Use of fNIRS to assess resting state functional connectivity

Reduced interhemispheric functional connectivity of children with autism spectrum disorder: evidence from functional near infrared spectroscopy studies

Autism spectrum disorder (ASD) is a neuro-developmental disorder, which has been associated with atypical neural synchronization. In this study, functional near infrared spectroscopy (fNIRS) was used to study the differences in functional connectivity in bilateral inferior frontal cortices (IFC) and bilateral temporal cortices (TC) between ASD and typically developing (TD) children between 8 and 11 years of age. As the first report of fNIRS study on the resting state functional connectivity (RSFC) in children with ASD, ten children with ASD and ten TD children were recruited in this study for 8 minute resting state measurement. Compared to TD children, children with ASD showed reduced interhemispheric connectivity in TC. Children with ASD also showed significantly lower local connectivity in bilateral temporal cortices. In contrast to TD children, children with ASD did not show typical patterns of symmetry in functional connectivity in temporal cortex. These results support the feasibility of using the fNIRS method to assess atypical functional connectivity of cortical responses of ASD and its potential application in diagnosis.

Wavelet coherence analysis of prefrontal oxygenation signals in elderly subjects with hypertension

This study aims to assess the prefrontal functional connectivity in elderly subjects with hypertension during the resting state using wavelet coherence analysis of changes in prefrontal tissue oxyhaemoglobin concentrations (Δ[HbO2]) signals measured by near-infrared spectroscopy (NIRS). Continuous recordings of NIRS signals were obtained from the left and right prefrontal lobes in 24 elderly subjects with hypertension (age: 70.7 ± 8.4 years) and 26 elderly normotensive subjects (age: 70.6 ± 7.9 years) during the resting state. The coherence between the left and right prefrontal oscillations in four frequency intervals (I, 0.4 Hz to 2 Hz; II, 0.15 Hz to 0.4 Hz; III, 0.05 Hz to 0.15 Hz; and IV, 0.02 Hz to 0.05 Hz) was analyzed using wavelet coherence method. The Δ[HbO2] oscillations showed significant wavelet coherence (WCO) in intervals I and III, and significant wavelet phase coherence (WPCO) in intervals from I to IV. Remarkably, in elderly subjects with hypertension, the WCO and WPCO in interval III were significantly lower in the left and right prefrontal regions than in healthy elderly subjects (p = 0.014 for WCO, p = 0.007 for WPCO). The lower coherence in interval III indicates a decreased synchronization of neural control in the left and right prefrontal regions in elderly subjects with hypertension. This might suggest a weakened brain functional connectivity in the elderly subjects with hypertension.

Sensitivity of fNIRS to cognitive state and load

Functional near-infrared spectroscopy (fNIRS) is an emerging low-cost noninvasive neuroimaging technique that measures cortical bloodflow. While fNIRS has gained interest as a potential alternative to fMRI for use with clinical and pediatric populations, it remains unclear whether fNIRS has the necessary sensitivity to serve as a replacement for fMRI. The present study set out to examine whether fNIRS has the sensitivity to detect linear changes in activation and functional connectivity in response to cognitive load, and functional connectivity changes when transitioning from a task-free resting state to a task. Sixteen young adult subjects were scanned with a continuous-wave fNIRS system during a 10-min resting-state scan followed by a letter n-back task with three load conditions. Five optical probes were placed over frontal and parietal cortices, covering bilateral dorsolateral PFC (dlPFC), bilateral ventrolateral PFC (vlPFC), frontopolar cortex (FP), and bilateral parietal cortex. Activation was found to scale linearly with working memory load in bilateral prefrontal cortex. Functional connectivity increased with increasing n-back loads for fronto-parietal, interhemispheric dlPFC, and local connections. Functional connectivity differed between the resting state scan and the n-back scan, with fronto-parietal connectivity greater during the n-back, and interhemispheric vlPFC connectivity greater during rest. These results demonstrate that fNIRS is sensitive to both cognitive load and state, suggesting that fNIRS is well-suited to explore the full complement of neuroimaging research questions and will serve as a viable alternative to fMRI.

Temporal correlation of spontaneous hemodynamic activity in language areas measured with functional near-infrared spectroscopy

Functional near-infrared spectroscopy (fNIRS) was used to investigate resting state connectivity of language areas including bilateral inferior frontal gyrus (IFG) and superior temporal gyrus (STG). Thirty-two subjects participated in the experiment, including twenty adults and twelve children. Spontaneous hemodynamic fluctuations were recorded, and then intra- and inter-hemispheric temporal correlations of these signals were computed. The correlations of all hemoglobin components were observed significantly higher for adults than children. Moreover, the differences for the STG were more significant than for the IFG. In the adult group, differences in the correlations between males and females were not significant. Our results suggest by measuring resting state intra- and inter-hemispheric correlations, fNIRS is able to provide qualitative and quantitative evaluation on the functioning of the cortical network.

Analyzing the resting state functional connectivity in the human language system using near infrared spectroscopy

We have evaluated the use of phase synchronization to identify resting state functional connectivity (RSFC) in the language system in infants using functional near infrared spectroscopy (fNIRS). We used joint probability distribution of phase between fNIRS channels with a seed channel in the language area to estimate phase relations and to identify the language system network. Our results indicate the feasibility of this method in identifying the language system. The connectivity maps are consistent with anatomical cortical connections and are also comparable to those obtained from functional magnetic resonance imaging (fMRI) functional connectivity studies. The results also indicate left hemisphere lateralization of the language network.

