The NIRS Analysis Package: noise reduction and statistical inference

Diagnostic machine learning applications on clinical populations using functional near infrared spectroscopy: a review

Functional near-infrared spectroscopy (fNIRS) and its interaction with machine learning (ML) is a popular research topic for the diagnostic classification of clinical disorders due to the lack of robust and objective biomarkers. This review provides an overview of research on psychiatric diseases by using fNIRS and ML. Article search was carried out and 45 studies were evaluated by considering their sample sizes, used features, ML methodology, and reported accuracy. To our best knowledge, this is the first review that reports diagnostic ML applications using fNIRS. We found that there has been an increasing trend to perform ML applications on fNIRS-based biomarker research since 2010. The most studied populations are schizophrenia (n = 12), attention deficit and hyperactivity disorder (n = 7), and autism spectrum disorder (n = 6) are the most studied populations. There is a significant negative correlation between sample size (>21) and accuracy values. Support vector machine (SVM) and deep learning (DL) approaches were the most popular classifier approaches (SVM = 20) (DL = 10). Eight of these studies recruited a number of participants more than 100 for classification. Concentration changes in oxy-hemoglobin (ΔHbO) based features were used more than concentration changes in deoxy-hemoglobin (ΔHb) based ones and the most popular ΔHbO-based features were mean ΔHbO (n = 11) and ΔHbO-based functional connections (n = 11). Using ML on fNIRS data might be a promising approach to reveal specific biomarkers for diagnostic classification.

Rapid and non-destructive detection of ponceau 4R red colored pork

The characteristic colour of pork desired by consumers is a widespread phenomenon on the Ghanaian market that has led to some suspected adulteration practices. Currently available methods for monitoring pork quality are time consuming but above all, destructive (destroys the integrity of meat). This study aimed to develop rapid models that can be used to detect, classify and predict the presence of ponceau 4R in fresh pork in the Kumasi metropolis of Ghana using near-infrared spectroscopy together with chemometrics. Fresh pork samples, 120 obtained from the markets and 120 adulterated artificially in the laboratory, were subjected to near-infrared measurements. The spectra obtained were evaluated using Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and Partial Least Square Regression (PLSR). PCA and LDA showed that scanning the skin of the pork and pretreating the spectra with Savitzky-Golay smoothing sufficed for further chemometric analysis. The classification models built using LDA showed similarities between samples obtained from the markets and the artificially adulterated samples, indicating the presence of colour adulterant. The models also revealed the importance of processing time in making the adulterated meat more appealing to consumers. PLSR, however, yielded poor results for predicting colour and adulterant concentration. In effect, PCA and LDA methods proved to be better alternatives for the detection of colored pork adulteration and can be adopted for quality control applications together with near infrared spectroscopy.

Cognitive Effort during Visuospatial Problem Solving in Physical Real World, on Computer Screen, and in Virtual Reality

Spatial cognition plays a crucial role in academic achievement, particularly in science, technology, engineering, and mathematics (STEM) domains. Immersive virtual environments (VRs) have the growing potential to reduce cognitive load and improve spatial reasoning. However, traditional methods struggle to assess the mental effort required for visuospatial processes due to the difficulty in verbalizing actions and other limitations in self-reported evaluations. In this neuroergonomics study, we aimed to capture the neural activity associated with cognitive workload during visuospatial tasks and evaluate the impact of the visualization medium on visuospatial task performance. We utilized functional near-infrared spectroscopy (fNIRS) wearable neuroimaging to assess cognitive effort during spatial-reasoning-based problem-solving and compared a VR, a computer screen, and a physical real-world task presentation. Our results reveal a higher neural efficiency in the prefrontal cortex (PFC) during 3D geometry puzzles in VR settings compared to the settings in the physical world and on the computer screen. VR appears to reduce the visuospatial task load by facilitating spatial visualization and providing visual cues. This makes it a valuable tool for spatial cognition training, especially for beginners. Additionally, our multimodal approach allows for progressively increasing task complexity, maintaining a challenge throughout training. This study underscores the potential of VR in developing spatial skills and highlights the value of comparing brain data and human interaction across different training settings.

Evaluation of Morlet Wavelet Analysis for Artifact Detection in Low-Frequency Commercial Near-Infrared Spectroscopy Systems

Regional cerebral oxygen saturation (rSO2), a method of cerebral tissue oxygenation measurement, is recorded using non-invasive near-infrared Spectroscopy (NIRS) devices. A major limitation is that recorded signals often contain artifacts. Manually removing these artifacts is both resource and time consuming. The objective was to evaluate the applicability of using wavelet analysis as an automated method for simple signal loss artifact clearance of rSO2 signals obtained from commercially available devices. A retrospective observational study using existing populations (healthy control (HC), elective spinal surgery patients (SP), and traumatic brain injury patients (TBI)) was conducted. Arterial blood pressure (ABP) and rSO2 data were collected in all patients. Wavelet analysis was determined to be successful in removing simple signal loss artifacts using wavelet coefficients and coherence to detect signal loss artifacts in rSO2 signals. The removal success rates in HC, SP, and TBI populations were 100%, 99.8%, and 99.7%, respectively (though it had limited precision in determining the exact point in time). Thus, wavelet analysis may prove to be useful in a layered approach NIRS signal artifact tool utilizing higher-frequency data; however, future work is needed.

Prefrontal NIRS signal is unaffected by forehead Doppler flux during incremental cycling exercise

Near-infrared spectroscopy (NIRS) is used to measure tissue concentrations of oxyhemoglobin (O2 Hb) and deoxyhemoglobin (HHb). In the context of exercise, NIRS confers a higher signal-to-noise ratio than other neuroimaging techniques. However, part of the signal may be influenced by thermoregulatory hyperemia in the superficial cutaneous capillaries of the forehead. The degree to which NIRS signals during exercise reflect cerebral or extracerebral hemodynamic changes is a continuing source of controversy. However, the influence of skin blood flow may be attenuated depending on the NIRS technique (e.g., frequency domain machines with maximal optode separation distances >3.5 cm). The purpose of this study was to compare the changes in forehead skin blood flow and cerebral hemoglobin concentration during incremental exercise versus direct vasodilation of the forehead skin induced by gradual local heating. Thirty participants (12 females, 18 males; age: 20.8 ± 3.2 years; body mass index: 23.8 ± 3.7 kg·m-2 ) participated in the study. Forehead skin blood flow was quantified laser Doppler flux and absolute concentrations of cerebral O2 Hb and HHb were measured by NIRS. Local heating significantly increased the Doppler flux signal across time and these changes were significantly correlated with skin temperature. During incremental exercise, skin temperature, Doppler flux, O2 Hb and HHb increased however, the only significant change that was consistently correlated with Doppler flux was skin temperature. Therefore, a significant change in forehead skin blood flow may not significantly the NIRS hemoglobin data, depending on the type of NIRS device used.

