HomER: a review of time-series analysis methods for near-infrared spectroscopy of the brain

Evoked hemodynamic response estimation using ensemble empirical mode decomposition based adaptive algorithm applied to dual channel functional near infrared spectroscopy (fNIRS)

BACKGROUND

The quality of the functional near infrared spectroscopy (fNIRS) recordings is highly degraded by the presence of physiological interferences. It is crucial to efficiently separate the evoked hemodynamic responses (EHRs) from other background hemodynamic activities prior to any further processing.

NEW METHOD

This paper presents a novel algorithm for physiological interferences reduction from the dual channel fNIRS measurements using ensemble empirical mode decomposition (EEMD) technique. The proposed algorithm is comprised of two main steps: (1) decomposing reference signal into its constituents called intrinsic mode functions (IMFs) and (2) adaptively defining appropriate weights of the corresponding IMFs to estimate the proportion of physiological interference in standard channel measurement.

RESULTS

Performance of the proposed algorithm was evaluated using both synthetic and semi-real brain hemodynamic data based on four parameters of relative mean squared error (rMSE), Pearson's correlation coefficient (R(2)), percentage estimation error of peak amplitude (EPA) and peak latency (EL).

COMPARISON WITH EXISTING METHODS

Results obtained from synthetic data revealed that both the EEMD based normalized least mean squares (EEMD-NLMS) and EEMD based recursive least squares (EEMD-RLS) methods could reduce the average rMSE by at least 34% and 49%, respectively, when compared with widely used methods: block averaging, band-pass filtering and principal and/or independent component analysis. Furthermore, the two proposed methods outperform the regression method in reducing rMSE by at least 21% and 35% respectively when applied to semi-real data.

CONCLUSIONS

An effective algorithm for estimating the EHRs from raw fNIRS data was proposed in which no assumption about the amplitude, shape and duration of the responses is considered.

Auditory cortex activation to natural speech and simulated cochlear implant speech measured with functional near-infrared spectroscopy

The primary goal of most cochlear implant procedures is to improve a patient's ability to discriminate speech. To accomplish this, cochlear implants are programmed so as to maximize speech understanding. However, programming a cochlear implant can be an iterative, labor-intensive process that takes place over months. In this study, we sought to determine whether functional near-infrared spectroscopy (fNIRS), a non-invasive neuroimaging method which is safe to use repeatedly and for extended periods of time, can provide an objective measure of whether a subject is hearing normal speech or distorted speech. We used a 140 channel fNIRS system to measure activation within the auditory cortex in 19 normal hearing subjects while they listed to speech with different levels of intelligibility. Custom software was developed to analyze the data and compute topographic maps from the measured changes in oxyhemoglobin and deoxyhemoglobin concentration. Normal speech reliably evoked the strongest responses within the auditory cortex. Distorted speech produced less region-specific cortical activation. Environmental sounds were used as a control, and they produced the least cortical activation. These data collected using fNIRS are consistent with the fMRI literature and thus demonstrate the feasibility of using this technique to objectively detect differences in cortical responses to speech of different intelligibility.

Monitoring attentional state with fNIRS

The ability to distinguish between high and low levels of task engagement in the real world is important for detecting and preventing performance decrements during safety-critical operational tasks. We therefore investigated whether functional Near Infrared Spectroscopy (fNIRS), a portable brain neuroimaging technique, can be used to distinguish between high and low levels of task engagement during the performance of a selective attention task. A group of participants performed the multi-source interference task (MSIT) while we recorded brain activity with fNIRS from two brain regions. One was a key region of the “task-positive” network, which is associated with relatively high levels of task engagement. The second was a key region of the “task-negative” network, which is associated with relatively low levels of task engagement (e.g., resting and not performing a task). Using activity in these regions as inputs to a multivariate pattern classifier, we were able to predict above chance levels whether participants were engaged in performing the MSIT or resting. We were also able to replicate prior findings from functional magnetic resonance imaging (fMRI) indicating that activity in task-positive and task-negative regions is negatively correlated during task performance. Finally, data from a companion fMRI study verified our assumptions about the sources of brain activity in the fNIRS experiment and established an upper bound on classification accuracy in our task. Together, our findings suggest that fNIRS could prove quite useful for monitoring cognitive state in real-world settings.

Functional near-infrared spectroscopy maps cortical plasticity underlying altered motor performance induced by transcranial direct current stimulation

Transcranial direct current stimulation (tDCS) of the human sensorimotor cortex during physical rehabilitation induces plasticity in the injured brain that improves motor performance. Bi-hemispheric tDCS is a noninvasive technique that modulates cortical activation by delivering weak current through a pair of anodal-cathodal (excitation-suppression) electrodes, placed on the scalp and centered over the primary motor cortex of each hemisphere. To quantify tDCS-induced plasticity during motor performance, sensorimotor cortical activity was mapped during an event-related, wrist flexion task by functional near-infrared spectroscopy (fNIRS) before, during, and after applying both possible bi-hemispheric tDCS montages in eight healthy adults. Additionally, torque applied to a lever device during isometric wrist flexion and surface electromyography measurements of major muscle group activity in both arms were acquired concurrently with fNIRS. This multiparameter approach found that hemispheric suppression contralateral to wrist flexion changed resting-state connectivity from intra-hemispheric to inter-hemispheric and increased flexion speed (p<0.05). Conversely, exciting this hemisphere increased opposing muscle output resulting in a decrease in speed but an increase in accuracy (p<0.05 for both). The findings of this work suggest that tDCS with fNIRS and concurrent multimotor measurements can provide insights into how neuroplasticity changes muscle output, which could find future use in guiding motor rehabilitation.

