Detection of fast neuronal signals in the motor cortex from functional near infrared spectroscopy measurements using independent component analysis

Elevated brain temperature under severe heat exposure impairs cortical motor activity and executive function

BACKGROUND

Excessive heat exposure can lead to hyperthermia in humans, which impairs physical performance and disrupts cognitive function. While heat is a known physiological stressor, it is unclear how severe heat stress affects brain physiology and function.

METHODS

Eleven healthy participants were subjected to heat stress from prolonged exercise or warm water immersion until their rectal temperatures (Tre) attained 39.5°C, inducing exertional or passive hyperthermia, respectively. In a separate trial, blended ice was ingested before and during exercise as a cooling strategy. Data were compared to a control condition with seated rest (normothermic). Brain temperature (Tbr), cerebral perfusion, and task-based brain activity were assessed using magnetic resonance imaging techniques.

RESULTS

Tbr in motor cortex was found to be tightly regulated at rest (37.3°C ± 0.4°C (mean ± SD)) despite fluctuations in Tre. With the development of hyperthermia, Tbr increases and dovetails with the rising Tre. Bilateral motor cortical activity was suppressed during high-intensity plantarflexion tasks, implying a reduced central motor drive in hyperthermic participants (Tre = 38.5°C ± 0.1°C). Global gray matter perfusion and regional perfusion in sensorimotor cortex were reduced with passive hyperthermia. Executive function was poorer under a passive hyperthermic state, and this could relate to compromised visual processing as indicated by the reduced activation of left lateral-occipital cortex. Conversely, ingestion of blended ice before and during exercise alleviated the rise in both Tre and Tbr and mitigated heat-related neural perturbations.

CONCLUSION

Severe heat exposure elevates Tbr, disrupts motor cortical activity and executive function, and this can lead to impairment of physical and cognitive performance.

An efficient online peak detection algorithm for synchronized intestinal electrical stimulation and its application for treating diabetes

Obesity is one of leading risk factors for type 2 diabetes and other types of chronic diseases. Synchronized intestinal electrical stimulation (SIES) has been explored for treating obesity and diabetes. In SIES, electrical stimulation is delivered to the small intestine in synchronization with the intrinsic intestinal myoelectrical activity (its basic rhythm is called slow wave) and therefore, the accurate detection of intestinal slow waves is critically important for SIES. The aim of this study is to detect the peaks in intestinal slow waves in real-time based on the automatic multiscale peak detection (AMPD) method. In this paper, we introduce an efficient technique for real-time detection of peaks in intestinal slow waves. The presented method is based on peak estimation of a given quasi-periodic signal using the AMPD method. This method uses a multi-scale approach to identify the peaks of the intestinal slow waves with high detection accuracy and a minimal delay. Throughout the experiments, the multi-scale technique is used to estimate the quasi-periodic signals using different signal-to-noise ratio, λ (optimal scale), and the "lag" β (number of datapoints for right hand estimation) as important performance factors. The performance of the presented method is also calculated and utilized in the comparison process for 10 datasets of the intestinal slow waves from rats at λ = 150 ms and two values of β = 100 ms and 150 ms. The experimental results show that the presented method has good overall accuracy for online peak detection while maintaining low memory and computational complexity. Numerically, the overall accuracy is above 90%, and 98% for the rodent intestinal slow waves at a time-lag of 150 ms. The developed SIES system has been applied to successfully reduce postprandial blood glucose in a rodent model of hyperglycemia. In conclusion, the developed algorithm is adequate for on-line peak detection of the intestinal slow waves; the SIES method used the developed peak detection algorithm which is effective in reducing postprandial blood glucose in a rodent model of hyperglycemia.

Virtual reality-based music attention training for acquired brain injury: A protocol for randomized cross-over trial

Attention training is the primary step in the rehabilitation for patients with acquired brain injury (ABI). While active music performance has been reported to aid neural and functional recovery, its efficacy for patients with ABI remains uncertain due to methodological concerns. The purpose of the study is to develop a virtual reality-based music attention training (VR-MAT), which utilizes a visually guided, bilateral drumming in an immersive environment to train attention and executive functions. We also aims to examine the feasibility and effectiveness of the VR-MAT with a small sample size of participants (3-60 months after ABI, N = 20 approximately). Participants will be randomly assigned to either a waitlist control or music group, in which VR-MAT will take place five times weekly over 4 weeks (randomized crossover design). The evaluation of VR-MAT performance will include accuracy and response time in music responses. Neurocognitive outcome measures will be administered to quantify pre-post changes in attention, working memory, and executive functions. Additionally, functional near-infrared spectroscopy will be employed to explore the relationships between musical behavior, neurocognitive function, and neurophysiological responses.

Higher prefrontal activity based on short-term neurofeedback training can prevent working memory decline in acute stroke

This study aimed to clarify whether short-term neurofeedback training during the acute stroke phase led to prefrontal activity self-regulation, providing positive efficacy to working memory. A total of 30 patients with acute stroke performed functional near-infrared spectroscopy-based neurofeedback training for a day to increase their prefrontal activity. A randomized, Sham-controlled, double-blind study protocol was used comparing working memory ability before and after neurofeedback training. Working memory was evaluated using a target-searching task requiring spatial information retention. A decline in spatial working memory performance post-intervention was prevented in patients who displayed a higher task-related right prefrontal activity during neurofeedback training compared with the baseline. Neurofeedback training efficacy was not associated with the patient's clinical background such as Fugl-Meyer Assessment score and time since stroke. These findings demonstrated that even short-term neurofeedback training can strengthen prefrontal activity and help maintain cognitive ability in acute stroke patients, at least immediately after training. However, further studies investigating the influence of individual patient clinical background, especially cognitive impairment, on neurofeedback training is needed. Current findings provide an encouraging option for clinicians to design neurorehabilitation programs, including neurofeedback protocols, for acute stroke patients.