Functional near-infrared spectroscopy is a sensitive marker of neurophysiological deficits on executive function tasks in young adults with a history of child abuse

Previous research has shown the utility of imaging measures of neural activity in identifying deficits in cognitive functioning in individuals with a history of child abuse. The purpose of the present study was to measure differences that may exist between individuals who reported physical, emotional, or sexual abuse as children (n = 37) vs. those who did not (n = 47) using Functional Near Infrared Spectroscopy (fNIRS) during the completion of cognitive tasks of executive function. The results showed a significantly higher rate and number of errors of commission on the Conners CPT test in the child abuse group compared to the control group. The analyses also showed a statistically significant decrease in oxyhemoglobin (oxy-Hb) concentration in the left rostral prefrontal cortex in the child abuse group compared to the no-abuse group during the Wisconsin Card Sorting Test (WCST). A similar, albeit non-significant, trend toward decreased oxy-Hb concentration was observed in the child abuse group in the right dorsolateral prefrontal cortex (dlPFC) on the OSPAN and Connors CPT. The results suggest that the latter group may show subtle neurological deficits that persist into adulthood that may not manifest on traditional measures of cognitive function. These findings have implications for the development of remediation and treatment strategies in this population.

Functional near-infrared spectroscopy is a useful tool for multi-perspective psychobiological study of neurophysiological correlates of parenting behaviour

The quality of the relationship between caregiver and child has long-term effects on the cognitive and socio-emotional development of children. A process involved in human parenting is the bio-behavioural synchrony that occurs between the partners in the relationship during interaction. Through interaction, bio-behavioural synchronicity allows the adaptation of the physiological systems of the parent to those of the child and promotes the positive development and modelling of the child's social brain. The role of bio-behavioural synchrony in building social bonds could be investigated using functional near-infrared spectroscopy (fNIRS). In this paper we have (a) highlighted the importance of the quality of the caregiver-child relationship for the child's cognitive and socio-emotional development, as well as the relevance of infantile stimuli in the activation of parenting behaviour; (b) discussed the tools used in the study of the neurophysiological substrates of the parental response; (c) proposed fNIRS as a particularly suitable tool for the study of parental responses; and (d) underlined the need for a multi-systemic psychobiological approach to understand the mechanisms that regulate caregiver-child interactions and their bio-behavioural synchrony. We propose to adopt a multi-system psychobiological approach to the study of parental behaviour and social interaction.

Effects of Baduanjin imagery and exercise on cognitive function in the elderly: A functional near-infrared spectroscopy study

Objective

Cognitive function is essential in ensuring the quality of life of the elderly. This study aimed to investigate the effects of Baduanjin imagery and Baduanjin movement (a traditional Chinese health exercise, TCHE) on cognitive function in the elderly using functional near-infrared spectroscopy (fNIRS).

Methods

72 participants with a mean age of 66.92 years (SD = 4.77) were recruited for this study. The participants were randomly assigned to three groups: the Baduanjin imagery, the Baduanjin exercise, and the Control. Stroop task was used to record the accuracy and reaction times, and a near-infrared spectral brain imaging system was used to monitor the brain's oxy-hemoglobin concentration responses.

Results

(1) For the reaction times of Stroop incongruent tasks, the main effect of the test phase (F = 114.076, p < 0.001) and the interaction effect between test phase and group (F = 10.533, p < 0.001) were all significant. The simple effect analysis further demonstrated that the reaction times of the Baduanjin imagery group and Baduanjin exercise group in the post-test was faster than that in the pre-test (ps < 0.001); (2) Analysis of fNIRS data showed the significant interaction effect (F = 2.554, p = 0.013) between the test phase and group in the left dorsolateral prefrontal cortex. Further analysis showed that, during the post-test incongruent tasks, the oxy-Hb variations were significantly higher in participants of the Baduanjin imagery group (p = 0.005) and Baduanjin exercise group (p = 0.002) than in the control group; For the right inferior frontal gyrus, the interaction between the test phase and group was significant (F = 2.060, p = 0.044). Further analysis showed that, during the post-test incongruent tasks, the oxy-Hb variations were significantly higher in participants of the Baduanjin imagery group than in the control group (p = 0.001).

Conclusion

Baduanjin imagery and exercise positively affect cognitive performance; Baduanjin imagery and exercise activated the left dorsolateral prefrontal cortex; Baduanjin imagery activated the right inferior frontal gyrus, while Baduanjin exercise could not.

Acupuncture enhances brain function in patients with mild cognitive impairment: evidence from a functional-near infrared spectroscopy study

Mild cognitive impairment (MCI) is a precursor to Alzheimer’s disease. It is imperative to develop a proper treatment for this neurological disease in the aging society. This observational study investigated the effects of acupuncture therapy on MCI patients. Eleven healthy individuals and eleven MCI patients were recruited for this study. Oxy- and deoxy-hemoglobin signals in the prefrontal cortex during working-memory tasks were monitored using functional near-infrared spectroscopy. Before acupuncture treatment, working-memory experiments were conducted for healthy control (HC) and MCI groups (MCI-0), followed by 24 sessions of acupuncture for the MCI group. The acupuncture sessions were initially carried out for 6 weeks (two sessions per week), after which experiments were performed again on the MCI group (MCI-1). This was followed by another set of acupuncture sessions that also lasted for 6 weeks, after which the experiments were repeated on the MCI group (MCI-2). Statistical analyses of the signals and classifications based on activation maps as well as temporal features were performed. The highest classification accuracies obtained using binary connectivity maps were 85.7% HC vs. MCI-0, 69.5% HC vs. MCI-1, and 61.69% HC vs. MCI-2. The classification accuracies using the temporal features mean from 5 seconds to 28 seconds and maximum (i.e, max(5:28 seconds)) values were 60.6% HC vs. MCI-0, 56.9% HC vs. MCI-1, and 56.4% HC vs. MCI-2. The results reveal that there was a change in the temporal characteristics of the hemodynamic response of MCI patients due to acupuncture. This was reflected by a reduction in the classification accuracy after the therapy, indicating that the patients’ brain responses improved and became comparable to those of healthy subjects. A similar trend was reflected in the classification using the image feature. These results indicate that acupuncture can be used for the treatment of MCI patients.

Brain–Computer Interfacing Using Functional Near-Infrared Spectroscopy (fNIRS)

Functional Near-Infrared Spectroscopy (fNIRS) is a wearable optical spectroscopy system originally developed for continuous and non-invasive monitoring of brain function by measuring blood oxygen concentration. Recent advancements in brain–computer interfacing allow us to control the neuron function of the brain by combining it with fNIRS to regulate cognitive function. In this review manuscript, we provide information regarding current advancement in fNIRS and how it provides advantages in developing brain–computer interfacing to enable neuron function. We also briefly discuss about how we can use this technology for further applications.

