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

Assessment of dynamic cerebral autoregulation in near-infrared spectroscopy using short channels: A feasibility study in acute ischemic stroke patients

Introduction

In acute ischemic stroke, progressive impairment of cerebral autoregulation (CA) is frequent and associated with unfavorable outcomes. Easy assessment of cerebral blood flow and CA in stroke units bedside tools like near-infrared spectroscopy (NIRS) might improve early detection of CA deterioration. This study aimed to assess dynamic CA with multichannel CW-NIRS in acute ischemic stroke (AIS) patients compared to agematched healthy controls.

Methods

CA reaction was amplified by changes in head of bed position. Long- and short channels were used to monitor systemic artery pressure- and intracranial oscillations simultaneously. Gain and phase shift in spontaneous low- and very low-frequency oscillations (LFO, VLFO) of blood pressure were assessed.

Results

A total of 54 participants, 27 with AIS and 27 age-matched controls were included. Gain was significantly lower in the AIS group in the LFO range (i) when the upper body was steadily elevated to 30. and (ii) after its abrupt elevation to 30°. No other differences were found between groups.

Discussion

This study demonstrates the feasibility of NIRS short channels to measure CA in AIS patients in one single instrument. A lower gain in AIS might indicate decreased CA activity in this pilot study, but further studies investigating the role of NIRS short channels in AIS are needed.

Differential auditory cortical development in left and right cochlear implanted children

Unilateral aural stimulation has been shown to cause massive cortical reorganization in brain with congenital deafness, particularly during the sensitive period of brain development. However, it is unclear which side of stimulation provides most advantages for auditory development. The left hemisphere dominance of speech and linguistic processing in normal hearing adult brain has led to the assumption of functional and developmental advantages of right over left implantation, but existing evidence is controversial. To test this assumption and provide evidence for clinical choice, we examined 34 prelingually deaf children with unilateral cochlear implants using near-infrared spectroscopy. While controlling for age of implantation, residual hearing, and dominant hand, cortical processing of speech showed neither developmental progress nor influence of implantation side weeks to months after implant activation. In sharp contrast, for nonspeech (music signal vs. noise) processing, left implantation showed functional advantages over right implantation that were not yet discernable using clinical, questionnaire-based outcome measures. These findings support the notion that the right hemisphere develops earlier and is better preserved from adverse environmental influences than its left counterpart. This study thus provides, to our knowledge, the first evidence for differential influences of left and right auditory peripheral stimulation on early cortical development of the human brain.

PPARγ lipodystrophy mutants reveal intermolecular interactions required for enhancer activation

Peroxisome proliferator-activated receptor γ (PPARγ) is the master regulator of adipocyte differentiation, and mutations that interfere with its function cause lipodystrophy. PPARγ is a highly modular protein, and structural studies indicate that PPARγ domains engage in several intra- and inter-molecular interactions. How these interactions modulate PPARγ's ability to activate target genes in a cellular context is currently poorly understood. Here we take advantage of two previously uncharacterized lipodystrophy mutations, R212Q and E379K, that are predicted to interfere with the interaction of the hinge of PPARγ with DNA and with the interaction of PPARγ ligand binding domain (LBD) with the DNA-binding domain (DBD) of the retinoid X receptor, respectively. Using biochemical and genome-wide approaches we show that these mutations impair PPARγ function on an overlapping subset of target enhancers. The hinge region-DNA interaction appears mostly important for binding and remodelling of target enhancers in inaccessible chromatin, whereas the PPARγ-LBD:RXR-DBD interface stabilizes the PPARγ:RXR:DNA ternary complex. Our data demonstrate how in-depth analyses of lipodystrophy mutants can unravel molecular mechanisms of PPARγ function.

Intrinsic Organization of Occipital Hubs Predicts Depression: A Resting-State fNIRS Study

Dysfunctional brain networks have been found in patients with major depressive disorder (MDD). In this study, to verify this in a more straightforward way, we investigated the intrinsic organization of brain networks in MDD by leveraging the resting-state functional near-infrared spectroscopy (rs-fNIRS). Thirty-four MDD patients (24 females, 38.41 ± 13.14 years old) and thirty healthy controls (22 females, 34.43 ± 5.03 years old) underwent a 10 min rest while their brain activity was recorded via fNIRS. The results showed that MDD patients and healthy controls exhibited similar resting-state functional connectivity. Moreover, the depression group showed lower small-world Lambda (1.12 ± 0.04 vs. 1.16 ± 0.10, p = 0.04) but higher global efficiency (0.51 ± 0.03 vs. 0.48 ± 0.05, p = 0.03) than the control group. Importantly, MDD patients, as opposed to healthy controls, showed a significantly lower nodal local efficiency at the left middle occipital gyrus (0.56 ± 0.36 vs. 0.81 ± 0.20, pFDR < 0.05), which predicted the level of depression in MDD (r = 0.45, p = 0.01, R2 = 0.15). In sum, we found a more integrated brain network in MDD patients with a lower nodal local efficiency at the occipital hub, which could predict depressive symptoms.

Treadmill training in Parkinson’s disease is underpinned by the interregional connectivity in cortical-subcortical network

Treadmill training (TT) has been extensively used as an intervention to improve gait and mobility in patients with Parkinson’s disease (PD). Regional and global effects on brain activity could be induced through TT. Training effects can lead to a beneficial shift of interregional connectivity towards a physiological range. The current work investigates the effects of TT on brain activity and connectivity during walking and at rest by using both functional near-infrared spectroscopy and functional magnetic resonance imaging. Nineteen PD patients (74.0 ± 6.59 years, 13 males, disease duration 10.45 ± 6.83 years) before and after 6 weeks of TT, along with 19 age-matched healthy controls were assessed. Interregional effective connectivity (EC) between cortical and subcortical regions were assessed and its interrelation to prefrontal cortex (PFC) activity. Support vector regression (SVR) on the resting-state ECs was used to predict prefrontal connectivity. In response to TT, EC analysis indicated modifications in the patients with PD towards the level of healthy controls during walking and at rest. SVR revealed cerebellum related connectivity patterns that were associated with the training effect on PFC. These findings suggest that the potential therapeutic effect of training on brain activity may be facilitated via changes in compensatory modulation of the cerebellar interregional connectivity.

High-density diffuse correlation tomography with enhanced depth localization and minimal surface artefacts

A spatially weighted filter applied to both the measurement and the Jacobian is proposed for high-density diffuse correlation tomography (DCT) to remove unwanted extracerebral interferences and artefacts along with better depth localization in the reconstructed blood flow images. High-density DCT is implemented by appropriate modification of recently introduced Multi-speckle Diffuse Correlation Spectroscopy (M-DCS) system. Additionally, we have used autocorrelation measurements at multiple delay-times in an iterative manner to improve the reconstruction results. The proposed scheme has been validated by simulations, phantom experiments and in-vivo human experiments.

