False Positives In Functional Nearinfrared Topography

Impaired Neurovascular Coupling and Increased Functional Connectivity in the Frontal Cortex Predict Age-Related Cognitive Dysfunction

Impaired cerebrovascular function contributes to the genesis of age-related cognitive decline. In this study, the hypothesis is tested that impairments in neurovascular coupling (NVC) responses and brain network function predict cognitive dysfunction in older adults. Cerebromicrovascular and working memory function of healthy young (n = 21, 33.2±7.0 years) and aged (n = 30, 75.9±6.9 years) participants are assessed. To determine NVC responses and functional connectivity (FC) during a working memory (n-back) paradigm, oxy- and deoxyhemoglobin concentration changes from the frontal cortex using functional near-infrared spectroscopy are recorded. NVC responses are significantly impaired during the 2-back task in aged participants, while the frontal networks are characterized by higher local and global connection strength, and dynamic FC (p < 0.05). Both impaired NVC and increased FC correlate with age-related decline in accuracy during the 2-back task. These findings suggest that task-related brain states in older adults require stronger functional connections to compensate for the attenuated NVC responses associated with working memory load.

Frequency-domain analysis of fNIRS fluctuations induced by rhythmic mental arithmetic

Functional near‐infrared spectroscopy (fNIRS) is an increasingly used technology for imaging neural correlates of cognitive processes. However, fNIRS signals are commonly impaired by task‐evoked and spontaneous hemodynamic oscillations of non‐cerebral origin, a major challenge in fNIRS research. In an attempt to isolate the task‐evoked cortical response, we investigated the coupling between hemodynamic changes arising from superficial and deep layers during mental effort. For this aim, we applied a rhythmic mental arithmetic task to induce cyclic hemodynamic fluctuations suitable for effective frequency‐resolved measurements. Twenty university students aged 18–25 years (eight males) underwent the task while hemodynamic changes were monitored in the forehead using a newly developed NIRS device, capable of multi‐channel and multi‐distance recordings. We found significant task‐related fluctuations for oxy‐ and deoxy‐hemoglobin, highly coherent across shallow and deep tissue layers, corroborating the strong influence of surface hemodynamics on deep fNIRS signals. Importantly, after removing such surface contamination by linear regression, we show that the frontopolar cortex response to a mental math task follows an unusual inverse oxygenation pattern. We confirm this finding by applying for the first time an alternative method to estimate the neural signal, based on transfer function analysis and phasor algebra. Altogether, our results demonstrate the feasibility of using a rhythmic mental task to impose an oscillatory state useful to separate true brain functional responses from those of non‐cerebral origin. This separation appears to be essential for a better understanding of fNIRS data and to assess more precisely the dynamics of the neuro‐visceral link.

We proposed the use of rhythmic mental arithmetic tasks to induce cyclic oscillations in multi‐distance fNIRS signals measured on the forehead, suitable for effective frequency‐domain analysis to better identify the actual neural functional response. We confirm the impairment of deep signals by task‐evoked non‐cerebral confounds, while providing evidence for an inverse oxygenation response in the frontopolar cortex.

Cerebral hemodynamics predicts the cortical area and coding scheme in the human brain for force generation by wrist muscles

The goal of this study is to identify the cortical area maximally active over the primary sensorimotor cortex (SM1) and characterize the cortical encoding for force production by wrist muscles in the human brain. The technique of functional near-infrared spectroscopy (fNIRS) was used to continuously monitor the changes in hemoglobin concentrations from the left hemisphere during isometric contractions of wrist flexion muscles over a broad range of load forces (0 ∼ 8 kgf) on the right hand. As previously shown in primate studies, this action produced hemodynamic activity predominantly in the wrist area localized dorsally to the finger region over SM1 and the hemodynamic response was systematically related to the level of load intensity. The coding scheme for force production in terms of hemodynamic signals was characterized defining eight trajectory parameters (four for amplitude coding and four for temporal coding) and analyzed for the area maximally activated over SM1. The trajectory parameter representing the oxygenated hemoglobin concentration change at the end of motor task (amplitude coding) and the timing of maximum change in oxygenated hemoglobin concentration (temporal coding) was most strongly correlated with the load variation in a superliner manner. All these results indicate the applicability of fNIRS to monitor and decode cortical activity that is correlated with low-level motor control such as isometric muscle contractions. This study may provide not only insights into cortical neural control of muscle force but also predictors of muscle force in clinical diagnostics and neural interfaces for the human brain.

Depth-resolved assessment of changes in concentration of chromophores using time-resolved near-infrared spectroscopy: estimation of cytochrome-c-oxidase uncertainty by Monte Carlo simulations

Time-resolved near-infrared spectroscopy (TR-NIRS) measurements can be used to recover changes in concentrations of tissue constituents ( Δ C ) by applying the moments method and the Beer-Lambert law. In this work we carried out the error propagation analysis allowing to calculate the standard deviations of uncertainty in estimation of the Δ C . Here, we show the process of choosing wavelengths for the evaluation of hemodynamic (oxy-, deoxyhemoglobin) and metabolic (cytochrome-c-oxidase (CCO)) responses within the brain tissue as measured with an in-house developed TR-NIRS multi-wavelength system, which measures at 16 consecutive wavelengths separated by 12.5 nm and placed between 650 and 950 nm. Data generated with Monte Carlo simulations on three-layered model (scalp, skull, brain) for wavelengths range from 650 to 950 nm were used to carry out the error propagation analysis for varying choices of wavelengths. For a detector with a spectrally uniform responsivity, the minimal standard deviation of the estimated changes in CCO within the brain layer, σ Δ C CCO brain  = 0.40 µM, was observed for the 16 consecutive wavelengths from 725 to 912.5 nm. For realistic a detector model, i.e. the spectral responsivity characteristic is considered, the minimum, σ Δ C CCO brain  = 0.47 µM, was observed at the 16 consecutive wavelengths from 688 to 875 nm. We introduce the method of applying the error propagation analysis to data as measured with spectral TR-NIRS systems to calculate uncertainty of recovery of tissue constituents concentrations.

