The efficacy and methodology of using near-infrared spectroscopy to determine resting-state brain networks

Functional connectivity is a critical aspect of brain function and is essential for understanding, diagnosing, and treating neurological and psychiatric disorders. It refers to the synchronous activity between different regions of the brain, which gives rise to communication and information processing. Resting-state functional connectivity is a subarea of study that allows researchers to examine brain activity in the absence of a task or stimulus. This can provide insight into the brain's intrinsic functional architecture and help identify neural networks that are active during rest. Thus, determining functional connectivity topography is valuable both clinically and in research. Traditional methods using functional magnetic resonance imaging have proven to be effective, however, they have their limitations. In this review, we investigate the feasibility of using functional near-infrared spectroscopy (fNIRS) as a low-cost, portable alternative for measuring functional connectivity. We first establish fNIRS' ability to detect localized brain activity during task-based experiments. Next, we verify its use in resting-state studies with results showing a high degree of correspondence with resting-state functional magnetic resonance imaging (rs-fMRI). Also discussed are various data-processing methods and the validity of filtering the global signal, which is the current standard for analysis. We consider the possible origins of the global signal, if it contains pertinent neuronal information that could be of importance in better understanding neuronal networks, and what we believe is the best method of approaching signal analysis and regression.

Abnormal prefrontal functional network in adult obstructive sleep apnea: A resting-state fNIRS study

To assess prefrontal brain network abnormality in adults with obstructive sleep apnea (OSA), resting-state functional near infrared spectroscopy (rs-fNIRS) was used to evaluate 52 subjects, including 27 with OSA and 25 healthy controls (HC). The study found that patients with OSA had a decreased connection edge number, particularly in the connection between the right medial frontal cortex (MFG-R) and other right-hemisphere regions. Graph-based analysis also revealed that patients with OSA had a lower global efficiency, local efficiency, and clustering coefficient than the HC group. Additionally, the study found a significant positive correlation between the Montreal Cognitive Assessment (MoCA) score and both the connection edge number and the graph-based indicators in patients with OSA. These preliminary results suggest that prefrontal rs-fNIRS could be a useful tool for objectively and quantitatively assessing cognitive function impairment in patients with OSA.

Naturalistic auditory stimuli with fNIRS prefrontal cortex imaging: A potential paradigm for disorder of consciousness diagnostics (a study with healthy participants)

Disorder of consciousness (DOC) is a devastating condition due to brain damage. A patient in this condition is non-responsive, but nevertheless might be conscious at least at some level. Determining the conscious level of DOC patients is important for both medical and ethical reasons, but reliably achieving this has been a major challenge. Naturalistic stimuli in combination with neuroimaging have been proposed as a promising approach for DOC patient diagnosis. Capitalizing on and extending this proposal, the goal of the present study conducted with healthy participants was to develop a new paradigm with naturalistic auditory stimuli and functional near-infrared spectroscopy (fNIRS) - an approach that can be used at the bedside. Twenty-four healthy participants passively listened to 9 min of auditory story, scrambled auditory story, classical music, and scrambled classical music segments while their prefrontal cortex activity was recorded using fNIRS. We found much higher intersubject correlation (ISC) during story compared to scrambled story conditions both at the group level and in the majority of individual subjects, suggesting that fNIRS imaging of the prefrontal cortex might be a sensitive method to capture neural changes associated with narrative comprehension. In contrast, the ISC during the classical music segment did not differ reliably from scrambled classical music and was also much lower than the story condition. Our main result is that naturalistic auditory stories with fNIRS might be used in a clinical setup to identify high-level processing and potential consciousness in DOC patients.

Lack of functional brain connectivity was associated with poor inhibition in children with attention-deficit/hyperactivity disorder using near-infrared spectroscopy

Objectives

The present study aimed to evaluate the characteristics of functional brain connectivity in the resting state in children with attention deficit hyperactivity disorder (ADHD) and to assess the association between the connectivity and inhibition function using near-infrared spectroscopy (NIRS).

Methods

In total, 34 children aged 6-13 diagnosed with ADHD were recruited from Hangzhou Seventh People's Hospital. In comparison, 37 healthy children were recruited from a local primary school as controls matched by age and sex. We used NIRS to collect information on brain images. The Stroop test assessed inhibition function. We compared the differences in functional brain connectivity in two groups by analyzing the resting-state brain network. Pearson partial correlation analysis was applied to evaluate the correlation between functional brain connectivity and inhibition in all the children.

Results

Compared with the control group, results of NIRS images analysis showed that children with ADHD had significantly low functional brain connectivity in regions of the orbitofrontal cortex, left dorsolateral prefrontal cortex, left pre-motor and supplementary motor cortex, inferior prefrontal gyrus, and right middle temporal gyrus (p = 0.006). Inhibition function of children with ADHD was negatively correlated with functional brain connectivity (p = 0.009), while such correlation was not found in the control group.

Conclusion

The present study demonstrated that children with ADHD had relatively low connectivity in several brain regions measured at the resting state. Our results supported the evidence that lack of functional brain connectivity was associated with impaired inhibition function in children with ADHD.

Characteristics of corticomuscular coupling during wheelchair Tai Chi in patients with spinal cord injury

BACKGROUND

Wheelchair Tai Chi (WCTC) has been proved to have benefits for the brain and motor system of spinal cord injury (SCI) patients. However, the characteristics of corticomuscular coupling during WCTC are scarcely known. We aimed to investigate changes following SCI on corticomuscular coupling, and further compare the coupling characteristics of WCTC with aerobic exercise in SCI patients.

METHODS

A total of 15 SCI patients and 25 healthy controls were recruited. The patients had to perform aerobic exercise and WCTC, while healthy controls needed to complete a set of WCTC. The participants accomplished the test following the tutorial video in a sitting position. The upper limb muscle activation was measured from upper trapezius, medial deltoid, biceps brachii and triceps brachii with surface electromyography. Cortical activity in the prefrontal cortex, premotor cortex, supplementary motor area and primary motor cortex was simultaneously collected by functional near-infrared spectroscopy. The functional connectivity, phase synchronization index and coherence values were then calculated and statistically analyzed.

RESULTS

Compared to healthy controls, changes in functional connectivity and higher muscle activation were observed in the SCI group. There was no significant difference in phase synchronization between groups. Among patients, significantly higher coherence values between the left biceps brachii as well as the right triceps brachii and contralateral regions of interest were found during WCTC than during aerobic exercise.

CONCLUSION

The patients may compensate for the lack of corticomuscular coupling by enhancing muscle activation. This study demonstrated the potential and advantages of WCTC in eliciting corticomuscular coupling, which may optimize rehabilitation following SCI.

The analysis of brain functional connectivity of post-stroke cognitive impairment patients: an fNIRS study

Background

Post-stroke cognitive impairment (PSCI) is a considerable risk factor for developing dementia and reoccurrence of stroke. Understanding the neural mechanisms of cognitive impairment after stroke can facilitate early identification and intervention.