Fast Optical Signals for Real-Time Retinotopy and Brain Computer Interface

A brain-computer interface (BCI) allows users to control external devices through brain activity. Portable neuroimaging techniques, such as near-infrared (NIR) imaging, are suitable for this goal. NIR imaging has been used to measure rapid changes in brain optical properties associated with neuronal activation, namely fast optical signals (FOS) with good spatiotemporal resolution. However, FOS have a low signal-to-noise ratio, limiting their BCI application. Here FOS were acquired with a frequency-domain optical system from the visual cortex during visual stimulation consisting of a rotating checkerboard wedge, flickering at 5 Hz. We used measures of photon count (Direct Current, DC light intensity) and time of flight (phase) at two NIR wavelengths (690 nm and 830 nm) combined with a machine learning approach for fast estimation of visual-field quadrant stimulation. The input features of a cross-validated support vector machine classifier were computed as the average modulus of the wavelet coherence between each channel and the average response among all channels in 512 ms time windows. An above chance performance was obtained when differentiating visual stimulation quadrants (left vs. right or top vs. bottom) with the best classification accuracy of ~63% (information transfer rate of ~6 bits/min) when classifying the superior and inferior stimulation quadrants using DC at 830 nm. The method is the first attempt to provide generalizable retinotopy classification relying on FOS, paving the way for the use of FOS in real-time BCI.

Individual Sensory Modality Dominance as an Influential Factor in the Prefrontal Neurofeedback Training for Spatial Processing: A Functional Near-Infrared Spectroscopy Study

Neurofeedback is a neuromodulation technique used to improve brain function by self-regulating brain activity. However, the efficacy of neurofeedback training varies widely between individuals, and some participants fail to self-regulate brain activity. To overcome intersubject variation in neurofeedback training efficacy, it is critical to identify the factors that influence this type of neuromodulation. In this study, we considered that individual differences in cognitive ability may influence neurofeedback training efficacy and aimed to clarify the effect of individual working memory (WM) abilities, as characterized by sensory modality dominance, on neurofeedback training efficacy in healthy young adults. In particular, we focused on the abilities of individuals to retain internal (tactile or somatosensory) or external (visual) body information in their WM. Forty participants performed functional near-infrared spectroscopy-based neurofeedback training aimed at producing efficient and lower-level activity in the bilateral dorsolateral prefrontal cortex and frontopolar cortex. We carried out a randomized, sham-controlled, double-blind study that compared WM ability before and after neurofeedback training. Individual WM ability was quantified using a target searching task that required the participants to retain spatial information presented as vibrotactile or visual stimuli. Participants who received feedback information based on their own prefrontal activity showed gradually decreasing activity in the right prefrontal area during the neurofeedback training and demonstrated superior WM ability during the target searching task with vibrotactile stimuli compared with the participants who performed dummy neurofeedback training. In comparison, left prefrontal activity was not influenced by the neurofeedback training. Furthermore, the efficacy of neurofeedback training (i.e., lower right prefrontal activity and better searching task performance) was higher in participants who exhibited tactile dominance rather than visual dominance in their WM. These findings indicate that sensory modality dominance in WM may be an influential neurophysiological factor in determining the efficacy of neurofeedback training. These results may be useful in the development of neurofeedback training protocols tailored to individual needs.

NIRS-ICA: A MATLAB Toolbox for Independent Component Analysis Applied in fNIRS Studies

Independent component analysis (ICA) is a multivariate approach that has been widely used in analyzing brain imaging data. In the field of functional near-infrared spectroscopy (fNIRS), its promising effectiveness has been shown in both removing noise and extracting neuronal activity-related sources. The application of ICA remains challenging due to its complexity in usage, and an easy-to-use toolbox dedicated to ICA processing is still lacking in the fNIRS community. In this study, we propose NIRS-ICA, an open-source MATLAB toolbox to ease the difficulty of ICA application for fNIRS studies. NIRS-ICA incorporates commonly used ICA algorithms for source separation, user-friendly GUI, and quantitative evaluation metrics assisting source selection, which facilitate both removing noise and extracting neuronal activity-related sources. The options used in the processing can also be reported easily, which promotes using ICA in a more reproducible way. The proposed toolbox is validated and demonstrated based on both simulative and real fNIRS datasets. We expect the release of the toolbox will extent the application for ICA in the fNIRS community.

Detection of cellular micromotion by advanced signal processing

Cellular micromotion—a tiny movement of cell membranes on the nm-µm scale—has been proposed as a pathway for inter-cellular signal transduction and as a label-free proxy signal to neural activity. Here we harness several recent approaches of signal processing to detect such micromotion in video recordings of unlabeled cells. Our survey includes spectral filtering of the video signal, matched filtering, as well as 1D and 3D convolutional neural networks acting on pixel-wise time-domain data and a whole recording respectively.

Pitch Processing Can Indicate Cognitive Alterations in Chronic Liver Disease: An fNIRS Study

Early detection and evaluation of cognitive alteration in chronic liver disease is important for predicting the subsequent development of hepatic encephalopathy. While visuomotor tasks have been rigorously employed for cognitive evaluation in chronic liver disease, there is a paucity of auditory processing task. Here we focused on auditory perception and examined behavioral and haemodynamic responses to a melodic contour identification task (CIT) to compare cognitive abilities in patients with chronic liver disease (CLD, N = 30) and healthy controls (N = 25). Further, we used support vector machines to examine the optimal combination of channels of functional near-infrared spectroscopy that can classify cognitive alterations in CLD. Behavioral findings showed that CIT performance was significantly worse in the patient group and CIT significantly correlated with neurocognitive evaluation (i.e., number connection test, digit span test). The findings indicated that CIT can measure auditory cognitive capacity and its difference existing between patient group and healthy controls. Additionally, optimal subsets classified the 16-dimensional haemodynamic data with 78.35% classification accuracy, yielding markers of cognitive alterations in the prefrontal regions (CH6, CH7, CH10, CH13, CH14, and CH16). The results confirmed the potential use of behavioral as well as haemodynamic responses to music perception as an alternative or supplementary method for evaluating cognitive alterations in chronic liver disease.