Prefrontal hemodynamic after-effects caused by rebreathing may predict affective states - A multimodal functional near-infrared spectroscopy study

Brain activity has been shown to be influenced by respiratory behavior. Here, we evaluated whether respiration-induced hypo- or hypercapnia may support differentiation between physiological versus pathological respiratory behavior. In particular, we investigated whether systemic physiological measures could predict the brain's time-frequency hemodynamics after three respiratory challenges (i.e., breath-holding, rebreathing, and hyperventilation) compared to resting-state. Prefrontal hemodynamics were assessed in healthy subjects (N = 27) using functional near-infrared spectroscopy (fNIRS). Systemic physiological measures were assessed in form of heart rate, partial end-tidal carbon dioxide, respiration rate, and saturation of peripheral oxygen. Time-frequency dynamics were quantified using the wavelet transform coherence (i.e., defined here as cortical-systemic coherence). We found that the three respiratory challenges modulated cortical-systemic coherence differently: (1) After rebreathing, cortical-systemic coherence could be predicted from the amplitude of the heart rate (strong negative correlation). (2) After breath-holding, the same observation was made (moderate negative correlation). (3) After hyperventilation, no significant effect was observed. (4) These effects were found only in the frequency range of very low-frequency oscillations. The presented findings highlight a distinct role of rebreathing in predicting cortical-systemic coupling based on heart rate changes, which may represents a measure of affective states in the brain. The applied multimodal assessment of hemodynamic and systemic physiological measures during respiratory challenges may therefore have potential applications in the differentiation between physiological and pathological respiratory behavior.

A decade of imaging surgeons' brain function (part II): A systematic review of applications for technical and nontechnical skills assessment

BACKGROUND

Functional neuroimaging technologies enable assessment of operator brain function and can deepen our understanding of skills learning, ergonomic optima, and cognitive processes in surgeons. Although there has been a critical mass of data detailing surgeons' brain function, this literature has not been reviewed systematically.

METHODS

A systematic search of original neuroimaging studies assessing surgeons' brain function and published up until November 2016 was conducted using Medline, Embase, and PsycINFO databases.

RESULTS

Twenty-seven studies fulfilled the inclusion criteria, including 3 feasibility studies, 14 studies exploring the neural correlates of technical skill acquisition, and the remainder investigating brain function in the context of intraoperative decision-making (n = 1), neurofeedback training (n = 1), robot-assisted technology (n = 5), and surgical teaching (n = 3). Early stages of learning open surgical tasks (knot-tying) are characterized by prefrontal cortical activation, which subsequently attenuates with deliberate practice. However, with complex laparoscopic skills (intracorporeal suturing), prefrontal cortical engagement requires substantial training, and attenuation occurs over a longer time course, after years of refinement. Neurofeedback and interventions that improve neural efficiency may enhance technical performance and skills learning.

CONCLUSION

Imaging surgeons' brain function has identified neural signatures of expertise that might help inform objective assessment and selection processes. Interventions that improve neural efficiency may target skill-specific brain regions and augment surgical performance.

A decade of imaging surgeons' brain function (part I): Terminology, techniques, and clinical translation

BACKGROUND

Functional neuroimaging has the potential to deepen our understanding of technical and nontechnical skill acquisition in surgeons, particularly as established assessment tools leave unanswered questions about inter-operator differences in ability that seem independent of experience.

METHODS

In this first of a 2-part article, we aim to utilize our experience in neuroimaging surgeons to orientate the nonspecialist reader to the principles of brain imaging. Terminology commonly used in brain imaging research is explained, placing emphasis on the "activation response" to an surgical task and its effect on local cortical hemodynamic parameters (neurovascular coupling).

RESULTS

Skills learning and subsequent consolidation and refinement through practice lead to reorganization of the functional architecture of the brain (known as "neuroplasticity"), evidenced by changes in the strength of regional activation as well as alterations in connectivity between brain regions, culminating in more efficient use of neural resources during task performance.

CONCLUSION

Currently available neuroimaging techniques that either directly (ie, measure electrical activity) or indirectly (ie, measure tissue hemodynamics) assess brain function are discussed. Finally, we highlight the important practical considerations when conducting brain imaging research in surgeons.

Prefrontal activation may predict working-memory training gain in normal aging and mild cognitive impairment

Cognitive training has been shown to result in improved behavioral performance in normal aging and mild cognitive impairment (MCI), yet little is known about the neural correlates of cognitive plasticity, or about individual differences in responsiveness to cognitive training. In this study, 21 healthy older adults and 14 patients with MCI received five weeks of adaptive computerized working-memory (WM) training. Before and after training, functional Near-Infrared Spectroscopy (fNIRS) was used to assess the hemodynamic response in left and right prefrontal cortex during performance of a verbal n-back task with varying levels of WM load. After training, healthy older adults demonstrated decreased prefrontal activation at high WM load, which may indicate increased processing efficiency. Although MCI patients showed improved behavioral performance at low WM load after training, no evidence was found for training-related changes in prefrontal activation. Whole-group analyses showed that a relatively strong hemodynamic response at low WM load was related to worse behavioral performance, while a relatively strong hemodynamic response at high WM load was related to higher training gain. Therefore, a 'youth-like' prefrontal activation pattern at older age may be associated with better behavioral outcome and cognitive plasticity.

Modelling confounding effects from extracerebral contamination and systemic factors on functional near-infrared spectroscopy

Haemodynamics-based neuroimaging is widely used to study brain function. Regional blood flow changes characteristic of neurovascular coupling provide an important marker of neuronal activation. However, changes in systemic physiological parameters such as blood pressure and concentration of CO2 can also affect regional blood flow and may confound haemodynamics-based neuroimaging. Measurements with functional near-infrared spectroscopy (fNIRS) may additionally be confounded by blood flow and oxygenation changes in extracerebral tissue layers. Here we investigate these confounds using an extended version of an existing computational model of cerebral physiology, ‘BrainSignals’. Our results show that confounding from systemic physiological factors is able to produce misleading haemodynamic responses in both positive and negative directions. By applying the model to data from previous fNIRS studies, we demonstrate that such potentially deceptive responses can indeed occur in at least some experimental scenarios. It is therefore important to record the major potential confounders in the course of fNIRS experiments. Our model may then allow the observed behaviour to be attributed among the potential causes and hence reduce identification errors.

