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Functional near-infrared spectroscopy (fNIRS) is a frequently used neuroimaging tool to explore the developing brain, particularly in infancy, with studies spanning from birth to toddlerhood (0 to 2 years). We provide an overview of the challenges and opportunities that the developmental fNIRS field faces, after almost 25 years of research. We discuss the most recent advances in fNIRS brain imaging with infants and outlines the trends and perspectives that will likely influence progress in the field in the near future. We discuss recent progress and future challenges in various areas and applications of developmental fNIRS from methodological and technological innovations to data processing and statistical approaches. The major trends identified include uses of fNIRS \"in the wild,\" such as global health contexts, home and community testing, and hyperscanning; advances in hardware, such as wearable technology; assessment of individual variation and developmental trajectories particularly while embedded in studies examining other environmental, health, and context specific factors and longitudinal designs; statistical advances including resting-state network and connectivity, machine learning and reproducibility, and collaborative studies. Standardization and larger studies have been, and will likely continue to be, a major goal in the field, and new data analysis techniques, statistical methods, and collaborative cross-site projects are emerging.

Significance: Functional near-infrared spectroscopy (fNIRS) enables measuring the brain activity of two subjects while they interact, i.e., the hyperscanning approach. Aim: In our exploratory study, we extended classical fNIRS hyperscanning by adding systemic physiological measures to obtain systemic physiology augmented fNIRS (SPA-fNIRS) hyperscanning while blocking and not blocking the visual communication between the subjects. This approach enables access brain-to-brain, brain-to-body, and body-to-body coupling between the subjects simultaneously. Approach: Twenty-four pairs of subjects participated in the experiment. The paradigm consisted of two subjects that sat in front of each other and had their eyes closed for 10 min, followed by a phase of 10 min where they made eye contact. Brain and body activity was measured continuously by SPA-fNIRS. Results: Our study shows that making eye contact for a prolonged time causes significant changes in brain-to-brain, brain-to-body, and body-to-body coupling, indicating that eye contact is followed by entrainment of the physiology between subjects. Subjects that knew each other generally showed a larger trend to change between the two conditions. Conclusions: The main point of this study is to introduce a new framework to investigate brain-to-brain, body-to-body, and brain-to-body coupling through a simple social experimental paradigm. The study revealed that eye contact leads to significant synchronization of spontaneous activity of the brain and body physiology. Our study is the first that employed the SPA-fNIRS approach and showed its usefulness to investigate complex interpersonal physiological changes.

In our previous investigations using systemic physiology augmented functional near-infrared spectroscopy (SPA-fNIRS) neuroimaging, we found larger variability between subjects in changes of cerebral hemodynamics and oxygenation induced by an intricate experimental paradigm involving colored light exposure and a cognitive task. We aimed to investigate the role the activity of the systemic physiology has on individual variations in the fNIRS data. Thirty-two healthy subjects (17 female, 15 male and age: 25.5 ± 4.3 years) were exposed to blue and red light for 9 min (colored light exposure, CLE) while performing a verbal fluency task (VFT). We found that (i), at the group level, the visual cortex showed a stronger deoxyhemoglobin concentration response during blue light exposure than during red light exposure, and (ii) this relationship was influenced by individually different baseline blood pressure values. Furthermore, we found other correlations between changes in fNIRS signals and changes in systemic physiology. Our study demonstrates the usefulness and necessity of the SPA-fNIRS approach to gain insights into the individual variability of hemodynamic responses measured with fNIRS, especially in the case of an intricate experimental paradigm (i.e., CLE-VFT) as used in our study.

A brain-computer interface (BCI) is a communication system that allows the use of brain activity to control computers or other external devices. It can, by bypassing the peripheral nervous system, provide a means of communication for people suffering from severe motor disabilities or in a persistent vegetative state. In this paper, brain-signal generation tasks, noise removal methods, feature extraction/selection schemes, and classification techniques for fNIRS-based BCI are reviewed. The most common brain areas for fNIRS BCI are the primary motor cortex and the prefrontal cortex. In relation to the motor cortex, motor imagery tasks were preferred to motor execution tasks since possible proprioceptive feedback could be avoided. In relation to the prefrontal cortex, fNIRS showed a significant advantage due to no hair in detecting the cognitive tasks like mental arithmetic, music imagery, emotion induction, etc. In removing physiological noise in fNIRS data, band-pass filtering was mostly used. However, more advanced techniques like adaptive filtering, independent component analysis (ICA), multi optodes arrangement, etc. are being pursued to overcome the problem that a band-pass filter cannot be used when both brain and physiological signals occur within a close band. In extracting features related to the desired brain signal, the mean, variance, peak value, slope, skewness, and kurtosis of the noised-removed hemodynamic response were used. For classification, the linear discriminant analysis method provided simple but good performance among others: support vector machine (SVM), hidden Markov model (HMM), artificial neural network, etc. fNIRS will be more widely used to monitor the occurrence of neuro-plasticity after neuro-rehabilitation and neuro-stimulation. Technical breakthroughs in the future are expected via bundled-type probes, hybrid EEG-fNIRS BCI, and through the detection of initial dips.