Local syntactic violations evoke fast mismatch-related neural activity detected by optical neuroimaging

It remains to be investigated whether syntax-related mismatch activity would be evoked in event-related optical signals by syntactic violations that deviate from our language knowledge and expectations. In the current study, we have employed fast optical neuroimaging with a frequency-domain oximeter to examine whether syntactic violations of English bare infinitives in the non-finite complement clause would trigger syntax-related mismatch effects. Recorded sentences of bare or full infinitive structures (without or with the 'to' infinitival marker) with syntactically correct or incorrect versions and non-syntactic lexical items (verbs) were presented to native speakers of English (n = 8) during silent movie viewing as a passive oddball task. The analysis of source strength (i.e., minimum norm current amplitudes) revealed that the syntactic category violations of bare object infinitives led to significantly more robust optical mismatch effects than the other syntactic violation and non-structural, lexical elements. This mismatch response had a peak latency of 186 ms in the left anterior superior temporal gyrus. In combination with our prior MEG report (Kubota et al. in Neurosci Lett 662:195-204, 2018), the present optical neuroimaging findings show that syntactic marking (unmarked-to-marked) violations of the bare object infinitive against the rule of the mental grammar enhance the signal strength exactly in the same manner seen with MEG scanning, including the peak latency of mismatch activity and the activated area of the brain.

Distinct bilateral prefrontal activity patterns associated with the qualitative aspect of working memory characterized by individual sensory modality dominance

In addition to quantitative individual differences in working memory (WM) capacity, qualitative aspects, such as enhanced sensory modality (modality dominance), can characterize individual WM ability. This study aimed to examine the neurological basis underlying the individual modality dominance component of WM using functional near-infrared spectroscopy (fNIRS). To quantify the degree of individual WM modality dominance, 24 participants were required to find seven hidden targets and hold their spatial location and appearance order with vibrotactile or visual stimuli aids. In this searching task, eight participants demonstrated higher performance with the tactile condition (tactile-dominant) whereas sixteen demonstrated visual dominance. We then measured prefrontal activity by fNIRS during memorization of visual stimulus numbers while finger tapping as a cognitive-motor dual-task. Individual modality dominance significantly correlated with bilateral frontopolar and dorsolateral prefrontal activity changes over repeated fNIRS sessions. In particular, individuals with stronger visual dominance showed marked decreases in prefrontal area activity. These results suggest that distinct processing patterns in the prefrontal cortex reflect an individual’s qualitative WM characteristics. Considering the individual modality dominance underlying the prefrontal areas could enhance cognitive or motor performance, possibly by optimizing cognitive resources.

Frequency-Domain Techniques for Cerebral and Functional Near-Infrared Spectroscopy

This article reviews the basic principles of frequency-domain near-infrared spectroscopy (FD-NIRS), which relies on intensity-modulated light sources and phase-sensitive optical detection, and its non-invasive applications to the brain. The simpler instrumentation and more straightforward data analysis of continuous-wave NIRS (CW-NIRS) accounts for the fact that almost all the current commercial instruments for cerebral NIRS have embraced the CW technique. However, FD-NIRS provides data with richer information content, which complements or exceeds the capabilities of CW-NIRS. One example is the ability of FD-NIRS to measure the absolute optical properties (absorption and reduced scattering coefficients) of tissue, and thus the absolute concentrations of oxyhemoglobin and deoxyhemoglobin in brain tissue. This article reviews the measured values of such optical properties and hemoglobin concentrations reported in the literature for animal models and for the human brain in newborns, infants, children, and adults. We also review the application of FD-NIRS to functional brain studies that focused on slower hemodynamic responses to brain activity (time scale of seconds) and faster optical signals that have been linked to neuronal activation (time scale of 100 ms). Another example of the power of FD-NIRS data is related to the different regions of sensitivity featured by intensity and phase data. We report recent developments that take advantage of this feature to maximize the sensitivity of non-invasive optical signals to brain tissue relative to more superficial extracerebral tissue (scalp, skull, etc.). We contend that this latter capability is a highly appealing quality of FD-NIRS, which complements absolute optical measurements and may result in significant advances in the field of non-invasive optical sensing of the brain.

Prefrontal activity predicts individual differences in optimal attentional strategy for preventing motor performance decline: a functional near-infrared spectroscopy study

Directing attention to movement outcomes (external focus; EF), not body movements (internal focus; IF), is a better cognitive strategy for motor performance. However, EF is not effective in some healthy individuals or stroke patients. We aimed to identify the neurological basis reflecting the individual optimal attentional strategy using functional near-infrared spectroscopy. Sixty-four participants (23 healthy young, 23 healthy elderly, and 18 acute stroke) performed a reaching movement task under IF and EF conditions. Of these, 13 healthy young participants, 11 healthy elderly participants, and 6 stroke patients showed better motor performance under EF conditions (EF-dominant), whereas the others showed IF-dominance. We then measured prefrontal activity during rhythmic hand movements under both attentional conditions. IF-dominant participants showed significantly higher left prefrontal activity than EF-dominant participants under IF condition. In addition, receiver operating characteristic analysis supported that the higher activity in the left frontopolar and dorsolateral prefrontal cortices could detect IF-dominance as an individual's optimal attentional strategy for preventing motor performance decline. Taken together, these results suggest that prefrontal activity during motor tasks reflects an individual's ability to process internal body information, thereby conferring IF-dominance. These findings could be applied for the development of individually optimized rehabilitation programs.