Coherent slow cortical potentials reveal a superior localization of resting-state functional connectivity using voltage-sensitive dye imaging

The resting-state functional connectivity (RSFC) of spontaneous hemodynamic fluctuations is widely used to investigate large-scale functional brain networks based on neurovascular mechanisms. However, high-resolution RSFC networks based on neural activity have not been disclosed to explore the neural basis of these spontaneous hemodynamic signals. The present study examines the neural RSFC networks in mice at high spatial resolution using optical imaging with voltage-sensitive dyes (VSDs). Our results show that neural RSFC networks for the slow cortical potentials (0.1-4Hz) showed similar correlation patterns to the RSFC networks for the spontaneous hemodynamic signals, indicating a tight coupling between the slow cortical potential and the spontaneous hemodynamic signals during rest, but the bilateral symmetry of the RSFC networks for the slow cortical potentials was significantly lower than that for the spontaneous hemodynamic signals. Moreover, similar asymmetric neural activation patterns could also be found between the bilateral cortexes after stimulating the paws of mice. By increasing anesthetic levels to induce the reduction of consciousness, the RSFC networks for the slow cortical potentials persisted, but those for the spontaneous hemodynamic signals became discrete. These results suggest that the coherent slow cortical potentials underlie the spontaneous hemodynamic fluctuations and reveal a superior localization of RSFC networks. VSD imaging may potentially be used to examine the RSFC of neural activity, particularly under conditions of impaired neurovascular coupling.

Resting-State Functional Brain Connectivity

Resting-state functional near-infrared spectroscopy (R-fNIRS) is an active area of interest and is currently attracting considerable attention as a new imaging tool for the study of resting-state brain function. Using variations in hemodynamic concentration signals, R-fNIRS measures the brain’s low-frequency spontaneous neural activity, combining the advantages of portability, low-cost, high temporal sampling rate and less physical burden to participants. The temporal synchronization of spontaneous neuronal activity in anatomically separated regions is referred to as resting-state functional connectivity (RSFC). In the past several years, an increasing body of R-fNIRS RSFC studies has led to many important findings about functional integration among local or whole-brain regions by measuring inter-regional temporal synchronization. Here, we summarize recent advances made in the R-fNIRS RSFC methodologies, from the detection of RSFC (e.g., seed-based correlation analysis, independent component analysis, whole-brain correlation analysis, and graph-theoretical topological analysis), to the assessment of RSFC performance (e.g., reliability, repeatability, and validity), to the application of RSFC in studying normal development and brain disorders. The literature reviewed here suggests that RSFC analyses based on R-fNIRS data are valid and reliable for the study of brain function in healthy and diseased populations, thus providing a promising imaging tool for cognitive science and clinics.

Test-retest reliability of graph metrics in functional brain networks: a resting-state fNIRS study

Recent research has demonstrated the feasibility of combining functional near-infrared spectroscopy (fNIRS) and graph theory approaches to explore the topological attributes of human brain networks. However, the test-retest (TRT) reliability of the application of graph metrics to these networks remains to be elucidated. Here, we used resting-state fNIRS and a graph-theoretical approach to systematically address TRT reliability as it applies to various features of human brain networks, including functional connectivity, global network metrics and regional nodal centrality metrics. Eighteen subjects participated in two resting-state fNIRS scan sessions held ∼20 min apart. Functional brain networks were constructed for each subject by computing temporal correlations on three types of hemoglobin concentration information (HbO, HbR, and HbT). This was followed by a graph-theoretical analysis, and then an intraclass correlation coefficient (ICC) was further applied to quantify the TRT reliability of each network metric. We observed that a large proportion of resting-state functional connections (∼90%) exhibited good reliability (0.6< ICC <0.74). For global and nodal measures, reliability was generally threshold-sensitive and varied among both network metrics and hemoglobin concentration signals. Specifically, the majority of global metrics exhibited fair to excellent reliability, with notably higher ICC values for the clustering coefficient (HbO: 0.76; HbR: 0.78; HbT: 0.53) and global efficiency (HbO: 0.76; HbR: 0.70; HbT: 0.78). Similarly, both nodal degree and efficiency measures also showed fair to excellent reliability across nodes (degree: 0.52∼0.84; efficiency: 0.50∼0.84); reliability was concordant across HbO, HbR and HbT and was significantly higher than that of nodal betweenness (0.28∼0.68). Together, our results suggest that most graph-theoretical network metrics derived from fNIRS are TRT reliable and can be used effectively for brain network research. This study also provides important guidance on the choice of network metrics of interest for future applied research in developmental and clinical neuroscience.

Molecular concentration of deoxyHb in human prefrontal cortex predicts the emergence and suppression of consciousness

This is the first study to use fNIRS to explore anaesthetic depth and awakening during surgery with general anaesthesia. A 16 channel continuous wave (CW) functional near-infrared system (fNIRS) was used to monitor PFC activity. These outcomes were compared to BIS measures. The results indicate that deoxyHb concentration in the PFC varies during the suppression and emergence of consciousness. During suppression, deoxyHb levels increase, signalling the deactivation of the PFC, while during emergence, deoxyHb concentration drops, initiating PFC activation and the recovery of consciousness. Furthermore, BIS and deoxyHb concentrations in the PFC display a high negative correlation throughout the different anaesthetic phases. These findings suggest that deoxyHb could be a reliable marker for monitoring anaesthetic depth, and that the PFC intervenes in the suppression and emergence of consciousness.