From reversal to normal: Robust improvement in conflict adaptation through real-time functional near infrared spectroscopy-based neurofeedback training

Conflict adaptation refers to the improved conflict control induced after experiencing conflict and is a prominent index of adaptive cognitive control. Reversal of conflict adaptation may be maladaptive and predictive of certain mental disorders. Here, we employed real-time functional near infrared spectroscopy-based neurofeedback training, with the left dorsolateral prefrontal cortex as the target brain area, to investigate whether reversal of conflict adaptation during a word-color Stroop task could be recovered to be normal. Healthy human individuals with reversal pattern of conflict adaptation in the pretest were randomly assigned into the experimental or control groups. Distributed training for 80 min led to greater improvements in the experimental group who received real neurofeedback compared to those in the control group who received sham neurofeedback. These results indicated causal evidence for understanding the generation of conflict adaptation and heighten the prospects of clinical application of neurofeedback training.

Effects of acute psychosocial stress on interpersonal cooperation and competition in young women

Although tend-and-befriend is believed to be the dominant stress response in women, little is known regarding the effects of acute psychosocial stress on different dynamic social interactions. To measure these effects, 80 female participants were recruited, paired into the dyads, and instructed to complete cooperative and competitive key-pressing tasks after experiencing acute stress or a control condition. Each dyad of participants should press the key synchronously when the signal was presented in the cooperative task and as fast as possible in the competitive task. During the tasks, brain activities of prefrontal and right temporo-parietal areas were recorded from each dyad using functional near-infrared spectroscopy (fNIRS). The results showed that acute psychosocial stress evidently promoted competitive behavior, accompanied by increased interpersonal neural synchronization (INS) in the right dorsolateral prefrontal cortex. Despite the lack of a significant difference in the overall cooperation rate, the response time difference between two stressed participants markedly declined over time with more widespread INS in the prefrontal cortex, suggesting that there ensued cooperative improvement among stressed women. These findings behaviorally and neurologically revealed context-dependent response patterns to psychosocial stress in women during dynamic social interactions.

Improving Emotion Regulation Through Real-Time Neurofeedback Training on the Right Dorsolateral Prefrontal Cortex: Evidence From Behavioral and Brain Network Analyses

We investigated if emotion regulation can be improved through self-regulation training on non-emotional brain regions, as well as how to change the brain networks implicated in this process. During the training period, the participants were instructed to up-regulate their right dorsolateral prefrontal cortex (rDLPFC) activity according to real-time functional near-infrared spectroscopy (fNIRS) neurofeedback signals, and there was no emotional element. The results showed that the training significantly increased emotion regulation, resting-state functional connectivity (rsFC) within the emotion regulation network (ERN) and frontoparietal network (FPN), and rsFC between the ERN and amygdala; however, training did not influence the rsFC between the FPN and the amygdala. However, self-regulation training on rDLPFC significantly improved emotion regulation and generally increased the rsFCs within the networks; the rsFC between the ERN and amygdala was also selectively increased. The present study also described a safe approach that may improve emotion regulation through self-regulation training on non-emotional brain regions.

Deconvolution of hemodynamic responses along the cortical surface using personalized functional near infrared spectroscopy

In functional near infrared spectroscopy (fNIRS), deconvolution analysis of oxy and deoxy-hemoglobin concentration changes allows estimating specific hemodynamic response functions (HRF) elicited by neuronal activity, taking advantage of the fNIRS excellent temporal resolution. Diffuse optical tomography (DOT) is also becoming the new standard reconstruction procedure as it is more accurate than the modified Beer Lambert law approach at the sensor level. The objective of this study was to assess the relevance of HRF deconvolution after DOT constrained along the cortical surface. We used local personalized fNIRS montages which consists in optimizing the position of fNIRS optodes to ensure maximal sensitivity to subject specific target brain regions. We carefully evaluated the accuracy of deconvolution when applied after DOT, using realistic simulations involving several HRF models at different signal to noise ratio (SNR) levels and on real data related to motor and visual tasks in healthy subjects and from spontaneous pathological activity in one patient with epilepsy. We demonstrated that DOT followed by deconvolution was able to accurately recover a large variability of HRFs over a large range of SNRs. We found good performances of deconvolution analysis for SNR levels usually encountered in our applications and we were able to reconstruct accurately the temporal dynamics of HRFs in real conditions.

High density optical neuroimaging predicts surgeons's subjective experience and skill levels

Measuring cognitive load is important for surgical education and patient safety. Traditional approaches of measuring cognitive load of surgeons utilise behavioural metrics to measure performance and surveys and questionnaires to collect reports of subjective experience. These have disadvantages such as sporadic data, occasionally intrusive methodologies, subjective or misleading self-reporting. In addition, traditional approaches use subjective metrics that cannot distinguish between skill levels. Functional neuroimaging data was collected using a high density, wireless NIRS device from sixteen surgeons (11 attending surgeons and 5 surgery resident) and 17 students while they performed two laparoscopic tasks (Peg transfer and String pass). Participant’s subjective mental load was assessed using the NASA-TLX survey. Machine learning approaches were used for predicting the subjective experience and skill levels. The Prefrontal cortex (PFC) activations were greater in students who reported higher-than-median task load, as measured by the NASA-TLX survey. However in the case of attending surgeons the opposite tendency was observed, namely higher activations in the lower v higher task loaded subjects. We found that response was greater in the left PFC of students particularly near the dorso- and ventrolateral areas. We quantified the ability of PFC activation to predict the differences in skill and task load using machine learning while focussing on the effects of NIRS channel separation distance on the results. Our results showed that the classification of skill level and subjective task load could be predicted based on PFC activation with an accuracy of nearly 90%. Our finding shows that there is sufficient information available in the optical signals to make accurate predictions about the surgeons’ subjective experiences and skill levels. The high accuracy of results is encouraging and suggest the integration of the strategy developed in this study as a promising approach to design automated, more accurate and objective evaluation methods.

The relationship of cortical activity induced by pain stimulation with clinical and cognitive features of somatic symptom disorder: A controlled functional near infrared spectroscopy study

OBJECTIVE

The neurobiological correlates of Somatic Symptom Disorder (SSD) introduced in the DSM-5 has been the focus of a limited investigation. We aimed to examine the cortical response to painful stimuli and its relationship to symptom severity as well as cognitive and psychological characteristics in proposed models of somatoform disorders.

METHODS

We measured hemodynamic responses by 52-channel functional near-infrared spectroscopy. We compared the cortical response to painful stimuli in index patients with SSD (N = 21) versus age, and gender matched healthy control subjects (N = 21). We used brush stimulation as the control condition. We analyzed the relationship of cortical activity with SSD symptom severity as well as somatosensory amplification (SSA), alexithymia, dysfunctional illness behaviour, worry, and neuroticism.

RESULTS

Patients with SSD had higher somatic symptom severity, SSA, alexithymia, neuroticism, illness-related worry, and behaviour. Somatic symptom severity was predicted by a model including SSA and subjective feeling of pain in the index patients. Activity in the left-angular and right-middle temporal gyri was higher in the SSD subjects than the controls during pain stimulation. Positive correlations were detected between mean pain threshold levels and left middle occipital gyrus activity, as well as between SSA-scores and right-angular gyrus activity during pain condition in the index patients with SSD.