High Oxygen Exchange to Music Indicates Auditory Distractibility in Acquired Brain Injury: An fNIRS Study with a Vector-Based Phase Analysis

Attention deficits due to auditory distractibility are pervasive among patients with acquired brain injury (ABI). It remains unclear, however, whether attention deficits following ABI specific to auditory modality are associated with altered haemodynamic responses. Here, we examined cerebral haemodynamic changes using functional near-infrared spectroscopy combined with a topological vector-based analysis method. A total of thirty-seven participants (22 healthy adults, 15 patients with ABI) performed a melodic contour identification task (CIT) that simulates auditory distractibility. Findings demonstrated that the melodic CIT was able to detect auditory distractibility in patients with ABI. The rate-corrected score showed that the ABI group performed significantly worse than the non-ABI group in both CIT1 (target contour identification against environmental sounds) and CIT2 (target contour identification against target-like distraction). Phase-associated response intensity during the CITs was greater in the ABI group than in the non-ABI group. Moreover, there existed a significant interaction effect in the left dorsolateral prefrontal cortex (DLPFC) during CIT1 and CIT2. These findings indicated that stronger hemodynamic responses involving oxygen exchange in the left DLPFC can serve as a biomarker for evaluating and monitoring auditory distractibility, which could potentially lead to the discovery of the underlying mechanism that causes auditory attention deficits in patients with ABI.

Cognitive Load Changes during Music Listening and its Implication in Earcon Design in Public Environments: An fNIRS Study

A key for earcon design in public environments is to incorporate an individual’s perceived level of cognitive load for better communication. This study aimed to examine the cognitive load changes required to perform a melodic contour identification task (CIT). While healthy college students (N = 16) were presented with five CITs, behavioral (reaction time and accuracy) and cerebral hemodynamic responses were measured using functional near-infrared spectroscopy. Our behavioral findings showed a gradual increase in cognitive load from CIT1 to CIT3 followed by an abrupt increase between CIT4 (i.e., listening to two concurrent melodic contours in an alternating manner and identifying the direction of the target contour, p < 0.001) and CIT5 (i.e., listening to two concurrent melodic contours in a divided manner and identifying the directions of both contours, p < 0.001). Cerebral hemodynamic responses showed a congruent trend with behavioral findings. Specific to the frontopolar area (Brodmann’s area 10), oxygenated hemoglobin increased significantly between CIT4 and CIT5 (p < 0.05) while the level of deoxygenated hemoglobin decreased. Altogether, the findings indicate that the cognitive threshold for young adults (CIT5) and appropriate tuning of the relationship between timbre and pitch contour can lower the perceived cognitive load and, thus, can be an effective design strategy for earcon in a public environment.

Shining a Light on Awareness: A Review of Functional Near-Infrared Spectroscopy for Prolonged Disorders of Consciousness

Qualitative clinical assessments of the recovery of awareness after severe brain injury require an assessor to differentiate purposeful behavior from spontaneous behavior. As many such behaviors are minimal and inconsistent, behavioral assessments are susceptible to diagnostic errors. Advanced neuroimaging tools can bypass behavioral responsiveness and reveal evidence of covert awareness and cognition within the brains of some patients, thus providing a means for more accurate diagnoses, more accurate prognoses, and, in some instances, facilitated communication. The majority of reports to date have employed the neuroimaging methods of functional magnetic resonance imaging, positron emission tomography, and electroencephalography (EEG). However, each neuroimaging method has its own advantages and disadvantages (e.g., signal resolution, accessibility, etc.). Here, we describe a burgeoning technique of non-invasive optical neuroimaging—functional near-infrared spectroscopy (fNIRS)—and review its potential to address the clinical challenges of prolonged disorders of consciousness. We also outline the potential for simultaneous EEG to complement the fNIRS signal and suggest the future directions of research that are required in order to realize its clinical potential.

Quantifying fast optical signal and event-related potential relationships during a visual oddball task

Event-related potentials (ERPs) have previously been used to confirm the existence of the fast optical signal (FOS) but validation methods have mainly been limited to exploring the temporal correspondence of FOS peaks to those of ERPs. The purpose of this study was to systematically quantify the relationship between FOS and ERP responses to a visual oddball task in both time and frequency domains. Near-infrared spectroscopy (NIRS) and electroencephalography (EEG) sensors were co-located over the prefrontal cortex while participants performed a visual oddball task. Fifteen participants completed 2 data collection sessions each, where they were instructed to keep a mental count of oddball images. The oddball condition produced a positive ERP at 200 ms followed by a negativity 300-500 ms after image onset in the frontal electrodes. In contrast to previous FOS studies, a FOS response was identified only in DC intensity signals and not in phase delay signals. A decrease in DC intensity was found 150-250 ms after oddball image onset with a 400-trial average in 10 of 15 participants. The latency of the positive 200 ms ERP and the FOS DC intensity decrease were significantly correlated for only 6 (out of 15) participants due to the low signal-to-noise ratio of the FOS response. Coherence values between the FOS and ERP oddball responses were found to be significant in the 3-5 Hz frequency band for 10 participants. A significant Granger causal influence of the ERP on the FOS oddball response was uncovered in the 2-6 Hz frequency band for 7 participants. Collectively, our findings suggest that, for a majority of participants, the ERP and the DC intensity signal of the FOS are spectrally coherent, specifically in narrow frequency bands previously associated with event-related oscillations in the prefrontal cortex. However, these electro-optical relationships were only found in a subset of participants. Further research on enhancing the quality of the event-related FOS signal is required before it can be practically exploited in applications such as brain-computer interfacing.