When humans move both hands simultaneously, bimanual coupling or interference can occur. The circles‐lines paradigm is used to study the bimanual coupling and interference effects: Participants simultaneously draw either lines or circles with both hands (congruent), or draw lines with one hand and circles with the other hand (incongruent condition). Despite extensive behavioral research on bimanual coupling with this paradigm, our knowledge of the neural circuitry involved remains limited. Here, we capitalized on the advantages provided by functional near‐infrared spectroscopy to unveil the neural substrates of bimanual coupling within an ecologically valid experimental setting. Behavioral results confirmed previous literature, showing that the shapes become more oval due to the interference between the hands, causing the circle to resemble a line and vice versa. Additionally, performance in the congruent condition correlated with performance in the incongruent condition. From a neural perspective, we observed greater activity in sensorimotor areas and the right premotor area during the incongruent compared to the congruent condition. A novel temporal analysis of the time course of oxyhemoglobin signals revealed that the right hemisphere reached maximum amplitude before the left during the incongruent condition and revealed differences between conditions in parietal areas, showing that bimanual interference is associated not only with motor areas but also with associative areas. Finally, right inferior parietal lobe activity correlated with bimanual performance, suggesting a role for this area in bimanual tasks when the motor program of one hand is influenced by sensorimotor information from the contralateral hand. Our study demonstrates fNIRS effectiveness in investigating bimanual interference during the circles‐lines paradigm. fNIRS allows correct drawing positions, ensuring ecological validity. Performance in congruent tasks predicts incongruent performance. Time‐course analysis shows parietal differences, with the right hemisphere peaking earlier during the incongruent condition. Right inferior parietal lobe activity correlates with bimanual interference.

In the present study, we proposed and evaluated a workflow of personalized near infra‐red optical tomography (NIROT) using functional near‐infrared spectroscopy (fNIRS) for spatiotemporal imaging of cortical hemodynamic fluctuations. The proposed workflow from fNIRS data acquisition to local 3D reconstruction consists of: (a) the personalized optimal montage maximizing fNIRS channel sensitivity to a predefined targeted brain region; (b) the optimized fNIRS data acquisition involving installation of optodes and digitalization of their positions using a neuronavigation system; and (c) the 3D local reconstruction using maximum entropy on the mean (MEM) to accurately estimate the location and spatial extent of fNIRS hemodynamic fluctuations along the cortical surface. The workflow was evaluated on finger‐tapping fNIRS data acquired from 10 healthy subjects for whom we estimated the reconstructed NIROT spatiotemporal images and compared with functional magnetic resonance imaging (fMRI) results from the same individuals. Using the fMRI activation maps as our reference, we quantitatively compared the performance of two NIROT approaches, the MEM framework and the conventional minimum norm estimation (MNE) method. Quantitative comparisons were performed at both single subject and group‐level. Overall, our results suggested that MEM provided better spatial accuracy than MNE, while both methods offered similar temporal accuracy when reconstructing oxygenated (HbO) and deoxygenated hemoglobin (HbR) concentration changes evoked by finger‐tapping. Our proposed complete workflow was made available in the brainstorm fNIRS processing plugin—NIRSTORM, thus providing the opportunity for other researchers to further apply it to other tasks and on larger populations. This study was to introduce and evaluate a workflow for personalized near infra‐red optical tomography (NIROT). The workflow comprises a full pipeline from functional near‐infrared spectroscopy (fNIRS) data acquisition to local 3D imaging of cortical hemodynamic fluctuations.