Objectives

Using functional near-infrared spectroscopy (fNRIS), the present study aimed to examine whether resting-state functional connectivity (FC) of brain networks differs in patients with PSCI, patients with Non-PSCI (NPSCI), and healthy controls (HCs), and whether these features could be used for clinical diagnosis of PSCI.

Methods

The present study recruited 16 HCs and 32 post-stroke patients. Based on the diagnostic criteria of PSCI, post-stroke patients were divided to the PSCI or NPSCI group. All participants underwent a 6-min resting-state fNRIS test to measure the hemodynamic responses from regions of interests (ROIs) that were primarily distributed in the prefrontal, somatosensory, and motor cortices.

Results

The results showed that, when compared to the HC group, the PSCI group exhibited significantly decreased interhemispheric FC and intra-right hemispheric FC. ROI analyses showed significantly decreased FC among the regions of somatosensory cortex, dorsolateral prefrontal cortex, and medial prefrontal cortex for the PSCI group than for the HC group. However, no significant difference was found in the FC between the PSCI and the NPSCI groups.

Conclusion

Our findings provide evidence for compromised interhemispheric and intra-right hemispheric functional connectivity in patients with PSCI, suggesting that fNIRS is a promising approach to investigate the effects of stroke on functional connectivity of brain networks.

Reduced brain activity and functional connectivity during creative idea generation in individuals with smartphone addiction

Since the coronavirus disease 2019 outbreak, the frequency of smartphone use has surged, which has caused an increase in smartphone addiction among individuals. Smartphone addiction can impair various cognitive abilities. However, to date, the impact of smartphone addiction on creative cognition remains unclear. The current functional near-infrared spectroscopy study compared neural differences between smartphone addiction tendency (SAT) and healthy control (HC) individuals during creative idea generation. In particular, by manipulating a key component of creative cognition, that is, overcoming semantic constraints, we explored whether SAT individuals could overcome semantic constraints. Both the SAT and HC groups completed the alternate uses task (AUT) in semantic constraint and unconstraint conditions. The results indicated that the prefrontal cortex (PFC) and temporal regions were less active during AUT in the SAT group than in the HC group. In the SAT group, the PFC was less active under constraint than unconstraint conditions. Moreover, both task-related and resting-state functional connectivity analyses indicated weaker coupling between the PFC and temporal regions in the SAT than in the HC group. Furthermore, the left dorsolateral PFC mediated the effect of smartphone addiction on creative performance. These findings provide unprecedented neuroimaging evidence on the negative impact of smartphone addiction on creative cognition.

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

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

Low-dissipation optimization of the prefrontal cortex in the -12° head-down tilt position: A functional near-infrared spectroscopy study

Introduction

Our present study set out to investigate the instant state of the prefrontal cortex (PFC) in healthy subjects before and after placement in the -12°head-down tilt (HDT) position in order to explore the mechanism behind the low-dissipation optimization state of the PFC.

Methods

40 young, right-handed healthy subjects (male: female = 20: 20) were enrolled in this study. Three resting state positions, 0°initial position, -12°HDT position, and 0°rest position were sequentially tested, each for 10 minutes. A continuous-wave functional near-infrared spectroscopy (fNIRS) instrument was used to assess the resting state hemodynamic data of the PFC. After preprocessing the hemodynamics data, we evaluated changes in resting-state functional connectivity (rsFC) level and beta values of PFC. The subjective visual analogue scale (VAS) was applied before and after the experiment. The presence of sleep changes or adverse reactions were also recorded.

Results

Pairwise comparisons of the concentrations of oxyhemoglobin (HbO), deoxyhemoglobin (HbR), and hemoglobin (HbT) revealed significant differences in the aforementioned positions. Specifically, the average rsFC of PFC showed a gradual increase throughout the whole process. In addition, based on graph theory, the topological properties of brain network, such as small-world network and nodal degree centrality were analyzed. The results show that global efficiency and small-world sigma (σ) value were differences between 0°initial and 0°rest.

Discussion

In this study, placement in the -12°HDT had a significant effect on PFC function, mainly manifested as self-inhibition, decreased concentration of HbO in the PFC, and improved rsFC, which may provide ideas to the understanding and explanation of neurological diseases.

Frequency-specific electrogastrography as a non-invasive tool to measure gastrointestinal maturity in preterm infants

Enteral feeding is challenging in preterm infants because of gastrointestinal (GI) immaturity. Electrogastrography (EGG) is a non-invasive technology that measures gastric myoelectrical activity and can be utilized to measure changes that occur with maturation at different gestational ages (GA). Three gastric rhythms (GR) exist between 0.5-9 cycles per minute (cpm), namely, bradygastria (0.5 ≤ GR < 2 cpm), normogastria (2 ≤ GR < 4 cpm), and tachygastria (4 ≤ GR < 9 cpm). We aimed to characterize EGG-derived parameters for different GA by quantifying (1) power spectral density (PSD) and its spectral means at three GR bands (i.e., mPSD_GR) and (2) the percent (%) time spent in each band. Data analyzed was from a longitudinal cohort of preterm infants (n = 51) born at early, mid, and term GA of < 29, 29-33, and ≥ 37 weeks, respectively. Weekly EGG monitoring was performed until 40 weeks' postmenstrual age or discharge. Pre-, during, and post-feed data were analyzed for mPSD_GR at each GR band. Also, % bradygastria, % normogastria, and % tachygastria were calculated by continuous wavelet transform analysis. Results showed (1) mPSD values in normogastria and tachygastria during feeding increased with advancing GA, and (2) % normogastria increased with advancing GA regardless of GR ranges, suggesting EGG may measure GI maturity in preterm infants.

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

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

The Brain Connectome for Chinese Reading

Chinese, as a logographic language, fundamentally differs from alphabetic languages like English. Previous neuroimaging studies have mainly focused on alphabetic languages, while the exploration of Chinese reading is still an emerging and fast-growing research field. Recently, a growing number of neuroimaging studies have explored the neural circuit of Chinese reading. Here, we summarize previous research on Chinese reading from a connectomic perspective. Converging evidence indicates that the left middle frontal gyrus is a specialized hub region that connects the ventral with dorsal pathways for Chinese reading. Notably, the orthography-to-phonology and orthography-to-semantics mapping, mainly processed in the ventral pathway, are more specific during Chinese reading. Besides, in addition to the left-lateralized language-related regions, reading pathways in the right hemisphere also play an important role in Chinese reading. Throughout, we comprehensively review prior findings and emphasize several challenging issues to be explored in future work.