Functional near-infrared spectroscopy in movement science: a systematic review on cortical activity in postural and walking tasks

Safe locomotion is a crucial aspect of human daily living that requires well-functioning motor control processes. The human neuromotor control of daily activities such as walking relies on the complex interaction of subcortical and cortical areas. Technical developments in neuroimaging systems allow the quantification of cortical activation during the execution of motor tasks. Functional near-infrared spectroscopy (fNIRS) seems to be a promising tool to monitor motor control processes in cortical areas in freely moving subjects. However, so far, there is no established standardized protocol regarding the application and data processing of fNIRS signals that limits the comparability among studies. Hence, this systematic review aimed to summarize the current knowledge about application and data processing in fNIRS studies dealing with walking or postural tasks. Fifty-six articles of an initial yield of 1420 publications were reviewed and information about methodology, data processing, and findings were extracted. Based on our results, we outline the recommendations with respect to the design and data processing of fNIRS studies. Future perspectives of measuring fNIRS signals in movement science are discussed.

The Temporal Muscle of the Head Can Cause Artifacts in Optical Imaging Studies with Functional Near-Infrared Spectroscopy

Background: Extracranial signals are the main source of noise in functional near-infrared spectroscopy (fNIRS) as light is penetrating the cortex but also skin and muscles of the head. Aim: Here we performed three experiments to investigate the contamination of fNIRS measurements by temporal muscle activity. Material and methods: For experiment 1, we provoked temporal muscle activity by instructing 31 healthy subjects to clench their teeth three times. We measured fNIRS signals over left temporal and frontal channels with an interoptode distance of 3 cm, in one short optode distance (SOD) channel (1 cm) and electromyography (EMG) over the edge of the temporal muscle. In experiment 2, we screened resting state fNIRS-fMRI (functional magnetic resonance imaging) data of one healthy subject for temporal muscle artifacts. In experiment 3, we screened a dataset of sound-evoked activity (n = 33) using bi-temporal probe-sets and systematically contrasted subjects presenting vs. not presenting artifacts and blocks/events contaminated or not contaminated with artifacts. Results: In experiment 1, we could demonstrate a hemodynamic-response-like increase in oxygenated (O2Hb) and decrease in deoxygenated (HHb) hemoglobin with a large amplitude and large spatial extent highly exceeding normal cortical activity. Correlations between EMG, SOD, and fNIRS artifact activity showed only limited evidence for associations on a group level with rather clear associations in a sub-group of subjects. The fNIRS-fMRI experiment showed that during the temporal muscle artifact, fNIRS is completely saturated by muscle oxygenation. Experiment 3 showed hints for contamination of sound-evoked oxygenation by the temporal muscle artifact. This was of low relevance in analyzing the whole sample. Discussion: Temporal muscle activity e.g., by clenching the teeth induces a large hemodynamic-like artifact in fNIRS measurements which should be avoided by specific subject instructions. Data should be screened for this artifact might be corrected by exclusion of contaminated blocks/events. The usefulness of established artifact correction methods should be evaluated in future studies. Conclusion: Temporal muscle activity, e.g., by clenching the teeth is one major source of noise in fNIRS measurements.

From brain to blood vessels and back: a noninvasive optical imaging approach

The seminal work of Grinvald et al. has paved the way for the use of intrinsic optical signals measured with reflection methods for the analysis of brain function. Although this work has focused on the absorption signal associated with deoxygenation, due to its detailed mapping ability and good signal-to-noise ratio, Grinvald's group has also described other intrinsic signals related to increased blood flow, scattering effects directly related to neural activation, and pulsation effects related to arterial function. These intrinsic optical signals can also be measured using noninvasive diffuse optical topographic and tomographic imaging (DOT) methods that can be applied to humans. Here we compare the reflection and DOT methods and the evidence for each type of intrinsic signal in these two domains, with particular attention to work that has been conducted in our laboratory. This work reveals the refined two-way relationship that exists between vascular and neural phenomena in the brain: arterial health is related to normal brain structure and function, both across individuals and across brain regions within an individual, and neural function influences blood flow to specific cortical regions. DOT methods can provide quantitative tools for investigating these relationships in normal human subjects.

Shedding light on interictal epileptic spikes: An in vivo study using fast optical signal and electrocorticography

OBJECTIVE

Interictal epileptic spikes (IESs), apart from being a key marker of epileptic neuronal networks, constitute a nice model of the widespread endogenous phenomenon of neuronal hypersynchronization. Many questions concerning the mechanisms that drive neurons to hypersynchronize remain unresolved, but synaptic as well as nonsynaptic events are likely to be involved. In this study, changes in optical properties of neural tissues were observed in rats with penicillin-induced IES using fast optical signal (FOS) concomitantly with electrocorticography (ECoG).

METHODS

In this study, near-infrared optical imaging was used with ECoG to investigate variations in the optical properties of cortical tissue directly associated with neuronal activity in 15 rats. FOS changes correspond to variations of scattered light from neuronal tissue when neurons are activated. To independently evaluate our method, a control experiment on somatosensory was designed and applied to seven different rats. Time-frequency analysis was also used to track variations of (de)synchronization concomitantly with changes in optical signals during IES.

RESULTS

FOS responses revealed that changes in optical signals occurred 320 msec before to 370 msec after the IES peak. These changes started before any changes in ECoG signal. In addition, time-frequency domain electrocorticography revealed an alternating decrease-increase-decrease in the ECoG spectral power (pointing to desynchronization-synchronization-desynchronization), which occurred concomitantly with an increase-decrease-increase in relative optical signal during the IES. These results suggest a relationship between (de)synchronization and optical changes.

SIGNIFICANCE

These changes in the neuronal environment around IESs raise new questions about the mechanisms that induce changes in optical properties of neural tissues before the IES, which may provide suitable conditions for neuronal synchronization during IESs. FOS-ECoG constitutes a multimodal approach and opens new avenues to study the mechanisms of neuronal synchronization in the pathologic brain, which has clinical implications, at least in epilepsy.