INTRODUCTION Identifying individuals at risk of developing dementia is crucial for early intervention. Mild cognitive impairment (MCI) and subjective memory complaints (SMCs) are considered its preceding stages. This study aimed to assess the utility of functional near‐infrared spectroscopy (fNIRS) in identifying individuals with MCI and SMC. METHODS One hundred fifty‐one participants were categorized into normal cognition (NC); amnestic MCI (aMCI); non‐amnestic MCI (naMCI); and mild, moderate, and severe SMC groups. Task‐related prefrontal hemodynamics were measured using fNIRS during a visual memory span task. RESULTS Results showed significantly lower oxyhemoglobin (HbO) levels in aMCI, but not in naMCI, compared to the NC. In addition, severe SMC had lower HbO levels than the NC, mild, and moderate SMC. Receiver operating characteristic analysis demonstrated 69.23% and 69.70% accuracy in differentiating aMCI and severe SMC from NC, respectively. DISCUSSION FNIRS may serve as a potential non‐invasive biomarker for early detection of dementia. Highlights Only amnestic mild cognitive impairment (aMCI), but not non‐amnestic MCI, showed lower oxyhemoglobin (HbO) than normal individuals. Reduced HbO was observed in those with severe subjective memory complaints (SMCs) compared to normal cognition (NC), mild, and moderate SMCs. Functional near‐infrared spectroscopy measures were associated with performance in memory assessments. Prefrontal hemodynamics could distinguish aMCI and severe SMC from NC.

Background Executive function enhancement is considered necessary for improving the quality of life of patients with neurological or psychiatric disorders, such as attention‐deficit/hyperactivity disorder, obsessive‐compulsive disorder and Alzheimer's disease. Transcranial electrical stimulation (tES) has been shown to have some beneficial effects on executive functioning, but the quantification of these improvements remains controversial. We aimed to explore the potential beneficial effects on executive functioning induced by the use of transcranial alternating current stimulation (tACS)/transcranial direct current stimulation (tDCS) on the right inferior frontal gyrus (IFG) and the accompanying brain function variations in the resting state. Methods We recruited 229 healthy adults to participate in Experiments 1 (105 participants) and 2 (124 participants). The participants in each experiment were randomly divided into tACS, tDCS, and sham groups. The participants completed cognitive tasks to assess behavior related to three core components of executive functions. Functional near‐infrared spectroscopy (fNIRS) was used to monitor the hemodynamic changes in crucial cortical regions in the resting state. Results Inhibition and cognitive flexibility (excluding working memory) were significantly increased after tACS/tDCS, but there were no significant behavioral differences between the tACS and tDCS groups. fNIRS revealed that tDCS induced decreases in the functional connectivity (increased neural efficiency) of the relevant cortices. Conclusions Enhancement of executive function was observed after tES, and the beneficial effects of tACS/tDCS may need to be precisely evaluated via brain imaging indicators at rest. tDCS revealed better neural benefits than tACS during the stimulation phase. These findings might provide new insights for selecting intervention methods in future studies and for evaluating the clinical efficacy of tES. This study found that both 20 Hz tACS and tDCS on the right IFG could effectively enhance the behavioral performance related to executive functions, and variations in cortical activity are more sensitive for assessing benefits than behavior changes by tES intervention.

Sensor-level human brain activity is studied during real and imaginary motor execution using functional near-infrared spectroscopy (fNIRS). Blood oxygenation and deoxygenation spatial dynamics exhibit pronounced hemispheric lateralization when performing motor tasks with the left and right hands. This fact allowed us to reveal biomarkers of hemodynamical response of the motor cortex on the motor execution, and use them for designing a sensing method for classification of the type of movement. The recognition accuracy of real movements is close to 100%, while the classification accuracy of imaginary movements is lower but quite high (at the level of 90%). The advantage of the proposed method is its ability to classify real and imaginary movements with sufficiently high efficiency without the need for recalculating parameters. The proposed system can serve as a sensor of motor activity to be used for neurorehabilitation after severe brain injuries, including traumas and strokes.

In this Outlook paper, we explain why an accurate physiological interpretation of functional near-infrared spectroscopy (fNIRS) neuroimaging signals is facilitated when systemic physiological activity (e.g., cardiorespiratory and autonomic activity) is measured simultaneously by employing systemic physiology augmented functional near-infrared spectroscopy (SPA-fNIRS). The rationale for SPA-fNIRS is twofold: (i) SPA-fNIRS enables a more complete interpretation and understanding of the fNIRS signals measured at the head since they contain components originating from neurovascular coupling and from systemic physiological sources. The systemic physiology signals measured with SPA-fNIRS can be used for regressing out physiological confounding components in fNIRS signals. Misinterpretations can thus be minimized. (ii) SPA-fNIRS enables to study the embodied brain by linking the brain with the physiological state of the entire body, allowing novel insights into their complex interplay. We envisage the SPA-fNIRS approach will become increasingly important in the future.