Correction of global physiology in resting-state functional near-infrared spectroscopy

Significance: Resting-state functional connectivity (RSFC) analyses of functional near-infrared spectroscopy (fNIRS) data reveal cortical connections and networks across the brain. Motion artifacts and systemic physiology in evoked fNIRS signals present unique analytical challenges, and methods that control for systemic physiological noise have been explored. Whether these same methods require modification when applied to resting-state fNIRS (RS-fNIRS) data remains unclear. Aim: We systematically examined the sensitivity and specificity of several RSFC analysis pipelines to identify the best methods for correcting global systemic physiological signals in RS-fNIRS data. Approach: Using numerically simulated RS-fNIRS data, we compared the rates of true and false positives for several connectivity analysis pipelines. Their performance was scored using receiver operating characteristic analysis. Pipelines included partial correlation and multivariate Granger causality, with and without short-separation measurements, and a modified multivariate causality model that included a non-traditional zeroth-lag cross term. We also examined the effects of pre-whitening and robust statistical estimators on performance. Results: Consistent with previous work on bivariate correlation models, our results demonstrate that robust statistics and pre-whitening are effective methods to correct for motion artifacts and autocorrelation in the fNIRS time series. Moreover, we found that pre-filtering using principal components extracted from short-separation fNIRS channels as part of a partial correlation model was most effective in reducing spurious correlations due to shared systemic physiology when the two signals of interest fluctuated synchronously. However, when there was a temporal lag between the signals, a multivariate Granger causality test incorporating the short-separation channels was better. Since it is unknown if such a lag exists in experimental data, we propose a modified version of Granger causality that includes the non-traditional zeroth-lag term as a compromising solution. Conclusions: A combination of pre-whitening, robust statistical methods, and partial correlation in the processing pipeline to reduce autocorrelation, motion artifacts, and global physiology are suggested for obtaining statistically valid connectivity metrics with RS-fNIRS. Further studies should validate the effectiveness of these methods using human data.

Prefrontal cortical connectivity and coupling of infraslow oscillation in the resting human brain: a 2-channel broadband NIRS study

The resting-state infraslow oscillation (ISO) of the cerebral cortex reflects the neurophysiological state of the human brain. ISO results from distinct vasomotion with endogenic (E), neurogenic (N), and myogenic (M) frequency bands. Quantification of prefrontal ISO in cortical hemodynamics and metabolism in the resting human brain may facilitate the identification of objective features that are characteristic of certain brain disorders. The goal of this study was to explore and quantify the prefrontal ISO of the cortical concentration changes of oxygenated hemoglobin (Δ[HbO]) and redox-state cytochrome c oxidase (Δ[CCO]) as hemodynamic and metabolic activity metrics in all 3 E/N/M bands. Two-channel broadband near-infrared spectroscopy (2-bbNIRS) enabled measurements of the forehead of 26 healthy young participants in a resting state once a week for 5 weeks. After quantifying the ISO spectral amplitude (SA) and coherence at each E/N/M band, several key and statistically reliable metrics were obtained as features: (i) SA of Δ[HbO] at all E/N/M bands, (ii) SA of Δ[CCO] in the M band, (iii) bilateral connectivity of hemodynamics and metabolism across the E and N bands, and (iv) unilateral hemodynamic–metabolic coupling in each of the E and M bands. These features have promising potential to be developed as objective biomarkers for clinical applications in the future.

Enhancement of Frequency-Specific Hemodynamic Power and Functional Connectivity by Transcranial Photobiomodulation in Healthy Humans

Transcranial photobiomodulation (tPBM) has been considered a safe and effective brain stimulation modality being able to enhance cerebral oxygenation and neurocognitive function. To better understand the underlying neurophysiological effects of tPBM in the human brain, we utilized a 111-channel functional near infrared spectroscopy (fNIRS) system to map cerebral hemodynamic responses over the whole head to 8-min tPBM with 1,064-nm laser given on the forehead of 19 healthy participants. Instead of analyzing broad-frequency hemodynamic signals (0–0.2 Hz), we investigated frequency-specific effects of tPBM on three infra-slow oscillation (ISO) components consisting of endogenic, neurogenic, and myogenic vasomotions. Significant changes induced by tPBM in spectral power of oxygenated hemoglobin concentration (Δ[HbO]), functional connectivity (FC), and global network metrics at each of the three ISO frequency bands were identified and mapped topographically for frequency-specific comparisons. Our novel findings revealed that tPBM significantly increased endogenic Δ[HbO] powers over the right frontopolar area near the stimulation site. Also, we demonstrated that tPBM enabled significant enhancements of endogenic and myogenic FC across cortical regions as well as of several global network metrics. These findings were consistent with recent reports and met the expectation that myogenic oscillation is highly associated with endothelial activity, which is stimulated by tPBM-evoked nitric oxide (NO) release.

Hasty sensorimotor decisions rely on an overlap of broad and selective changes in motor activity

Humans and other animals are able to adjust their speed–accuracy trade-off (SAT) at will depending on the urge to act, favoring either cautious or hasty decision policies in different contexts. An emerging view is that SAT regulation relies on influences exerting broad changes on the motor system, tuning its activity up globally when hastiness is at premium. The present study aimed to test this hypothesis. A total of 50 participants performed a task involving choices between left and right index fingers, in which incorrect choices led either to a high or to a low penalty in 2 contexts, inciting them to emphasize either cautious or hasty policies. We applied transcranial magnetic stimulation (TMS) on multiple motor representations, eliciting motor-evoked potentials (MEPs) in 9 finger and leg muscles. MEP amplitudes allowed us to probe activity changes in the corresponding finger and leg representations, while participants were deliberating about which index to choose. Our data indicate that hastiness entails a broad amplification of motor activity, although this amplification was limited to the chosen side. On top of this effect, we identified a local suppression of motor activity, surrounding the chosen index representation. Hence, a decision policy favoring speed over accuracy appears to rely on overlapping processes producing a broad (but not global) amplification and a surround suppression of motor activity. The latter effect may help to increase the signal-to-noise ratio of the chosen representation, as supported by single-trial correlation analyses indicating a stronger differentiation of activity changes in finger representations in the hasty context.

Many have argued that the regulation of the speed-accuracy tradeoff relies on an urgency signal, which implements "collapsing decision thresholds" by tuning neural activity in a global manner in decision-related structures. This study indicates that the reality is more subtle, with several aspects of "urgency" being specifically targeted to particular corticospinal populations within the motor system.

Hemispheric Lateralization of Visuospatial Attention Is Independent of Language Production on Right-Handers: Evidence From Functional Near-Infrared Spectroscopy

It is well-established that visuospatial attention is mainly lateralized to the right hemisphere, whereas language production is mainly left-lateralized. However, there is a significant controversy regarding how these two kinds of lateralization interact with each other. The present research used functional near-infrared spectroscopy (fNIRS) to examine whether visuospatial attention is indeed right-lateralized, whereas language production is left-lateralized, and more importantly, whether the extent of lateralization in the visuospatial task is correlated with that in the task involving language. Specifically, fifty-two healthy right-handed participants participated in this study. Multiple-channel fNIRS technique was utilized to record the cerebral hemodynamic changes when participants were engaged in naming objects depicted in pictures (the picture naming task) or judging whether a presented line was bisected correctly (the landmark task). The degree of hemispheric lateralization was quantified according to the activation difference between the left and right hemispheres. We found that the picture-naming task predominantly activated the inferior frontal gyrus (IFG) of the left hemisphere. In contrast, the landmark task predominantly activated the inferior parietal sulcus (IPS) and superior parietal lobule (SPL) of the right hemisphere. The quantitative calculation of the laterality index also showed a left-lateralized distribution for the picture-naming task and a right-lateralized distribution for the landmark task. Intriguingly, the correlation analysis revealed no significant correlation between the laterality indices of these two tasks. Our findings support the independent hypothesis, suggesting that different cognitive tasks may engender lateralized processing in the brain, but these lateralized activities may be independent of each other. Meanwhile, we stress the importance of handedness in understanding the relationship between functional asymmetries. Methodologically, we demonstrated the effectiveness of using the multichannel fNIRS technique to investigate the hemispheric specialization of different cognitive tasks and their lateralization relations between different tasks. Our findings and methods may have important implications for future research to explore lateralization-related issues in individuals with neural pathologies.

