Simultaneous functional near-infrared spectroscopy and electroencephalography for monitoring of human brain activity and oxygenation: a review

A Review of Functional Near-Infrared Spectroscopy Studies of Motor and Cognitive Function in Preterm Infants

Preterm infants are vulnerable to brain injuries, and have a greater chance of experiencing neurodevelopmental disorders throughout development. Early screening for motor and cognitive functions is critical to assessing the developmental trajectory in preterm infants, especially those who may have motor or cognitive deficits. The brain imaging technology functional near-infrared spectroscopy (fNIRS) is a portable and low-cost method of assessing cerebral hemodynamics, making it suitable for large-scale use even in remote and underdeveloped areas. In this article, we review peer-reviewed, scientific fNIRS studies of motor performance, speech perception, and facial recognition in preterm infants. fNIRS provides a link between hemodynamic activity and the development of brain functions in preterm infants. Research using fNIRS has shown different patterns of hemoglobin change during some behavioral tasks in early infancy. fNIRS helps to promote our understanding of the developmental mechanisms of brain function in preterm infants when performing motor or cognitive tasks in a less-restricted environment.

A Combined EEG-fNIRS Study Investigating Mechanisms Underlying the Association between Aerobic Fitness and Inhibitory Control in Young Adults

The current evidence suggests that aerobic fitness is associated with inhibitory control of executive functioning in children and older adults. However, the relative contributions of different neurophysiological mechanisms to this relation remain unclear and have not yet been examined in young adults. The present study aimed to compare inhibitory control between high and low-fit young adult men, and to investigate a possible mediation of fitness effects by conflict monitoring (N450 component of event-related potentials) and lateralized oxygenation difference (LOD) in the DLPFC. For the present cross-sectional study, participants with different physical activity levels were recruited and divided into low-fit and high-fit participants based on relative power on the PWC170. A Stroop Color-Word task was administered and combined EEG-fNIRS was simultaneously utilized to assess the N450 and LOD, because these parameters are linked with behavioral performance. The results of the statistical analysis showed that high-fitcompared to low-fit participants showed less Stroop interference and lower negativity of the N450, whereas no difference was found for LOD. Path-analyses further revealed that the relation between aerobic fitness levels and Stroop interference was indirect and mediated by N450. In contrast, LOD was inversely correlated with Stroop interference, but did not explain the relation of aerobic fitness with behavioral performance. The present findings indicate that greater inhibitory control in high- compared to low-fit young men can be explained by more effective conflict monitoring. Moreover, young adults with left-lateralizedDLPFC oxygenation also show higher inhibitory control, but this oxygenation pattern is not influenced by aerobic fitness.

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

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

NIRS-EMG for Clinical Applications: A Systematic Review

In this review, we present an overview of the applications and computed parameters of electromyography (EMG) and near-infrared spectroscopy (NIRS) methods on patients in clinical practice. The eligible studies were those where both techniques were combined in order to assess muscle characteristics from the electrical and hemodynamic points of view. With this aim, a comprehensive screening of the literature based on related keywords in the most-used scientific data bases allowed us to identify 17 papers which met the research criteria. We also present a brief overview of the devices designed specifically for muscular applications with EMG and NIRS sensors (a total of eight papers). A critical analysis of the results of the review suggests that the combined use of EMG and NIRS on muscle has been only partially exploited for assessment and evaluation in clinical practice and, thus, this field shows promises for future developments.

Combined Monitoring-Brain Function Monitoring and Cerebral Oximetry

Peri-operative brain function monitoring is still seen by most clinicians as complex, difficult to interpret and is therefore adopted very slowly. Current available technology mainly focusses on either a processed parameter based on the electroencephalogram to titrate anesthetics and central acting agents or on cerebral oximetry, a wider term to obtain information on the cerebral oxygen balance. There is still a lack of technological offerings that allow to monitor both entities in one device. However, there is scientific evidence that it is possible to combine measurements in an algorithmic approach that allows to better manage brain function in the surgical setting. Such integrated solutions should be made available to clinicians as they are likely to optimize patient care dependent on a sound health technology assessment.

Differential pathlength factor in continuous wave functional near-infrared spectroscopy: reducing hemoglobin's cross talk in high-density recordings

Functional near-infrared spectroscopy (fNIRS) estimates the functional oscillations of oxyhemoglobin and deoxyhemoglobin in the cortex through scalp-located multiwavelength recordings. Hemoglobin oscillations are inferred through temporal changes in continuous-wave (CW) light attenuation. However, because of the diffusive multilayered head tissue structures, the photon path is longer than the source-detector separation, complicating hemoglobin evaluation. This aspect is incorporated in the modified Beer-Lambert law where the source-detector distance is multiplied by the differential pathlength factor (DPF). Since DPF estimation requires photons' time-of-flight information, DPF is assumed a priori in CW-fNIRS. Importantly, errors in the DPF spectrum induce hemoglobin cross talk, which is detrimental for fNIRS. We propose to estimate subject-specific DPF spectral dependence relying on multidistance high-density measurements. The procedure estimates the effective attenuation coefficient (EAC), which is proportional to the geometric mean of absorption and reduced scattering. Since DPF depends on the scattering-to-absorption ratio, EAC limits the spectral dependence assumption to scattering. This approach was compared to a standard frequency-domain multidistance procedure. A good association between the two methods ( r 2 = 0.69 ) was obtained. This approach could estimate low-resolution maps of the DPF spectral dependence through large field of view, high-density systems, reducing hemoglobin cross talk, and increasing fNIRS sensitivity and specificity to brain activity without instrumentation modification.