Dataset of parent-child hyperscanning functional near-infrared spectroscopy recordings

The term “hyperscanning” refers to the simultaneous recording of multiple individuals’ brain activity. As a methodology, hyperscanning allows the investigation of brain-to-brain synchrony. Despite being a promising technique, there is a limited number of publicly available functional Near-infrared Spectroscopy (fNIRS) hyperscanning recordings. In this paper, we report a dataset of fNIRS recordings from the prefrontal cortical (PFC) activity of 33 mother-child dyads and 29 father-child dyads. Data was recorded while the parent-child dyads participated in an experiment with two sessions: a passive video attention task and a free play session. Dyadic metadata, parental psychological traits, behavioural annotations of the play sessions and information about the video stimuli complementing the dataset of fNIRS signals are described. The dataset presented here can be used to design, implement, and test novel fNIRS analysis techniques, new hyperscanning analysis tools, as well as investigate the PFC activity in participants of different ages when they engage in passive viewing tasks and active interactive tasks.

Measurement(s)	Blood Oxygen Level-Dependent Response
Technology Type(s)	Functional Near-Infrared Spectroscopy
Factor Type(s)	Parenting Stress • Parental Bonding • Attachment Style
Sample Characteristic - Organism	Homo sapiens
Sample Characteristic - Location	Singapore

Neural Correlates of Dual-Task Processing following Motor Sequence Learning: A Functional Near-Infrared Spectroscopy (fNIRS) Study

The current study used functional near-infrared spectroscopy (fNIRS) to examine cerebral oxygenation changes in the prefrontal cortex (PFC) associated with dual-task processing before and after motor sequence learning. Participants performed self-initiated sequential finger movements that were 4 and 12 units in length with a visual letter-counting task. After practice, dual-task sequence-4 performance revealed decreased activity in the right dorsolateral PFC, medial PFC, and orbitofrontal cortex. However, dual-task sequence-12 performance revealed increased activity in the right ventrolateral PFC when compared to the left hemisphere. The findings suggest that dual-task interference was reduced following practice for dual-task sequence-4. The results also suggest that increased right hemisphere activation is needed to maintain performance when the primary sequential task (e.g., dual-task sequence-12) has a high level of difficulty.

Motion artifacts removal and evaluation techniques for functional near-infrared spectroscopy signals: A review

With the emergence of an increasing number of functional near-infrared spectroscopy (fNIRS) devices, the significant deterioration in measurement caused by motion artifacts has become an essential research topic for fNIRS applications. However, a high requirement for mathematics and programming limits the number of related researches. Therefore, here we provide the first comprehensive review for motion artifact removal in fNIRS aiming to (i) summarize the latest achievements, (ii) present the significant solutions and evaluation metrics from the perspective of application and reproduction, and (iii) predict future topics in the field. The present review synthesizes information from fifty-one journal articles (screened according to three criteria). Three hardware-based solutions and nine algorithmic solutions are summarized, and their application requirements (compatible signal types, the availability for online applications, and limitations) and extensions are discussed. Five metrics for noise suppression and two metrics for signal distortion were synthesized to evaluate the motion artifact removal methods. Moreover, we highlight three deficiencies in the existing research: (i) The balance between the use of auxiliary hardware and that of an algorithmic solution is not clarified; (ii) few studies mention the filtering delay of the solutions, and (iii) the robustness and stability of the solution under extreme application conditions are not discussed.

Multiarea Brain Activation and Gait Deterioration During a Cognitive and Motor Dual Task in Individuals With Parkinson Disease

BACKGROUND AND PURPOSE

In people with Parkinson disease (PD), gait performance deteriorating during dual-task walking has been noted in previous studies. However, the effects of different types of dual tasks on gait performance and brain activation are still unknown. The purpose of this study was to investigate cognitive and motor dual-task walking performance on multiarea brain activity in individuals with PD.

METHODS

Twenty-eight participants with PD were recruited and performed single walking (SW), walking while performing a cognitive task (WCT), and walking while performing a motor task (WMT) at their self-selected speed. Gait performance including walking speed, stride length, stride time, swing cycle, temporal and spatial variability, and dual-task cost (DTC) was recorded. Brain activation of the prefrontal cortex (PFC), premotor cortex (PMC), and supplementary motor areas (SMA) were measured using functional near-infrared spectroscopy during walking.

RESULTS

Walking performance deteriorated upon performing a secondary task, especially the cognitive task. Also, a higher and more sustained activation in the PMC and SMA during WCT, as compared with the WMT and SW, in the late phase of walking was found. During WMT, however, the SMA and PMC did not show increased activation compared with during SW. Moreover, gait performance was negatively correlated with PMC and SMA activity during different walking tasks.

DISCUSSION AND CONCLUSIONS

Individuals with mild to moderate PD demonstrated gait deterioration during dual-task walking, especially during WCT. The SMA and PMC were further activated in individuals with PD when performing cognitive dual-task walking.Supplemental Digital Content is Available in the Text.Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A383 ).

Deep learning-based motion artifact removal in functional near-infrared spectroscopy

Significance: Functional near-infrared spectroscopy (fNIRS), a well-established neuroimaging technique, enables monitoring cortical activation while subjects are unconstrained. However, motion artifact is a common type of noise that can hamper the interpretation of fNIRS data. Current methods that have been proposed to mitigate motion artifacts in fNIRS data are still dependent on expert-based knowledge and the post hoc tuning of parameters. Aim: Here, we report a deep learning method that aims at motion artifact removal from fNIRS data while being assumption free. To the best of our knowledge, this is the first investigation to report on the use of a denoising autoencoder (DAE) architecture for motion artifact removal. Approach: To facilitate the training of this deep learning architecture, we (i) designed a specific loss function and (ii) generated data to mimic the properties of recorded fNIRS sequences. Results: The DAE model outperformed conventional methods in lowering residual motion artifacts, decreasing mean squared error, and increasing computational efficiency. Conclusion: Overall, this work demonstrates the potential of deep learning models for accurate and fast motion artifact removal in fNIRS data.

Acquisition time for functional near-infrared spectroscopy resting-state functional connectivity in assessing autism

SIGNIFICANCE

Resting state functional connectivity (RSFC) can be used to assess autism spectrum disorder (ASD). Measuring RSFC usually takes 5 to 10 min, during which children with ASD may have difficulty keeping their heads motionless. Therefore, a short acquisition time for RSFC would make clinical implementation more feasible.

AIM

To find a suitable acquisition time necessary for measuring RSFC with functional near-infrared spectroscopy (fNIRS) for the differentiation between children with ASD and typically developing (TD) children.

APPROACH

We used fNIRS to record the spontaneous hemodynamic fluctuations from the bilateral temporal lobes of 25 children with ASD and 22 TD children. The recorded signals were truncated into several segments with different time windows, and then the homotopic RSFC was computed for each of these segments and compared between the two groups.

RESULTS

We observed even in a very short time duration of 0.5 min, the RSFC had already existed a significant difference between the two groups, and 2.0 min might be the minimal time required for measuring RSFC for accurate differentiation between the two groups.

CONCLUSIONS

The fNIRS-RSFC acquired even in a short time, e.g., 2.0 min, might be a reliable feature for the differentiation between children with ASD and TD children.