Studying hemispheric lateralization of 4-month-old infants from different language groups through near-infrared spectroscopy-based connectivity

INTRODUCTION

Early monolingual versus bilingual experience affects linguistic and cognitive processes during the first months of life, as well as functional activation patterns. The previous study explored the influence of a bilingual environment in the first months of life on resting-state functional connectivity and reported no significant difference between language groups.

METHODS

To further explore the influence of a bilingual environment on brain development function, we used the resting-state functional near-infrared spectroscopy public dataset of the 4-month-old infant group in the sleep state (30 Spanish; 33 Basque; 36 bilingual). Wavelet Transform Coherence, graph theory, and Granger causality methods were performed on the functional connectivity of the frontal lobes.

RESULTS

The results showed that functional connectivity strength was significantly higher in the left hemisphere than that in the right hemisphere in both monolingual and bilingual groups. The graph theoretic analysis showed that the characteristic path length was significantly higher in the left hemisphere than in the right hemisphere for the bilingual infant group. Contrary to the monolingual infant group, the left-to-right direction of information flow was found in the frontal regions of the bilingual infant group in the effective connectivity analysis.

DISCUSSION

The results suggested that the left hemispheric lateralization of functional connectivity in frontal regions is more pronounced in the bilingual group compared to the monolingual group. Furthermore, effective connectivity analysis may be a useful method to investigate the resting-state brain networks of infants.

Multimodal Autoencoder Predicts fNIRS Resting State From EEG Signals

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

Neural Variability in the Prefrontal Cortex as a Reflection of Neural Flexibility and Stability in Patients With Parkinson Disease

BACKGROUND AND OBJECTIVES

Functional Near-Infrared Spectroscopy (fNIRS) studies provide direct evidence to the important role of the prefrontal cortex (PFC) during walking in aging and Parkinson's disease (PD). Most studies mainly explored mean HbO2 levels, while moment-to-moment variability measures have been rarely investigated. Variability measures can inform on flexibility that is imperative for adaptive function. We hypothesized that patients with PD will show less variability in HbO2 signals during walking compared to healthy controls.

METHODS

206 participants, 57 healthy controls (age: 68.9±1.0 years; 27 women) and 149 idiopathic PD patients (age: 69.8±0.6 years, 50 women, disease duration: 8.27±5.51 years) performed usual walking and dual-task walking (serial 3 subtractions) with an fNIRS system placed on the forehead. HbO2 variability was calculated using the standard deviation (SD), range, and mean detrended time series of fNIRS-derived HbO2 signal evaluated during each walking task. HbO2 variability was compared between groups and between walking tasks using mixed model analyses.

RESULTS

Higher variability (SD, range, mean detrended time series) was observed during dual-task walking, compared to usual walking (p<0.025), but this was derived from the differences within the healthy control group (group X task interaction: p<0.007). On the other hand, task repetition demonstrated reduced variability in healthy controls but increased variability in patients with PD (interaction group*walk-repetition: p<0.048). The MDS-UPDRS motor score correlated with HbO2 range (r=0.142, p=0.050) and HbO2 SD (r=0.173, p=0.018) during usual walking in all participants.

DISCUSSION

In this study, we suggest a new way to interpret changes in HbO2 variability. We relate increased HbO2 variability to flexible adaptation to environmental challenges and decreased HbO2 variability to the stability of performance. Our results show that both are limited in PD however, further investigation of these concepts is required. Moreover, HbO2 variability measures are an important aspect of brain function that adds new insights into the role of PFC during walking with aging and PD.

CLASSIFICATION OF EVIDENCE

This study provides Class III evidence that patients with PD have more variability within Hb02 signals during usual-walking, compared to healthy controls, but not during dual-task walking.

Imagined speech increases the hemodynamic response and functional connectivity of the dorsal motor cortex

Objective. Decoding imagined speech from brain signals could provide a more natural, user-friendly way for developing the next generation of the brain-computer interface (BCI). With the advantages of non-invasive, portable, relatively high spatial resolution and insensitivity to motion artifacts, the functional near-infrared spectroscopy (fNIRS) shows great potential for developing the non-invasive speech BCI. However, there is a lack of fNIRS evidence in uncovering the neural mechanism of imagined speech. Our goal is to investigate the specific brain regions and the corresponding cortico-cortical functional connectivity features during imagined speech with fNIRS.Approach. fNIRS signals were recorded from 13 subjects' bilateral motor and prefrontal cortex during overtly and covertly repeating words. Cortical activation was determined through the mean oxygen-hemoglobin concentration changes, and functional connectivity was calculated by Pearson's correlation coefficient.Main results. (a) The bilateral dorsal motor cortex was significantly activated during the covert speech, whereas the bilateral ventral motor cortex was significantly activated during the overt speech. (b) As a subregion of the motor cortex, sensorimotor cortex (SMC) showed a dominant dorsal response to covert speech condition, whereas a dominant ventral response to overt speech condition. (c) Broca's area was deactivated during the covert speech but activated during the overt speech. (d) Compared to overt speech, dorsal SMC(dSMC)-related functional connections were enhanced during the covert speech.Significance. We provide fNIRS evidence for the involvement of dSMC in speech imagery. dSMC is the speech imagery network's key hub and is probably involved in the sensorimotor information processing during the covert speech. This study could inspire the BCI community to focus on the potential contribution of dSMC during speech imagery.

Sleep deprivation alters task-related changes in functional connectivity of the frontal cortex: A near-infrared spectroscopy study

Sleep deprivation (SD) is known to be associated with decreased cognitive performance; however, the underlying mechanisms are poorly understood. As interactions between distinct brain regions depend on mental state, functional brain networks established by these connections typically show a reorganization during task. Hence, analysis of functional connectivity (FC) could reveal the task-related change in the examined frontal brain networks. Our objective was to assess the impact of SD on static FC in the prefrontal and motor cortices and find whether changes in FC correlate with changes in neuropsychological scores. Healthy young male individuals (n = 10, 27.6 ± 3.7 years of age) participated in the study. A battery of tests from the Cambridge Neuropsychological Test Automated Battery (CANTAB) and 48 channel functional near-infrared spectroscopy (fNIRS) measurements were performed before and after 24 hr of SD. Network metrics were obtained by graph theoretical analysis using the fNIRS records in resting state and during finger-tapping sessions. During task, SD resulted in a significantly smaller decrease in the number and strength of functional connections (characterizing FC) in the frontal cortex. Changes in the global connection strengths correlated with decreased performance in the paired association learning test. These results indicate a global impact of SD on functional brain networks in the frontal lobes.