Blind Source Separation for Unimodal and Multimodal Brain Networks: A Unifying Framework for Subspace Modeling

In the past decade, numerous advances in the study of the human brain were fostered by successful applications of blind source separation (BSS) methods to a wide range of imaging modalities. The main focus has been on extracting "networks" represented as the underlying latent sources. While the broad success in learning latent representations from multiple datasets has promoted the wide presence of BSS in modern neuroscience, it also introduced a wide variety of objective functions, underlying graphical structures, and parameter constraints for each method. Such diversity, combined with a host of datatype-specific know-how, can cause a sense of disorder and confusion, hampering a practitioner's judgment and impeding further development. We organize the diverse landscape of BSS models by exposing its key features and combining them to establish a novel unifying view of the area. In the process, we unveil important connections among models according to their properties and subspace structures. Consequently, a high-level descriptive structure is exposed, ultimately helping practitioners select the right model for their applications. Equipped with that knowledge, we review the current state of BSS applications to neuroimaging. The gained insight into model connections elicits a broader sense of generalization, highlighting several directions for model development. In light of that, we discuss emerging multi-dataset multidimensional (MDM) models and summarize their benefits for the study of the healthy brain and disease-related changes.

Melodic Contour Identification Reflects the Cognitive Threshold of Aging

Cognitive decline is a natural phenomenon of aging. Although there exists a consensus that sensitivity to acoustic features of music is associated with such decline, no solid evidence has yet shown that structural elements and contexts of music explain this loss of cognitive performance. This study examined the extent and the type of cognitive decline that is related to the contour identification task (CIT) using tones with different pitches (i.e., melodic contours). Both younger and older adult groups participated in the CIT given in three listening conditions (i.e., focused, selective, and alternating). Behavioral data (accuracy and response times) and hemodynamic reactions were measured using functional near-infrared spectroscopy (fNIRS). Our findings showed cognitive declines in the older adult group but with a subtle difference from the younger adult group. The accuracy of the melodic CITs given in the target-like distraction task (CIT2) was significantly lower than that in the environmental noise (CIT1) condition in the older adult group, indicating that CIT2 may be a benchmark test for age-specific cognitive decline. The fNIRS findings also agreed with this interpretation, revealing significant increases in oxygenated hemoglobin (oxyHb) concentration in the younger (p < 0.05 for Δpre - on task; p < 0.01 for Δon – post task) rather than the older adult group (n.s for Δpre - on task; n.s for Δon – post task). We further concluded that the oxyHb difference was present in the brain regions near the right dorsolateral prefrontal cortex. Taken together, these findings suggest that CIT2 (i.e., the melodic contour task in the target-like distraction) is an optimized task that could indicate the degree and type of age-related cognitive decline.

Cortical Signal Analysis and Advances in Functional Near-Infrared Spectroscopy Signal: A Review

Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging modality that measures the concentration changes of oxy-hemoglobin (HbO) and de-oxy hemoglobin (HbR) at the same time. It is an emerging cortical imaging modality with a good temporal resolution that is acceptable for brain-computer interface applications. Researchers have developed several methods in last two decades to extract the neuronal activation related waveform from the observed fNIRS time series. But still there is no standard method for analysis of fNIRS data. This article presents a brief review of existing methodologies to model and analyze the activation signal. The purpose of this review article is to give a general overview of variety of existing methodologies to extract useful information from measured fNIRS data including pre-processing steps, effects of differential path length factor (DPF), variations and attributes of hemodynamic response function (HRF), extraction of evoked response, removal of physiological noises, instrumentation, and environmental noises and resting/activation state functional connectivity. Finally, the challenges in the analysis of fNIRS signal are summarized.

Low-Power Wearable Systems for Continuous Monitoring of Environment and Health for Chronic Respiratory Disease

We present our efforts toward enabling a wearable sensor system that allows for the correlation of individual environmental exposures with physiologic and subsequent adverse health responses. This system will permit a better understanding of the impact of increased ozone levels and other pollutants on chronic asthma conditions. We discuss the inefficiency of existing commercial off-the-shelf components to achieve continuous monitoring and our system-level and nano-enabled efforts toward improving the wearability and power consumption. Our system consists of a wristband, a chest patch, and a handheld spirometer. We describe our preliminary efforts to achieve a submilliwatt system ultimately powered by the energy harvested from thermal radiation and motion of the body with the primary contributions being an ultralow-power ozone sensor, an volatile organic compounds sensor, spirometer, and the integration of these and other sensors in a multimodal sensing platform. The measured environmental parameters include ambient ozone concentration, temperature, and relative humidity. Our array of sensors also assesses heart rate via photoplethysmography and electrocardiography, respiratory rate via photoplethysmography, skin impedance, three-axis acceleration, wheezing via a microphone, and expiratory airflow. The sensors on the wristband, chest patch, and spirometer consume 0.83, 0.96, and 0.01 mW, respectively. The data from each sensor are continually streamed to a peripheral data aggregation device and are subsequently transferred to a dedicated server for cloud storage. Future work includes reducing the power consumption of the system-on-chip including radio to reduce the entirety of each described system in the submilliwatt range.

Nonverbal auditory working memory: Can music indicate the capacity?

Different working memory (WM) mechanisms that underlie words, tones, and timbres have been proposed in previous studies. In this regard, the present study developed a WM test with nonverbal sounds and compared it to the conventional verbal WM test. A total of twenty-five, non-music major, right-handed college students were presented with four different types of sounds (words, syllables, pitches, timbres) that varied from two to eight digits in length. Both accuracy and oxygenated hemoglobin (oxyHb) were measured. The results showed significant effects of number of targets on accuracy and sound type on oxyHb. A further analysis showed prefrontal asymmetry with pitch being processed by the right hemisphere (RH) and timbre by the left hemisphere (LH). These findings suggest a potential for employing musical sounds (i.e., pitch and timbre) as a complementary stimuli for conventional nonverbal WM tests, which can additionally examine its asymmetrical roles in the prefrontal regions.