Fusion of fNIRS and fMRI data: identifying when and where hemodynamic signals are changing in human brains

In this study we implemented a new imaging method to fuse functional near infrared spectroscopy (fNIRS) measurements and functional magnetic resonance imaging (fMRI) data to reveal the spatiotemporal dynamics of the hemodynamic responses with high spatiotemporal resolution across the brain. We evaluated this method using multimodal data acquired from human right finger tapping tasks. And we found the proposed method is able to clearly identify from the linked components of fMRI and fNIRS where and when the hemodynamic signals are changing. In particular, the estimated associations between fNIRS and fMRI will be displayed as time varying spatial fMRI maps along with the fNIRS time courses. In addition, the joint components between fMRI and fNIRS are combined together to generate full spatiotemporal “snapshots” and movies, which provides an excellent way to examine the dynamic interplay between hemodynamic fNIRS and fMRI measurements.

Effects of krill oil containing n-3 polyunsaturated fatty acids in phospholipid form on human brain function: a randomized controlled trial in healthy elderly volunteers

Background

Krill oil, rich in n-3 (omega-3) polyunsaturated fatty acids (PUFAs) incorporated in phosphatidylcholine, has been reported to have many effects on physiological function. However, there are few studies using psychophysiological methods published that describe the effects of krill oil on brain function. We investigated the influence of ingestion of krill oil on cognitive function in elderly subjects by using near-infrared spectroscopy and electroencephalography.

Methods

A randomized, double-blind, parallel-group comparative study design was adopted. Forty-five healthy elderly males aged 61–72 years were assigned to receive 12 weeks of treatment with: medium-chain triglycerides as placebo; krill oil, which is rich in n-3 PUFAs incorporated in phosphatidylcholine; or sardine oil, which is abundant in n-3 PUFAs incorporated in triglycerides. Changes in oxyhemoglobin concentrations in the cerebral cortex during memory and calculation tasks were measured. The P300 component of event-related potentials was also measured during a working memory task.

Results

During the working memory task, changes in oxyhemoglobin concentrations in the krill oil and sardine oil groups were significantly greater than those in the medium-chain triglyceride group at week 12. The differential value for P300 latency in the krill oil group was significantly lower than that in the medium-chain triglyceride group at week 12. With regard to the calculation task, changes in oxyhemoglobin concentrations in the krill oil group were significantly greater than those in the medium-chain triglyceride group at week 12.

Conclusion

This study provides evidence that n-3 PUFAs activate cognitive function in the elderly. This is especially the case with krill oil, in which the majority of n-3 PUFAs are incorporated into phosphatidylcholine, causing it to be more effective than sardine oil, in which n-3 PUFAs are present as triglycerides.

Spatial registration for functional near-infrared spectroscopy: from channel position on the scalp to cortical location in individual and group analyses

Functional near-infrared spectroscopy (fNIRS) has now become widely accepted as a common functional imaging modality. In order for fNIRS to achieve genuine neuroimaging citizenship, it would ideally be equipped with functional and structural image analyses. However, fNIRS measures cortical activities from the head surface without anatomical information of the object being measured. In this review article, we will present a methodological overview of spatial registration of fNIRS data to overcome this technical drawback of fNIRS. We first introduce and explore the use of standard stereotaxic space and anatomical labeling. Second, we explain different ways of describing scalp landmarks using 10-20 based systems. Third, we describe the simplest case of fNIRS data co-registration to a subject's own MRI. Fourth, we extend the concept to fNIRS data registration of group data. Fifth, we describe probabilistic registration methods, which use a reference-MRI database instead of a subject's own MRIs, and thus enable MRI-free registration for standalone fNIRS data. Sixth, we further extend the concept of probabilistic registration to three-dimensional image reconstruction in diffuse optical tomography. Seventh, we describe a 3D-digitizer-free method for the virtual registration of fNIRS data. Eighth, we provide practical guidance on how these techniques are implemented in software. Finally, we provide information on current resources and limitations for spatial registration of child and infant data. Through these technical descriptions, we stress the importance of presenting fNIRS data on a common platform to facilitate both intra- and inter-modal data sharing among the neuroimaging community.

Reducing motion artifacts for long-term clinical NIRS monitoring using collodion-fixed prism-based optical fibers

As the applications of near-infrared spectroscopy (NIRS) continue to broaden and long-term clinical monitoring becomes more common, minimizing signal artifacts due to patient movement becomes more pressing. This is particularly true in applications where clinically and physiologically interesting events are intrinsically linked to patient movement, as is the case in the study of epileptic seizures. In this study, we apply an approach common in the application of EEG electrodes to the application of specialized NIRS optical fibers. The method provides improved optode-scalp coupling through the use of miniaturized optical fiber tips fixed to the scalp using collodion, a clinical adhesive. We investigate and quantify the performance of this new method in minimizing motion artifacts in healthy subjects, and apply the technique to allow continuous NIRS monitoring throughout epileptic seizures in two epileptic in-patients. Using collodion-fixed fibers reduces the percent signal change of motion artifacts by 90% and increases the SNR by 6 and 3 fold at 690 and 830 nm wavelengths respectively when compared to a standard Velcro-based array of optical fibers. The SNR has also increased by 2 fold during rest conditions without motion with the new probe design because of better light coupling between the fiber and scalp. The change in both HbO and HbR during motion artifacts is found to be statistically lower for the collodion-fixed fiber probe. The collodion-fixed optical fiber approach has also allowed us to obtain good quality NIRS recording of three epileptic seizures in two patients despite excessive motion in each case.

Continuous correction of differential path length factor in near-infrared spectroscopy

In continuous-wave near-infrared spectroscopy (CW-NIRS), changes in the concentration of oxyhemoglobin and deoxyhemoglobin can be calculated by solving a set of linear equations from the modified Beer-Lambert Law. Cross-talk error in the calculated hemodynamics can arise from inaccurate knowledge of the wavelength-dependent differential path length factor (DPF). We apply the extended Kalman filter (EKF) with a dynamical systems model to calculate relative concentration changes in oxy- and deoxyhemoglobin while simultaneously estimating relative changes in DPF. Results from simulated and experimental CW-NIRS data are compared with results from a weighted least squares (WLSQ) method. The EKF method was found to effectively correct for artificially introduced errors in DPF and to reduce the cross-talk error in simulation. With experimental CW-NIRS data, the hemodynamic estimates from EKF differ significantly from the WLSQ (p < 0.001). The cross-correlations among residuals at different wavelengths were found to be significantly reduced by the EKF method compared to WLSQ in three physiologically relevant spectral bands 0.04 to 0.15 Hz, 0.15 to 0.4 Hz and 0.4 to 2.0 Hz (p < 0.001). This observed reduction in residual cross-correlation is consistent with reduced cross-talk error in the hemodynamic estimates from the proposed EKF method.