Quantitative Assessment of Resting-State for Mild Cognitive Impairment Detection: A Functional Near-Infrared Spectroscopy and Deep Learning Approach

BACKGROUND

Mild cognitive impairment (MCI) is considered a prodromal stage of Alzheimer's disease. Early diagnosis of MCI can allow for treatment to improve cognitive function and reduce modifiable risk factors.

OBJECTIVE

This study aims to investigate the feasibility of individual MCI detection from healthy control (HC) using a minimum duration of resting-state functional near-infrared spectroscopy (fNIRS) signals.

METHODS

In this study, nine different measurement durations (i.e., 30, 60, 90, 120, 150, 180, 210, 240, and 270 s) were evaluated for MCI detection via the graph theory analysis and traditional machine learning approach, such as linear discriminant analysis, support vector machine, and K-nearest neighbor algorithms. Moreover, feature representation- and classification-based transfer learning (TL) methods were applied to identify MCI from HC through the input of connectivity maps with 30 and 90 s duration.

RESULTS

There was no significant difference among the nine various time windows in the machine learning and graph theory analysis. The feature representation-based TL showed improved accuracy in both 30 and 90 s cases (i.e., 30 s: 81.27% and 90 s: 76.73%). Notably, the classification-based TL method achieved the highest accuracy of 95.81% using the pre-trained convolutional neural network (CNN) model with the 30 s interval functional connectivity map input.

CONCLUSION

The results indicate that a 30 s measurement of the resting-state with fNIRS could be used to detect MCI. Moreover, the combination of neuroimaging (e.g., functional connectivity maps) and deep learning methods (e.g., CNN and TL) can be considered as novel biomarkers for clinical computer-assisted MCI diagnosis.

Alterations of Cerebral Hemodynamics and Network Properties Induced by Newsvendor Problem in the Human Prefrontal Cortex

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 (NP), have been investigated in conjunction with neuroimaging. In this study, we hypothesized (I) that NP stimulates the dorsolateral prefrontal cortex (DLPFC) and the orbitofrontal cortex (OFC) joined with frontal polar area (FPA) significantly in the human brain, and (II) that local brain network properties are increased when a person transits from rest to the NP decision-making phase. A 77-channel functional near infrared spectroscopy (fNIRS) system with wide field-of-view (FOV) 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 (GLM) and graph theory analysis (GTA). Significant activation induced by NP was shown in both DLPFC and OFC+FPA across all subjects. Specifically, higher risk NP with low-profit margins (LM) activated left-DLPFC but deactivated right-DLPFC in 14 subjects, while lower risk NP with high-profit margins (HM) 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.

NIRS-KIT: a MATLAB toolbox for both resting-state and task fNIRS data analysis

Significance: Functional near-infrared spectroscopy (fNIRS) has been widely used to probe human brain function during task state and resting state. However, the existing analysis toolboxes mainly focus on task activation analysis, few software packages can assist resting-state fNIRS studies. Aim: We aimed to provide a versatile and easy-to-use toolbox to perform analysis for both resting state and task fNIRS. Approach: We developed a MATLAB toolbox called NIRS-KIT that works for both resting-state analysis and task activation detection. Results: NIRS-KIT implements common and necessary processing steps for performing fNIRS data analysis, including data preparation, quality control, preprocessing, individual-level analysis, group-level statistics with several popular statistical models, and multiple comparison correction methods, and finally results visualization. For resting-state fNIRS analysis, functional connectivity analysis, graph theory-based network analysis, and amplitude of low-frequency fluctuations analysis are provided. Additionally, NIRS-KIT also supports activation analysis for task fNIRS. Conclusions: NIRS-KIT offers an open source tool for researchers to analyze resting-state and/or task fNIRS data in one suite. It contains several key features: (1) good compatibility, supporting multiple fNIRS recording systems, data formats of NIRS-SPM and Homer2, and the shared near-infrared spectroscopy format data format recommended by the fNIRS society; (2) flexibility, supporting customized preprocessing scripts; (3) ease-to-use, allowing processing fNIRS signals in batch manner with user-friendly graphical user interfaces; and (4) feature-packed data viewing and result visualization. We anticipate that this NIRS-KIT will facilitate the development of the fNIRS field.

Applications of functional near-infrared spectroscopy (fNIRS) in neonates

Functional near-infrared spectroscopy (fNIRS) is a method of monitoring brain oxygenation. This technique investigates hemodynamic changes in the cerebral cortex. fNIRS is widely used in clinical and scientific research. In this review, we focus on the applications of fNIRS on neonates. Here, applications form two distinct categories: task associated studies, and hemoglobin phase change studies. fNIRS is non-invasive, easily performed, and repeatable. However, it has limited monitoring depth and spatial resolution when used in newborns. Moreover, with recent technological advances, it is now possible to explore neuronal activity patterns using fNIRS in both healthy and pathological conditions. For more than 20 years, fNIRS has enabled clinicians to gain insight into cerebral development and mechanisms of injury in neonates. fNIRS is a useful supplement to existing technologies due to its ability to interrogate the neonatal brain function.

A Review of Cerebral Hemodynamics During Sleep Using Near-Infrared Spectroscopy

Investigating cerebral hemodynamic changes during regular sleep cycles and sleep disorders is fundamental to understanding the nature of physiological and pathological mechanisms in the regulation of cerebral oxygenation during sleep. Although sleep neuroimaging methods have been studied and have been well-reviewed, they have limitations in terms of technique and experimental design. Neurologists are convinced that Near-infrared spectroscopy (NIRS) provides essential information and can be used to assist the assessment of cerebral hemodynamics, and numerous studies regarding sleep have been carried out based on NIRS. Thus, a brief historical overview of the sleep studies using NIRS will be helpful for the biomedical students, academicians, and engineers to better understand NIRS from various perspectives. In this study, the existing literature on sleep studies is reviewed, and an overview of the NIRS applications is synthesized and provided. The paper first reviews the application scenarios, as well as the patterns of fluctuation of NIRS, which includes the investigation in regular sleep and sleep-disordered breathing. Various factors such as different sleep stages, populations, and degrees of severity were considered. Furthermore, the experimental design and signal processing, as well as the regulation mechanisms involved in regular and pathological sleep, are investigated and discussed. The strengths and weaknesses of the existing NIRS applications are addressed and presented, which can direct further NIRS analysis and utilization.