Does the resting state connectivity have hemispheric asymmetry? A near-infrared spectroscopy study

Near-infrared spectroscopy (NIRS) is a novel technology for low-cost noninvasive brain imaging suitable for use in virtually all subject and patient populations. Numerous studies of brain functional connectivity using fMRI, and recently NIRS, suggest new tools for the assessment of cognitive functions during task performance and the resting state (RS). We analyzed functional connectivity and its possible hemispheric asymmetry measuring coherence of optical signals at low frequencies (0.01-0.1 Hz) in the prefrontal cortex in 13 right-handed (RH) and 2 left-handed (LH) healthy subjects at rest (4-8 min) using a continuous-wave NIRS instrument CW5 (TechEn, Milford, MA). Two optical probes were placed bilaterally over the inferior frontal gyrus (IFG) and the middle frontal gyrus (MFG) using anatomical landmarks of the 10-20 system. As a result, 28 optical channels (14 for each hemisphere) were recorded for changes in oxygenated (HbO) and de-oxygenated (HbR) hemoglobin. Global physiological signals (respiratory and cardiac) were removed using Principal and Independent Component Analyses. Inter-channel coherences for HbO and HbR signals were calculated using Morlet wavelets along with correlation coefficients. Connectivity matrices showed specific patterns of connectivity which was higher within each anatomical region (IFG and MFG) and between hemispheres (e.g., left IFG<->right IFG) than between IFG and MFG in the same hemisphere. Laterality indexes were calculated as t-values for the 'left>right' comparisons of intrinsic connectivity within each regional group of channels in each subject. Regardless of handedness, the group average laterality indexes were negative thus revealing significantly higher connectivity in the right hemisphere in the majority of RH subjects and in both LH subjects. The analysis of Granger causality between hemispheres has also shown a greater flow of information from the right to the left hemisphere which may point to an important role of the right hemisphere in the resting state. These data encourage further exploration of the NIRS connectivity and its application for the analysis of hemispheric relationships within the functional architecture of the brain.

Dynamic model for the tissue concentration and oxygen saturation of hemoglobin in relation to blood volume, flow velocity, and oxygen consumption: Implications for functional neuroimaging and coherent hemodynamics spectroscopy (CHS)

This article presents a dynamic model that quantifies the temporal evolution of the concentration and oxygen saturation of hemoglobin in tissue, as determined by time-varying hemodynamic and metabolic parameters: blood volume, flow velocity, and oxygen consumption. This multi-compartment model determines separate contributions from arterioles, capillaries, and venules that comprise the tissue microvasculature, and treats them as a complete network, without making assumptions on the details of the architecture and morphology of the microvascular bed. A key parameter in the model is the effective blood transit time through the capillaries and its associated probability of oxygen release from hemoglobin to tissue, as described by a rate constant for oxygen diffusion. The solution of the model in the time domain predicts the signals measured by hemodynamic-based neuroimaging techniques such as functional near-infrared spectroscopy (fNIRS) and functional magnetic resonance imaging (fMRI) in response to brain activation. In the frequency domain, the model yields an analytical solution based on a phasor representation that provides a framework for quantitative spectroscopy of coherent hemodynamic oscillations. I term this novel technique coherent hemodynamics spectroscopy (CHS), and this article describes how it can be used for the assessment of cerebral autoregulation and the study of hemodynamic oscillations resulting from a variety of periodic physiological challenges, brain activation protocols, or physical maneuvers.

Evaluating the effects of systemic low frequency oscillations measured in the periphery on the independent component analysis results of resting state networks

Independent component analysis (ICA) is widely used in resting state functional connectivity studies. ICA is a data-driven method, which uses no a priori anatomical or functional assumptions. However, as a result, it still relies on the user to distinguish the independent components (ICs) corresponding to neuronal activation, peripherally originating signals (without directly attributable neuronal origin, such as respiration, cardiac pulsation and Mayer wave), and acquisition artifacts. In this concurrent near infrared spectroscopy (NIRS)/functional MRI (fMRI) resting state study, we developed a method to systematically and quantitatively identify the ICs that show strong contributions from signals originating in the periphery. We applied group ICA (MELODIC from FSL) to the resting state data of 10 healthy participants. The systemic low frequency oscillation (LFO) detected simultaneously at each participant's fingertip by NIRS was used as a regressor to correlate with every subject-specific IC time course. The ICs that had high correlation with the systemic LFO were those closely associated with previously described sensorimotor, visual, and auditory networks. The ICs associated with the default mode and frontoparietal networks were less affected by the peripheral signals. The consistency and reproducibility of the results were evaluated using bootstrapping. This result demonstrates that systemic, low frequency oscillations in hemodynamic properties overlay the time courses of many spatial patterns identified in ICA analyses, which complicates the detection and interpretation of connectivity in these regions of the brain.