Motion artifacts in functional near-infrared spectroscopy: a comparison of motion correction techniques applied to real cognitive data

Motion artifacts are a significant source of noise in many functional near-infrared spectroscopy (fNIRS) experiments. Despite this, there is no well-established method for their removal. Instead, functional trials of fNIRS data containing a motion artifact are often rejected completely. However, in most experimental circumstances the number of trials is limited, and multiple motion artifacts are common, particularly in challenging populations. Many methods have been proposed recently to correct for motion artifacts, including principle component analysis, spline interpolation, Kalman filtering, wavelet filtering and correlation-based signal improvement. The performance of different techniques has been often compared in simulations, but only rarely has it been assessed on real functional data. Here, we compare the performance of these motion correction techniques on real functional data acquired during a cognitive task, which required the participant to speak aloud, leading to a low-frequency, low-amplitude motion artifact that is correlated with the hemodynamic response. To compare the efficacy of these methods, objective metrics related to the physiology of the hemodynamic response have been derived. Our results show that it is always better to correct for motion artifacts than reject trials, and that wavelet filtering is the most effective approach to correcting this type of artifact, reducing the area under the curve where the artifact is present in 93% of the cases. Our results therefore support previous studies that have shown wavelet filtering to be the most promising and powerful technique for the correction of motion artifacts in fNIRS data. The analyses performed here can serve as a guide for others to objectively test the impact of different motion correction algorithms and therefore select the most appropriate for the analysis of their own fNIRS experiment.

Wireless recording systems: from noninvasive EEG-NIRS to invasive EEG devices

In this paper, we present the design and implementation of a wireless wearable electronic system dedicated to remote data recording for brain monitoring. The reported wireless recording system is used for a) simultaneous near-infrared spectrometry (NIRS) and scalp electro-encephalography (EEG) for noninvasive monitoring and b) intracerebral EEG (icEEG) for invasive monitoring. Bluetooth and dual radio links were introduced for these recordings. The Bluetooth-based device was embedded in a noninvasive multichannel EEG-NIRS system for easy portability and long-term monitoring. On the other hand, the 32-channel implantable recording device offers 24-bit resolution, tunable features, and a sampling frequency up to 2 kHz per channel. The analog front-end preamplifier presents low input-referred noise of 5 μ VRMS and a signal-to-noise ratio of 112 dB. The communication link is implemented using a dual-band radio frequency transceiver offering a half-duplex 800 kb/s data rate, 16.5 mW power consumption and less than 10(-10) post-correction Bit-Error Rate (BER). The designed system can be accessed and controlled by a computer with a user-friendly graphical interface. The proposed wireless implantable recording device was tested in vitro using real icEEG signals from two patients with refractory epilepsy. The wirelessly recorded signals were compared to the original signals recorded using wired-connection, and measured normalized root-mean square deviation was under 2%.

Functional brain imaging of multi-sensory vestibular processing during computerized dynamic posturography using near-infrared spectroscopy

Functional near-infrared spectroscopy (fNIRS) is a non-invasive brain imaging method that uses light to record regional changes in cerebral blood flow in the cortex during activation. fNIRS uses portable wearable sensors to allow measurements of brain activation during tasking. In this study, fNIRS was used to investigate how the brain processes information from multiple sensory modalities during dynamic posturography. Fifteen healthy volunteers (9M/6F; ages 28+/-9 yrs) participated in the posturography study while undergoing fNIRS brain imaging. Four standard conditions from the sensory organization test (SOT) were performed and a bilateral fNIRS probe was used to examine the cortical brain responses from the frontal, temporal, and parietal brain regions. We found that there was bilateral activation in the temporal-parietal areas (superior temporal gyrus, STG, and supramarginal gyrus, SMG) when both vision and proprioceptive information were degraded; forcing reliance on primarily vestibular information in the control of balance. This is consistent with previous reports of the role of these regions in vestibular control and demonstrates the potential utility of fNIRS in the study of cortical control of vestibular function during standing balance tasks.

Somatosensory evoked changes in cerebral oxygen consumption measured non-invasively in premature neonates

The hemodynamic functional response is used as a reliable marker of neuronal activity in countless studies of brain function and cognition. In newborns and infants, however, conflicting results have appeared in the literature concerning the typical response, and there is little information on brain metabolism and functional activation. Measurement of all hemodynamic components and oxygen metabolism is critical for understanding neurovascular coupling in the developing brain. To this end, we combined multiple near infrared spectroscopy techniques to measure oxy- and deoxy-hemoglobin concentrations, cerebral blood volume (CBV), and relative cerebral blood flow (CBF) in the somatosensory cortex of 6 preterm neonates during passive tactile stimulation of the hand. By combining these measures we estimated relative changes in the cerebral metabolic rate of oxygen consumption (rCMRO2). CBF starts increasing immediately after stimulus onset, and returns to baseline before blood volume. This is consistent with the model of pre-capillary arteriole active dilation driving the CBF response, with a subsequent CBV increase influenced by capillaries and veins dilating passively to accommodate the extra blood. rCMRO2 estimated using the steady-state formulation shows a biphasic pattern: an increase immediately after stimulus onset, followed by a post-stimulus undershoot due to blood flow returning faster to baseline than oxygenation. However, assuming a longer mean transit time from the arterial to the venous compartment, due to the immature vascular system of premature infants, reduces the post-stimulus undershoot and increases the flow/consumption ratio to values closer to adult values reported in the literature. We are the first to report changes in local rCBF and rCMRO2 during functional activation in preterm infants. The ability to measure these variables in addition to hemoglobin concentration changes is critical for understanding neurovascular coupling in the developing brain, and for using this coupling as a reliable functional imaging marker in neonates.