CONCLUSION

We present the first evidence that representation of pain in terms of cortical activity is different in subjects with SSD than healthy controls. SSA has functional neuroanatomic correlates and predicts symptom severity in SSD and therefore is involved as a valid intermediate phenotype in SSD pathophysiology.

Neonatal NIRS monitoring: recommendations for data capture and review of analytics

Brain injury is one of the most consequential problems facing neonates, with many preterm and term infants at risk for cerebral hypoxia and ischemia. To develop effective neuroprotective strategies, the mechanistic basis for brain injury must be understood. The fragile state of neonates presents unique research challenges; invasive measures of cerebral blood flow and oxygenation assessment exceed tolerable risk profiles. Near-infrared spectroscopy (NIRS) can safely and non-invasively estimate cerebral oxygenation, a correlate of cerebral perfusion, offering insight into brain injury-related mechanisms. Unfortunately, lack of standardization in device application, recording methods, and error/artifact correction have left the field fractured. In this article, we provide a framework for neonatal NIRS research. Our goal is to provide a rational basis for NIRS data capture and processing that may result in better comparability between studies. It is also intended to serve as a primer for new NIRS researchers and assist with investigation initiation.

Does Everyday Conversation Contribute to Cognitive Functioning? A Comparison of Brain Activity During Task-Oriented and Life-Worldly Communication Using Near-Infrared Spectroscopy

This study aimed to explore differences in frontal lobe brain activity associated with two types of communication: task-oriented and life-worldly, the latter of which largely overlaps with everyday conversation. Using near-infrared spectroscopy, we explored differences by comparing oxygenated hemoglobin concentrations associated with periods of rest and conversation in two experimental groups comprising older and younger adults. Artifacts were removed from the signals using discrete wavelet transforms. Paired t-tests were used to compare the resulting data for the two types. The results showed that oxygenated hemoglobin levels during life-worldly communication were significantly higher than at baseline or during task-oriented communication, particularly for the older adult group. In addition, during life-worldly communication, relatively high levels of brain activity were found in the upper part of the Broca area and in the premotor cortex. These results, which suggest that life-worldly communication generates more activity in the frontal lobe, could potentially contribute to improving how caregivers communicate with older patients/residents in hospitals and nursing homes.

Automated Thresholding Method for fNIRS-Based Functional Connectivity Analysis: Validation With a Case Study on Alzheimer's Disease

While functional integration has been suggested to reflect brain health, non-standardized network thresholding methods complicate network interpretation. We propose a new method to analyze functional near-infrared spectroscopy-based functional connectivity (fNIRS-FC). In this study, we employed wavelet analysis for motion correction and orthogonal minimal spanning trees (OMSTs) to derive the brain connectivity. The proposed method was applied to an Alzheimer's disease (AD) dataset and was compared with a number of well-known thresholding techniques. The results demonstrated that the proposed method outperformed the benchmarks in filtering cost-effective networks and in differentiation between patients with mild AD and healthy controls. The results also supported the proposed method as a feasible technique to analyze fNIRS-FC, especially with cost-efficiency, assortativity and laterality as a set of effective features for the diagnosis of AD.

Change in telescoping leg strategy with varying walking speed to modulate force advantage

Human walking consists of two major sequential events (i.e., single- and double-support phases). Although there have been many studies relating to basic principles of the each stage, how the two distinct but continuous phases interact with each other remains to be clarified. We examined the change in walking strategy with varying walking speed on a local reference frame with telescoping and tangential axes; we expect that the telescoping directional dynamics at the end of a single-support phase change with walking speed to facilitate the modulation of the push-off work during a double-support phase. The telescoping directional force and power are calculated using two methods: model simulation and kinematic configuration. The empirical walking data for eight healthy young subjects and the corresponding model parameters obtained from a data-fit optimization were used to investigate the changing trend of each factor (i.e., force and power) with the increase in speed. The resulting force at the end of the single-support phase significantly increased with the walking speed for both methods, whereas the resulting power remained nearly unchanged and was close to zero for the entire range of walking speeds. This result implies that the positive amount of the telescoping directional force at the end of the single-support phase may be a certain type of preparation for the double-support phase, which can contribute to a larger push-off.

Simulation and in vivo investigation of light-emitting diode, near infrared Gaussian beam profiles

Near infrared spectroscopy is an optical imaging technique which offers a non-invasive, portable, and low-cost method for continuously measuring the oxygenation of tissues. In particular, it can provide the brain activation through measuring the blood oxygenation and blood volume in the cortex. Understanding and then improving the spatial and depth sensitivity of near infrared spectroscopy measurements to brain tissue are essential for designing experiments as well as interpreting research findings. In this study, we investigate the effect of applying two common light beam profiles including Uniform and Gaussian on the penetration depth of an LED-based near infrared spectroscopy. In this regard, two Gaussian profiles were produced by adjusting plano-convex and bi-convex lenses and the Uniform profile was provided by applying a flat lens. Two experiments were conducted in this study. First, a simulation experiment was carried out based on scanning the intra space of a liquid phantom by using static and pulsating absorbers to compare the penetration depth of the configurations applied on the LED-based near infrared spectroscopy with that of a laser-based near infrared spectroscopy. Second, to show the feasibility of the best proposed configuration applied, an in vivo experiment of stress assessment has been performed and its results have been compared with that results obtained by laser one. The results showed that the LED-based near infrared spectroscopy equipped with bi-convex lens provides a penetration depth and hence quality measurements of near infrared spectroscopy and its extracted heart rate variability signals as well as laser-based near infrared spectroscopy especially in the application of stress assessment.

A Newcomer's Guide to Functional Near Infrared Spectroscopy Experiments

This review presents a practical primer for functional near-infrared spectroscopy (fNIRS) with respect to technology, experimentation, and analysis software. Its purpose is to jump-start interested practitioners considering utilizing a non-invasive, versatile, nevertheless challenging window into the brain using optical methods. We briefly recapitulate relevant anatomical and optical foundations and give a short historical overview. We describe competing types of illumination (trans-illumination, reflectance, and differential reflectance) and data collection methods (continuous wave, time domain and frequency domain). Basic components (light sources, detection, and recording components) of fNIRS systems are presented. Advantages and limitations of fNIRS techniques are offered, followed by a list of very practical recommendations for its use. A variety of experimental and clinical studies with fNIRS are sampled, shedding light on many brain-related ailments. Finally, we describe and discuss a number of freely available analysis and presentation packages suited for data analysis. In conclusion, we recommend fNIRS due to its ever-growing body of clinical applications, state-of-the-art neuroimaging technique and manageable hardware requirements. It can be safely concluded that fNIRS adds a new arrow to the quiver of neuro-medical examinations due to both its great versatility and limited costs.