Neural synchronization during face-to-face communication

Although the human brain may have evolutionarily adapted to face-to-face communication, other modes of communication, e.g., telephone and e-mail, increasingly dominate our modern daily life. This study examined the neural difference between face-to-face communication and other types of communication by simultaneously measuring two brains using a hyperscanning approach. The results showed a significant increase in the neural synchronization in the left inferior frontal cortex during a face-to-face dialog between partners but none during a back-to-back dialog, a face-to-face monologue, or a back-to-back monologue. Moreover, the neural synchronization between partners during the face-to-face dialog resulted primarily from the direct interactions between the partners, including multimodal sensory information integration and turn-taking behavior. The communicating behavior during the face-to-face dialog could be predicted accurately based on the neural synchronization level. These results suggest that face-to-face communication, particularly dialog, has special neural features that other types of communication do not have and that the neural synchronization between partners may underlie successful face-to-face communication.

Determination of dominant frequency of resting-state brain interaction within one functional system

Accumulating evidence has revealed that the resting-state functional connectivity (RSFC) is frequency specific and functional system dependent. Determination of dominant frequency of RSFC (RSFC(df)) within a functional system, therefore, is of importance for further understanding the brain interaction and accurately assessing the RSFC within the system. Given the unique advantages over other imaging techniques, functional near-infrared spectroscopy (fNIRS) holds distinct merits for RSFC(df) determination. However, an obstacle that hinders fNIRS from potential RSFC(df) investigation is the interference of various global noises in fNIRS data which could bring spurious connectivity at the frequencies unrelated to spontaneous neural activity. In this study, we first quantitatively evaluated the interferences of multiple systemic physiological noises and the motion artifact by using simulated data. We then proposed a functional system dependent and frequency specific analysis method to solve the problem by introducing anatomical priori information on the functional system of interest. Both the simulated and real resting-state fNIRS experiments showed that the proposed method outperforms the traditional one by effectively eliminating the negative effects of the global noises and significantly improving the accuracy of the RSFC(df) estimation. The present study thus provides an effective approach to RSFC(df) determination for its further potential applications in basic and clinical neurosciences.

Capturing dynamic patterns of task-based functional connectivity with EEG

A new approach to trace the dynamic patterns of task-based functional connectivity, by combining signal segmentation, dynamic time warping (DTW), and Quality Threshold (QT) clustering techniques, is presented. Electroencephalography (EEG) signals of 5 healthy subjects were recorded as they performed an auditory oddball and a visual modified oddball tasks. To capture the dynamic patterns of functional connectivity during the execution of each task, EEG signals are segmented into durations that correspond to the temporal windows of previously well-studied event-related potentials (ERPs). For each temporal window, DTW is employed to measure the functional similarities among channels. Unlike commonly used temporal similarity measures, such as cross correlation, DTW compares time series by taking into consideration that their alignment properties may vary in time. QT clustering analysis is then used to automatically identify the functionally connected regions in each temporal window. For each task, the proposed approach was able to establish a unique sequence of dynamic pattern (observed in all 5 subjects) for brain functional connectivity.

Revealing topological organization of human brain functional networks with resting-state functional near infrared spectroscopy

BACKGROUND

The human brain is a highly complex system that can be represented as a structurally interconnected and functionally synchronized network, which assures both the segregation and integration of information processing. Recent studies have demonstrated that a variety of neuroimaging and neurophysiological techniques such as functional magnetic resonance imaging (MRI), diffusion MRI and electroencephalography/magnetoencephalography can be employed to explore the topological organization of human brain networks. However, little is known about whether functional near infrared spectroscopy (fNIRS), a relatively new optical imaging technology, can be used to map functional connectome of the human brain and reveal meaningful and reproducible topological characteristics.

RESULTS

We utilized resting-state fNIRS (R-fNIRS) to investigate the topological organization of human brain functional networks in 15 healthy adults. Brain networks were constructed by thresholding the temporal correlation matrices of 46 channels and analyzed using graph-theory approaches. We found that the functional brain network derived from R-fNIRS data had efficient small-world properties, significant hierarchical modular structure and highly connected hubs. These results were highly reproducible both across participants and over time and were consistent with previous findings based on other functional imaging techniques.

CONCLUSIONS

Our results confirmed the feasibility and validity of using graph-theory approaches in conjunction with optical imaging techniques to explore the topological organization of human brain networks. These results may expand a methodological framework for utilizing fNIRS to study functional network changes that occur in association with development, aging and neurological and psychiatric disorders.

Altered resting-state functional connectivity after cortical spreading depression in mice

Cortical spreading depression (CSD) underlies some neurological disorders. Previous imaging work suggests that CSD is associated with functional and structural alterations in the cerebral cortex. However, the changes in cortical functional network following CSD are poorly understood. The present study examines the changes in resting-state function connectivity (RSFC) of the mouse sensorimotor cortex after the onset of CSD by using optical intrinsic signal imaging. Our results show that RSFC between ipsilateral sensorimotor cortex (the cortex where CSD spreads) and contralateral sensorimotor cortex (the cortex where CSD does not spread) was significantly reduced after CSD. Moreover, a marked connectivity increase was found after CSD not only within contralateral somatosensory cortex and contralateral motor cortex themselves, but also between contralateral somatosensory cortex and contralateral motor cortex. Amplitude of low-frequency fluctuation (ALFF) analysis revealed an increase in ALFF in the ipsilateral cortex but a decrease in the contralateral cortex after CSD, indicating different effects of CSD on the neural activity in the ipsilateral and contralateral sensorimotor cortexes. These results suggest that CSD would alter the RSFC in the sensorimotor cortexes, and functional connectivity analysis may help to understand the effect of CSD on the cerebral functional network.