Effects of essence of chicken on cognitive brain function: a near-infrared spectroscopy study

The aim of this study was to investigate the effects of the essence of chicken on brain function by near-infrared spectroscopy. Twelve healthy elderly subjects took the essence of chicken or a placebo for 7 d in a double-blind cross-over design study. Changes in oxy-hemoglobin concentrations in the bilateral prefrontal areas of the brain were measured while the subjects performed the simple reaction task, the Groton Maze Learning Test, and the working memory task. In the latter case, there were significant interactions in the changes in oxy-hemoglobin concentrations between treatment and period of intake according to two-way repeated ANOVA. The changes in oxy-hemoglobin concentrations significantly increased in several regions of the prefrontal areas of the brain in those taking essence of chicken for 7 d. These results suggest that essence of chicken is useful as a nutritional supplement to enhance or maintain brain function in the elderly.

Combining independent component analysis and Granger causality to investigate brain network dynamics with fNIRS measurements

In this study a new strategy that combines Granger causality mapping (GCM) and independent component analysis (ICA) is proposed to reveal complex neural network dynamics underlying cognitive processes using functional near infrared spectroscopy (fNIRS) measurements. The GCM-ICA algorithm implements the following two procedures: (i) extraction of the region of interests (ROIs) of cortical activations by ICA, and (ii) estimation of the direct causal influences in local brain networks using Granger causality among voxels of ROIs. Our results show that the use of GCM in conjunction with ICA is able to effectively identify the directional brain network dynamics in time-frequency domain based on fNIRS recordings.

Autoregressive model based algorithm for correcting motion and serially correlated errors in fNIRS

Systemic physiology and motion-induced artifacts represent two major sources of confounding noise in functional near infrared spectroscopy (fNIRS) imaging that can reduce the performance of analyses and inflate false positive rates (i.e., type I errors) of detecting evoked hemodynamic responses. In this work, we demonstrated a general algorithm for solving the general linear model (GLM) for both deconvolution (finite impulse response) and canonical regression models based on designing optimal pre-whitening filters using autoregressive models and employing iteratively reweighted least squares. We evaluated the performance of the new method by performing receiver operating characteristic (ROC) analyses using synthetic data, in which serial correlations, motion artifacts, and evoked responses were controlled via simulations, as well as using experimental data from children (3-5 years old) as a source baseline physiological noise and motion artifacts. The new method outperformed ordinary least squares (OLS) with no motion correction, wavelet based motion correction, or spline interpolation based motion correction in the presence of physiological and motion related noise. In the experimental data, false positive rates were as high as 37% when the estimated p-value was 0.05 for the OLS methods. The false positive rate was reduced to 5-9% with the proposed method. Overall, the method improves control of type I errors and increases performance when motion artifacts are present.

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.

Separation of fNIRS signals into functional and systemic components based on differences in hemodynamic modalities

In conventional functional near-infrared spectroscopy (fNIRS), systemic physiological fluctuations evoked by a body's motion and psychophysiological changes often contaminate fNIRS signals. We propose a novel method for separating functional and systemic signals based on their hemodynamic differences. Considering their physiological origins, we assumed a negative and positive linear relationship between oxy- and deoxyhemoglobin changes of functional and systemic signals, respectively. Their coefficients are determined by an empirical procedure. The proposed method was compared to conventional and multi-distance NIRS. The results were as follows: (1) Nonfunctional tasks evoked substantial oxyhemoglobin changes, and comparatively smaller deoxyhemoglobin changes, in the same direction by conventional NIRS. The systemic components estimated by the proposed method were similar to the above finding. The estimated functional components were very small. (2) During finger-tapping tasks, laterality in the functional component was more distinctive using our proposed method than that by conventional fNIRS. The systemic component indicated task-evoked changes, regardless of the finger used to perform the task. (3) For all tasks, the functional components were highly coincident with signals estimated by multi-distance NIRS. These results strongly suggest that the functional component obtained by the proposed method originates in the cerebral cortical layer. We believe that the proposed method could improve the reliability of fNIRS measurements without any modification in commercially available instruments.

Measurement of brain activation during an upright stepping reaction task using functional near-infrared spectroscopy

Functional near-infrared spectroscopy (fNIRS) is a non-invasive brain imaging technology that uses light to measure changes in cortical hemoglobin concentrations. FNIRS measurements are recorded through fiber optic cables, which allow the participant to wear the fNIRS sensors while standing upright. Thus, fNIRS technology is well suited to study cortical brain activity during upright balance, stepping, and gait tasks. In this study, fNIRS was used to measure changes in brain activation from the frontal, motor, and premotor brain regions during an upright step task that required subjects to step laterally in response to visual cues that required executive function control. We hypothesized that cognitive processing during complex stepping cues would elicit brain activation of the frontal cortex in areas involved in cognition. Our results show increased prefrontal activation associated with the processing of the stepping cues. Moreover, these results demonstrate the potential to use fNIRS to investigate cognitive processing during cognitively demanding balance and gait studies.