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Confounding of fNIRS haemoglobin signals is simulated using a computational model.

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Model is extended to simulate scalp haemodynamics.

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Changes in blood pressure and CO₂ can mimic and mask functional activation.

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Experimental recording of systemic factors is recommended to aid interpretation.

False positives and false negatives in functional near-infrared spectroscopy: issues, challenges, and the way forward

We highlight a significant problem that needs to be considered and addressed when performing functional near-infrared spectroscopy (fNIRS) studies, namely the possibility of inadvertently measuring fNIRS hemodynamic responses that are not due to neurovascular coupling. These can be misinterpreted as brain activity, i.e., "false positives" (errors caused by wrongly assigning a detected hemodynamic response to functional brain activity), or mask brain activity, i.e., "false negatives" (errors caused by wrongly assigning a not observed hemodynamic response in the presence of functional brain activity). Here, we summarize the possible physiological origins of these issues and suggest ways to avoid and remove them.

False positives and false negatives in functional near-infrared spectroscopy: issues, challenges, and the way forward

We highlight a significant problem that needs to be considered and addressed when performing functional near-infrared spectroscopy (fNIRS) studies, namely the possibility of inadvertently measuring fNIRS hemodynamic responses that are not due to neurovascular coupling. These can be misinterpreted as brain activity, i.e., "false positives" (errors caused by wrongly assigning a detected hemodynamic response to functional brain activity), or mask brain activity, i.e., "false negatives" (errors caused by wrongly assigning a not observed hemodynamic response in the presence of functional brain activity). Here, we summarize the possible physiological origins of these issues and suggest ways to avoid and remove them.

Dynamic filtering improves attentional state prediction with fNIRS

Brain activity can predict a person's level of engagement in an attentional task. However, estimates of brain activity are often confounded by measurement artifacts and systemic physiological noise. The optimal method for filtering this noise - thereby increasing such state prediction accuracy - remains unclear. To investigate this, we asked study participants to perform an attentional task while we monitored their brain activity with functional near infrared spectroscopy (fNIRS). We observed higher state prediction accuracy when noise in the fNIRS hemoglobin [Hb] signals was filtered with a non-stationary (adaptive) model as compared to static regression (84% ± 6% versus 72% ± 15%).

Tutorial on platform for optical topography analysis tools

Optical topography/functional near-infrared spectroscopy (OT/fNIRS) is a functional imaging technique that noninvasively measures cerebral hemoglobin concentration changes caused by neural activities. The fNIRS method has been extensively implemented to understand the brain activity in many applications, such as neurodisorder diagnosis and treatment, cognitive psychology, and psychiatric status evaluation. To assist users in analyzing fNIRS data with various application purposes, we developed a software called platform for optical topography analysis tools (POTATo). We explain how to handle and analyze fNIRS data in the POTATo package and systematically describe domain preparation, temporal preprocessing, functional signal extraction, statistical analysis, and data/result visualization for a practical example of working memory tasks. This example is expected to give clear insight in analyzing data using POTATo. The results specifically show the activated dorsolateral prefrontal cortex is consistent with previous studies. This emphasizes analysis robustness, which is required for validating decent preprocessing and functional signal interpretation. POTATo also provides a self-developed plug-in feature allowing users to create their own functions and incorporate them with established POTATo functions. With this feature, we continuously encourage users to improve fNIRS analysis methods. We also address the complications and resolving opportunities in signal analysis.

Simultaneous fNIRS and thermal infrared imaging during cognitive task reveal autonomic correlates of prefrontal cortex activity

Functional Near Infrared-Spectroscopy (fNIRS) represents a powerful tool to non-invasively study task-evoked brain activity. fNIRS assessment of cortical activity may suffer for contamination by physiological noises of different origin (e.g. heart beat, respiration, blood pressure, skin blood flow), both task-evoked and spontaneous. Spontaneous changes occur at different time scales and, even if they are not directly elicited by tasks, their amplitude may result task-modulated. In this study, concentration changes of hemoglobin were recorded over the prefrontal cortex while simultaneously recording the facial temperature variations of the participants through functional infrared thermal (fIR) imaging. fIR imaging provides touch-less estimation of the thermal expression of peripheral autonomic. Wavelet analysis revealed task-modulation of the very low frequency (VLF) components of both fNIRS and fIR signals and strong coherence between them. Our results indicate that subjective cognitive and autonomic activities are intimately linked and that the VLF component of the fNIRS signal is affected by the autonomic activity elicited by the cognitive task. Moreover, we showed that task-modulated changes in vascular tone occur both at a superficial and at larger depth in the brain. Combined use of fNIRS and fIR imaging can effectively quantify the impact of VLF autonomic activity on the fNIRS signals.

Using Fiberless, Wearable fNIRS to Monitor Brain Activity in Real-world Cognitive Tasks

Functional Near Infrared Spectroscopy (fNIRS) is a neuroimaging technique that uses near-infrared light to monitor brain activity. Based on neurovascular coupling, fNIRS is able to measure the haemoglobin concentration changes secondary to neuronal activity. Compared to other neuroimaging techniques, fNIRS represents a good compromise in terms of spatial and temporal resolution. Moreover, it is portable, lightweight, less sensitive to motion artifacts and does not impose significant physical restraints. It is therefore appropriate to monitor a wide range of cognitive tasks (e.g., auditory, gait analysis, social interaction) and different age populations (e.g., new-borns, adults, elderly people). The recent development of fiberless fNIRS devices has opened the way to new applications in neuroscience research. This represents a unique opportunity to study functional activity during real-world tests, which can be more sensitive and accurate in assessing cognitive function and dysfunction than lab-based tests. This study explored the use of fiberless fNIRS to monitor brain activity during a real-world prospective memory task. This protocol is performed outside the lab and brain haemoglobin concentration changes are continuously measured over the prefrontal cortex while the subject walks around in order to accomplish several different tasks.