Motion artifact correction for resting-state neonatal functional near-infrared spectroscopy through adaptive estimation of physiological oscillation denoising

SIGNIFICANCE

Functional near-infrared spectroscopy (fNIRS) for resting-state neonatal brain function evaluation provides assistance for pediatricians in diagnosis and monitoring treatment outcomes. Artifact contamination is an important challenge in the application of fNIRS in the neonatal population.

AIM

Our study aims to develop a correction algorithm that can effectively remove different types of artifacts from neonatal data.

APPROACH

In the study, we estimate the recognition threshold based on the amplitude characteristics of the signal and artifacts. After artifact recognition, Spline and Gaussian replacements are used separately to correct the artifacts. Various correction method recovery effects on simulated artifact and actual neonatal data are compared using the Pearson correlation ( R ) and root mean square error (RMSE). Simulated data connectivity recovery is used to compare various method performances.

RESULTS

The neonatal resting-state data corrected by our method showed better agreement with results by visual recognition and correction, and significant improvements ( R = 0.732 ± 0.155 , RMSE = 0.536 ± 0.339 ; paired t -test, ** p < 0.01 ). Moreover, the method showed a higher degree of recovery of connectivity in simulated data.

CONCLUSIONS

The proposed algorithm corrects artifacts such as baseline shifts, spikes, and serial disturbances in neonatal fNIRS data quickly and more effectively. It can be used for preprocessing in clinical applications of neonatal fNIRS brain function detection.

Cognitive deficit in adults with ADHD lies in the cognitive state disorder rather than the working memory deficit: A functional near-infrared spectroscopy study

This study tested whether cognitive deficit in patients with adult attention deficit hyperactivity disorder (ADHD) is a working memory deficit or cognitive state disorder during the N-back task. Twenty-two adults with ADHD and twenty-four healthy controls participated in the N-back task. The functional near-infrared spectroscopy (fNIRS) was combined with three perspectives from behavioral and spatial and temporal activation characteristics of blood oxygen levels in the prefrontal cortex to examine the psychological and neuroprocessing characteristics of adult ADHD. Data were acquired using a block design during an N-back task with three memory loads. Visual stimuli were presented on a computer monitor. Behaviorally, response time and accuracy showed no significant differences between the two groups. Spatially, in the left orbitofrontal area and the left frontopolar area (Channels 4 and 11), adult ADHD had significantly higher activation levels of oxyHb in the 2-back task and lower activation levels of deoxyHb in the 3-back task than healthy controls (corrected p &lt; 0.05). Therefore, Channel 4 in the 2-back condition and Channel 11 in the 3-back condition were used as the regions of interest (ROI). Temporally, adults with ADHD peaked earlier in the ROIs than healthy controls. Furthermore, working memory deficit was not found directly from the behavioral performance in adult ADHD. However, adult ADHD can be affected by memory load, task duration, and novelty stimulus. Our findings suggest that patients with adult ADHD have cognitive state disorder instead of working memory deficit.

The mediating role of inhibitory control in the relationship between prefrontal cortex hemodynamics and exercise performance in adults with overweight or obesity

Physical inactivity has been suggested to impair physical performance, cognitive functions and facilitate weight gain. One hypothesis is that long periods of physical inactivity could impair oxygen delivery to the prefrontal cortex (PFC), impairing one's cognitive ability to inhibit unhealthy automated behaviors and, therefore, reduce exercise tolerance. The present study sought to further understand the relationship among PFC hemodynamics, inhibitory control, and exercise tolerance in individuals with low physical fitness levels who are overweight or obese. Thirty-four participants were asked to perform a series of inhibitory control tests (i.e., Stroop task) in one testing session and complete an incremental cycling exercise test with hemodynamic fluctuations of the PFC measured with functional near-infrared spectroscopy in another session. Our results indicate that exercise performance varied with PFC oxygenation. We also found that inhibitory control played a key role mediating the relationship between PFC oxygenation and exercise performance, suggesting that the cognitive ability to inhibit automated responses has an impact on exercise behavior in adults with overweight and obesity.

Review of Applications of Near-Infrared Spectroscopy in Two Rare Disorders with Executive and Neurological Dysfunction: UCD and PKU

Studying rare diseases, particularly those with neurological dysfunction, is a challenge to researchers and healthcare professionals due to their complexity and small population with geographical dispersion. Universal and standardized biomarkers generated by tools such as functional neuroimaging have been forged to collect baseline data as well as treatment effects. However, the cost and heavily infrastructural requirement of those technologies have substantially limited their availability. Thus, developing non-invasive, portable, and inexpensive modalities has become a major focus for both researchers and clinicians. When considering neurological disorders and diseases with executive dysfunction, EEG is the most convenient tool to obtain biomarkers which can correlate the objective severity and clinical observation of these conditions. However, studies have also shown that EEG biomarkers and clinical observations alone are not sensitive enough since not all the patients present classical phenotypical features or EEG evidence of dysfunction. This article reviews disorders, including two rare disorders with neurological dysfunction and the usefulness of functional near-infrared spectroscopy (fNIRS) as a non-invasive optical modality to obtain hemodynamic biomarkers of diseases and for screening and monitoring the disease.

The prediction model for haze pollution based on stacking framework and feature extraction of time series images

In this paper, we propose a new model called "image-feature-stacking prediction model" to study the prediction problem of univariate time series data. Its main idea is to convert univariate time series data into corresponding images, and then use the optimized Inception-v1 network to extract hidden features from the images as input variables, based on these features, a two-layer stacking ensemble learning framework is constructed to output the final predicted values. The main contribution of the newly proposed model is to convert one-dimensional time series data into two-dimensional images, and automatically extract features from images. This method can truly mine the intrinsic relationship between the data instead of simply relying on descriptive statistical features to replace the original time series, thereby improving the prediction performance of the model. We use the new prediction model to predict daily PM_2.5 concentration, for one-step prediction, the results show that compared with the other three time series prediction models, the proposed prediction model reduces the mean absolute percentage error and mean absolute scaled error to 19.204% and 1.242, respectively, which is 76.607% and 77.004% lower than the maximum value of mean absolute percentage error and mean absolute scaled error of four prediction models. We also make two-step and three-step predictions, and the newly proposed model also shows encouraging performance.

A direct comparison of voice pitch processing in acoustic and electric hearing

In single-sided deafness patients fitted with a cochlear implant (CI) in the affected ear and preserved normal hearing in the other ear, acoustic and electric hearing can be directly compared without the need for an external control group. Although poor pitch perception is a crucial limitation when listening through CIs, it remains unclear how exactly the cortical processing of pitch information differs between acoustic and electric hearing. Hence, we separately presented both ears of 20 of these patients with vowel sequences in which the pitch contours were either repetitive or variable, while simultaneously recording functional near-infrared spectroscopy (fNIRS) and EEG data. Overall, the results showed smaller and delayed auditory cortex activity in electric hearing, particularly for the P2 event-related potential component, which appears to reflect the processing of voice pitch information. Both the fNIRS data and EEG source reconstructions furthermore showed that vowel sequences with variable pitch contours evoked additional activity in posterior right auditory cortex in electric but not acoustic hearing. This surprising discrepancy demonstrates, firstly, that the acoustic detail transmitted by CIs is sufficient to distinguish between speech sounds that only vary regarding their pitch information. Secondly, the absence of a condition difference when stimulating the normal-hearing ears suggests a saturation of cortical activity levels following unilateral deafness. Taken together, these results provide strong evidence in favour of using CIs in this patient group.