Approach to optimize 3-dimensional brain functional activation image with high resolution: a study on functional near-infrared spectroscopy

In this study, 3-dimensional (3-D) enhanced brain-function-map generation and estimation methodology is presented. Optical signals were modelled in the form of numerical optimization problem to infer the best existing waveform of canonical hemodynamic response function. Inter-channel activity patterns were also estimated. The estimation of activation of inter-channel gap depends on the minimization of generalized cross-validation. 3-D brain activation maps were produced through inverse discrete cosine transform. The proposed algorithm acquired significant results for 3-D functional maps with high resolution, in comparison with that of 2-D functional t-maps. A comprehensive analysis by exhibiting images corresponding to several layers has also been appended.

Effects of Acupuncture Therapy on MCI Patients Using Functional Near-Infrared Spectroscopy

Acupuncture therapy (AT) is a non-pharmacological method of treatment that has been applied to various neurological diseases. However, studies on its longitudinal effect on the neural mechanisms of patients with mild cognitive impairment (MCI) for treatment purposes are still lacking in the literature. In this clinical study, we assess the longitudinal effects of ATs on MCI patients using two methods: (i) Montreal Cognitive Assessment test (MoCA-K, Korean version), and (ii) the hemodynamic response (HR) analyses using functional near-infrared spectroscopy (fNIRS). fNIRS signals of a working memory (WM) task were acquired from the prefrontal cortex. Twelve elderly MCI patients and 12 healthy people were recruited as target and healthy control (HC) groups, respectively. Each group went through an fNIRS scanning procedure three times: The initial data were obtained without any ATs, and subsequently a total of 24 AT sessions were conducted for MCI patients (i.e., MCI-0: the data prior to ATs, MCI-1: after 12 sessions of ATs for 6 weeks, MCI-2: another 12 sessions of ATs for 6 weeks). The mean HR responses of all MCI-0–2 cases were lower than those of HCs. To compare the effects of AT on MCI patients, MoCA-K results, temporal HR data, and spatial activation patterns (i.e., t-maps) were examined. In addition, analyses of functional connectivity (FC) and graph theory upon WM tasks were conducted. With ATs, (i) the averaged MoCA-K test scores were improved (MCI-1, p = 0.002; MCI-2, p = 2.9e^–4); (ii) the mean HR response of WM tasks was increased (p < 0.001); and (iii) the t-maps of MCI-1 and MCI-2 were enhanced. Furthermore, an increased FC in the prefrontal cortex in both MCI-1/MCI-2 cases in comparison to MCI-0 was obtained (p < 0.01), and an increasing trend in the graph theory parameters was observed. All these findings reveal that ATs have a positive impact on improving the cognitive function of MCI patients. In conclusion, ATs can be used as a therapeutic tool for MCI patients as a non-pharmacological method (Clinical trial registration number: KCT 0002451 https://cris.nih.go.kr/cris/en/).

Interhemispheric Synchrony of Spontaneous Cortical States at the Cortical Column Level

In cat early visual cortex, neural activity patterns resembling evoked orientation maps emerge spontaneously under anesthesia. To test if such patterns are synchronized between hemispheres, we performed bilateral imaging in anesthetized cats using a new improved voltage-sensitive dye. We observed map-like activity patterns spanning early visual cortex in both hemispheres simultaneously. Patterns virtually identical to maps associated with the cardinal and oblique orientations emerged as leading principal components of the spontaneous fluctuations, and the strength of transient orientation states was correlated with their duration, providing evidence that these maps are transiently attracting states. A neural mass model we developed reproduced the dynamics of both smooth and abrupt orientation state transitions observed experimentally. The model suggests that map-like activity arises from slow modulations in spontaneous firing in conjunction with interplay between excitation and inhibition. Our results highlight the efficiency and functional precision of interhemispheric connectivity.

Affect and prefrontal hemodynamics during exercise under immersive audiovisual stimulation: Improving the experience of exercise for overweight adults

OBJECTIVE

Research on methods of improving the affective experience of exercise remains limited, especially for low-active overweight adults. We investigated the effectiveness of a virtual-reality headset and headphones in improving affective responses over conventionally delivered audiovisual stimulation.

METHODS

Low-active, overweight adults (16 women, 5 men; age: 34.67 ± 9.62 years; body mass index: 28.56 ± 4.95 kg/m²; peak oxygen uptake for men: 29.14 ± 6.56 mL/kg/min, for women: 22.67 ± 4.52 mL/kg/min, mean ± SD) completed 15-min sessions of recumbent cycling at the ventilatory threshold: (a) high immersion (HI, virtual reality headset and headphones), (b) low immersion (LI, television screen and speakers), and (c) Control. During-exercise pleasure and post-exercise enjoyment were self-reported. Oxygenation of the right dorsolateral prefrontal cortex (dlPFC) was assessed with near infrared spectroscopy.

RESULTS

Higher pleasure was reported during HI than during LI and Control (Condition × Time interaction; p < 0.001, η _p ² = 0.43). Participants who reported a preference for low exercise intensity showed higher dlPFC oxygenation during Control, but this difference diminished during LI and HI (Condition × Time × Preference interaction; p = 0.036, η_p ² = 0.10).

CONCLUSION

Compared with conventionally delivered audiovisual stimulation, using a virtual-reality headset strengthens the dissociative effect, further improving affective responses to exercise at the ventilatory threshold among overweight, low-active adults. Presumably by competing with interoceptive afferents at the level of sensory input, audiovisual stimulation may lessen reliance on cognitive efforts to attenuate declining affect, as indicated by lower right dlPFC activity, particularly among participants disinclined toward high exercise intensity.

Psychophysiological Responses to Stress Related to Anxiety in Healthy Aging

Abstract. The aim of the study was to explore the effects of situational stress and anxiety in a group of healthy elderly, both in terms of psychophysiological correlates and cognitive performance. Eighteen participants ( Mage = 70 ± 6.3; range 60–85) were assessed for anxiety and were instructed to perform a computerized math task, under both a stressful and a control condition, while near-infrared spectroscopy (NIRS) signal and electrocardiography (ECG) were recorded. NIRS results evidenced an increased activation of right PFC during the entire procedure, even if effect sizes between left and right channels were larger during the experimental condition. The amount of right activation during the stressful condition was positively correlated with anxiety. Response times (RTs) were slower in more anxious than in less anxious individuals, both during the control and stressful conditions. Accuracy was lower in more anxious than in less anxious individuals, only during the stressful condition. Moreover, heart rate (HR) was not modulated by situational stress, nor by anxiety. Overall, the present study suggests that in healthy elderly, anxiety level has a significant impact on cerebral responses, and both on the amount of cognitive resources and the quality of performance in stressful situations.