Functional near-infrared spectroscopy for the assessment of overt reading

Functional near-infrared spectroscopy (fNIRS) has become increasingly established as a promising technique for monitoring functional brain activity. To our knowledge, no study has yet used fNIRS to investigate overt reading of irregular words and nonwords with a full coverage of the cerebral regions involved in reading processes. The aim of our study was to design and validate a protocol using fNIRS for the assessment of overt reading. Twelve healthy French-speaking adults underwent one session of fNIRS recording while performing an overt reading of 13 blocks of irregular words and nonwords. Reading blocks were separated by baseline periods during which participants were instructed to fixate a cross. Sources (n = 55) and detectors (n = 16) were placed bilaterally over frontal, temporal, parietal, and occipital regions. Two wavelengths were used: 690 nm, more sensitive to deoxyhemoglobin (HbR) concentration changes, and 830 nm, more sensitive to oxyhemoglobin (HbO) concentration changes. For all participants, total hemoglobin (HbT) concentrations (HbO + HbR) were significantly higher than baseline for both irregular word and nonword reading in the inferior frontal gyri, the middle and superior temporal gyri, and the occipital cortices bilaterally. In the temporal gyri, although the difference was not significant, [HbT] values were higher in the left hemisphere. In the bilateral inferior frontal gyri, higher [HbT] values were found in nonword than in irregular word reading. This activation could be related to the grapheme-to-phoneme conversion characterizing the phonological pathway of reading. Our findings confirm that fNIRS is an appropriate technique to assess the neural correlates of overt reading.

A systematic comparison of motion artifact correction techniques for functional near-infrared spectroscopy

Near-infrared spectroscopy (NIRS) is susceptible to signal artifacts caused by relative motion between NIRS optical fibers and the scalp. These artifacts can be very damaging to the utility of functional NIRS, particularly in challenging subject groups where motion can be unavoidable. A number of approaches to the removal of motion artifacts from NIRS data have been suggested. In this paper we systematically compare the utility of a variety of published NIRS motion correction techniques using a simulated functional activation signal added to 20 real NIRS datasets which contain motion artifacts. Principle component analysis, spline interpolation, wavelet analysis, and Kalman filtering approaches are compared to one another and to standard approaches using the accuracy of the recovered, simulated hemodynamic response function (HRF). Each of the four motion correction techniques we tested yields a significant reduction in the mean-squared error (MSE) and significant increase in the contrast-to-noise ratio (CNR) of the recovered HRF when compared to no correction and compared to a process of rejecting motion-contaminated trials. Spline interpolation produces the largest average reduction in MSE (55%) while wavelet analysis produces the highest average increase in CNR (39%). On the basis of this analysis, we recommend the routine application of motion correction techniques (particularly spline interpolation or wavelet analysis) to minimize the impact of motion artifacts on functional NIRS data.

Neurovascular saturation thresholds under high intensity auditory stimulation during wake

Coupling between neural activity and hemodynamic responses is important in understanding brain function, interpreting brain-imaging signals, and assessing pathological conditions. Tissue state is a major factor in neurovascular coupling and may alter the relationship between neural and hemodynamic activity. However, most neurovascular-coupling studies are performed under anesthetized or sedated states which may have severe consequences on coupling mechanisms. Our previous studies showed that following prolonged periods of sleep deprivation, evoked hemodynamic responses were muted despite consistent electrical responses, suggesting that sustained neural activity may decrease vascular compliance and limit blood perfusion. To investigate potential perfusion limitations during natural waking conditions, we simultaneously measured evoked response potentials (ERPs) and evoked hemodynamic responses using optical-imaging techniques to increase intensity auditory stimulation. The relationship between evoked hemodynamic responses and integrated ERPs followed a sigmoid relationship where the hemodynamic response approached saturation at lower stimulus intensities than the ERP. If limits in blood perfusion are caused by stretching of the vessel wall, then these results suggest there may be decreased vascular compliance due to sustained neural activity during wake, which could limit vascular responsiveness and local blood perfusion. Conditions that stress cerebral vasculature, such as sleep deprivation and some pathologies (e.g., epilepsy), may further decrease vascular compliance, limit metabolic delivery, and cause tissue trauma. While ERPs and evoked hemodynamic responses provide an indication of the correlated neural activity and metabolic demand, the relationship between these two responses is complex and the different measurement techniques are not directly correlated. Future studies are required to verify these findings and further explore neurovascular coupling during wake by assessing local field potentials, vascular expansion, hemodynamic response localization.

Functional Near Infrared Spectroscopy (fNIRS) synthetic data generation

Accurately modelled computer-generated data can be used in place of real-world signals for the design, test and validation of signal processing techniques in situations where real data is difficult to obtain. Bio-signal processing researchers interested in working with fNIRS data are restricted due to the lack of freely available fNIRS data and by the prohibitively expensive cost of fNIRS systems. We present a simplified mathematical description and associated MATLAB implementation of model-based synthetic fNIRS data which could be used by researchers to develop fNIRS signal processing techniques. The software, which is freely available, allows users to generate fNIRS data with control over a wide range of parameters and allows for fine-tuning of the synthetic data. We demonstrate how the model can be used to generate raw fNIRS data similar to recorded fNIRS signals. Signal processing steps were then applied to both the real and synthetic data. Visual comparisons between the temporal and spectral properties of the real and synthetic data show similarity. This paper demonstrates that our model for generating synthetic fNIRS data can replicate real fNIRS recordings.

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.

Improving optical contact for functional near‑infrared brain spectroscopy and imaging with brush optodes

A novel brush optode was designed and demonstrated to overcome poor optical contact with the scalp that can occur during functional near infrared spectroscopy (fNIRS) and imaging due to light obstruction by hair. The brush optodes were implemented as an attachment to existing commercial flat-faced (conventional) fiber bundle optodes. The goal was that the brush optodes would thread through hair and improve optical contact on subjects with dense hair. Simulations and experiments were performed to assess the magnitude of these improvements. FNIRS measurements on 17 subjects with varying hair colors (blonde, brown, and black) and hair densities (0-2.96 hairs/mm(2)) were performed during a finger tapping protocol for both flat and brush optodes. In addition to reaching a study success rate of almost 100% when using the brush optode extensions, the measurement setup times were reduced by a factor of three. Furthermore, the brush optodes enabled improvements in the activation signal-to-noise ratio (SNR) by up to a factor of ten as well as significant (p < 0.05) increases in the detected area of activation (dAoA). The measured improvements in SNR were matched by Monte Carlo (MC) simulations of photon propagation through scalp and hair. In addition, an analytical model was derived to mathematically estimate the observed light power losses due to different hair colors and hair densities. Interestingly, the derived analytical formula produced excellent estimates of the experimental data and MC simulation results despite several simplifying assumptions. The analytical model enables researchers to readily estimate the light power losses due to obstruction by hair for both flat-faced fiber bundles and individual fibers for a given subject.