Optimized multimodal functional magnetic resonance imaging/near-infrared spectroscopy probe for ultrahigh-resolution mapping

Functional near-infrared spectroscopy (fNIRS) is an increasingly important noninvasive method in neuroscience due to its high temporal resolution and ability to independently measure oxy- and deoxy-hemoglobin. However, the relatively low spatial resolution of fNIRS makes it difficult to relate this signal to underlying anatomy. Simultaneous functional magnetic resonance imaging (fMRI) can complement fNIRS with superior spatial resolution and the ability to image the entire brain, providing additional information to improve fNIRS localization. However, current simultaneous fMRI/fNIRS acquisition methods are not optimal, due to the poor physical compatibility of existing MR coils and fNIRS optodes. Here, we present a technique to manufacture a true multimodal fMRI/fNIRS probe in which both modalities can be used with maximal sensitivity. To achieve this, we designed custom MR coils with integral fNIRS optodes using three-dimensional printing. This multimodal probe can be used to optimize spatial ([Formula: see text]) and temporal resolution (2.5 Hz) of fMRI, and it provides maximal MRI sensitivity, while allowing for high flexibility in the location and density of fNIRS optodes within the area of interest. Phantom and human data are shown to confirm the improvement in sensitivity in both modalities. This probe shows promise for addressing fundamental questions of the relation of fNIRS to physiology.

Time-frequency dynamics of the sum of intra- and extracerebral hemodynamic functional connectivity during resting-state and respiratory challenges assessed by multimodal functional near-infrared spectroscopy

Monitoring respiratory processes is important for evaluating neuroimaging data, given their influence on time-frequency dynamics of intra- and extracerebral hemodynamics. Here we investigated the time-frequency dynamics of the sum of intra- and extracerebral hemodynamic functional connectivity states during hypo- and hypercapnia by using three different respiratory challenge tasks (i.e., hyperventilation, breath-holding, and rebreathing) compared to resting-state. The sum of intra- and extracerebral hemodynamic responses were assessed using functional near-infrared spectroscopy (fNIRS) within two regions of interest (i.e., the dorsolateral and the medial prefrontal cortex). Time-frequency fNIRS analysis was performed based on wavelet transform coherence to quantify functional connectivity in terms of positive and negative phase-coupling within each region of interest. Physiological measures were assessed in the form of partial end-tidal carbon dioxide, heart rate, arterial tissue oxygen saturation, and respiration rate. We found that the three respiration challenges modulated time-frequency dynamics differently with respect to resting-state: 1) Hyperventilation and breath-holding exhibited inverse patterns of positive and negative phase-coupling. 2) In contrast, rebreathing had no significant effect. 3) Low-frequency oscillations contributed to a greater extent to time-frequency dynamics compared to high-frequency oscillations. The results highlight that there exist distinct differences in time-frequency dynamics of the sum of intra- and extracerebral functional connectivity not only between hypo- (hyperventilation) and hypercapnia but also between different states of hypercapnia (breath-holding versus rebreathing). This suggests that a multimodal assessment of intra-/extracerebral and systemic physiological changes during respiratory challenges compared to resting-state may have potential use in the differentiation between physiological and pathological respiratory behavior accompanied by the psycho-physiological state of a human.

A hybrid BCI based on EEG and fNIRS signals improves the performance of decoding motor imagery of both force and speed of hand clenching

OBJECTIVE

In order to increase the number of states classified by a brain-computer interface (BCI), we utilized a motor imagery task where subjects imagined both force and speed of hand clenching.

APPROACH

The BCI utilized simultaneously recorded electroencephalographic (EEG) and functional near-infrared spectroscopy (fNIRS) signals. The time-phase-frequency feature was extracted from EEG, whereas the HbD [the difference of oxy-hemoglobin (HbO) and deoxy-hemoglobin (Hb)] feature was used to improve the classification accuracy of fNIRS. The EEG and fNIRS features were combined and optimized using the joint mutual information (JMI) feature selection criterion; then the extracted features were classified with the extreme learning machines (ELMs).

MAIN RESULTS

In this study, the averaged classification accuracy of EEG signals achieved by the time-phase-frequency feature improved by 7%, to 18%, more than the single-type feature, and improved by 15% more than common spatial pattern (CSP) feature. The HbD feature of fNIRS signals improved the accuracy by 1%, to 4%, more than Hb, HbO, or HbT (total hemoglobin). The EEG-fNIRS feature for decoding motor imagery of both force and speed of hand clenching achieved an accuracy of 89% ± 2%, and improved the accuracy by 1% to 5% more than the sole EEG or fNIRS feature.

SIGNIFICANCE

Our novel motor imagery paradigm improves BCI performance by increasing the number of extracted commands. Both the time-phase-frequency and the HbD feature improve the classification accuracy of EEG and fNIRS signals, respectively, and the hybrid EEG-fNIRS technique achieves a higher decoding accuracy for two-class motor imagery, which may provide the framework for future multi-modal online BCI systems.

Dynamic causal modelling for functional near-infrared spectroscopy

Functional near-infrared spectroscopy (fNIRS) is an emerging technique for measuring changes in cerebral hemoglobin concentration via optical absorption changes. Although there is great interest in using fNIRS to study brain connectivity, current methods are unable to infer the directionality of neuronal connections. In this paper, we apply Dynamic Causal Modelling (DCM) to fNIRS data. Specifically, we present a generative model of how observed fNIRS data are caused by interactions among hidden neuronal states. Inversion of this generative model, using an established Bayesian framework (variational Laplace), then enables inference about changes in directed connectivity at the neuronal level. Using experimental data acquired during motor imagery and motor execution tasks, we show that directed (i.e., effective) connectivity from the supplementary motor area to the primary motor cortex is negatively modulated by motor imagery, and this suppressive influence causes reduced activity in the primary motor cortex during motor imagery. These results are consistent with findings of previous functional magnetic resonance imaging (fMRI) studies, suggesting that the proposed method enables one to infer directed interactions in the brain mediated by neuronal dynamics from measurements of optical density changes.