Functional near-infrared spectroscopy imaging of the prefrontal cortex during a naturalistic comedy movie

Naturalistic stimulation (i.e., movies and auditory narratives of some minutes' length) has been a powerful approach to bringing more real-life experiences into laboratory experiments. Data-driven, intersubject correlation (ISC) analysis permits examining to what extent activity in a specific brain region correlates across participants during exposure to a naturalistic stimulus, as well as testing whether neural activity correlates with behavioral measures. Notably, most of the previous research with naturalistic stimuli was conducted using functional fMRI (fMRI). Here, we tested whether a naturalistic approach and the ISC are feasible using functional near-infrared spectroscopy (fNIRS) - the imaging method particularly suited for populations of patients and children. Fifty-three healthy adult participants watched twice a 3-min segment of a Charlie Chaplin movie while we recorded the brain activity on the surface of their prefrontal cortex using fNIRS. In addition, an independent group of 18 participants used a continuous scoring procedure to rate the extent to which they felt that different parts of the movie fragment were funny. Our two findings were as follows. First, we found higher-than-zero ISC in fNIRS signals in the prefrontal cortex lobes, a result that was particularly high in the oxygenated channels during the first repetition of the movie. Second, we found a significant negative correlation between oxygenated brain signals and ratings of the movie's humorousness. In a series of control analyses we demonstrated that this latter correlation could not be explained by various non-humor-related movie sensory properties (e.g., auditory volume and image brightness). The key overall outcome of the present study is that fNIRS in combination with the naturalistic paradigms and the ISC might be a sensitive and powerful research method to explore cognitive processing. Our results also suggest a potential role of the prefrontal cortex in humor appreciation.

Segregation over time in functional networks in prefrontal cortex for individuals suffering from pathological fatigue after traumatic brain injury

Pathological fatigue is present when fatigue is perceived to continually interfere with everyday life. Pathological fatigue has been linked with a dysfunction in the cortico-striatal-thalamic circuits. Previous studies have investigated measures of functional connectivity, such as modularity to quantify levels of segregation. However, previous results have shown both increases and decreases in segregation for pathological fatigue. There are multiple factors why previous studies might have differing results, including: (i) Does the functional connectivity of patients with pathological fatigue display more segregation or integration compared to healthy controls? (ii) Do network properties differ depending on whether patients with pathological fatigue perform a task compared to periods of rest? (iii) Are the brain networks of patients with pathological fatigue and healthy controls differently affected by prolonged cognitive activity? We recruited individuals suffering from pathological fatigue after mild traumatic brain injury (n = 20) and age-matched healthy controls (n = 20) to perform cognitive tasks for 2.5 h. We used functional near-infrared spectroscopy (fNIRS) to assess hemodynamic changes in the frontal cortex. The participants had a resting state session before and after the cognitive test session. Cognitive testing included the Digit Symbol Coding test at the beginning and the end of the procedure to measure processing speed. We conducted an exploratory network analysis on these resting state and Digit Symbol Coding sessions with no a priori hypothesis relating to how patients and controls differ in their functional networks since previous research has found results in both directions. Our result showed a Group vs. Time interaction (p = 0.026, η_p² = 0.137), with a post hoc test revealing that the TBI patients developed higher modularity toward the end of the cognitive test session. This work helps to identify how functional networks differ under pathological fatigue compared to healthy controls. Further, it shows how the functional networks dynamically change over time as the patient performs tasks over a time scale that affect their fatigue level.

Neuroimaging Assessment of Pain

Pain is an unpleasant sensory and emotional experience. Understanding the neural mechanisms of acute and chronic pain and the brain changes affecting pain factors is important for finding pain treatment methods. The emergence and progress of non-invasive neuroimaging technology can help us better understand pain at the neural level. Recent developments in identifying brain-based biomarkers of pain through advances in advanced imaging can provide some foundations for predicting and detecting pain. For example, a neurologic pain signature (involving brain regions that receive nociceptive afferents) and a stimulus intensity-independent pain signature (involving brain regions that do not show increased activity in proportion to noxious stimulus intensity) were developed based on multivariate modeling to identify processes related to the pain experience. However, an accurate and comprehensive review of common neuroimaging techniques for evaluating pain is lacking. This paper reviews the mechanism, clinical application, reliability, strengths, and limitations of common neuroimaging techniques for assessing pain to promote our further understanding of pain.

Prefrontal cortical activation associated with prospective memory while walking around a real-world street environment

Rostral PFC (area 10) activation is common during prospective memory (PM) tasks. But it is not clear what mental processes these activations index. Three candidate explanations from cognitive neuroscience theory are: (i) monitoring of the environment; (ii) spontaneous intention retrieval; (iii) a combination of the two. These explanations make different predictions about the temporal and spatial patterns of activation that would be seen in rostral PFC in naturalistic settings. Accordingly, we plotted functional events in PFC using portable fNIRS while people were carrying out a PM task outside the lab and responding to cues when they were encountered, to decide between these explanations. Nineteen people were asked to walk around a street in London, U.K. and perform various tasks while also remembering to respond to prospective memory (PM) cues when they detected them. The prospective memory cues could be either social (involving greeting a person) or non-social (interacting with a parking meter) in nature. There were also a number of contrast conditions which allowed us to determine activation specifically related to the prospective memory components of the tasks. We found that maintaining both social and non-social intentions was associated with widespread activation within medial and right hemisphere rostral prefrontal cortex (BA 10), in agreement with numerous previous lab-based fMRI studies of prospective memory. In addition, increased activation was found within lateral prefrontal cortex (BA 45 and 46) when people were maintaining a social intention compared to a non-social one. The data were then subjected to a GLM-based method for automatic identification of functional events (AIDE), and the position of the participants at the time of the activation events were located on a map of the physical space. The results showed that the spatial and temporal distribution of these events was not random, but aggregated around areas in which the participants appeared to retrieve their future intentions (i.e., where they saw intentional cues), as well as where they executed them. Functional events were detected most frequently in BA 10 during the PM conditions compared to other regions and tasks. Mobile fNIRS can be used to measure higher cognitive functions of the prefrontal cortex in "real world" situations outside the laboratory in freely ambulant individuals. The addition of a "brain-first" approach to the data permits the experimenter to determine not only when haemodynamic changes occur, but also where the participant was when it happened. This can be extremely valuable when trying to link brain and cognition.