Near-infrared imaging of the effects of glucose ingestion and regulation on prefrontal activation during dual-task execution in healthy fasting older adults

RATIONALE

Glucose enhancing effects in older adults have mostly been observed for episodic memory, but have recently been found for attentional control performance. Yet, brain activation patterns underlying these effects are still unknown.

OBJECTIVE

The present study examined the acute effects of glucose ingestion on prefrontal brain activation during the execution of a divided attention task in fasting non-diabetic older adults.

METHODS

Twenty older adults (60 years and older) took part in the study that included two experimental sessions. After an overnight fast, participants received either a glucose drink (50 g) or a placebo (saccharin) drink, following which they completed a dual-task. During task execution, prefrontal activation was recorded with functional near-infrared spectroscopy (fNIRS). A repeated-measures design was used such that each participant served as his or her own control. The two experimental sessions were counterbalanced among participants and were performed two weeks apart.

RESULTS

When participants were in the glucose condition, they showed similar dual-task costs for both tasks, whereas in the placebo condition they prioritized one task over the other, with a significantly larger dual-task cost for the non-prioritized task (p<0.01). Differential brain activation was also observed in right ventral-lateral prefrontal regions for oxygenated hemoglobin and deoxygenated hemoglobin, with more activation apparent in the glucose condition (p<0.05). Furthermore, behavioral and activation data were influenced by individual differences in glucose regulation.

CONCLUSIONS

Glucose ingestion appears to momentarily enhance fasting seniors' capacity to coordinate more equally two concurrent tasks and this is reflected in brain activation patterns.

Multifunctionality of indocyanine green-loaded biodegradable nanoparticles for enhanced optical imaging and hyperthermia intervention of cancer

The aim of this study was to develop and characterize multifunctional biodegradable and biocompatible poly lactic-co-glycolic acid (PLGA) nanoparticles loaded with indocyanine green (ICG) as an optical-imaging contrast agent for cancer imaging and as a photothermal therapy agent for cancer treatment. PLGA-ICG nanoparticles (PIN) were synthesized with a particle diameter of 246±11 nm, a polydispersity index of 0.10±0.03, and ICG loading efficiency of 48.75±5.48%. PIN were optically characterized with peak excitation and emission at 765 and 810±5 nm, a fluorescence lifetime of 0.30±0.01 ns, and peak absorbance at 780 nm. The cytocompatibility study of PIN showed 85% cell viability till 1-mg/ml concentration of PIN. Successful cellular uptake of ligand conjugated PIN by prostate cancer cells (PC3) was also obtained. Both phantom-based and in vitro cell culture results demonstrated that PIN (1) have the great potential to induce local hyperthermia (i.e., temperature increase of 8 to 10°C) in tissue within 5 mm both in radius and in depth; (2) result in improved optical stability, excellent biocompatibility with healthy cells, and a great targeting capability; (3) have the ability to serve as an image contrast agent for deep-tissue imaging in diffuse optical tomography.

The cortical control of cycling exercise in stroke patients: an fNIRS study

Stroke survivors suffering from deficits in motor control typically have limited functional abilities, which could result in poor quality of life. Cycling exercise is a common training paradigm for restoring locomotion rhythm in patients. The provision of speed feedback has been used to facilitate the learning of controlled cycling performance and the neuromuscular control of the affected leg. However, the central mechanism for motor relearning of active and passive pedaling motions in stroke patients has not been investigated as extensively. The aim of this study was to measure the cortical activation patterns during active cycling with and without speed feedback and during power-assisted (passive) cycling in stroke patients. A frequency-domain near-infrared spectroscopy (FD-NIRS) system was used to detect the hemodynamic changes resulting from neuronal activity during the pedaling exercise from the bilateral sensorimotor cortices (SMCs), supplementary motor areas (SMAs), and premotor cortices (PMCs). The variation in cycling speed and the level of symmetry of muscle activation of bilateral rectus femoris were used to evaluate cycling performance. The results showed that passive cycling had a similar cortical activation pattern to that observed during active cycling without feedback but with a smaller intensity of the SMC of the unaffected hemisphere. Enhanced PMC activation of the unaffected side with improved cycling performance was observed during active cycling with feedback, with respect to that observed without feedback. This suggests that the speed feedback enhanced the PMC activation and improved cycling performance in stroke patients.

Brain activity during the Clock-Drawing Test: multichannel near-infrared spectroscopy study

The Clock-Drawing Test (CDT) is widely used in clinical practice for the screening of dementia. However, neural activity during real clock drawing has not been investigated due to motion artifacts. In the present study, we examined brain activity during real clock drawing using multichannel near-infrared spectroscopy (NIRS). We measured hemoglobin concentration changes in the prefrontal and temporal surface areas during clock drawing using 52-channel NIRS. Data obtained from 37 right-handed healthy volunteers were analyzed. We found significant increases in oxy-Hb in more than 96.2% of the channels (false-discovery rate corrected, p < .025). The time required for CDT performance showed a negative correlation with changes in oxy-Hb in the prefrontal region (r = -.529, p = .002). The mean value for oxy-Hb changes was higher in the left hemisphere in 20 subjects (54%) and in the right hemisphere in 17 subjects (46%). The NIRS/CDT combination is acceptable as a clinical tool, as the method has the advantages of direct measurement of cortical activation with high temporal resolution. Our results confirm the aspects of the CDT involving the frontal-lobe battery.