Linear regression models and k-means clustering for statistical analysis of fNIRS data

We propose a new algorithm, based on a linear regression model, to statistically estimate the hemodynamic activations in fNIRS data sets. The main concern guiding the algorithm development was the minimization of assumptions and approximations made on the data set for the application of statistical tests. Further, we propose a K-means method to cluster fNIRS data (i.e. channels) as activated or not activated. The methods were validated both on simulated and in vivo fNIRS data. A time domain (TD) fNIRS technique was preferred because of its high performances in discriminating cortical activation and superficial physiological changes. However, the proposed method is also applicable to continuous wave or frequency domain fNIRS data sets.

Greater contribution of cerebral than extracerebral hemodynamics to near-infrared spectroscopy signals for functional activation and resting-state connectivity in infants

While near-infrared spectroscopy (NIRS) has been increasingly applied to neuroimaging and functional connectivity studies in infants, it has not been quantitatively examined as to what extent the deep tissue (such as cerebral tissue) as opposed to shallow tissue (such as scalp), contributes to NIRS signals measured in infants. A method for separating the effects of deep- and shallow-tissue layers was applied to data of nine sleeping three-month-old infants who had been exposed to 3-s speech sounds or silence (i.e., resting state) and whose hemodynamic changes over their bilateral temporal cortices had been measured by using an NIRS system with multiple source-detector (S-D) distances. The deep-layer contribution was found to be large during resting [67% at S-D 20 mm, 78% at S-D 30 mm for oxygenated hemoglobin (oxy-Hb)] as well as during the speech condition (72% at S-D 20 mm, 82% at S-D 30 mm for oxy-Hb). A left-right connectivity analysis showed that correlation coefficients between left and right channels did not differ between original- and deep-layer signals under no-stimulus conditions and that of original- and deep-layer signals were larger than those of the shallow layer. These results suggest that NIRS signals obtained in infants with appropriate S-D distances largely reflected cerebral hemodynamic changes.

The relationship between sympathetic nervous activity and cerebral hemodynamics and oxygenation: a study using skin conductance measurement and functional near-infrared spectroscopy

Simultaneous measurement of cortical and peripheral affective processing is relevant in many neuroscientific research fields. The aim was to investigate the influence of different affective task components on the coherence between cortical hemodynamic signals and peripheral autonomic skin potential signals. Seventeen healthy subjects performed four tasks, i.e. a finger-tapping task, a hyperventilation task, a working memory task and a risk-taking task. Cortical hemodynamic responses were measured using functional near-infrared spectroscopy (fNIRS). Peripheral skin conductance responses (SCRs) were assessed using electrodermal activity (EDA). Coherence between the fNIRS and the EDA time series was calculated using the S transform coherence (STC), a method that tests the temporal dynamics between two time series for consistent phase relationships and thus for a functional relationship. The following characteristics of fNIRS-EDA coherence were observed: (1) Simple motor performance was not a contributor to enhanced coherence, as revealed by the finger-tapping task. (2) Changes in respiration rate and/or heart rate acted as relevant contributors to enhanced coherence, as revealed by the hyperventilation task. (3) Working memory performance did not induce changes in coherence, (4) whereas risk-taking behavior was a significant contributor to enhanced coherence. (5) Based on all four tasks, we also observed that coherence may be subject to habituation or sensitization effects over the trial-to-trial course of a task. Increased fNIRS-EDA coherence may be an indicator of a psychophysiological link between the underlying cortical and peripheral affective systems. Our findings are relevant for several neuroscientific research areas seeking to evaluate the interplay between cortical and peripheral affective performance.

Investigation of frontal lobe activation with fNIRS and systemic changes during video gaming

Frontal lobe activation caused by tasks such as videogames can be investigated using multichannel near-infrared spectroscopy (fNIRS), sometimes called optical topography. The aims of this study are to investigate the effects of video gaming (fighting and puzzle games) in the brain and the systemic physiology and to determine whether systemic responses during the gaming task are associated with the measurement of localised cerebral haemodynamic changes as measured by fNIRS. We used a continuous-wave 8-channel fNIRS system to measure the changes in concentration of oxy-haemoglobin (HbO2) and deoxy-haemoglobin (HHb) and changes in total haemoglobin (ΔtHb = ΔHbO2 + ΔHHb) over the frontal lobe in 30 healthy volunteers. The Portapres system was used to measure mean blood pressure (MBP) and heart rate (HR), and a laser Doppler was employed to measure the changes in scalp blood flow (or flux). Even though we observed significant changes in systemic variables during gaming, in particular in scalp flow, we also managed to see localised activation patterns over the frontal polar (FP1) region. However, in some channels over the frontal lobe, we also observed significant correlations between the HbO2 and systemic variables.

Separation of superficial and cerebral hemodynamics using a single distance time-domain NIRS measurement

In functional near-infrared spectroscopy (fNIRS) superficial hemodynamics can mask optical signals related to brain activity. We present a method to separate superficial and cerebral absorption changes based on the analysis of changes in moments of time-of-flight distributions and a two-layered model. The related sensitivity factors were calculated from individual optical properties. The method was validated on a two-layer liquid phantom. Absorption changes in the lower layer were retrieved with an accuracy better than 20%. The method was successfully applied to in vivo data and compared to the reconstruction of homogeneous absorption changes.

Monitoring cerebral oxygenation during balloon occlusion with multichannel NIRS

We report on oxygenation changes noninvasively recorded by multichannel continuous-wave near infrared spectroscopy (CW-NIRS) during endovascular neuroradiologic interventions requiring temporary balloon occlusion of arteries supplying the cerebral circulation. Digital subtraction angiography (DSA) provides reference data on the site, timing, and effectiveness of the flow stagnation as well as on the amount and direction of collateral circulation. This setting allows us to relate CW-NIRS findings to brain specific perfusion changes. We focused our analysis on the transition from normal perfusion to vessel occlusion, i.e., before hypoxia becomes clinically apparent. The localization of the maximal response correlated either with the core (occlusion of the middle cerebral artery) or with the watershed areas (occlusion of the internal carotid artery) of the respective vascular territories. In one patient with clinically and angiographically confirmed insufficient collateral flow during carotid artery occlusion, the total hemoglobin concentration became significantly asymmetric, with decreased values in the ipsilateral watershed area and contralaterally increased values. Multichannel CW-NIRS monitoring might serve as an objective and early predictive marker of critical perfusion changes during interventions-to prevent hypoxic damage of the brain. It also might provide valuable human reference data on oxygenation changes as they typically occur during acute stroke.