BCI Monitor Enhances Electroencephalographic and Cerebral Hemodynamic Activations During Motor Training

Motor imagery-based brain-computer interface (MI-BCI) controlling functional electrical stimulation (FES) is promising for disabled patients to restore their motor functions. However, it remains unclear how much the BCI part can contribute to the functional coupling between the brain and muscle. Specifically, whether it can enhance the cerebral activation for motor training? Here, we investigate the electroencephalographic and cerebral hemodynamic responses for MI-BCI-FES training and MI-FES training, respectively. Twelve healthy subjects were recruited in the motor training study when concurrent electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) were recorded. Compared with the MI-FES training conditions, the MI-BCI-FES could induce significantly stronger event-related desynchronization (ERD) and blood oxygen response, which demonstrates that BCI indeed plays a functional role in the closed-loop motor training. Therefore, this paper verifies the feasibility of using BCI to train motor functions in a closed-loop manner.

fNIRS improves seizure detection in multimodal EEG-fNIRS recordings

In the context of epilepsy monitoring, electroencephalography (EEG) remains the modality of choice. Functional near-infrared spectroscopy (fNIRS) is a relatively innovative modality that cannot only characterize hemodynamic profiles of seizures but also allow for long-term recordings. We employ deep learning methods to investigate the benefits of integrating fNIRS measures for seizure detection. We designed a deep recurrent neural network with long short-term memory units and subsequently validated it using the CHBMIT scalp EEG database-a compendium of 896 h of surface EEG seizure recordings. After validating our network using EEG, fNIRS, and multimodal data comprising a corpus of 89 seizures from 40 refractory epileptic patients was used as model input to evaluate the integration of fNIRS measures. Following heuristic hyperparameter optimization, multimodal EEG-fNIRS data provide superior performance metrics (sensitivity and specificity of 89.7% and 95.5%, respectively) in a seizure detection task, with low generalization errors and loss. False detection rates are generally low, with 11.8% and 5.6% for EEG and multimodal data, respectively. Employing multimodal neuroimaging, particularly EEG-fNIRS, in epileptic patients, can enhance seizure detection performance. Furthermore, the neural network model proposed and characterized herein offers a promising framework for future multimodal investigations in seizure detection and prediction.

Complexity of Frontal Cortex fNIRS Can Support Alzheimer Disease Diagnosis in Memory and Visuo-Spatial Tests

Decline in visuo-spatial skills and memory failures are considered symptoms of Alzheimer's Disease (AD) and they can be assessed at early stages employing clinical tests. However, performance in a single test is generally not indicative of AD. Functional neuroimaging, such as functional Near Infrared Spectroscopy (fNIRS), may be employed during these tests in an ecological setting to support diagnosis. Indeed, neuroimaging should not alter clinical practice allowing free doctor-patient interaction. However, block-designed paradigms, necessary for standard functional neuroimaging analysis, require tests adaptation. Novel signal analysis procedures (e.g., signal complexity evaluation) may be useful to establish brain signals differences without altering experimental conditions. In this study, we estimated fNIRS complexity (through Sample Entropy metric) in frontal cortex of early AD and controls during three tests that assess visuo-spatial and short-term-memory abilities (Clock Drawing Test, Digit Span Test, Corsi Block Tapping Test). A channel-based analysis of fNIRS complexity during the tests revealed AD-induced changes. Importantly, a multivariate analysis of fNIRS complexity provided good specificity and sensitivity to AD. This outcome was compared to cognitive tests performances that were predictive of AD in only one test. Our results demonstrated the capabilities of fNIRS and complexity metric to support early AD diagnosis.

Deep learning for hybrid EEG-fNIRS brain-computer interface: application to motor imagery classification

OBJECTIVE

Brain-computer interface (BCI) refers to procedures that link the central nervous system to a device. BCI was historically performed using electroencephalography (EEG). In the last years, encouraging results were obtained by combining EEG with other neuroimaging technologies, such as functional near infrared spectroscopy (fNIRS). A crucial step of BCI is brain state classification from recorded signal features. Deep artificial neural networks (DNNs) recently reached unprecedented complex classification outcomes. These performances were achieved through increased computational power, efficient learning algorithms, valuable activation functions, and restricted or back-fed neurons connections. By expecting significant overall BCI performances, we investigated the capabilities of combining EEG and fNIRS recordings with state-of-the-art deep learning procedures.

APPROACH

We performed a guided left and right hand motor imagery task on 15 subjects with a fixed classification response time of 1 s and overall experiment length of 10 min. Left versus right classification accuracy of a DNN in the multi-modal recording modality was estimated and it was compared to standalone EEG and fNIRS and other classifiers.

MAIN RESULTS

At a group level we obtained significant increase in performance when considering multi-modal recordings and DNN classifier with synergistic effect.

SIGNIFICANCE

BCI performances can be significantly improved by employing multi-modal recordings that provide electrical and hemodynamic brain activity information, in combination with advanced non-linear deep learning classification procedures.