Reduced functional connectivity in the prefrontal cortex of elderly catatonia patients: A longitudinal study using functional near-infrared spectroscopy

Catatonia is a syndrome that manifests in patients with mental disorders and general medical conditions. However, functional changes to the brain that cause catatonia remain unknown. In the present study, we used functional near-infrared spectroscopy (fNIRS) to assess spontaneous hemodynamic activities in the brain at the times of onset and resolution of catatonic symptoms in patients with catatonia. We used 22-channel and 49-channel fNIRS to examine hemodynamic activities in the prefrontal cortex (PFC), and both frontal and parietal cortices, respectively. A total of ten patients who were diagnosed with catatonia were included in the study. Resting state measurements were taken for five minutes at the time of the onset and resolution of catatonic symptoms. Analyses were performed for the prefrontal region and the motor cortex within the parietal-frontal region of the brain. Functional connectivity between the cerebral hemispheres was evaluated systematically based on spontaneous oscillation of Δ[HbO2]. In the PFC, the resting state functional connectivity (RSFC) was significantly lower in the catatonic state than in the eyes-closed non-catatonic state (p = 0.047). The study demonstrated that the RSFC in the PFC, measured using fNIRS, may be an objective indicator of the change in catatonic symptoms.

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.

Immediate effects of visual-motor illusion on resting-state functional connectivity

Visual-motor illusion (VMI) is to evoke a kinesthetic sensation by viewing images of oneself performing physical exercise while the body is at rest. Previous studies demonstrated that VMI activates the motor association brain areas; however, it is unclear whether VMI immediately alters the resting-state functional connectivity (RSFC). This study is aimed to verify whether the VMI induction changed the RSFC using functional near-infrared spectroscopy (fNIRS). The right hands of 13 healthy adults underwent illusion and observation conditions for 20 min each. Before and after each condition, RSFC was measured using fNIRS. After each condition, degree of kinesthetic illusion and a sense of body ownership measured using the Likert scale. Our results indicated that, compared with the observation condition, the degree of kinesthetic illusion and the sense of body ownership were significantly higher after the illusion condition. Compared with the observation condition, RSFC after the illusion condition significantly increased brain areas associated with kinesthetic illusion, a sense of body ownership, and motor execution. In conclusion, RSFC has become a biomarker that shows changes in brain function occurring due to VMI. VMI may be applied to the treatment of patients with stroke or orthopedic diseases.

Which obstacle attributes place additional demands on higher-level cognitive function in patients with Parkinson's disease?

BACKGROUND

Previous reports show that patients with Parkinson's disease (PD) rely on prefrontal activation to compensate for impaired motor function during complex activities such as obstacle negotiation. However, the influence of the properties of the obstacles on prefrontal activation has not been systematically evaluated. Here, we examined the effects of obstacle height and anticipation time on prefrontal activation in patients with PD and older adults.

METHODS

34 patients with PD (age: 67.4 ± 5.7 years; 14 women) and 26 older adults (age: 71.3 ± 8.9 years; 11 women) walked in an obstacle course while negotiating anticipated and unanticipated obstacles (long/short available time response, ART) at heights of 50 mm and 100 mm. Prefrontal activation was measured using functional Near-Infrared Spectroscopy (fNIRS); obstacle negotiation performance was measured using Kinect cameras.

RESULTS

PD patients showed greater increases in prefrontal activation during and after obstacle crossing compared to the older adults (p < 0.001). Obstacle height affected prefrontal activity only when crossing anticipated obstacles (ARTxheight interaction, p = 0.011), in which case higher obstacles were accompanied by higher prefrontal activity. PD patients showed higher levels of activation during unanticipated obstacles, compared to older adults (groupXART: p = 0.015). Different correlations between prefrontal activation and obstacle negotiation strategies were observed in patients and controls.

CONCLUSIONS

These results point to the use of prefrontal activation as a compensatory mechanism in PD. Moreover, the higher activation observed when negotiating more challenging obstacles suggests that there is greater reliance on cognitive resources in these demanding situations that may contribute to the higher risk of falls in PD patients.

Lower Small-Worldness of Intrinsic Brain Networks Facilitates the Cognitive Protection of Intellectual Engagement in Elderly People Without Dementia: A Near-Infrared Spectroscopy Study

OBJECTIVE

Lifetime intellectual engagement may be associated with cognitive ability late in life. However, the current evidence on whether cognitive activities will improve and/or maintain cognitive function is heterogeneous. Drawing on knowledge of the brain's intrinsic small-world organization which combines regional specialization and efficient global information transfer, we aimed to explore that whether individual differences in the small-worldness of resting-state functional connectivity (rsFC) networks would explain the variability in the strength of the association between intellectual engagement and cognitive functioning.

METHODS

Sixty-five elderly people without dementia were enrolled and scanned with a 52-channel near-infrared spectroscopy system. The number, frequency, and participation hours of intellectual activities were investigated to measure intellectual engagement. Global cognition was assessed by the Montreal Cognitive Assessment. The general linear models and the simple slope analysis were employed to measure the modulatory role of network properties.

RESULTS

The small-worldness of the brain network emerged as a moderator of the association between intellectual engagement and cognition. Exclusively among elderly people with lower small-worldness, greater intellectual engagement, including the frequency and participation hours of activities, was associated with greater global cognitive function. Furthermore, we observed that elderly people with lower small-worldness exhibited decreased rsFC across the bilateral frontopolar areas and increased rsFC across the bilateral parietal cortex.

CONCLUSION

The individual differences in the small-worldness of rsFC networks might explain the varying strength of the association between intellectual engagement and cognitive functioning. Our findings imply that the intrinsic small-worldness of the brain network might be a potential neurobiological contributor that interacts with the intellectual engagement in enhancing the cognitive ability in late life.

Applications of Resting-State fNIRS in the Developing Brain: A Review From the Connectome Perspective

Early brain development from infancy through childhood is closely related to the development of cognition and behavior in later life. Human brain connectome is a novel framework for describing topological organization of the developing brain. Resting-state functional near-infrared spectroscopy (fNIRS), with a natural scanning environment, low cost, and high portability, is considered as an emerging imaging technique and has shown valuable potential in exploring brain network architecture and its changes during the development. Here, we review the recent advances involving typical and atypical development of the brain connectome from neonates to children using resting-state fNIRS imaging. This review highlights that the combination of brain connectome and resting-state fNIRS imaging offers a promising framework for understanding human brain development.

