task performance was positively correlated to the pretask resting-state whole functional connectivity ( r = 0.512 , p = 0.009 ). Conclusions: Our results suggest that fNIRS might be a feasible tool to develop a neurofeedback system based on the self-regulation of affective networks. This finding enables future investigations using an fNIRS-based affective neurofeedback in psychiatric populations. Furthermore, functional connectivity profiles proved to be a good predictor of performance and suggested an increased effort to maintain task control in the presence of feedback distractors.

Hemoglobin state-flux: A finite-state model representation of the hemoglobin signal for evaluation of the resting state and the influence of disease

SUMMARY

In this report we introduce a weak-model approach for examination of the intrinsic time-varying properties of the hemoglobin signal, with the aim of advancing the application of functional near infrared spectroscopy (fNIRS) for the detection of breast cancer, among other potential uses. The developed methodology integrates concepts from stochastic network theory with known modulatory features of the vascular bed, and in doing so provides access to a previously unrecognized dense feature space that is shown to have promising diagnostic potential. Notable features of the methodology include access to this information solely from measures acquired in the resting state, and analysis of these by treating the various components of the hemoglobin (Hb) signal as a co-varying interacting system.

APPROACH

The principal data-transform kernel projects Hb state-space trajectories onto a coordinate system that constitutes a finite-state representation of covariations among the principal elements of the Hb signal (i.e., its oxygenated (ΔoxyHb) and deoxygenated (ΔdeoxyHb) forms and the associated dependent quantities: total hemoglobin (ΔtotalHb = ΔoxyHb + ΔdeoxyHb), hemoglobin oxygen saturation (ΔHbO2Sat = 100Δ(oxyHb/totalHb)), and tissue-hemoglobin oxygen exchange (ΔHbO2Exc = ΔdeoxyHb-ΔoxyHb)). The resulting ten-state representation treats the evolution of this signal as a one-space, spatiotemporal network that undergoes transitions from one state to another. States of the network are defined by the algebraic signs of the amplitudes of the time-varying components of the Hb signal relative to their temporal mean values. This assignment produces several classes of coefficient arrays, most with a dimension of 10×10.

BIOLOGICAL MOTIVATION

Motivating our approach is the understanding that effector mechanisms that modulate blood delivery to tissue operate on macroscopic scales, in a spatially and temporally varying manner. Also recognized is that this behavior is sensitive to nonlinear actions of these effectors, which include the binding properties of hemoglobin. Accessible phenomenology includes measures of the kinetics and probabilities of network dynamics, which we treat as surrogates for the actions of feedback mechanisms that modulate tissue-vascular coupling.

FINDINGS

Qualitative and quantitative features of this space, and their potential to serve as markers of disease, have been explored by examining continuous-wave fNIRS 3D tomographic time series obtained from the breasts of women who do and do not have breast cancer. Inspection of the coefficient arrays reveals that they are governed predominantly by first-order rate processes, and that each array class exhibits preferred structure that is mainly independent of the others. Discussed are strategies that may serve to extend evaluation of the accessible feature space and how the character of this information holds potential for development of novel clinical and preclinical uses.

Predicting affective valence using cortical hemodynamic signals

Ascribing affective valence to stimuli or mental states is a fundamental property of human experiences. Recent neuroimaging meta-analyses favor the workspace hypothesis for the neural underpinning of valence, in which both positive and negative values are encoded by overlapping networks but are associated with different patterns of activity. In the present study, we further explored this framework using functional near-infrared spectroscopy (fNIRS) in conjunction with multivariate analyses. We monitored the fronto-temporal and occipital hemodynamic activity of 49 participants during the viewing of affective images (passive condition) and during the imagination of affectively loaded states (active condition). Multivariate decoding techniques were applied to determine whether affective valence is encoded in the cortical areas assessed. Prediction accuracies of 89.90 ± 13.84% and 85.41 ± 14.43% were observed for positive versus neutral comparisons, and of 91.53 ± 13.04% and 81.54 ± 16.05% for negative versus neutral comparisons (passive/active conditions, respectively). Our results are consistent with previous studies using other neuroimaging modalities that support the affective workspace hypothesis and the notion that valence is instantiated by the same network, regardless of whether the affective experience is passively or actively elicited.