Early detection of diving-related cognitive impairment of different nitrogen-oxygen gas mixtures using critical flicker fusion frequency

INTRODUCTION

Cognitive impairment related to inert gas narcosis (IGN) is a threat to diving safety and operations at depth that might be reduced by using enriched air nitrox (EANx) mixtures. Using critical flicker fusion frequency (CFFF), a possible early detection of cognitive abilities/cerebral arousal impairment when breathing different oxygen (O2) fractions was investigated.

METHODS

Eight male volunteers performed, in random order, two dry chamber dives breathing either air or EANx40 (40% O₂-60% nitrogen) for 20 minutes (min) at 0.4 MPa. Cognition and arousal were assessed before the dive; upon arrival at 0.4 MPa; after 15 min exposure at 0.4 MPa; on surfacing and 30 min post-dive using behavioural computer-based testing psychology experiment building language (PEBL) and by CFFF while continuously recording brain oxygenation with near-infrared spectroscopy.

RESULTS

In both breathing conditions, CFFF and PEBL demonstrated a significant inverse correlation (Pearson r of -0.90, P < 0.0001), improved cognitive abilities/cerebral arousal occurred upon arrival at 0.4 MPa followed by a progressive deterioration. Initial brain activation was associated with a significant increase in oxyhaemoglobin (HbO2) and a simultaneous decrease of deoxyhaemoglobin (HHb). The magnitude of the changes was significantly greater under EANx (P = 0.038).

CONCLUSIONS

Since changes were not related to haemodynamic variables, HbO₂ and HHb values indicate a significant, O₂-dependent activation in the prefrontal cortex. Owing to the correlation with some tests from the PEBL, CFFF could be a convenient measure of cognitive performance/ability in extreme environments, likely under the direct influence of oxygen partial pressure, a potent modulator of IGN symptoms.

Functional near-infrared spectroscopy-informed neurofeedback: regional-specific modulation of lateral orbitofrontal activation and cognitive flexibility

Cognitive flexibility and reward processing critically rely on the orbitofrontal cortex (OFC). Dysregulations in these domains and orbitofrontal activation have been reported in major psychiatric disorders. Hemodynamic brain imaging-informed neurofeedback allows regional-specific control over brain activation and thus may represent an innovative intervention to regulate orbitofrontal dysfunctions. Against this background the present proof-of-concept study evaluates the feasibility and behavioral relevance of functional near-infrared spectroscopy (fNIRS)-assisted neurofeedback training of the lateral orbitofrontal cortex (lOFC). In a randomized sham-controlled between-subject design, 60 healthy participants have undergone four subsequent runs of training to enhance the lOFC activation. Training-induced changes in the lOFC, attentional set-shifting performance, and reward experience have served as primary outcomes. Feedback from the target channel significantly increases the regional-specific lOFC activation over the four training runs in comparison with sham neurofeedback. The real-time OFC neurofeedback group demonstrates a trend for faster responses during the set-shifting relative to the sham neurofeedback group. Within the real-time OFC neurofeedback group, stronger training-induced lOFC increases are associated with higher reward experience. The present results demonstrate that fNIRS-informed neurofeedback allows regional-specific regulation of lOFC activation and may have the potential to modulate the associated behavioral domains. As such fNIRS-informed neurofeedback may represent a promising strategy to regulate OFC dysfunctions in psychiatric disorders.

Newborns are sensitive to multiple cues for word segmentation in continuous speech

Before infants can learn words, they must identify those words in continuous speech. Yet, the speech signal lacks obvious boundary markers, which poses a potential problem for language acquisition (Swingley, Philos Trans R Soc Lond. Series B, Biol Sci 364(1536), 3617-3632, 2009). By the middle of the first year, infants seem to have solved this problem (Bergelson & Swingley, Proc Natl Acad Sci 109(9), 3253-3258, 2012; Jusczyk & Aslin, Cogn Psychol 29, 1-23, 1995), but it is unknown if segmentation abilities are present from birth, or if they only emerge after sufficient language exposure and/or brain maturation. Here, in two independent experiments, we looked at two cues known to be crucial for the segmentation of human speech: the computation of statistical co-occurrences between syllables and the use of the language's prosody. After a brief familiarization of about 3 min with continuous speech, using functional near-infrared spectroscopy, neonates showed differential brain responses on a recognition test to words that violated either the statistical (Experiment 1) or prosodic (Experiment 2) boundaries of the familiarization, compared to words that conformed to those boundaries. Importantly, word recognition in Experiment 2 occurred even in the absence of prosodic information at test, meaning that newborns encoded the phonological content independently of its prosody. These data indicate that humans are born with operational language processing and memory capacities and can use at least two types of cues to segment otherwise continuous speech, a key first step in language acquisition.

An Information-Theoretic Approach to Quantitative Analysis of the Correspondence Between Skin Blood Flow and Functional Near-Infrared Spectroscopy Measurement in Prefrontal Cortex Activity

Effect of Skin blood flow (SBF) on functional near-infrared spectroscopy (fNIRS) measurement of cortical activity proves to be an illusive subject matter with divided stances in the neuroscientific literature on its extent. Whereas, some reports on its non-significant influence on fNIRS time series of cortical activity, others consider its impact misleading, even detrimental, in analysis of the brain activity as measured by fNIRS. This situation is further escalated by the fact that almost all analytical studies are based on comparison with functional Magnetic Resonance Imaging (fMRI). In this article, we pinpoint the lack of perspective in previous studies on preservation of information content of resulting fNIRS time series once the SBF is attenuated. In doing so, we propose information-theoretic criteria to quantify the necessary and sufficient conditions for SBF attenuation such that the information content of frontal brain activity in resulting fNIRS times series is preserved. We verify these criteria through evaluation of their utility in comparative analysis of principal component (PCA) and independent component (ICA) SBF attenuation algorithms. Our contributions are 2-fold. First, we show that mere reduction of SBF influence on fNIRS time series of frontal activity is insufficient to warrant preservation of cortical activity information. Second, we empirically justify a higher fidelity of PCA-based algorithm in preservation of the fontal activity's information content in comparison with ICA-based approach. Our results suggest that combination of the first two principal components of PCA-based algorithm results in most efficient SBF attenuation while preserving maximum frontal activity's information. These results contribute to the field by presenting a systematic approach to quantification of the SBF as an interfering process during fNIRS measurement, thereby drawing an informed conclusion on this debate. Furthermore, they provide evidence for a reliable choice among existing SBF attenuation algorithms and their inconclusive number of components, thereby ensuring minimum loss of cortical information during SBF attenuation process.