Prefrontal cortex oxygenation and autonomic nervous system activity under transcutaneous auricular vagus nerve stimulation in adolescents

INTRODUCTION

The Neurovisceral Integration Model (NIM) proposes a complex interplay of visceral and neural structures that are crucial for adaptive responses to environmental demands. The aim of the present study was to investigate this circuitry using experimental manipulation via transcutaneous auricular vagus nerve stimulation (tVNS), measures of peripheral autonomic nervous system (ANS) activity and prefrontal cortex (PFC) oxygenation, quantified using functional near-infrared spectroscopy (fNIRS).

METHODS

In a sample of n = 30 adolescents (age 14-17 years), tVNS versus sham stimulation was applied each during a 15-minute stimulation phase in a within-subject-cross-randomized-design. Mean oxygenation of the PFC and functional connectivity were assessed using fNIRS. Additionally, heart rate variability (HRV), heart rate (HR), electrodermal activity (EDA), and saliva alpha-amylase (sAA) were assessed to quantify peripheral ANS activity.

RESULTS

Using linear mixed-effects models, HRV increased (p < .0001) and HR (p < .0001) decreased during tVNS compared to sham. No effect on EDA or sAA was observed. PFC oxygenation increased over time under tVNS compared to sham (p = .017). The relative increase in HRV and decrease in HR was associated with increased oxygenation of the PFC (HR: p < .0001; HRV: p = .007). Exploratory analyses illustrated, that under tVNS, PFC connectivity increased compared to sham.

CONCLUSION

The present study supports the NIM by showing that tVNS influences ANS activity and that relative changes in PFC oxygenation contribute to these effects. Implications of these findings and directions for further research are discussed.

Effects of Long-Term Exposure to 2260 m Altitude on Working Memory and Resting-State Activity in the Prefrontal Cortex: A Large-Sample Cross-Sectional Study

It has been well established that very-high-altitude (>4000 m) environments can affect human cognitive function and brain activity. However, the effects of long-term exposure to moderate altitudes (2000−3000 m) on cognitive function and brain activity are not well understood. In the present cross-sectional study, we utilized an N-back working memory task and resting-state functional near-infrared spectroscopy to examine the effects of two years of exposure to 2260 m altitude on working memory and resting-state brain activity in 208 college students, compared with a control group at the sea level. The results showed that there was no significant change in spatial working memory performance after two years of exposure to 2260 m altitude. In contrast, the analysis of resting-state brain activity revealed changes in functional connectivity patterns in the prefrontal cortex (PFC), with the global efficiency increased and the local efficiency decreased after two years of exposure to 2260 m altitude. These results suggest that long-term exposure to moderate altitudes has no observable effect on spatial working memory performance, while significant changes in functional connectivity and brain network properties could possibly occur to compensate for the effects of mild hypoxic environments. To our knowledge, this study is the first to examine the resting state activity in the PFC associated with working memory in people exposed to moderate altitudes.

Investigating effortful speech perception using fNIRS and pupillometry measures

The current study examined the neural mechanisms for mental effort and its correlation to speech perception using functional near-infrared spectroscopy (fNIRS) in listeners with normal hearing (NH). Data were collected while participants listened and responded to unprocessed and degraded sentences, where words were presented in grammatically correct or shuffled order. Effortful listening and task difficulty due to stimulus manipulations was confirmed using a subjective questionnaire and a well-established objective measure of mental effort - pupillometry. fNIRS measures focused on cortical responses in two a priori regions of interest, the left auditory cortex (AC) and lateral frontal cortex (LFC), which are closely related to auditory speech perception and listening effort, respectively. We examined the relations between the two objective measures and behavioral measures of speech perception (task performance) and task difficulty.

Results

demonstrated that changes in pupil dilation were positively correlated with the self-reported task difficulty levels and negatively correlated with the task performance scores. A significant and negative correlation between the two behavioral measures was also found. That is, as perceived task demands increased and task performance scores decreased, pupils dilated more. fNIRS measures (cerebral oxygenation) in the left AC and LFC were both negatively correlated with the self-reported task difficulty levels and positively correlated with task performance scores. These results suggest that pupillometry measures can indicate task demands and listening effort; whereas, fNIRS measures using a similar paradigm seem to reflect speech processing, but not effort.

Speaker-listener neural coupling reveals a right-lateralized mechanism for non-native speech-in-noise comprehension

While the increasingly globalized world has brought more and more demands for non-native language communication, the prevalence of background noise in everyday life poses a great challenge to non-native speech comprehension. The present study employed an interbrain approach based on functional near-infrared spectroscopy (fNIRS) to explore how people adapt to comprehend non-native speech information in noise. A group of Korean participants who acquired Chinese as their non-native language was invited to listen to Chinese narratives at 4 noise levels (no noise, 2 dB, -6 dB, and - 9 dB). These narratives were real-life stories spoken by native Chinese speakers. Processing of the non-native speech was associated with significant fNIRS-based listener-speaker neural couplings mainly over the right hemisphere at both the listener's and the speaker's sides. More importantly, the neural couplings from the listener's right superior temporal gyrus, the right middle temporal gyrus, as well as the right postcentral gyrus were found to be positively correlated with their individual comprehension performance at the strongest noise level (-9 dB). These results provide interbrain evidence in support of the right-lateralized mechanism for non-native speech processing and suggest that both an auditory-based and a sensorimotor-based mechanism contributed to the non-native speech-in-noise comprehension.

The neural correlates of inhibitory control in 10-month-old infants: A functional near-infrared spectroscopy study

Inhibitory control, a core executive function, emerges in infancy and develops rapidly across childhood. Methodological limitations have meant that studies investigating the neural correlates underlying inhibitory control in infancy are rare. Employing functional near-infrared spectroscopy alongside a novel touchscreen task that measures response inhibition, this study aimed to uncover the neural underpinnings of inhibitory control in 10-month-old infants (N = 135). We found that when inhibition was required, the right prefrontal and parietal cortices were more activated than when there was no inhibitory demand. This demonstrates that inhibitory control in infants as young as 10 months of age is supported by similar brain areas as in older children and adults. With this study we have lowered the age-boundary for localising the neural substrates of response inhibition to the first year of life.

Association of psychosocial adversity and social information processing in children raised in a low-resource setting: an fNIRS study

Social cognition skills and socioemotional development are compromised in children growing up in low SES contexts, however, the mechanisms underlying this association remain unknown. Exposure to psychosocial risk factors early in life alters the child's social milieu and in turn, could lead to atypical processing of social stimuli. In this study, we used functional Near Infrared Spectroscopy (fNIRS) to measure cortical responses to a social discrimination task in children raised in a low-resource setting at 6, 24, and 36 months. In addition, we assessed the relation between cortical responses to social and non-social information with psychosocial risk factors assessed using the Childhood Psychosocial Adversity Scale (CPAS). In line with previous findings, we observed specialization to social stimuli in cortical regions in all age groups. In addition, we found that risk factors were associated with social discrimination at 24 months (intimate partner violence and verbal abuse and family conflict) and 36 months (verbal abuse and family conflict and maternal depression) but not at 6 months. Overall, the results show that exposure to psychosocial adversity has more impact on social information processing in toddlerhood than earlier in infancy.