Enhancement of teaching outcome through neural prediction of the students' knowledge state

The neural mechanism for the dyadic process of teaching is poorly understood. Although theories about teaching have proposed that before any teaching takes place, the teacher will predict the knowledge state of the student(s) to enhance the teaching outcome, this theoretical Prediction-Transmission hypothesis has not been tested with any neuroimaging studies. Using functional near-infrared spectroscopy-based hyperscanning, this study measured brain activities of the teacher-student pairs simultaneously. Results showed that better teaching outcome was associated with higher time-lagged interpersonal neural synchronization (INS) between right temporal-parietal junction (TPJ) of the teacher and anterior superior temporal cortex (aSTC) of the student, when the teacher's brain activity preceded that of the student. Moreover, time course analyses suggested that such INS could mark the quality of the teaching outcome at an early stage of the teaching process. These results provided key neural evidence for the Prediction-Transmission hypothesis about teaching, and suggested that the INS plays an important role in the successful teaching.

fNIRS Optodes' Location Decider (fOLD): a toolbox for probe arrangement guided by brain regions-of-interest

The employment of functional near-infrared spectroscopy (fNIRS) as a method of brain imaging has increased over the last few years due to its portability, low-cost and robustness to subject movement. Experiments with fNIRS are designed in the face of a limited number of sources and detectors (optodes) to be positioned on selected portion(s) of the scalp. The optodes locations represent an expectation of assessing cortical regions relevant to the experiment’s hypothesis. However, this translation process remains a challenge for fNIRS experimental design. In the present study, we propose an approach that automatically decides the location of fNIRS optodes from a set of predefined positions with the aim of maximizing the anatomical specificity to brain regions-of-interest. The implemented method is based on photon transport simulations on two head atlases. The results are compiled into the publicly available “fNIRS Optodes’ Location Decider” (fOLD). This toolbox is a first-order approach to bring the achieved advancements of parcellation methods and meta-analyses from functional magnetic resonance imaging to more precisely guide the selection of optode positions for fNIRS experiments.

Listening in Naturalistic Scenes: What Can Functional Near-Infrared Spectroscopy and Intersubject Correlation Analysis Tell Us About the Underlying Brain Activity?

Listening to speech in the noisy conditions of everyday life can be effortful, reflecting the increased cognitive workload involved in extracting meaning from a degraded acoustic signal. Studying the underlying neural processes has the potential to provide mechanistic insight into why listening is effortful under certain conditions. In a move toward studying listening effort under ecologically relevant conditions, we used the silent and flexible neuroimaging technique functional near-infrared spectroscopy (fNIRS) to examine brain activity during attentive listening to speech in naturalistic scenes. Thirty normally hearing participants listened to a series of narratives continuously varying in acoustic difficulty while undergoing fNIRS imaging. Participants then listened to another set of closely matched narratives and rated perceived effort and intelligibility for each scene. As expected, self-reported effort generally increased with worsening signal-to-noise ratio. After controlling for better-ear signal-to-noise ratio, perceived effort was greater in scenes that contained competing speech than in those that did not, potentially reflecting an additional cognitive cost of overcoming informational masking. We analyzed the fNIRS data using intersubject correlation, a data-driven approach suitable for analyzing data collected under naturalistic conditions. Significant intersubject correlation was seen in the bilateral auditory cortices and in a range of channels across the prefrontal cortex. The involvement of prefrontal regions is consistent with the notion that higher order cognitive processes are engaged during attentive listening to speech in complex real-world conditions. However, further research is needed to elucidate the relationship between perceived listening effort and activity in these extended cortical networks.

Neuroimaging of learning and development: improving ecological validity

Modern neuroscience research, including neuroimaging techniques such as functional magnetic resonance imaging (fMRI), has provided valuable insights that advanced our understanding of brain development and learning processes significantly. However, there is a lively discussion about whether and how these insights can be meaningful to the educational practice. One of the main challenges is the low ecological validity of neuroimaging studies, making it hard to translate neuroimaging findings to real-life learning situations. Here, we describe four approaches that increase the ecological validity of neuroimaging experiments: using more naturalistic stimuli and tasks, moving the research to more naturalistic settings by using portable neuroimaging devices, combining tightly controlled lab-based neuroimaging measurements with real-life variables and follow-up field studies, and including stakeholders from the practice at all stages of the research. We illustrate these approaches with examples and explain how these directions of research optimize the benefits of neuroimaging techniques to study learning and development. This paper provides a frontline overview of methodological approaches that can be used for future neuroimaging studies to increase their ecological validity and thereby their relevance and applicability to the learning practice.