Assessing Brain Networks by Resting-State Dynamic Functional Connectivity: An fNIRS-EEG Study

The coordination of brain activity between disparate neural populations is highly dynamic. Investigations into intrinsic brain organization by evaluating dynamic resting-state functional connectivity (dRSFC) have attracted great attention in recent years. However, there are few dRSFC studies based on functional near-infrared spectroscopy (fNIRS) even though it has some advantages for studying the temporal evolution of brain function. In this research, we recruited 20 young adults and measured their resting-state brain fluctuations in several areas of the frontal, parietal, temporal, and occipital lobes using fNIRS-electroencephalography (EEG) simultaneous recording. Based on a sliding-window approach, we found that the variability of the dRSFC within any region of interest was significantly lower than the connections between region of interests but noticeably greater than the correlation between the channels with a short interoptode distance, which mainly consist of physiological fluctuations occurring in the superficial layers. Furthermore, based on a time-resolved k-means clustering analysis, the temporal evolution was extracted for three dominant functional networks. These networks were roughly consistent between different subject subgroups and in varying sliding time window lengths of 20, 30, and 60 s. Between these three functional networks, there were obvious time-varied and system-specific synchronous relationships. In addition, the oscillation of the frontal-parietal-temporal network showed significant correlation with the switching of one EEG microstate, a finding which is consistent with a previous functional MRI-EEG study. All this evidence implies the functional significance of fNIRS-dRSFC and demonstrates the feasibility of fNIRS for extracting the dominant functional networks based on RSFC dynamics.

Disrupted functional brain connectivity networks in children with attention-deficit/hyperactivity disorder: evidence from resting-state functional near-infrared spectroscopy

Significance: Attention-deficit/hyperactivity disorder (ADHD) is the most common psychological disease in childhood. Currently, widely used neuroimaging techniques require complete body confinement and motionlessness and thus are extremely hard for brain scanning of ADHD children. Aim: We present resting-state functional near-infrared spectroscopy (fNIRS) as an imaging technique to record spontaneous brain activity in children with ADHD. Approach: The brain functional connectivity was calculated, and the graph theoretical analysis was further applied to investigate alterations in the global and regional properties of the brain network in the patients. In addition, the relationship between brain network features and core symptoms was examined. Results: ADHD patients exhibited significant decreases in both functional connectivity and global network efficiency. Meanwhile, the nodal efficiency in children with ADHD was also found to be altered, e.g., increase in the visual and dorsal attention networks and decrease in somatomotor and default mode networks, compared to the healthy controls. More importantly, the disrupted functional connectivity and nodal efficiency significantly correlated with dimensional ADHD scores. Conclusions: We clearly demonstrate the feasibility and potential of fNIRS-based connectome technique in ADHD or other neurological diseases in the future.

Exploring attentive task-based connectivity for screening attention deficit/hyperactivity disorder children: a functional near-infrared spectroscopy study

Connectivity impairment has frequently been associated with the pathophysiology of attention-deficit/hyperactivity disorder (ADHD). Although the connectivity of the resting state has mainly been studied, we expect the transition between baseline and task may also be impaired in ADHD children. Twenty-three typically developing (i.e., control) and 36 disordered (ADHD and autism-comorbid ADHD) children were subjected to connectivity analysis. Specifically, they performed an attention task, visual oddball, while their brains were measured by functional near-infrared spectroscopy. The results of the measurements revealed three key findings. First, the control group maintained attentive connectivity, even in the baseline interval. Meanwhile, the disordered group showed enhanced bilateral intra- and interhemispheric connectivities while performing the task. However, right intrahemispheric connectivity was found to be weaker than those for the control group. Second, connectivity and activation characteristics might not be positively correlated with each other. In our previous results, disordered children lacked activation in the right middle frontal gyrus. However, within region connectivity of the right middle frontal gyrus was relatively strong in the baseline interval and significantly increased in the task interval. Third, the connectivity-based biomarker performed better than the activation-based biomarker in terms of screening. Activation and connectivity features were independently optimized and cross validated to obtain the best performing threshold-based classifier. The effectiveness of connectivity features, which brought significantly higher training accuracy than the optimum activation features, was confirmed (88% versus 76%). The optimum screening features were characterized by two trends: (1) strong connectivities of right frontal, left frontal, and left parietal lobes and (2) weak connectivities of left frontal, left parietal, and right parietal lobes in the control group. We conclude that the attentive task-based connectivity effectively shows the difference between control and disordered children and may represent pathological characteristics to be feasibly implemented as a supporting tool for clinical screening.

Fronto-temporoparietal connectivity and self-awareness in 18-month-olds: A resting state fNIRS study

How and when a concept of the 'self' emerges has been the topic of much interest in developmental psychology. Self-awareness has been proposed to emerge at around 18 months, when toddlers start to show evidence of physical self-recognition. However, to what extent physical self-recognition is a valid indicator of being able to think about oneself, is debated. Research in adult cognitive neuroscience has suggested that a common network of brain regions called Default Mode Network (DMN), including the temporo-parietal junction (TPJ) and the medial prefrontal cortex (mPFC), is recruited when we are reflecting on the self. We hypothesized that if mirror self-recognition involves self-awareness, toddlers who exhibit mirror self-recognition might show increased functional connectivity between frontal and temporoparietal regions of the brain, relative to those toddlers who do not yet show mirror self-recognition. Using fNIRS, we collected resting-state data from 18 Recognizers and 22 Non-Recognizers at 18 months of age. We found significantly stronger fronto-temporoparietal connectivity in Recognizers compared to Non-Recognizers, a finding which might support the hypothesized relationship between mirror-self recognition and self-awareness in infancy.

A Mini-Review on Functional Near-Infrared Spectroscopy (fNIRS): Where Do We Stand, and Where Should We Go?

This mini-review is aimed at briefly summarizing the present status of functional near-infrared spectroscopy (fNIRS) and predicting where the technique should go in the next decade. This mini-review quotes 33 articles on the different fNIRS basics and technical developments and 44 reviews on the fNIRS applications published in the last eight years. The huge number of review articles about a wide spectrum of topics in the field of cognitive and social sciences, functional neuroimaging research, and medicine testifies to the maturity achieved by this non-invasive optical vascular-based functional neuroimaging technique. Today, fNIRS has started to be utilized on healthy subjects while moving freely in different naturalistic settings. Further instrumental developments are expected to be done in the near future to fully satisfy this latter important aspect. In addition, fNIRS procedures, including correction methods for the strong extracranial interferences, need to be standardized before using fNIRS as a clinical tool in individual patients. New research avenues such as interactive neurosciences, cortical activation modulated by different type of sport performance, and cortical activation during neurofeedback training are highlighted.

Abnormal dynamic functional connectivity and brain states in Alzheimer's diseases: functional near-infrared spectroscopy study

Communication within the brain is highly dynamic. Alzheimer's disease (AD) exhibits dynamic progression corresponding to a decline in memory and cognition. However, little is known of whether brain dynamics are disrupted in AD and its prodromal stage, mild cognitive impairment (MCI). For our study, we acquired high sampling rate functional near-infrared spectroscopy imaging data at rest from the entire cortex of 23 patients with AD dementia, 25 patients with amnestic mild cognitive impairment (aMCI), and 30 age-matched healthy controls (HCs). Sliding-window correlation and k-means clustering analyses were used to construct dynamic functional connectivity (FC) maps for each participant. We discovered that the brain's dynamic FC variability strength ( Q ) significantly increased in both aMCI and AD group as compared to HCs. Using the Q value as a measurement, the classification performance exhibited a good power in differentiating aMCI [area under the curve ( AUC = 82.5 % )] or AD ( AUC = 86.4 % ) from HCs. Furthermore, we identified two abnormal brain FC states in the AD group, of which the occurrence frequency ( F ) exhibited a significant decrease for the first-level FC state (state 1) and a significant increase for the second-level FC state (state 2). We also found that the abnormal F in these two states significantly correlated with the cognitive impairment in patients. These findings provide the first evidence to demonstrate the disruptions of dynamic brain connectivity in aMCI and AD and extend the traditional static (i.e., time-averaged) FC findings in the disease (i.e., disconnection syndrome) and thus provide insights into understanding the pathophysiological mechanisms occurring in aMCI and AD.