Evaluation of cortical plasticity in children with cerebral palsy undergoing constraint-induced movement therapy based on functional near-infrared spectroscopy

Sensorimotor cortex plasticity induced by constraint-induced movement therapy (CIMT) in six children (10.2±2.1 years old) with hemiplegic cerebral palsy was assessed by functional near-infrared spectroscopy (fNIRS). The activation laterality index and time-to-peak/duration during a finger-tapping task and the resting-state functional connectivity were quantified before, immediately after, and 6 months after CIMT. These fNIRS-based metrics were used to help explain changes in clinical scores of manual performance obtained concurrently with imaging time points. Five age-matched healthy children (9.8±1.3 years old) were also imaged to provide comparative activation metrics for normal controls. Interestingly, the activation time-to-peak/duration for all sensorimotor centers displayed significant normalization immediately after CIMT that persisted 6 months later. In contrast to this improved localized activation response, the laterality index and resting-state connectivity metrics that depended on communication between sensorimotor centers improved immediately after CIMT, but relapsed 6 months later. In addition, for the subjects measured in this work, there was either a trade-off between improving unimanual versus bimanual performance when sensorimotor activation patterns normalized after CIMT, or an improvement occurred in both unimanual and bimanual performance but at the cost of very abnormal plastic changes in sensorimotor activity.

Evaluation of various mental task combinations for near-infrared spectroscopy-based brain-computer interfaces

A number of recent studies have demonstrated that near-infrared spectroscopy (NIRS) is a promisingneuroimaging modality for brain-computer interfaces (BCIs). So far, most NIRS-based BCI studies have focusedon enhancing the accuracy of the classification of different mental tasks. In the present study, we evaluated theperformances of a variety of mental task combinations in order to determine the mental task pairs that are bestsuited for customized NIRS-based BCIs. To this end, we recorded event-related hemodynamic responses whileseven participants performed eight different mental tasks. Classification accuracies were then estimated for allpossible pairs of the eight mental tasks (8C2 = 28). Based on this analysis, mental task combinations with relatively high classification accuracies frequently included the following three mental tasks: “mental multiplication,” “mental rotation,” and “right-hand motor imagery.” Specifically, mental task combinations consisting of two of these three mental tasks showed the highest mean classification accuracies. It is expected that our results will be a useful reference to reduce the time needed for preliminary tests when discovering individual-specific mental task combinations.

Detection of optical neuronal signals in the visual cortex using continuous wave near-infrared spectroscopy

Near-infrared spectroscopy (NIRS) measures slow hemodynamic signals noninvasively to indirectly infer the neuronal activity in the brain. However, it remains a controversy on whether this optical measurement technique can detect the optical neuronal signal, which reflects the optical changes directly associated with neuronal activity, within the visual cortex of human and non-human primates. By carefully reviewing the important factors in the detection of optical neuronal signals, we aim to investigate the feasibility of performing NIRS measurements of optical neuronal signals within the visual cortex in humans. To ensure a strong optical neuronal response, a full-field circular black and white reversing checkerboard stimulus was presented, and the reversal frequency was carefully chosen. We used a homemade continuous wave (CW) NIRS system with high detection sensitivity (of the order of 0.1 pW) to record a large area of the visual cortex (approximately 6 × 14 cm(2)). EEG was simultaneously acquired with the optical signal. Based on the mathematical morphology, we adapted the filter proposed by Gratton et al. to remove the influence of arterial pulsation and facilitate the detection and elimination of unknown artifacts from the data. We obtained reliable optical neuronal signals in 77% of the participants (10 out of 13). The amplitudes (latencies) of the obtained optical neuronal signals corresponding to the 785 and 850 nm wavelengths were 0.017 ± 0.003% (94.7 ± 8.4 ms) and 0.025 ± 0.006% (99.0 ± 7.7 ms), respectively. There were no significant differences between the latencies of the N75 component of the visual evoked potential (VEP) and optical neuronal signals at either wavelength. This is the first study to report optical neuronal signals within the visual cortex in the intact human brain using a CW NIRS system. These results indicate the feasibility of measuring noninvasive optical neuronal signals using a CW NIRS system with high detection sensitivity.

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.

Fast optical signals in the sensorimotor cortex: General Linear Convolution Model applied to multiple source-detector distance-based data

In this study, we applied the General Linear Convolution Model to detect fast optical signals (FOS) in the somatosensory cortex, and to study their dependence on the source-detector separation distance (2.0 to 3.5 cm) and irradiated light wavelength (690 and 830 nm). We modeled the impulse response function as a rectangular function that lasted 30 ms, with variable time delay with respect to the stimulus onset. The model was tested in a cohort of 20 healthy volunteers who underwent supra-motor threshold electrical stimulation of the median nerve. The impulse response function quantified the time delay for the maximal response at 70 ms to 110 ms after stimulus onset, in agreement with classical somatosensory-evoked potentials in the literature, previous optical imaging studies based on a grand-average approach, and grand-average based processing. Phase signals at longer wavelength were used to identify FOS for all the source-detector separation distances, but the shortest one. Intensity signals only detected FOS at the greatest distance; i.e., for the largest channel depth. There was no activation for the shorter wavelength light. Correlational analysis between the phase and intensity of FOS further confirmed diffusive rather than optical absorption changes associated with neuronal activity in the activated cortical volume. Our study demonstrates the reliability of our method based on the General Linear Convolution Model for the detection of fast cortical activation through FOS.

Neural processing of facial identity and emotion in infants at high-risk for autism spectrum disorders

Deficits in face processing and social impairment are core characteristics of autism spectrum disorder. The present work examined 7-month-old infants at high-risk for developing autism and typically developing controls at low-risk, using a face perception task designed to differentiate between the effects of face identity and facial emotions on neural response using functional Near-Infrared Spectroscopy. In addition, we employed independent component analysis, as well as a novel method of condition-related component selection and classification to identify group differences in hemodynamic waveforms and response distributions associated with face and emotion processing. The results indicate similarities of waveforms, but differences in the magnitude, spatial distribution, and timing of responses between groups. These early differences in local cortical regions and the hemodynamic response may, in turn, contribute to differences in patterns of functional connectivity.