Applications of Functional Near-Infrared Spectroscopy (fNIRS) Neuroimaging in Exercise⁻Cognition Science: A Systematic, Methodology-Focused Review

For cognitive processes to function well, it is essential that the brain is optimally supplied with oxygen and blood. In recent years, evidence has emerged suggesting that cerebral oxygenation and hemodynamics can be modified with physical activity. To better understand the relationship between cerebral oxygenation/hemodynamics, physical activity, and cognition, the application of state-of-the art neuroimaging tools is essential. Functional near-infrared spectroscopy (fNIRS) is such a neuroimaging tool especially suitable to investigate the effects of physical activity/exercises on cerebral oxygenation and hemodynamics due to its capability to quantify changes in the concentration of oxygenated hemoglobin (oxyHb) and deoxygenated hemoglobin (deoxyHb) non-invasively in the human brain. However, currently there is no clear standardized procedure regarding the application, data processing, and data analysis of fNIRS, and there is a large heterogeneity regarding how fNIRS is applied in the field of exercise⁻cognition science. Therefore, this review aims to summarize the current methodological knowledge about fNIRS application in studies measuring the cortical hemodynamic responses during cognitive testing (i) prior and after different physical activities interventions, and (ii) in cross-sectional studies accounting for the physical fitness level of their participants. Based on the review of the methodology of 35 as relevant considered publications, we outline recommendations for future fNIRS studies in the field of exercise⁻cognition science.

Measuring Cortical Activity During Auditory Processing with Functional Near-Infrared Spectroscopy

Functional near-infrared spectroscopy (fNIRS) is an optical, non-invasive neuroimaging technique that investigates human brain activity by calculating concentrations of oxy- and deoxyhemoglobin. The aim of this publication is to review the current state of the art as to how fNIRS has been used to study auditory function. We address temporal and spatial characteristics of the hemodynamic response to auditory stimulation as well as experimental factors that affect fNIRS data such as acoustic and stimulus-driven effects. The rising importance that fNIRS is generating in auditory neuroscience underlines the strong potential of the technology, and it seems likely that fNIRS will become a useful clinical tool.

Motion Artifact Correction of Multi-Measured Functional Near-Infrared Spectroscopy Signals Based on Signal Reconstruction Using an Artificial Neural Network

In this paper, a new motion artifact correction method is proposed based on multi-channel functional near-infrared spectroscopy (fNIRS) signals. Recently, wavelet transform and hemodynamic response function-based algorithms were proposed as methods of denoising and detrending fNIRS signals. However, these techniques cannot achieve impressive performance in the experimental environment with lots of movement such as gait and rehabilitation tasks because hemodynamic responses have features similar to those of motion artifacts. Moreover, it is difficult to correct motion artifacts in multi-measured fNIRS systems, which have multiple channels and different noise features in each channel. Thus, a new motion artifact correction method for multi-measured fNIRS is proposed in this study, which includes a decision algorithm to determine the most contaminated fNIRS channel based on entropy and a reconstruction algorithm to correct motion artifacts by using a wavelet-decomposed back-propagation neural network. The experimental data was achieved from six subjects and the results were analyzed in comparing conventional algorithms such as HRF smoothing, wavelet denoising, and wavelet MDL. The performance of the proposed method was proven experimentally using the graphical results of the corrected fNIRS signal, CNR that is a performance evaluation index, and the brain activation map.

Neuronal Activation Detection Using Vector Phase Analysis with Dual Threshold Circles: A Functional Near-Infrared Spectroscopy Study

In this paper, a new vector phase diagram differentiating the initial decreasing phase (i.e. initial dip) and the delayed hemodynamic response (HR) phase of oxy-hemoglobin changes ( Δ HbO) of functional near-infrared spectroscopy (fNIRS) is developed. The vector phase diagram displays the trajectories of Δ HbO and deoxy-hemoglobin changes ( Δ HbR), as orthogonal components, in the Δ HbO- Δ HbR polar coordinates. To determine the occurrence of an initial dip, dual threshold circles (an inner circle from the resting state, an outer circle from the peak values of the initial dip and the main HR) are incorporated into the phase diagram for making decisions. The proposed scheme is then applied to a brain-computer interface scheme, and its performance is evaluated in classifying two finger tapping tasks (right-hand thumb and little finger) from the left motor cortex. Three gamma functions are used to model the initial dip, the main HR, and the undershoot in generating the designed HR function. In classifying two tapping tasks, the signal mean and signal minimum values during 0-2.5 s, as features of initial dip, are used. The linear discriminant analysis was utilized as a classifier. The experimental results show that the active brain locations of the two tasks were quite distinctive ( p < 0.05 ), and moreover, spatially specific if using the initial dip map at 4 s in comparison to the map of HRs at 14 s. Also, the average classification accuracy was improved from 59% to 74.9% when using the phase diagram of dual threshold circles.

Differential Entropy Preserves Variational Information of Near-Infrared Spectroscopy Time Series Associated With Working Memory

Neuroscience research shows a growing interest in the application of Near-Infrared Spectroscopy (NIRS) in analysis and decoding of the brain activity of human subjects. Given the correlation that is observed between the Blood Oxygen Dependent Level (BOLD) responses that are exhibited by the time series data of functional Magnetic Resonance Imaging (fMRI) and the hemoglobin oxy/deoxy-genation that is captured by NIRS, linear models play a central role in these applications. This, in turn, results in adaptation of the feature extraction strategies that are well-suited for discretization of data that exhibit a high degree of linearity, namely, slope and the mean as well as their combination, to summarize the informational contents of the NIRS time series. In this article, we demonstrate that these features are inefficient in capturing the variational information of NIRS data, limiting the reliability and the adequacy of the conclusion on their results. Alternatively, we propose the linear estimate of differential entropy of these time series as a natural representation of such information. We provide evidence for our claim through comparative analysis of the application of these features on NIRS data pertinent to several working memory tasks as well as naturalistic conversational stimuli.

Cortical and Autonomic Patterns of Emotion Experiencing During a Recall Task

Abstract. Emotions characterized by opposite valences (positive vs. negative) seem to lead to specific patterns of autonomic and cortical activity. For example, according to valence or approach-withdrawal hypotheses, specific emotions lead to an asymmetrical activation of left or right prefrontal cortex (PFC). The aim of the present study was to explore the psychophysiological underpinnings of emotion experiencing using a paradigm with higher ecological validity than is typically accomplished in neuroimaging research. A total of 28 healthy participants were instructed to recall personally-relevant situations from the past that caused positive (happiness) or negative (anger) emotions, during a 2 min silent preparatory phase and a subsequent 3 min verbal phase. A wearable electrocardiographic (ECG) recording system and a portable 2-channel near-infrared spectroscopy (NIRS) device were used to collect heart rate (HR), high frequencies of heart rate variability (HF-HRV), and the hemodynamic responses of prefrontal cortex during the entire procedure. Results showed that during both anger and happiness recall tasks, HR increased and high frequencies of HRV decreased with respect to the baseline. HR and HF-HRV reached, respectively, their highest and lowest points during the verbal phase of anger recall task. NIRS data evidenced a bilateral increase of oxyhemoglobin concentration changes during both anger and happiness recall tasks, which was highest during the verbal phases. However, no lateralization patterns were found. Overall, present results suggest that the experience of negative emotions, if compared with positive ones, is characterized by a combination of reduced parasympathetic activation and/or increased sympathetic activation. Thus, cardiological data provided partial support to autonomic specificity of emotions. However, the recall paradigm did not evidence an asymmetry of PFC activity during the experience of emotions with opposite valences, probably due to the high number of factors impacting prefrontal activity during a recall paradigm.