Phase-amplitude investigation of spontaneous low-frequency oscillations of cerebral hemodynamics with near-infrared spectroscopy: a sleep study in human subjects

We have investigated the amplitude and phase of spontaneous low-frequency oscillations (LFOs) of the cerebral deoxy- and oxy-hemoglobin concentrations ([Hb] and [HbO]) in a human sleep study using near-infrared spectroscopy (NIRS). Amplitude and phase analysis was based on the analytic signal method, and phasor algebra was used to decompose measured [Hb] and [HbO] oscillations into cerebral blood volume (CBV) and flow velocity (CBFV) oscillations. We have found a greater phase lead of [Hb] vs. [HbO] LFOs during non-REM sleep with respect to the awake and REM sleep states (maximum increase in [Hb] phase lead: ~π/2). Furthermore, during non-REM sleep, the amplitudes of [Hb] and [HbO] LFOs are suppressed with respect to the awake and REM sleep states (maximum amplitude decrease: 87%). The associated cerebral blood volume and flow velocity oscillations are found to maintain their relative phase difference during sleep, whereas their amplitudes are attenuated during non-REM sleep. These results show the potential of phase-amplitude analysis of [Hb] and [HbO] oscillations measured by NIRS in the investigation of hemodynamics associated with cerebral physiology, activation, and pathological conditions.

A NIRS-fMRI study of resting state network

Resting state functional connectivity, which is defined as temporal correlation of spontaneous activity between diverse brain regions, has been reported to form resting state networks (RSNs), consisting of a specific set of brain regions, based on functional magnetic resonance imaging (fMRI). Recently, studies using near-infrared spectroscopy (NIRS) reported that NIRS signals also show temporal correlation between different brain regions. The local relationship between NIRS and fMRI signals has been examined by simultaneously recording these signals when participants perform tasks or respond to stimuli. However, the NIRS-fMRI signal relationship during the resting state has been reported only between NIRS signals obtained within limited regions and whole brain fMRI signals. Therefore, it remains unclear whether NIRS signals obtained at diverse regions correlate with regional fMRI signals close to the NIRS measurement channels, especially in relation to the RSNs. In this study, we tested whether the signals measured by these different modalities during the resting state have the consistent characteristics of the RSNs. Specifically, NIRS signals during the resting state were acquired over the frontal, temporal, and occipital cortices while whole brain fMRI data was simultaneously recorded. First, by projecting the NIRS channel positions over the cerebral cortical surface, we identified the most likely anatomical locations of all NIRS channels used in the study. Next, to investigate the regional signal relationship between NIRS and fMRI, we calculated the cross-correlation between NIRS signals and fMRI signals in the brain regions adjacent to each NIRS channel. For each NIRS channel, we observed the local maxima of correlation coefficients between NIRS and fMRI signals within a radius of 2 voxels from the projection point. Furthermore, we also found that highly correlated voxels with the NIRS signal were mainly localized within brain tissues for all NIRS channels, with the exception of 2 frontal channels. Finally, by calculating the correlation between NIRS signals at a channel and whole brain fMRI signals, we observed that NIRS signals correlate with fMRI signals not only within brain regions adjacent to NIRS channels but also within distant brain regions constituting RSNs, such as the dorsal attention, fronto-parietal control, and default mode networks. These results support the idea that NIRS signals obtained at several cortical regions during the resting state mainly reflect regional spontaneous hemodynamic fluctuations that originate from spontaneous cortical activity, and include information that characterizes the RSNs. Because NIRS is relatively easy to use and a less physically demanding neuroimaging technique, our findings should facilitate a broad application of this technique to examine RSNs, especially for clinical populations and conditions unsuitable for fMRI.

A brief review on the use of functional near-infrared spectroscopy (fNIRS) for language imaging studies in human newborns and adults

Upon stimulation, real time maps of cortical hemodynamic responses can be obtained by non-invasive functional near-infrared spectroscopy (fNIRS) which measures changes in oxygenated and deoxygenated hemoglobin after positioning multiple sources and detectors over the human scalp. The current commercially available transportable fNIRS systems have a time resolution of 1-10 Hz, a depth sensitivity of about 1.5 cm, and a spatial resolution of about 1cm. The goal of this brief review is to report infants, children and adults fNIRS language studies. Since 1998, 60 studies have been published on cortical activation in the brain's classic language areas in children/adults as well as newborns using fNIRS instrumentations of different complexity. In addition, the basic principles of fNIRS including features, strengths, advantages, and limitations are summarized in terms that can be understood even by non specialists. Future prospects of fNIRS in the field of language processing imaging are highlighted.

Usefulness of simultaneous EEG-NIRS recording in language studies

One of the most challenging tasks in neuroscience in language studies, is investigation of the brain's ability to integrate and process information. This task can only be successfully addressed by applying various assessment techniques integrated into a multimodal approach. Each of these techniques has its advantages and disadvantages, but help to elucidate certain aspects of the capacity of neural networks to process information. These methods provide information about changes in electrical, hemodynamic and metabolic activities. Ideally, they should be noninvasive in order to facilitate their use particularly in children. In the present review, we describe the advantages of simultaneous electroencephalographic (EEG) acquisition with near infrared spectroscopy (NIRS) to provide a better understanding of the mechanisms involved in cerebral activation. This coregistration is also useful to avoid misleading interpretation of NIRS, notably during the various phases of sleep. Development and implementation of the various tools required and assessment strategies are also discussed.