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.

A new methodical approach in neuroscience: assessing inter-personal brain coupling using functional near-infrared imaging (fNIRI) hyperscanning

Since the first demonstration of how to simultaneously measure brain activity using functional magnetic resonance imaging (fMRI) on two subjects about 10 years ago, a new paradigm in neuroscience is emerging: measuring brain activity from two or more people simultaneously, termed “hyperscanning”. The hyperscanning approach has the potential to reveal inter-personal brain mechanisms underlying interaction-mediated brain-to-brain coupling. These mechanisms are engaged during real social interactions, and cannot be captured using single-subject recordings. In particular, functional near-infrared imaging (fNIRI) hyperscanning is a promising new method, offering a cost-effective, easy to apply and reliable technology to measure inter-personal interactions in a natural context. In this short review we report on fNIRI hyperscanning studies published so far and summarize opportunities and challenges for future studies.

Exploration of cerebral activation using hemodynamic modality separation method in high-density multichannel fNIRS

Hemodynamic modality separation (HMS) is a method for separating the functional near infrared spectroscopy (fNIRS) signal into the cerebral functional and systemic physiological components based on their difference in hemodynamic modalities: 1) Changes in oxyhemoglobin and deoxyhemoglobin (ΔHbO and ΔHbR) in the cerebral capillaries during neural activation negatively correlate with each other; 2) Other physiological hemodynamic changes originating from major vessels cause a positive correlation in ΔHbO and ΔHbR. We applied this simple method to a high-density multichannel (HDM) fNIRS measurement. In the case of functional signal detection in the parietal area of human adults during a single-sided finger-tapping task, conventional fNIRS data showed very unclear signal laterality, while the functional components separated by the HMS method highly localized at the contralateral area of the tapping side. Using the HMS method for HDM NIRS, we successfully explored cerebral activation in the parietal area. This is the first report that HMS method was utilized for the exploratory detection of cerebral activity.

Effect of task-related extracerebral circulation on diffuse optical tomography: experimental data and simulations on the forehead

The effect of task-related extracerebral circulatory changes on diffuse optical tomography (DOT) of brain activation was evaluated using experimental data from 14 healthy human subjects and computer simulations. Total hemoglobin responses to weekday-recitation, verbal-fluency, and hand-motor tasks were measured with a high-density optode grid placed on the forehead. The tasks caused varying levels of mental and physical stress, eliciting extracerebral circulatory changes that the reconstruction algorithm was unable to fully distinguish from cerebral hemodynamic changes, resulting in artifacts in the brain activation images. Crosstalk between intra- and extracranial layers was confirmed by the simulations. The extracerebral effects were attenuated by superficial signal regression and depended to some extent on the heart rate, thus allowing identification of hemodynamic changes related to brain activation during the verbal-fluency task. During the hand-motor task, the extracerebral component was stronger, making the separation less clear. DOT provides a tool for distinguishing extracerebral components from signals of cerebral origin. Especially in the case of strong task-related extracerebral circulatory changes, however, sophisticated reconstruction methods are needed to eliminate crosstalk artifacts.

Quantitative evaluation of deep and shallow tissue layers' contribution to fNIRS signal using multi-distance optodes and independent component analysis

To quantify the effect of absorption changes in the deep tissue (cerebral) and shallow tissue (scalp, skin) layers on functional near-infrared spectroscopy (fNIRS) signals, a method using multi-distance (MD) optodes and independent component analysis (ICA), referred to as the MD-ICA method, is proposed. In previous studies, when the signal from the shallow tissue layer (shallow signal) needs to be eliminated, it was often assumed that the shallow signal had no correlation with the signal from the deep tissue layer (deep signal). In this study, no relationship between the waveforms of deep and shallow signals is assumed, and instead, it is assumed that both signals are linear combinations of multiple signal sources, which allows the inclusion of a "shared component" (such as systemic signals) that is contained in both layers. The method also assumes that the partial optical path length of the shallow layer does not change, whereas that of the deep layer linearly increases along with the increase of the source-detector (S-D) distance. Deep- and shallow-layer contribution ratios of each independent component (IC) are calculated using the dependence of the weight of each IC on the S-D distance. Reconstruction of deep- and shallow-layer signals are performed by the sum of ICs weighted by the deep and shallow contribution ratio. Experimental validation of the principle of this technique was conducted using a dynamic phantom with two absorbing layers. Results showed that our method is effective for evaluating deep-layer contributions even if there are high correlations between deep and shallow signals. Next, we applied the method to fNIRS signals obtained on a human head with 5-, 15-, and 30-mm S-D distances during a verbal fluency task, a verbal working memory task (prefrontal area), a finger tapping task (motor area), and a tetrametric visual checker-board task (occipital area) and then estimated the deep-layer contribution ratio. To evaluate the signal separation performance of our method, we used the correlation coefficients of a laser-Doppler flowmetry (LDF) signal and a nearest 5-mm S-D distance channel signal with the shallow signal. We demonstrated that the shallow signals have a higher temporal correlation with the LDF signals and with the 5-mm S-D distance channel than the deep signals. These results show the MD-ICA method can discriminate between deep and shallow signals.

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.