Reduced Functional Connectivity in Adults with Persistent Post-Concussion Symptoms: A Functional Near-Infrared Spectroscopy Study

Concussion, or mild traumatic brain injury (mTBI), accounts for ∼80% of all TBIs across North America. The majority of mTBI patients recover within days to weeks; however, 14-36% of the time, acute mTBI symptoms persist for months or even years and develop into persistent post-concussion symptoms (PPCS). There is a need to find biomarkers in patients with PPCS, to improve prognostic ability and to provide insight into the pathophysiology underlying chronic symptoms. Recent research has pointed toward impaired network integrity and cortical communication as a biomarker. In this study we investigated functional near-infrared spectroscopy (fNIRS) as a technique to assess cortical communication deficits in adults with PPCS. Specifically, we aimed to identify cortical communication patterns in prefrontal and motor areas during rest and task, in adult patients with persistent symptoms. We found that (1) the PPCS group showed reduced connectivity compared with healthy controls, (2) increased symptom severity correlated with reduced coherence, and (3) connectivity differences were best distinguishable during task and in particular during the working memory task (n-back task) in the right and left dorsolateral prefrontal cortex (DLPFC). These data show that reduced brain communication may be associated with the pathophysiology of mTBI and that fNIRS, with a relatively simple acquisition paradigm, may provide a useful biomarker of this injury.

Differential efficiency of transcutaneous electrical nerve stimulation in dominant versus nondominant hands in fibromyalgia: placebo-controlled functional near-infrared spectroscopy study

Using functional near-infrared spectroscopy (fNIRS), modulation of hemodynamic responses by transcutaneous electrical nerve stimulation (TENS) during delivery of nociceptive stimulation was investigated in fibromyalgia (FM) patients and healthy controls for both hands. Two experiments were conducted: (1) median nerve stimulation with TENS and (2) painful stimulation using electronic von Frey filaments with TENS/placebo TENS. Mean [Formula: see text] brain activity was compared across groups and conditions using factorial ANOVA. Dominant (right) hand stimulation indicated significant interactions between group and condition in both hemispheres. Post hoc results revealed that FM patients showed an increased activation in "pain + TENS" condition compared to the "pain + placebo TENS" condition while the brain activity patterns for these conditions in controls were reversed. Left-hand stimulation resulted in similar TENS effects (reduced activation for "pain + TENS" than "pain + placebo TENS") in both groups. TENS effects in FM patients might be manipulated by the stimulation side. While the nondominant hand was responsive to TENS treatment, the dominant hand was not. These results indicate that stimulation side might be an effective factor in FM treatment by using TENS. Future studies are needed to clarify the underlying mechanism for these findings.

Imperial College near infrared spectroscopy neuroimaging analysis framework

This paper describes the Imperial College near infrared spectroscopy neuroimaging analysis (ICNNA) software tool for functional near infrared spectroscopy neuroimaging data. ICNNA is a MATLAB-based object-oriented framework encompassing an application programming interface and a graphical user interface. ICNNA incorporates reconstruction based on the modified Beer-Lambert law and basic processing and data validation capabilities. Emphasis is placed on the full experiment rather than individual neuroimages as the central element of analysis. The software offers three types of analyses including classical statistical methods based on comparison of changes in relative concentrations of hemoglobin between the task and baseline periods, graph theory-based metrics of connectivity and, distinctively, an analysis approach based on manifold embedding. This paper presents the different capabilities of ICNNA in its current version.

The Effect of Motion Artifacts on Near-Infrared Spectroscopy (NIRS) Data and Proposal of a Video-NIRS System

AIMS

The aims of this study were (1) to investigate the influence of physical movement on near-infrared spectroscopy (NIRS) data, (2) to establish a video-NIRS system which simultaneously records NIRS data and the subject's movement, and (3) to measure the oxygenated hemoglobin (oxy-Hb) concentration change (Δoxy-Hb) during a word fluency (WF) task.

EXPERIMENT 1

In 5 healthy volunteers, we measured the oxy-Hb and deoxygenated hemoglobin (deoxy-Hb) concentrations during 11 kinds of facial, head, and extremity movements. The probes were set in the bilateral frontal regions. The deoxy-Hb concentration was increased in 85% of the measurements.

EXPERIMENT 2

Using a pillow on the backrest of the chair, we established the video-NIRS system with data acquisition and video capture software. One hundred and seventy-six elderly people performed the WF task. The deoxy-Hb concentration was decreased in 167 subjects (95%).

EXPERIMENT 3

Using the video-NIRS system, we measured the Δoxy-Hb, and compared it with the results of the WF task. Δoxy-Hb was significantly correlated with the number of words.

CONCLUSION

Like the blood oxygen level-dependent imaging effect in functional MRI, the deoxy-Hb concentration will decrease if the data correctly reflect the change in neural activity. The video-NIRS system might be useful to collect NIRS data by recording the waveforms and the subject's appearance simultaneously.

Effect of confounding variables on hemodynamic response function estimation using averaging and deconvolution analysis: An event-related NIRS study

Slow and rapid event-related designs are used in fMRI and functional near-infrared spectroscopy (fNIRS) experiments to temporally characterize the brain hemodynamic response to discrete events. Conventional averaging (CA) and the deconvolution method (DM) are the two techniques commonly used to estimate the Hemodynamic Response Function (HRF) profile in event-related designs. In this study, we conducted a series of simulations using synthetic and real NIRS data to examine the effect of the main confounding factors, including event sequence timing parameters, different types of noise, signal-to-noise ratio (SNR), temporal autocorrelation and temporal filtering on the performance of these techniques in slow and rapid event-related designs. We also compared systematic errors in the estimates of the fitted HRF amplitude, latency and duration for both techniques. We further compared the performance of deconvolution methods based on Finite Impulse Response (FIR) basis functions and gamma basis sets. Our results demonstrate that DM was much less sensitive to confounding factors than CA. Event timing was the main parameter largely affecting the accuracy of CA. In slow event-related designs, deconvolution methods provided similar results to those obtained by CA. In rapid event-related designs, our results showed that DM outperformed CA for all SNR, especially above -5 dB regardless of the event sequence timing and the dynamics of background NIRS activity. Our results also show that periodic low-frequency systemic hemodynamic fluctuations as well as phase-locked noise can markedly obscure hemodynamic evoked responses. Temporal autocorrelation also affected the performance of both techniques by inducing distortions in the time profile of the estimated hemodynamic response with inflated t-statistics, especially at low SNRs. We also found that high-pass temporal filtering could substantially affect the performance of both techniques by removing the low-frequency components of HRF profiles. Our results emphasize the importance of characterization of event timing, background noise and SNR when estimating HRF profiles using CA and DM in event-related designs.