Spatiotemporal properties of cortical haemodynamic response to auditory stimuli in sleeping infants revealed by multi-channel near-infrared spectroscopy

Multi-channel near-infrared spectroscopy (NIRS) has been used as a neuroimaging tool to study functional activation of the developing brain in infants. In this paper, we focus on spatiotemporal dynamics of cortical oxygenation changes during sensory processing in young infants. We use a 94-channel NIRS system to assess the activity of wide regions of the cortex in quietly sleeping three-month-old infants. Auditory stimuli composed of a random sequence of pure tones induced haemodynamic changes not only in the temporal auditory regions, but also in the occipital and frontal regions. Analyses of phase synchronization showed that mutual synchronizations of signal changes among the cortical regions were much stronger than the stimulus-induced synchronizations of signal changes. Furthermore, analyses of phase differences among cortical regions revealed phase advancement of the bilateral temporal auditory regions, and phase gradient in a posterior direction from the temporal auditory regions to the occipital regions and in an anterior direction within the frontal regions. We argue that multi-channel NIRS is capable of detecting the precise timing of cortical activation and its flow in the global network of the developing brain.

NIRS-based hyperscanning reveals increased interpersonal coherence in superior frontal cortex during cooperation

We used Near-Infrared Spectroscopy (NIRS) to simultaneously measure brain activity in two people while they played a computer-based cooperation game side by side. Inter-brain activity coherence was calculated between the two participants. We found that the coherence between signals generated by participants' right superior frontal cortices increased during cooperation, but not during competition. Increased coherence was also associated with better cooperation performance. To our knowledge, this work represents the first use of a single NIRS instrument for simultaneous measurements of brain activity in two people. This study demonstrates the use of NIRS-based hyperscanning in studies of social interaction in a naturalistic environment.

Bedside optical imaging of occipital resting-state functional connectivity in neonates

Resting-state networks derived from temporal correlations of spontaneous hemodynamic fluctuations have been extensively used to elucidate the functional organization of the brain in adults and infants. We have previously developed functional connectivity diffuse optical tomography methods in adults, and we now apply these techniques to study functional connectivity in newborn infants at the bedside. We present functional connectivity maps in the occipital cortices obtained from healthy term-born infants and premature infants, including one infant with an occipital stroke. Our results suggest that functional connectivity diffuse optical tomography has potential as a valuable clinical tool for the early detection of functional deficits and for providing prognostic information on future development.

Correlation of functional and resting state connectivity of cerebral oxy-, deoxy-, and total hemoglobin concentration changes measured by near-infrared spectrophotometry

The aim is to study cerebral vascular functional connectivity during motor tasks and resting state using multichannel frequency-domain near-infrared spectrophotometry. Maps of 5.7 × 10.8 cm size displaying changes in cerebral oxyhemoglobin (O(2)Hb), deoxyhemoglobin (HHb), and total hemoglobin (tHb) concentrations were measured in the motor cortex in 12 subjects (mean age of 28.8±12.7 yrs) during resting state and during two palm squeezing tasks with different timing. For each condition, phase plane plots, cross correlation functions, and connectivity indices were generated for O(2)Hb, HHb, and tHb. The amplitude of the concentration changes in O(2)Hb and HHb depends on the age of the subject. We found large regions of connectivity, which were similar for resting state and task conditions. This means the spatial relationships during resting state, when changes in O(2)Hb, HHb, and tHb corresponded to spontaneous oscillations, were correlated to the spatial patterns during the activation tasks, when changes in O(2)Hb, HHb, and tHb concentration were related to the alternation of stimulation and rest. Thus, the vascular functional connectivity was also present during resting state. The findings suggest that the vascular response to functional activation may be a nonlinear synchronization phenomenon and that resting state processes are more important than previously expected.

Is resting-state functional connectivity revealed by functional near-infrared spectroscopy test-retest reliable?

Recently, resting-state functional near-infrared spectroscopy (rs-fNIRS) research has experienced tremendous progress. Resting-state functional connectivity (RSFC) has been adopted as a pivotal biomarker in rs-fNIRS studies. However, it is yet to be clear if the RSFC derived from rs-fNIRS is reliable. This concern impedes extensive utilization of rs-fNIRS. We systematically address the issue of reliability. Sixteen subjects participate in two rs-fNIRS sessions held one week apart. RSFC in sensorimotor system is calculated using the seed-correlation approach. Then, test-retest reliability is evaluated at three different scales (map-, cluster-, and channelwise) for individual- and group-level RSFC derived from different types of fNIRS signals [oxygenated (HbO), deoxygenated (HbR), and total hemoglobin (HbT)]. The results show that, for HbO signals, individual-level RSFC generally has good-to-excellent map-/clusterwise reliability, while group-level RSFC has excellent reliability. For HbT signals, the results are similar. For HbR signals, the clusterwise reliability is comparable to that for HbO while the mapwise reliability is slightly lower (fair to good). Focusing on RSFC at a single channel, we report poor channelwise reliability for all three types of signals. We hereby propose that fNIRS-derived RSFC is a reliable biomarker if interpreted in map- and clusterwise manners. However, channelwise interpretation of individual RSFC should proceed with caution.