A working memory deficit among dyslexic readers with no phonological impairment as measured using the n-back task: an fNIR study

Data indicated that dyslexic individuals exhibited difficulties on tasks involving Working Memory (WM). Previous studies have suggested that these deficits stem from impaired processing in the Phonological Loop (PL). The PL impairment was connected to poor phonological processing. However, recent data has pointed to the Central Executive (CE) system as another source of WM deficit in dyslexic readers. This opened a debate whether the WM deficit stems solely from PL or can also be seen as an outcome of poor CE processing. In an attempt to verify this question, the current study compared adult skilled and compensated dyslexic readers with no impairment of phonological skills. The participants' PL and CE processing were tested by using the fNIR device attached to the frontal lobe and measured the changes in brain oxygen values when performing N-back task. As it was previously suggested, the N = 0 represented PL and N = 1 to 3 represent CE processing. It was hypothesized that dyslexic readers who show non-impaired phonological skills will exhibit deficits mainly in the CE subsystem and to a lesser extent in the PL. Results indicated that the two reading level groups did not differ in their accuracy and reaction times in any of the N-Back conditions. However, the dyslexic readers demonstrated significant lower maximum oxyHb values in the upper left frontal lobe, mainly caused due to a significant lower activity under the N = 1 condition. Significant task effects were found in the medial left hemisphere, and the high medial right hemisphere. In addition, significant correlations between fNIR-features, reading performance and speed of processing were found. The higher oxyHb values, the better reading and speed of processing performance obtained. The results of the current study support the hypothesis that at least for the group of dyslexics with non-impaired PL, WM deficit stems from poor CE activity.

End-tidal CO2: an important parameter for a correct interpretation in functional brain studies using speech tasks

The aim was to investigate the effect of different speech tasks, i.e. recitation of prose (PR), alliteration (AR) and hexameter (HR) verses and a control task (mental arithmetic (MA) with voicing of the result on end-tidal CO2 (PETCO2), cerebral hemodynamics and oxygenation. CO2 levels in the blood are known to strongly affect cerebral blood flow. Speech changes breathing pattern and may affect CO2 levels. Measurements were performed on 24 healthy adult volunteers during the performance of the 4 tasks. Tissue oxygen saturation (StO2) and absolute concentrations of oxyhemoglobin ([O2Hb]), deoxyhemoglobin ([HHb]) and total hemoglobin ([tHb]) were measured by functional near-infrared spectroscopy (fNIRS) and PETCO2 by a gas analyzer. Statistical analysis was applied to the difference between baseline before the task, 2 recitation and 5 baseline periods after the task. The 2 brain hemispheres and 4 tasks were tested separately. A significant decrease in PETCO2 was found during all 4 tasks with the smallest decrease during the MA task. During the recitation tasks (PR, AR and HR) a statistically significant (p<0.05) decrease occurred for StO2 during PR and AR in the right prefrontal cortex (PFC) and during AR and HR in the left PFC. [O2Hb] decreased significantly during PR, AR and HR in both hemispheres. [HHb] increased significantly during the AR task in the right PFC. [tHb] decreased significantly during HR in the right PFC and during PR, AR and HR in the left PFC. During the MA task, StO2 increased and [HHb] decreased significantly during the MA task. We conclude that changes in breathing (hyperventilation) during the tasks led to lower CO2 pressure in the blood (hypocapnia), predominantly responsible for the measured changes in cerebral hemodynamics and oxygenation. In conclusion, our findings demonstrate that PETCO2 should be monitored during functional brain studies investigating speech using neuroimaging modalities, such as fNIRS, fMRI to ensure a correct interpretation of changes in hemodynamics and oxygenation.

Systematic investigation of changes in oxidized cerebral cytochrome c oxidase concentration during frontal lobe activation in healthy adults

Using transcranial near-infrared spectroscopy (NIRS) to measure changes in the redox state of cerebral cytochrome c oxidase (Δ[oxCCO]) during functional activation in healthy adults is hampered by instrumentation and algorithm issues. This study reports the Δ[oxCCO] response measured in such a setting and investigates possible confounders of this measurement. Continuous frontal lobe NIRS measurements were collected from 11 healthy volunteers during a 6-minute anagram-solving task, using a hybrid optical spectrometer (pHOS) that combines multi-distance frequency and broadband components. Only data sets showing a hemodynamic response consistent with functional activation were interrogated for a Δ[oxCCO] response. Simultaneous systemic monitoring data were also available. Possible influences on the Δ[oxCCO] response were systematically investigated and there was no effect of: 1) wavelength range chosen for fitting the measured attenuation spectra; 2) constant or measured, with the pHOS in real-time, differential pathlength factor; 3) systemic hemodynamic changes during functional activation; 4) changes in optical scattering during functional activation. The Δ[oxCCO] response measured in the presence of functional activation was heterogeneous, with the majority of subjects showing significant increase in oxidation, but others having a decrease. We conclude that the heterogeneity in the Δ[oxCCO] response is physiological and not induced by confounding factors in the measurements.

Task-related component analysis for functional neuroimaging and application to near-infrared spectroscopy data

Reproducibility of experimental results lies at the heart of scientific disciplines. Here we propose a signal processing method that extracts task-related components by maximizing the reproducibility during task periods from neuroimaging data. Unlike hypothesis-driven methods such as general linear models, no specific time courses are presumed, and unlike data-driven approaches such as independent component analysis, no arbitrary interpretation of components is needed. Task-related components are constructed by a linear, weighted sum of multiple time courses, and its weights are optimized so as to maximize inter-block correlations (CorrMax) or covariances (CovMax). Our analysis method is referred to as task-related component analysis (TRCA). The covariance maximization is formulated as a Rayleigh-Ritz eigenvalue problem, and corresponding eigenvectors give candidates of task-related components. In addition, a systematic statistical test based on eigenvalues is proposed, so task-related and -unrelated components are classified objectively and automatically. The proposed test of statistical significance is found to be independent of the degree of autocorrelation in data if the task duration is sufficiently longer than the temporal scale of autocorrelation, so TRCA can be applied to data with autocorrelation without any modification. We demonstrate that simple extensions of TRCA can provide most distinctive signals for two tasks and can integrate multiple modalities of information to remove task-unrelated artifacts. TRCA was successfully applied to synthetic data as well as near-infrared spectroscopy (NIRS) data of finger tapping. There were two statistically significant task-related components; one was a hemodynamic response, and another was a piece-wise linear time course. In summary, we conclude that TRCA has a wide range of applications in multi-channel biophysical and behavioral measurements.