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.

Fast optical signal in visual cortex: Improving detection by General Linear Convolution Model

In this study we applied the General Linear Convolution Model to fast optical signals (FOS). We modeled the Impulse Response Function (IRF) as a rectangular function lasting 30ms, with variable time delay with respect to the stimulus onset. Simulated data confirmed the feasibility of this approach and its capability of detecting simulated activations in case of very unfavorable Signal to Noise Ratio (SNR), providing better results than the grand average method. The model was tested in a cohort of 10 healthy volunteers who underwent to hemi-field visual stimulation. Experimental data quantified the IRF time delay at 80-100ms after the stimulus onset, in agreement with classical visual evoked potential literature and previous optical imaging studies based on grand average approach and a larger number of trails. FOS confirmed the expected contralateral activation in the occipital region. Correlational analysis between hemodynamic intensity signal, phase and intensity FOS supports diffusive rather than optical absorption changes associated with neuronal activity in the activated cortical volume. Our study provides a feasible method for detecting fast cortical activations by means of FOS.

A fast neuronal signal-sensitive continuous-wave near-infrared imaging system

We have developed a continuous-wave near-infrared imaging system to measure fast neuronal signals. We used a simultaneous sampling method with a separate high-speed analog-to-digital converter for each input channel, which provides a much larger point sample in a digital lock-in algorithm, higher temporal resolution, and lower crosstalk among detected channels. Without any analog filter, digital lock-in detection with a large point sample suppresses noise excellently, making the system less complex and offering better flexibility. In addition, using a custom-made collimator, more photons can reach the brain tissue due to the smaller divergence angle. Performance analysis shows high detection sensitivity (on the order of 0.1 pW) and high temporal resolution (~50 Hz, 48 channels). Simulation experiments show that intensity changes on the order of 0.01% can be resolved by our instrument when averaging over approximately 500 stimuli. In vivo experiments over the motor cortex show that our instrument can detect fast neuronal signals in the human brain.

RLS adaptive filtering for physiological interference reduction in NIRS brain activity measurement: a Monte Carlo study

The non-invasive measurement of cerebral functional haemodynamics using near-infrared spectroscopy (NIRS) instruments is often affected by physiological interference. The suppression of this interference is crucial for reliable recovery of brain activity measurements because it can significantly affect the signal quality. In this study, we present a recursive least-squares (RLS) algorithm for adaptive filtering to reduce the magnitude of the physiological interference component. To evaluate it, we implemented Monte Carlo simulations based on a five-layer slab model of a human adult head with a multidistance source-detector arrangement, of a short pair and a long pair, for NIRS measurement. We derived measurements by adopting different interoptode distances, which is relevant to the process of optimizing the NIRS probe configuration. Both RLS and least mean squares (LMS) algorithms were used to attempt the removal of physiological interference. The results suggest that the RLS algorithm is more capable of minimizing the effect of physiological interference due to its advantages of faster convergence and smaller mean squared error (MSE). The influence of superficial layer thickness on the performance of the RLS algorithm was also investigated. We found that the near-detector position is an important variable in minimizing the MSE and a short source-detector separation less than 9 mm is robust to superficial layer thickness variation.

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.

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.

Towards a system-paced near-infrared spectroscopy brain-computer interface: differentiating prefrontal activity due to mental arithmetic and mental singing from the no-control state

Near-infrared spectroscopy (NIRS) has recently been investigated as a non-invasive brain-computer interface (BCI) for individuals with severe motor impairments. For the most part, previous research has investigated the development of NIRS-BCIs operating under synchronous control paradigms, which require the user to exert conscious control over their mental activity whenever the system is vigilant. Though functional, this is mentally demanding and an unnatural way to communicate. An attractive alternative to the synchronous control paradigm is system-paced control, in which users are required to consciously modify their brain activity only when they wish to affect the BCI output, and can remain in a more natural, 'no-control' state at all other times. In this study, we investigated the feasibility of a system-paced NIRS-BCI with one intentional control (IC) state corresponding to the performance of either mental arithmetic or mental singing. In particular, this involved determining if these tasks could be distinguished, individually, from the unconstrained 'no-control' state. Deploying a dual-wavelength frequency domain near-infrared spectrometer, we interrogated nine sites around the frontopolar locations (International 10-20 System) while eight able-bodied adults performed mental arithmetic and mental singing to answer multiple-choice questions within a system-paced paradigm. With a linear classifier trained on a six-dimensional feature set, an overall classification accuracy of 71.2% across participants was achieved for the mental arithmetic versus no-control classification problem. While the mental singing versus no-control classification was less successful across participants (62.7% on average), four participants did attain accuracies well in excess of chance, three of which were above 70%. Analyses were performed offline. Collectively, these results are encouraging, and demonstrate the potential of a system-paced NIRS-BCI with one IC state corresponding to either mental arithmetic or mental singing.

Recognition of stimulus-evoked neuronal optical response by identifying chaos levels of near-infrared spectroscopy time series

Near-infrared spectroscopy (NIRS) can detect two different kinds of signals from the human brain: the hemodynamic response (slow) and the neuronal response (fast). This paper explores a nonlinear aspect in the tactile-stimulus-evoked neuronal optical response over a NIRS time series (light intensity variation). The existence of the fast optical responses (FORs) over the time series recorded in stimulus sessions is confirmed by event-related averaging. The chaos levels of the NIRS time series recorded both in stimulus and in rest sessions are then identified according to the estimated largest Lyapunov exponent. The obtained results ascertain that stimulus-evoked neuronal optical responses can be detected in the somatosensory cortex using continuous-wave NIRS equipment. Further, the results strongly suggest that the chaos level can be used to recognize the FORs in NIRS time series and, thereby, the state of the pertinent brain activity.