Resting-state functional connectivity assessed with two diffuse optical tomographic systems

Functional near-infrared spectroscopy (fNIRS) is recently utilized as a new approach to assess resting-state functional connectivity (RSFC) in the human brain. For any new technique or new methodology, it is necessary to be able to replicate similar experiments using different instruments in order to establish its liability and reproducibility. We apply two different diffuse optical tomographic (DOT) systems (i.e., DYNOT and CW5), with various probe arrangements to evaluate RSFC in the sensorimotor cortex by utilizing a previously published experimental protocol and seed-based correlation analysis. Our results exhibit similar spatial patterns and strengths in RSFC between the bilateral motor cortexes. The consistent observations are obtained from both DYNOT and CW5 systems, and are also in good agreement with the previous fNIRS study. Overall, we demonstrate that the fNIRS-based RSFC is reproducible by various DOT imaging systems among different research groups, enhancing the confidence of neuroscience researchers and clinicians to utilize fNIRS for future applications.

Frequency-specific functional connectivity in the brain during resting state revealed by NIRS

Analyses of spontaneous hemodynamic fluctuations observed on functional magnetic resonance imaging (fMRI) have revealed the existence of temporal correlations in signal changes between widely separated brain regions during the resting state, termed "resting state functional connectivity." Recent studies have demonstrated that these correlations are also present in the hemodynamic signals measured by near infrared spectroscopy (NIRS). However, it is still uncertain whether frequency-specific characteristics exist in these signals. In the present study, we used multichannel NIRS to investigate the frequency dependency of functional connectivity between diverse regions in the cerebral cortex by decomposing fluctuations of oxygenated hemoglobin (oxy-Hb) and deoxygenated hemoglobin (deoxy-Hb) signals into various frequency bands. First, within a wide frequency range (0.009-0.1Hz), we observed that both oxy-Hb and deoxy-Hb signals showed functional connectivity within local regions and between contralateral hemispheric regions of the cortex. Next, by decomposing measured fluctuations into narrower frequency components, we determined that only oxy-Hb signals showed frequency-specific functional connectivity between the frontal and occipital regions, emerging in a narrow frequency range (0.04-0.1Hz). To clarify the coherency of functional connectivity, we calculated the average coherence values between selected channel pairs. This approach demonstrated that functional connectivity based on the oxy-Hb signals between homologous cortical regions of the contralateral hemisphere (homologous connectivity) showed high coherence over a wide frequency range (0.009-0.1Hz), whereas connectivity between the prefrontal and occipital regions (fronto-posterior connectivity) showed high coherence only within a specific narrow frequency range (0.04-0.1Hz). Our findings suggest that homologous connectivity may reflect synchronization of neural activation over a wide frequency range through direct neuroanatomical connections, whereas fronto-posterior connectivity as revealed by high coherence only within a specific narrow frequency range corresponding to the time scale of typical hemodynamic response to a single event may reflect synchronization of transient neural activation among distant cortical regions. The present study demonstrated that NIRS provides a powerful tool to elucidate network properties of the cortex during resting state.

Kalman estimator- and general linear model-based on-line brain activation mapping by near-infrared spectroscopy

BACKGROUND

Near-infrared spectroscopy (NIRS) is a non-invasive neuroimaging technique that recently has been developed to measure the changes of cerebral blood oxygenation associated with brain activities. To date, for functional brain mapping applications, there is no standard on-line method for analysing NIRS data.

METHODS

In this paper, a novel on-line NIRS data analysis framework taking advantages of both the general linear model (GLM) and the Kalman estimator is devised. The Kalman estimator is used to update the GLM coefficients recursively, and one critical coefficient regarding brain activities is then passed to a t-statistical test. The t-statistical test result is used to update a topographic brain activation map. Meanwhile, a set of high-pass filters is plugged into the GLM to prevent very low-frequency noises, and an autoregressive (AR) model is used to prevent the temporal correlation caused by physiological noises in NIRS time series. A set of data recorded in finger tapping experiments is studied using the proposed framework.

RESULTS

The obtained results suggest that the method can effectively track the task related brain activation areas, and prevent the noise distortion in the estimation while the experiment is running. Thereby, the potential of the proposed method for real-time NIRS-based brain imaging was demonstrated.

CONCLUSIONS

This paper presents a novel on-line approach for analysing NIRS data for functional brain mapping applications. This approach demonstrates the potential of a real-time-updating topographic brain activation map.

Quantification of functional near infrared spectroscopy to assess cortical reorganization in children with cerebral palsy

Cerebral palsy (CP) is the most common motor disorder in children. Currently available neuroimaging techniques require complete body confinement and steadiness and thus are extremely difficult for pediatric patients. Here, we report the use and quantification of functional near infrared spectroscopy (fNIRS) to investigate the functional reorganization of the sensorimotor cortex in children with hemiparetic CP. Ten of sixteen children with congenital hemiparesis were measured during finger tapping tasks and compared with eight of sixteen age-matched healthy children, with an overall measurement success rate of 60%. Spatiotemporal analysis was introduced to quantify the motor activation and brain laterality. Such a quantitative approach reveals a consistent, contralateral motor activation in healthy children at 7 years of age or older. In sharp contrast, children with congenital hemiparesis exhibit all three of contralateral, bilateral and ipsilateral motor activations, depending on specific ages of the pediatric subjects. This study clearly demonstrates the feasibility of fNIRS to be utilized for investigating cortical reorganization in children with CP or other cortical disorders.