Dynamic phantom with two stage-driven absorbers for mimicking hemoglobin changes in superficial and deep tissues

In near-infrared spectroscopy (NIRS) for monitoring brain activity and cerebral functional connectivity, the effect of superficial tissue on NIRS signals needs to be considered. Although some methods for determining the effect of scalp and brain have been proposed, direct validation of the methods has been difficult because the actual absorption changes cannot be known. In response to this problem, we developed a dynamic phantom that mimics hemoglobin changes in superficial and deep tissues, thus allowing us to experimentally validate the methods. Two absorber layers are independently driven with two one-axis automatic stages. We can use the phantom to design any type of waveform (e.g., brain activity or systemic fluctuation) of absorption change, which can then be reproducibly measured. To determine the effectiveness of the phantom, we used it for a multiple source-detector distance measurement. We also investigated the performance of a subtraction method with a short-distance regressor. The most accurate lower-layer change was obtained when a shortest-distance channel was used. Furthermore, when an independent component analysis was applied to the same data, the extracted components were in good agreement with the actual signals. These results demonstrate that the proposed phantom can be used for evaluating methods of discriminating the effects of superficial tissue.

Magnetic-stimulation-related physiological artifacts in hemodynamic near-infrared spectroscopy signals

Hemodynamic responses evoked by transcranial magnetic stimulation (TMS) can be measured with near-infrared spectroscopy (NIRS). This study demonstrates that cerebral neuronal activity is not their sole contributor. We compared bilateral NIRS responses following brain stimulation to those from the shoulders evoked by shoulder stimulation and contrasted them with changes in circulatory parameters. The left primary motor cortex of ten subjects was stimulated with 8-s repetitive TMS trains at 0.5, 1, and 2 Hz at an intensity of 75% of the resting motor threshold. Hemoglobin concentration changes were measured with NIRS on the stimulated and contralateral hemispheres. The photoplethysmograph (PPG) amplitude and heart rate were recorded as well. The left shoulder of ten other subjects was stimulated with the same protocol while the hemoglobin concentration changes in both shoulders were measured. In addition to PPG amplitude and heart rate, the pulse transit time was recorded. The brain stimulation reduced the total hemoglobin concentration (HbT) on the stimulated and contralateral hemispheres. The shoulder stimulation reduced HbT on the stimulated shoulder but increased it contralaterally. The waveforms of the HbT responses on the stimulated hemisphere and shoulder correlated strongly with each other (r = 0.65–0.87). All circulatory parameters were also affected. The results suggest that the TMS-evoked NIRS signal includes components that do not result directly from cerebral neuronal activity. These components arise from local effects of TMS on the vasculature. Also global circulatory effects due to arousal may affect the responses. Thus, studies involving TMS-evoked NIRS responses should be carefully controlled for physiological artifacts and effective artifact removal methods are needed to draw inferences about TMS-evoked brain activity.

Intra- and extra-cranial effects of transient blood pressure changes on brain near-infrared spectroscopy (NIRS) measurements

Brain near-infrared spectroscopy (NIRS) is an emerging neurophysiological tool that combines straightforward activity localization with cost–economy, portability and patient compatibility. NIRS is proving its empirical utility across specific cognitive and emotional paradigms. However, a potential limitation is that it is not only sensitive to haemodynamic changes taking place in the cortex, and task-related cardiovascular responses expressed in the perfusion of extracranial layers may be confounding. Existing literature reports correlations between brain NIRS and systemic blood pressure, yet it falls short of establishing whether in normal participants the blood pressure changes encountered in experimental settings can have confounding effects. Here, we tested this hypothesis by performing two experimental manipulations while recording from superficial occipital cortex, encompassing striate and extrastriate regions. Visual stimulation with reversing chequerboards evoked cortical haemodynamic responses. Simultaneously and independently, transient systemic blood pressure changes were generated through rapid arm-raising. Shallow-penetration NIRS recordings, probing only extra-cerebral tissues, highlighted close haemodynamic coupling with blood pressure. A different coupling pattern was observed in deep-penetration recordings directed at haemodynamic signals from visual cortex. In absence of blood-pressure changes, NIRS signals tracked differences in visual stimulus duration. However when blood pressure was actively manipulated, this effect was absent and replaced by a very large pressure-related response. Our observations demonstrate that blood pressure fluctuations can exert confounding effects on brain NIRS, through expression in extracranial tissues and within the brain itself. We highlight the necessity for continuous blood pressure monitoring alongside brain NIRS, and for further research on methods to correct for physiological confounds.

Quantification of systemic interference in optical topography data during frontal lobe and motor cortex activation: an independent component analysis

Functional near-infrared optical topography (OT) is used to non-invasively measure the changes in oxygenated and deoxygenated haemoglobin (Δ[HbO2], Δ[HHb]) and hence investigate the brain haemodynamic changes, which occur in response to functional activation at specific regions of the cerebral cortex. However, when analysing functional OT data the task-related systemic changes should be taken into account.Here we used an independent component analysis (ICA) method on the OT [HbO2] signal, to determine the task-related independent components and then compared them with the systemic measurements (blood pressure, heart rate, scalp blood flow) to assess whether the components are due to systemic noise or neuronal activation. This analysis can therefore extract the true OT haemodynamic neuronal response and hence discriminate between regional activated cortical areas and global haemodynamic changes.

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.

Functional optical topography analysis using statistical parametric mapping (SPM) methodology with and without physiological confounds

Functional optical topography (OT) measures the changes in oxygenated and deoxygenated hemoglobin (HbO(2), HHb) across multiple brain sites which occur in response to neuronal activation of the cerebral cortex. However, identification of areas of cortical activation is a complex task due to intrinsic physiological noise and systemic interference and careful statistical analysis is therefore required. A total of 10 young healthy adults were studied. The activation paradigm comprised of anagrams followed by finger tapping. 12 channels of the OT system were positioned over the frontal cortex and 12 channels over the motor cortex while the systemic physiology (mean blood pressure (MBP), heart rate (HR), scalp flux) was simultaneously monitored. Analysis was done using the functional Optical Signal Analysis (fOSA) software and Statistical Parametric Mapping (SPM), where we utilized two approaches: (i) using only HbO(2) as a regressor in the general linear model (GLM) and (ii) using all of the explanatory variables (HbO(2), MBP, HR and scalp flux) as regressors. Group analysis using SPM showed significant correlation in a large number of OT channels between HbO(2) and systemic regressors; however no differences in activation areas were seen between the two approaches.