Somatosensory impairment of the feet is associated with higher activation of prefrontal cortex during walking in older adults

BACKGROUND

Over-activation of prefrontal cortex during walking has been reported in older adults versus young adults. Heighted activity in prefrontal cortex suggests a shift toward an executive control strategy to control walking. A potential contributing factor is degraded functioning of pattern-generating locomotor circuits in the central nervous system that are important to walking coordination. Somatosensory information is a crucial input to these circuits, so age-related impairment of somatosensation would be expected to compromise the neural control of walking. The present study tested the hypothesis that poorer somatosensation in the feet of older adults will be associated with greater recruitment of the prefrontal cortex during walking. This study also examines the extent to which somatosensory function and prefrontal activity are associated with performance on walking and balance assessments.

METHODS

Forty seven older adults (age 74.6 ± 6.8 years; 32 female) participated in walking assessments (typical walking and obstacle negotiation) and Berg Balance Test. During walking, prefrontal activity was measured with functional near infrared spectroscopy (fNIRS). Participants also underwent somatosensory testing with Semmes-Weinstein monofilaments.

RESULTS

The primary findings is that worse somatosensory monofilament level was associated with greater prefrontal cortical activity during typical walking (r = 0.38, p = 0.008) and obstacle negotiation (r = 0.40, p = 0.006). For the obstacle negotiation task, greater prefrontal activity was associated with faster walking speed (p = 0.004). Poorer somatosensation was associated with slower typical walking speed (p = 0.07) and obstacles walking speed (p < 0.001), as well as poorer balance scores (p = 0.03).

CONCLUSIONS

The study findings are consistent with a compensation strategy of recruiting prefrontal/executive control resources to overcome loss of somatosensory input to the central nervous system. Future research should further establish the mechanisms by which somatosensory impairments are linked to the neural control and performance of walking tasks, as well as develop intervention approaches.

Lawrence K, Tachtsidis I, Tong Y, Torricelli A, Urner T, Wabnitz H, Wolf M, Wolf U, Xu S, Yang C, Yodh AG, Yücel MA, Zhou W. Optical imaging and spectroscopy for the study of the human brain: status report

This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function. While the first report focused on neurophotonic tools mostly applicable to animal studies, here, we highlight optical spectroscopy and imaging methods relevant to noninvasive human brain studies. We outline current state-of-the-art technologies and software advances, explore the most recent impact of these technologies on neuroscience and clinical applications, identify the areas where innovation is needed, and provide an outlook for the future directions.

Multitarget high-definition transcranial direct current stimulation improves response inhibition more than single-target high-definition transcranial direct current stimulation in healthy participants

Prior studies have focused on single-target anodal transcranial direct current stimulation (tDCS) over the right inferior frontal gyrus (rIFG) or pre-supplementary motor area (pre-SMA) to improve response inhibition in healthy individuals. However, the results are contradictory and the effect of multitarget anodal stimulation over both brain regions has never been investigated. The present study aimed to investigate the behavioral and neurophysiological effects of different forms of anodal high-definition tDCS (HD-tDCS) on improving response inhibition, including HD-tDCS over the rIFG or pre-SMA and multitarget HD-tDCS over both areas. Ninety-two healthy participants were randomly assigned to receive single-session (20 min) anodal HD-tDCS over rIFG + pre-SMA, rIFG, pre-SMA, or sham stimulation. Before and immediately after tDCS intervention, participants completed a stop-signal task (SST) and a go/nogo task (GNG). Their cortical activity was recorded using functional near-infrared spectroscopy (fNIRS) during the go/nogo task. The results showed multitarget stimulation produced a significant reduction in stop-signal reaction time (SSRT) relative to baseline. The pre-to-post SSRT change was not significant for rIFG, pre-SMA, or sham stimulation. Further analyses revealed multitarget HD-tDCS significantly decreased SSRT in both the high-performance and low-performance subgroups compared with the rIFG condition which decreased SSRT only in the low-performance subgroup. Only the multitarget condition significantly improved neural efficiency as indexed by lower △oxy-Hb after stimulation. In conclusion, the present study provides important preliminary evidence that multitarget HD-tDCS is a promising avenue to improve stimulation efficacy, establishing a more effective montage to enhance response inhibition relative to the commonly used single-target stimulation.

Comparing fixed-array and functionally-defined channel of interest approaches to infant functional near-infrared spectroscopy data

Functional near-infrared spectroscopy (fNIRS) is increasingly used to study brain function in infants, but the development and standardization of analysis techniques for use with infant fNIRS data have not paced other technical advances. Here we quantify and compare the effects of different methods of analysis of infant fNIRS data on two independent fNIRS datasets involving 6–9-month-old infants and a third simulated infant fNIRS dataset. With each, we contrast results from a traditional, fixed-array analysis with several functional channel of interest (fCOI) analysis approaches. In addition, we tested the effects of varying the number and anatomical location of potential data channels to be included in the fCOI definition. Over three studies we find that fCOI approaches are more sensitive than fixed-array analyses, especially when channels of interests were defined within-subjects. Applying anatomical restriction and/or including multiple channels in the fCOI definition does not decrease and in some cases increases sensitivity of fCOI methods. Based on these results, we recommend that researchers consider employing fCOI approaches to the analysis of infant fNIRS data and provide some guidelines for choosing between particular fCOI approaches and settings for the study of infant brain function and development.

The presence of adjacent others facilitates interpersonal neural synchronization in the left prefrontal cortex during a simple addition task

The hyperscanning technique, that is, simultaneous measurement of neural signals in more than one person, is a powerful research tool for understanding humans' social interactions. In recent years, many studies have investigated interpersonal neural synchronization during various types of communication processes. However, there has been little focus on the impact of the presence of others without explicit social interaction, despite the mere presence of others having been suggested as influencing behavior. In this study, we clarify whether neural signals during a self-paced, repeated, addition task are synchronized when another individual is adjacent without direct interaction. Twenty pairs of participants were measured using a hyperscanning approach with near-infrared spectroscopy. The results show that interpersonal neural synchronization of the task-related signal in the left forehead region was enhanced under the condition of being adjacent to another participant. By contrast, a significant decrease in neural synchronization in the center of the forehead region, where increased neural synchronization is often reported in explicit communication, was observed. Thus, the results indicate that the adjacency of others modulates interpersonal neural synchronization in the task-related signal, and the effect on cognitive processing is different from that of explicit social interaction.

Influence of the Somatic Rubber Hand Illusion on Maximum Grip Aperture

The classic rubber hand illusion (RHI), based on visual, proprioceptive, and tactile feedback, can affect actions. However, it is not known whether these effects still occur if the paradigm is administered without visual feedback. In this study, we used the somatic RHI to test in thirty-two healthy individuals whether the incorporation of the rubber hand based on proprioceptive and tactile information only is sufficient to generate changes in actions. We measured maximum grip aperture (GA) changes towards a target and associated brain activations within the dorsal stream before and after the somatic RHI. Behavioural and neuroimaging data do not support an effect on maximum GA when the RHI is based on proprioceptive and tactile information only.