Functional near-infrared spectroscopy evidence for the development of topological asymmetry between hemispheric brain networks from childhood to adulthood

Cerebral asymmetry is considered an important marker of the successful development of the human brain. Recent studies have demonstrated topological asymmetries between structurally hemispheric networks in the human brain. However, it remains largely unknown whether and how the functionally topological asymmetries evolve from childhood to adulthood, a critical period that constitutes the primary peak of human brain and cognitive development. Here, we adopted resting-state functional near-infrared spectroscopy imaging data to construct hemispheric functional networks and then applied graph theory analysis to quantify the topological characteristics of the hemispheric networks. We found that the adult group exhibited consistent leftward hemispheric asymmetries in both global and local network efficiency, and the degree of leftward asymmetry in local network efficiency was significantly increased with development from childhood to adulthood. At the nodal level, the degree of leftward asymmetry in nodal efficiency, mainly involving the frontal, parietal-occipital junction, and occipital regions, increased with development. These developmental patterns of topological asymmetries suggest that the protracted maturation of functional segregation in the left hemisphere could underlie language development from childhood to adulthood and provide insight into the development of human brain functional networks.

Capturing spontaneous activity in the medial prefrontal cortex using near-infrared spectroscopy and its application to schizophrenia

Near-infrared spectroscopy (NIRS) is an optimal imaging modality used to examine spontaneous brain activity because it can quietly measure blood flow changes with less physical restriction during the resting state. Here, NIRS was used at rest to measure spontaneous activity in the medial prefrontal cortex (mPFC), a main locus of default mode network. Consistent with previous fMRI studies, magnitude of the spontaneous activity in this region declined with increasing age in healthy subjects. The magnitude reduced in the mPFC of patients with schizophrenia. Additionally, in the mPFC of patients with schizophrenia, the spontaneous activity did not show any age-related decline; the activity was already low in younger patients. Further analysis using fractional amplitude of low-frequency fluctuations confirmed the reduction of spontaneous activity in the mPFC of patients with schizophrenia, consistent with the findings of fMRI studies. Our findings demonstrate the ability of NIRS to evaluate the spontaneous activity in the mPFC of patients with schizophrenia, particularly younger patients. Considering the safety and ease of the NIRS measurements, the current NIRS study of the resting-state activity indicates its utility for clinical applications to schizophrenia, which may facilitate chronological assessment of larger cohorts of patients with schizophrenia in further studies.

Human central auditory plasticity: A review of functional near-infrared spectroscopy (fNIRS) to measure cochlear implant performance and tinnitus perception

OBJECTIVE

Functional near-infrared spectroscopy (fNIRS) is an emerging noninvasive technology used to study cerebral cortex activity. Being virtually silent and compatible with cochlear implants has helped establish fNIRS as an important tool when investigating auditory cortex as well as cortices involved with hearing and language processing in adults and during child development. With respect to this review article, more recently, fNIRS has also been used to investigate central auditory plasticity following hearing loss and tinnitus or phantom sound perception.

METHODS

Here, we review the currently available literature reporting the use of fNIRS in human studies with cochlear implants and tinnitus to measure human central auditory cortical circuits. We also provide the reader with detailed reviews of the technology and traditional recording paradigms/methods used in these auditory-based studies.

RESULTS

The purpose of this review article is to summarize theoretical advancements in our understanding of the neurocognitive mechanisms underlying auditory processes and their plasticity through fNIRS research of human auditory performance with cochlear implantation and plasticity that may contribute to the central percepts of tinnitus.

CONCLUSION

fNIRS is an emerging noninvasive brain imaging technology that has wide reaching application that can be applied to human studies involving cochlear implants and tinnitus.

LEVEL OF EVIDENCE

N/A.

Neuroticism and conscientiousness respectively positively and negatively correlated with the network characteristic path length in dorsal lateral prefrontal cortex: A resting-state fNIRS study

BACKGROUND

Accumulating evidence shows that the dorsal lateral prefrontal cortex (dlPFC) is implicated in personality traits. In this study, resting-state functional near infrared spectroscopy (fNIRS) combined with small-world analysis was utilized to examine the relationship between the network properties of dlPFC and personality traits.

METHODS

Thirty college students (aged between 20 and 29) were recruited from the University of Macau campus, whose personality scores were accessed with the NEO-FFT questionnaire. Graph theory combined with resting-state fNIRS data was used to quantify the network properties of dlPFC, whereas Pearson correlation analysis was performed to generate the relationship between the small-world indicators and personality scores.

RESULTS

Compared to matched random networks, the resting-state brain networks exhibited a larger clustering coefficient (C_p , 0.1-0.66), shorter characteristic path length (L_p , 0.1-0.66), and higher global (E_g , 0.1-0.66) and local efficiency (E_loc , 0.1-0.65). In particular, conscientiousness (r = -0.63) and neuroticism (r = 0.40) respectively showed negative and positive correlation with the L_p .

CONCLUSIONS

The resting-state functional brain networks in dlPFC exhibited the small-world properties. In addition, participants with higher conscientiousness scores showed a shorter L_p .

Whole-cortical graphical networks at wakeful rest in young and older adults revealed by functional near-infrared spectroscopy

A good understanding of age-dependent changes and modifications in brain networks is crucial for fully exploring the effects of aging on the human brain. Few reports have been found in studies of functional brain networks using functional near-infrared spectroscopy (fNIRS). Moreover, little is known about the feasibility of using fNIRS to assess age-related changes in brain connectomes. This study applied whole brain fNIRS measurement, combined with graph theory analysis, to assess the age-dependent changes in resting-state brain networks. Five to eight minutes of resting-state brain hemodynamic signals were recorded from 48 participants (18 young adults and 30 older adults) with 133 optical channels covering the majority of the cortical regions. Both local and global graph metrics were computed to identify the age-related changes of topographical brain networks. Older adults showed an overall decline of both global and local efficiency compared to young adults, as well as the decline of small-worldness. In addition, young adults showed the abundance of hubs in the prefrontal cortex, whereas older adults revealed the hub shifts to the sensorimotor cortex. These obvious shifts of hubs may potentially indicate decreases of the decision-making, memory, and other high-order functions as people age. Our results showed consistent findings with published literature and also demonstrated the feasibility of whole-head fNIRS measurements to assess age-dependent changes in resting-state brain networks.