Functional near-infrared spectroscopy (fNIRS) of brain function during active balancing using a video game system

Functional near-infrared spectroscopy (fNIRS) is a portable, non-invasive, brain imaging technology that uses low levels of non-ionizing light to record changes in cerebral blood flow in the brain through optical sensors placed on the surface of the scalp. These signals are recorded via flexible fiber optic cables, which allow neuroimaging experiments to be conducted on participants while performing tasks such as standing or walking. FNIRS has the potential to provide new insights into the evolution of brain activation during ambulatory motor learning tasks and standing tasks to probe balance and vestibular function. In this study, a 32 channel fNIRS system was used to record blood flow changes in the frontal, motor, sensory, and temporal cortices during active balancing associated with playing a video game simulating downhill skiing (Nintendo Wii™; Wii-fit™). Using fNIRS, we found activation of superior temporal gyrus, which was modulated by the difficulty of the balance task. This region had been previously implicated in vestibular function from other animal and human studies.

Artifact removal in physiological signals--practices and possibilities

The combination of reducing birth rate and increasing life expectancy continues to drive the demographic shift toward an aging population. This, in turn, places an ever-increasing burden on healthcare due to the increasing prevalence of patients with chronic illnesses and the reducing income-generating population base needed to sustain them. The need to urgently address this healthcare "time bomb" has accelerated the growth in ubiquitous, pervasive, distributed healthcare technologies. The current move from hospital-centric healthcare toward in-home health assessment is aimed at alleviating the burden on healthcare professionals, the health care system and caregivers. This shift will also further increase the comfort for the patient. Advances in signal acquisition, data storage and communication provide for the collection of reliable and useful in-home physiological data. Artifacts, arising from environmental, experimental and physiological factors, degrade signal quality and render the affected part of the signal useless. The magnitude and frequency of these artifacts significantly increases when data collection is moved from the clinic into the home. Signal processing advances have brought about significant improvement in artifact removal over the past few years. This paper reviews the physiological signals most likely to be recorded in the home, documenting the artifacts which occur most frequently and which have the largest degrading effect. A detailed analysis of current artifact removal techniques will then be presented. An evaluation of the advantages and disadvantages of each of the proposed artifact detection and removal techniques, with particular application to the personal healthcare domain, is provided.

Spatiotemporal relations of primary sensorimotor and secondary motor activation patterns mapped by NIR imaging

Functional near infrared (fNIR) imaging was used to identify spatiotemporal relations between spatially distinct cortical regions activated during various hand and arm motion protocols. Imaging was performed over a field of view (FOV, 12 x 8.4 cm) including the secondary motor, primary sensorimotor, and the posterior parietal cortices over a single brain hemisphere. This is a more extended FOV than typically used in current fNIR studies. Three subjects performed four motor tasks that induced activation over this extended FOV. The tasks included card flipping (pronation and supination) that, to our knowledge, has not been performed in previous functional magnetic resonance imaging (fMRI) or fNIR studies. An earlier rise and a longer duration of the hemodynamic activation response were found in tasks requiring increased physical or mental effort. Additionally, analysis of activation images by cluster component analysis (CCA) demonstrated that cortical regions can be grouped into clusters, which can be adjacent or distant from each other, that have similar temporal activation patterns depending on whether the performed motor task is guided by visual or tactile feedback. These analyses highlight the future potential of fNIR imaging to tackle clinically relevant questions regarding the spatiotemporal relations between different sensorimotor cortex regions, e.g. ones involved in the rehabilitation response to motor impairments.

Implicit and explicit prior information in near-infrared spectral imaging: accuracy, quantification and diagnostic value

Near-infrared spectroscopy (NIRS) of tissue provides quantification of absorbers, scattering and luminescent agents in bulk tissue through the use of measurement data and assumptions. Prior knowledge can be critical about things such as (i) the tissue shape and/or structure, (ii) spectral constituents, (iii) limits on parameters, (iv) demographic or biomarker data, and (v) biophysical models of the temporal signal shapes. A general framework of NIRS imaging with prior information is presented, showing that prior information datasets could be incorporated at any step in the NIRS process, with the general workflow being: (i) data acquisition, (ii) pre-processing, (iii) forward model, (iv) inversion/reconstruction, (v) post-processing, and (vi) interpretation/diagnosis. Most of the development in NIRS has used ad hoc or empirical implementations of prior information such as pre-measured absorber or fluorophore spectra, or tissue shapes as estimated by additional imaging tools. A comprehensive analysis would examine what prior information maximizes the accuracy in recovery and value for medical diagnosis, when implemented at separate stages of the NIRS sequence. Individual applications of prior information can show increases in accuracy or improved ability to estimate biochemical features of tissue, while other approaches may not. Most beneficial inclusion of prior information has been in the inversion/reconstruction process, because it solves the mathematical intractability. However, it is not clear that this is always the most beneficial stage.

Nonlinear hemodynamic responses in human epilepsy: a multimodal analysis with fNIRS-EEG and fMRI-EEG

Functional magnetic resonance imaging (fMRI) combined with electroencephalography (fMRI-EEG) is a neuroimaging technique based on the blood oxygenation level dependent (BOLD) signal which has been shown to be useful in the study of epilepsy for the localization of the epileptogenic focus. Functional near-infrared spectroscopy (fNIRS) combined with EEG (fNIRS-EEG) is another imaging technique based on the measurement of oxygenated and deoxygenated hemoglobin with complementary clinical potential in epilepsy, for continuous patient monitoring, language lateralization, and focus localization. In this work fMRI-EEG and fNIRS-EEG are used to quantify nonlinear hemodynamic responses in three cases of human refractory focal epilepsy, by using the Volterra kernel expansion up to second order. Prior to analyzing real data, extensive simulations are carried out to show that nonlinearities are estimable. The Volterra methodology is then applied to multimodal data recorded from 3 epileptic patients selected for their frequent spiking activity. Care is taken to account for variability of hemodynamic responses due to other causes than Volterra nonlinearities. Statistically significant nonlinearities are observed for all patients and all modalities. Good concordance between fNIRS and fMRI is found for both the amplitude of the Volterra responses, and, with limitations, in the localization of the epileptic focus and regions of inverted responses (negative BOLD signals). In one patient, Volterra nonlinearities allowed epileptic focus identification with fMRI, while analyses without nonlinearities failed to see it. In simulations when nonlinearities were included, analysis without Volterra nonlinearities performed poorly. These two observations suggest routinely checking for nonlinearities in functional imaging of patients presenting with frequent spikes.