Joint-Channel-Connectivity-Based Feature Selection and Classification on fNIRS for Stress Detection in Decision-Making

Stress is one of the contributing factors affecting decision-making. Therefore, early stress recognition is essential to improve clinicians' decision-making performance. Functional near-infrared spectroscopy (fNIRS) has shown great potential in detecting stress. However, the majority of previous studies only used fNIRS features at the individual level for classification without considering the correlations among channels corresponding to the brain, which may provide distinguishing features. Hence, this study proposes a novel joint-channel-connectivity-based feature selection and classification algorithm for fNIRS to detect stress in decision-making. Specifically, this approach integrates feature selection and classifier modeling into a sparse model, where intra- and inter-channel regularizers are designed to explore potential correlations among channels to obtain discriminating features. In this paper, we simulated the decision-making of medical students under stress through the Trier Social Stress Test and the Balloon Analog Risk Task and recorded their cerebral hemodynamic alterations by fNIRS device. Experimental results illustrated that our method with the accuracy of 0.961 is superior to other machine learning methods. Additionally, the stress correlation and connectivity of brain regions calculated by feature selection have been confirmed in previous studies, which validates the effectiveness of our method and helps optimize the channel settings of fNIRS. This work was the first attempt to utilize a sparse model that simultaneously considers the sparsity of features and the correlation of brain regions for stress detection and obtained an admirable classification performance. Thus, the proposed model might be a useful tool for medical personnel to automatically detect stress in clinical decision-making situations.

Transient brain-wide coactivations and structured transitions revealed in hemodynamic imaging data

Brain-wide patterns in resting human brains, as either structured functional connectivity (FC) or recurring brain states, have been widely studied in the neuroimaging literature. In particular, resting-state FCs estimated over windowed timeframe neuroimaging data from sub-minutes to minutes using correlation or blind source separation techniques have reported many brain-wide patterns of significant behavioral and disease correlates. The present pilot study utilized a novel whole-head cap-based high-density diffuse optical tomography (DOT) technology, together with data-driven analysis methods, to investigate recurring transient brain-wide patterns in spontaneous fluctuations of hemodynamic signals at the resolution of single timeframes from thirteen healthy adults in resting conditions. Our results report that a small number, i.e., six, of brain-wide coactivation patterns (CAPs) describe major spatiotemporal dynamics of spontaneous hemodynamic signals recorded by DOT. These CAPs represent recurring brain states, showing spatial topographies of hemispheric symmetry, and exhibit highly anticorrelated pairs. Moreover, a structured transition pattern among the six brain states is identified, where two CAPs with anterior-posterior spatial patterns are significantly involved in transitions among all brain states. Our results further elucidate two brain states of global positive and negative patterns, indicating transient neuronal coactivations and co-deactivations, respectively, over the entire cortex. We demonstrate that these two brain states are responsible for the generation of a subset of peaks and troughs in global signals (GS), supporting the recent reports on neuronal relevance of hemodynamic GS. Collectively, our results suggest that transient neuronal events (i.e., CAPs), global brain activity, and brain-wide structured transitions co-exist in humans and these phenomena are closely related, which extend the observations of similar neuronal events recently reported in animal hemodynamic data. Future studies on the quantitative relationship among these transient events and their relationships to windowed FCs along with larger sample size are needed to understand their changes with behaviors and diseased conditions.

Phase-dependent Brain Activation of the Frontal and Parietal Regions During Walking After Stroke - An fNIRS Study

Background

Recovery of walking post-stroke is highly variable. Accurately measuring and documenting functional brain activation characteristics during walking can help guide rehabilitation. Previous work in this area has been limited to investigations of frontal brain regions and have not utilized recent technological and analytical advances for more accurate measurements. There were three aims for this study: to characterize the hemodynamic profile during walking post-stroke, to investigate regional changes in brain activation during different phases of walking, and to related brain changes to clinical measures.

Methods

Functional near-infrared spectroscopy (fNIRS) along the pre-frontal, premotor, sensorimotor, and posterior parietal cortices was used on twenty individuals greater than six months post-stroke. Individual fNIRS optodes were digitized and used to estimate channel locations on each participant and short separation channels were used to control for extracerebral hemodynamic changes. Participants walked at their comfortable pace several times along a hallway while brain activation was recorded. Exploratory cluster analysis was conducted to determine if there was a link between brain activation and clinical measures.

Results

Sustained activation was observed in the pre-frontal cortex with the ipsilesional hemisphere showing greater activation compared to the contralesional side. Sensorimotor cortex was active during the early, acceleration stage of walking only. Posterior parietal cortex showed changes in activation during the later, steady-state stage of walking. Faster gait speeds also related to increased activation in contralesional sensorimotor and posterior parietal cortices. Exploratory analysis clustered participants into two distinct groups based on their brain activation profiles and generally showed that individuals with greater activation tended to have better physical outcomes.

Conclusions

These findings can guide future research for obtaining adequate power and determining factors that can be used as effect modifiers to reduce inter-subject variability. Overall, this is the first study to report specific oxygenated and deoxygenated hemoglobin changes in frontal to parietal regions during walking in the stroke population. Our results shed light on the importance of measuring brain activation across the cortex and show the importance of pre-frontal, sensorimotor, and posterior parietal cortices in walking after a stroke.

fNIRS-based adaptive visuomotor task improves sensorimotor cortical activation

OBJECTIVE

Investigating how to promote the functional activation of the central sensorimotor system is an important goal in the neurorehabilitation research domain. We aim to validate the effectiveness of facilitating cortical excitability using a closed-loop visuomotor task, in which the task difficulty is adaptively adjusted based on an individual's sensorimotor cortical activation.

APPROACH

We developed a novel visuomotor task, in which subjects moved a handle of a haptic device along a specific path while exerting a constant force against a virtual surface under visual feedback. The difficulty levels of the task were adapted with the aim of increasing the activation of sensorimotor areas, measured non-invasively by functional near-infrared spectroscopy. The changes in brain activation of the bilateral prefrontal cortex, sensorimotor cortex, and the occipital cortex obtained during the adaptive visuomotor task (adaptive group), were compared to the brain activation pattern elicited by the same duration of task with random difficulties in a control group.

MAIN RESULTS

During one intervention session, the adaptive group showed significantly increased activation in the bilateral sensorimotor cortex, also enhanced effective connectivity between the prefrontal and sensorimotor areas compared to the control group.

SIGNIFICANCE

Our findings demonstrated that the fNIRS-based adaptive visuomotor task with high ecological validity can facilitate the neural activity in sensorimotor areas and thus has the potential to improve hand motor functions.