A quantitative comparison of NIRS and fMRI across multiple cognitive tasks

Near infrared spectroscopy (NIRS) is an increasingly popular technology for studying brain function. NIRS presents several advantages relative to functional magnetic resonance imaging (fMRI), such as measurement of concentration changes in both oxygenated and deoxygenated hemoglobin, finer temporal resolution, and ease of administration, as well as disadvantages, most prominently inferior spatial resolution and decreased signal-to-noise ratio (SNR). While fMRI has become the gold standard for in vivo imaging of the human brain, in practice NIRS is a more convenient and less expensive technology than fMRI. It is therefore of interest to many researchers how NIRS compares to fMRI in studies of brain function. In the present study we scanned participants with simultaneous NIRS and fMRI on a battery of cognitive tasks, placing NIRS probes over both frontal and parietal brain regions. We performed detailed comparisons of the signals in both temporal and spatial domains. We found that NIRS signals have significantly weaker SNR, but are nonetheless often highly correlated with fMRI measurements. Both SNR and the distance between the scalp and the brain contributed to variability in the NIRS/fMRI correlations. In the spatial domain, we found that a photon path forming an ellipse between the NIRS emitter and detector correlated most strongly with the BOLD response. Taken together these findings suggest that, while NIRS can be an appropriate substitute for fMRI for studying brain activity related to cognitive tasks, care should be taken when designing studies with NIRS to ensure that: 1) the spatial resolution is adequate for answering the question of interest and 2) the design accounts for weaker SNR, especially in brain regions more distal from the scalp.

Pathophysiological interference with neurovascular coupling - when imaging based on hemoglobin might go blind

Assessing neuronal activity by non-invasive functional brain imaging techniques which are based on the hemodynamic response depends totally on the physiological cascade of metabolism and blood flow. At present, functional brain imaging with near infrared spectroscopy (NIRS) or BOLD-fMRI is widely used in cognitive neuroscience in healthy subjects where neurovascular coupling and cerebrovascular reactivity can be assumed to be intact. Local activation studies as well as studies investigating functional connectivity between brain regions of the resting brain provide a rapidly increasing body of knowledge on brain function in humans and animals. Furthermore, functional NIRS and MRI techniques are increasingly being used in patients with severe brain diseases and this use might gain more and more importance for establishing their use in the clinical routine. However, more and more experimental evidence shows that changes in baseline physiological parameters, pharmacological interventions, or disease-related vascular changes may significantly alter the normal response of blood flow and blood oxygenation and thus may lead to misinterpretation of neuronal activity. In this article we present examples of recent experimental findings on pathophysiological changes of neurovascular coupling parameters in animals and discuss their potential implications for functional imaging based on hemodynamic signals such as fNIRS or BOLD-fMRI. To enable correct interpretation of neuronal activity by vascular signals, future research needs to deepen our understanding of the basic mechanisms of neurovascular coupling and the specific characteristics of disturbed neurovascular coupling in the diseased brain.

Resting state functional connectivity of the whole head with near-infrared spectroscopy

Resting state connectivity aims to identify spontaneous cerebral hemodynamic fluctuations that reflect neuronal activity at rest. In this study, we investigated the spatial-temporal correlation of hemoglobin concentration signals over the whole head during the resting state. By choosing a source-detector pair as a seed, we calculated the correlation value between its time course and the time course of all other source-detector combinations, and projected them onto a topographic map. In all subjects, we found robust spatial interactions in agreement with previous fMRI and NIRS findings. Strong correlations between the two opposite hemispheres were seen for both sensorimotor and visual cortices. Correlations in the prefrontal cortex were more heterogeneous and dependent on the hemodynamic contrast. HbT provided robust, well defined maps, suggesting that this contrast may be used to better localize functional connectivity. The effects of global systemic physiology were also investigated, particularly low frequency blood pressure oscillations which give rise to broad regions of high correlation and mislead interpretation of the results. These results confirm the feasibility of using functional connectivity with optical methods during the resting state, and validate its use to investigate cortical interactions across the whole head.

Detecting resting-state functional connectivity in the language system using functional near-infrared spectroscopy

Functional connectivity has become one of the important approaches to understanding the functional organization of the human brain. Recently, functional near-infrared spectroscopy (fNIRS) was demonstrated as a feasible method to study resting-state functional connectivity (RSFC) in the sensory and motor systems. However, whether such fNIRS-based RSFC can be revealed in high-level and complex functional systems remains unknown. In the present study, the feasibility of such an approach is tested on the language system, of which the neural substrates have been well documented in the literature. After determination of a seed channel by a language localizer task, the correlation strength between the low frequency fluctuations of the fNIRS signal at the seed channel and those at all other channels is used to evaluate the language system RSFC. Our results show a significant RSFC between the left inferior frontal cortex and superior temporal cortex, components both associated with dominant language regions. Moreover, the RSFC map demonstrates left lateralization of the language system. In conclusion, the present study successfully utilized fNIRS-based RSFC to study a complex and high-level neural system, and provides further evidence for the validity of the fNIRS-based RSFC approach.