Specific functional asymmetries of the human visual cortex revealed by functional near-infrared spectroscopy

Based on multiple invasive reports and neuroimaging studies, it is well established that the cytoarchitecture of the visual cortex is related to its functional organization, namely, its retinotopy. The present study aimed to further investigate retinotopic mapping as well as specific vertical and horizontal functional asymmetries within the human visual cortex using functional near-infrared spectroscopy (fNIRS). Black and white wedge checkerboard stimuli were randomly presented to the four visual field (VF) quadrants of eight healthy adults in order to quantify and compare the localization and the amplitude of hemodynamic cortical responses to each VF quadrant. Results showed the expected activation in the contralateral hemisphere, with respect to the side of the stimulated quadrant. We also measured significantly stronger activations in the upper visual cortex when low hemifield stimuli were presented compared to activations in the lower visual cortex when upper hemifield stimuli were shown, especially when the stimulation was presented in the right visual field. These findings confirm the vertical asymmetry of the visual cortex previously reported by neuroimaging and behavioral studies. More importantly, the present work confirms the reliability of the fNIRS technique for functional mapping of the human brain.

Using MazeSuite and functional near infrared spectroscopy to study learning in spatial navigation

MazeSuite is a complete toolset to prepare, present and analyze navigational and spatial experiments¹. MazeSuite can be used to design and edit adapted virtual 3D environments, track a participants' behavioral performance within the virtual environment and synchronize with external devices for physiological and neuroimaging measures, including electroencephalogram and eye tracking.

Functional near-infrared spectroscopy (fNIR) is an optical brain imaging technique that enables continuous, noninvasive, and portable monitoring of changes in cerebral blood oxygenation related to human brain functions^2-7. Over the last decade fNIR is used to effectively monitor cognitive tasks such as attention, working memory and problem solving^7-11. fNIR can be implemented in the form of a wearable and minimally intrusive device; it has the capacity to monitor brain activity in ecologically valid environments.

Cognitive functions assessed through task performance involve patterns of brain activation of the prefrontal cortex (PFC) that vary from the initial novel task performance, after practice and during retention¹². Using positron emission tomography (PET), Van Horn and colleagues found that regional cerebral blood flow was activated in the right frontal lobe during the encoding (i.e., initial naïve performance) of spatial navigation of virtual mazes while there was little to no activation of the frontal regions after practice and during retention tests. Furthermore, the effects of contextual interference, a learning phenomenon related to organization of practice, are evident when individuals acquire multiple tasks under different practice schedules^13,14. High contextual interference (random practice schedule) is created when the tasks to be learned are presented in a non-sequential, unpredictable order. Low contextual interference (blocked practice schedule) is created when the tasks to be learned are presented in a predictable order.

Our goal here is twofold: first to illustrate the experimental protocol design process and the use of MazeSuite, and second, to demonstrate the setup and deployment of the fNIR brain activity monitoring system using Cognitive Optical Brain Imaging (COBI) Studio software¹⁵. To illustrate our goals, a subsample from a study is reported to show the use of both MazeSuite and COBI Studio in a single experiment. The study involves the assessment of cognitive activity of the PFC during the acquisition and learning of computer maze tasks for blocked and random orders. Two right-handed adults (one male, one female) performed 315 acquisition, 30 retention and 20 transfer trials across four days. Design, implementation, data acquisition and analysis phases of the study were explained with the intention to provide a guideline for future studies.

Functional near infrared spectroscopy study of age-related difference in cortical activation patterns during cycling with speed feedback

Functional decline of lower-limb affects the ability of locomotion and the age-related brain differences have been elucidated among the elderly. Cycling exercise is a common training program for restoring motor function in the deconditioned elderly or stroke patients. The provision of speed feedback has been commonly suggested to clinical therapists for facilitating learning of controlled cycling performance and maintaining motivation in training programs with elderly participants. However, the cortical control of pedaling movements and the effect of external feedback remain poorly understanding. This study investigated the regional cortical activities detected by functional near infrared spectroscopy (fNIRS) in 12 healthy young and 13 healthy elderly subjects under conditions of cycling without-(free cycling) and with feedback (target cycling). The elderly exhibited predominant activation of the sensorimotor cortex during free cycling similar to young subjects but with poorer cycling performance. The cycling performance improved in both groups, and the elderly showed increased brain activities of the supplementary motor area and premotor cortex under target cycling condition. These findings demonstrated age-related changes in the cortical control in processing external feedback and pedaling movements. Use of fNIRS to evaluate brain activation patterns after training may facilitate brain-based design of tailored therapeutic rehabilitation strategies.

Isolating the sources of widespread physiological fluctuations in functional near-infrared spectroscopy signals

Physiological fluctuations at low frequency (<0.1 Hz) are prominent in functional near-infrared spectroscopy (fNIRS) measurements in both resting state and functional task studies. In this study, we used the high spatial resolution and full brain coverage of functional magnetic resonance imaging (fMRI) to understand the origins and commonalities of these fluctuations. Specifically, we applied a newly developed method, regressor interpolation at progressive time delays, to analyze concurrently recorded fNIRS and fMRI data acquired both in a resting state study and in a finger tapping study. The method calculates the voxelwise correlations between blood oxygen level dependent (BOLD) fMRI and fNIRS signals with different time shifts and localizes the areas in the brain that highly correlate with the fNIRS signal recorded at the surface of the head. The results show the wide spatial distribution of this physiological fluctuation in BOLD data, both in task and resting states. The brain areas that are highly correlated with global physiological fluctuations observed by fNIRS have a pattern that resembles the venous system of the brain, indicating the blood fluctuation from veins on the brain surface might strongly contribute to the overall fNIRS signal.