An Exploratory Analysis of the Neural Correlates of Human-Robot Interactions With Functional Near Infrared Spectroscopy

Functional near infrared spectroscopy (fNIRS) has been gaining increasing interest as a practical mobile functional brain imaging technology for understanding the neural correlates of social cognition and emotional processing in the human prefrontal cortex (PFC). Considering the cognitive complexity of human-robot interactions, the aim of this study was to explore the neural correlates of emotional processing of congruent and incongruent pairs of human and robot audio-visual stimuli in the human PFC with fNIRS methodology. Hemodynamic responses from the PFC region of 29 subjects were recorded with fNIRS during an experimental paradigm which consisted of auditory and visual presentation of human and robot stimuli. Distinct neural responses to human and robot stimuli were detected at the dorsolateral prefrontal cortex (DLPFC) and orbitofrontal cortex (OFC) regions. Presentation of robot voice elicited significantly less hemodynamic response than presentation of human voice in a left OFC channel. Meanwhile, processing of human faces elicited significantly higher hemodynamic activity when compared to processing of robot faces in two left DLPFC channels and a left OFC channel. Significant correlation between the hemodynamic and behavioral responses for the face-voice mismatch effect was found in the left OFC. Our results highlight the potential of fNIRS for unraveling the neural processing of human and robot audio-visual stimuli, which might enable optimization of social robot designs and contribute to elucidation of the neural processing of human and robot stimuli in the PFC in naturalistic conditions.

Temel Duygusal Durumların Hemodinamik Karşılıklarının Taşınabilir bir İşlevsel Yakın Kızılaltı Spektroskopi Sistemi ile Tanımlanması

Objective: The aim of this study was to test the feasibility of a functional near infrared spectroscopy (fNIRS) system for quantification of the similarities and differences in the spatial localization of cerebral hemodynamic activation induced by visual presentation of neutral, negative and positive valence emotional stimuli. Method: 13 healthy subjects viewed neutral, pleasant and unpleasant pictures from the International Affective Picture System (IAPS) database in a block design experiment while the prefrontal cortical hemodynamic changes induced by emotional stimuli were continuously recorded with a 20 channel fNIRS system that covered the forehead region. Results: Negative valence pictures induced higher hemodynamic activity in right lateralized regions involving dorsolateral and oribtofrontal cortex when compared to neutral and positive valence stimuli (pFDR

Children's Neural Sensitivity to Prosodic Features of Natural Speech and Its Significance to Speech Development in Cochlear Implanted Children

Catchy utterances, such as proverbs, verses, and nursery rhymes (i.e., "No pain, no gain" in English), contain strong-prosodic (SP) features and are child-friendly in repeating and memorizing; yet the way those prosodic features encoded by neural activity and their influence on speech development in children are still largely unknown. Using functional near-infrared spectroscopy (fNIRS), this study investigated the cortical responses to the perception of natural speech sentences with strong/weak-prosodic (SP/WP) features and evaluated the speech communication ability in 21 pre-lingually deaf children with cochlear implantation (CI) and 25 normal hearing (NH) children. A comprehensive evaluation of speech communication ability was conducted on all the participants to explore the potential correlations between neural activities and children's speech development. The SP information evoked right-lateralized cortical responses across a broad brain network in NH children and facilitated the early integration of linguistic information, highlighting children's neural sensitivity to natural SP sentences. In contrast, children with CI showed significantly weaker cortical activation and characteristic deficits in speech perception with SP features, suggesting hearing loss at the early age of life, causing significantly impaired sensitivity to prosodic features of sentences. Importantly, the level of neural sensitivity to SP sentences was significantly related to the speech behaviors of all children participants. These findings demonstrate the significance of speech prosodic features in children's speech development.

Multivariate Pattern Analysis of Entropy estimates in Fast- and Slow-Wave Functional Near Infrared Spectroscopy: A Preliminary Cognitive Stress study

Functional near infrared spectroscopy (fNIRS) is a modality that can measure shallow cortical brain signals and also contains pulsatile oscillations that originate from heartbeat dynamics. In particular, while fNIRS slow waves (0 Hz to 0.6 Hz) refer to the standard hemodynamic signal, fast-wave (0.8 Hz to 3 Hz) fNIRS signals refer to cardiac oscillations. Using a cognitive stress experiment paradigm with mental arithmetic, the aim of this study was to assess differences in cortical activity when using slow-wave or fast-wave fNIRS signals. Furthermore, we aimed to see whether fNIRS fast and slow waves provide different information to discriminate mental arithmetic tasks from baseline. We used data from 10 healthy subjects from an open dataset performing mental arithmetic tasks and assessed fNIRS signals using mean values in the time domain, as well as complexity estimates including sample, fuzzy, and distribution entropy. A searchlight representational similarity analysis with pairwise t-test group analysis was performed to compare the representational dissimilarity matrices of each searchlight center. We found significant representational differences between fNIRS fast and slow waves for all complexity estimates, at different brain regions. On the other hand, no statistical differences were observed for mean values. We conclude that entropy analysis of fNIRS data may be more sensitive than traditional methods like mean analysis at detecting the additional information provided by fast-wave signals for discriminating mental arithmetic tasks and warrants further research.

Head hemodynamics and systemic responses during auditory stimulation

The present study aims to analyze the systemic response to auditory stimulation by means of hemodynamic (cephalic and peripheral) and autonomic responses in a broad range of auditory intensities (70.9, 77.9, 84.5, 89.5, 94.5 dBA). This approach could help to understand the possible influence of the autonomic nervous system on the cephalic blood flow. Twenty-five subjects were exposed to auditory stimulation while electrodermal activity (EDA), photoplethysmography (PPG), electrocardiogram, and functional near-infrared spectroscopy signals were recorded. Seven trials with 20 individual tones, each for the five intensities, were presented. The results showed a differentiated response to the higher intensity (94.5 dBA) with a decrease in some peripheral signals such as the heart rate (HR), the pulse signal, the pulse transit time (PTT), an increase of the LFnu power in PPG, and at the head level a decrease in oxygenated and total hemoglobin concentration. After the regression of the visual channel activity from the auditory channels, a decrease in deoxyhemoglobin in the auditory cortex was obtained, indicating a likely active response at the highest intensity. Nevertheless, other measures, such as EDA (Phasic and Tonic), and heart rate variability (Frequency and time domain) showed no significant differences between intensities. Altogether, these results suggest a systemic and complex response to high-intensity auditory stimuli. The results obtained in the decrease of the PTT and the increase in LFnu power of PPG suggest a possible vasoconstriction reflex by a sympathetic control of vascular tone, which could be related to the decrease in blood oxygenation at the head level.

Correction of global physiology in resting-state functional near-infrared spectroscopy

Significance: Resting-state functional connectivity (RSFC) analyses of functional near-infrared spectroscopy (fNIRS) data reveal cortical connections and networks across the brain. Motion artifacts and systemic physiology in evoked fNIRS signals present unique analytical challenges, and methods that control for systemic physiological noise have been explored. Whether these same methods require modification when applied to resting-state fNIRS (RS-fNIRS) data remains unclear. Aim: We systematically examined the sensitivity and specificity of several RSFC analysis pipelines to identify the best methods for correcting global systemic physiological signals in RS-fNIRS data. Approach: Using numerically simulated RS-fNIRS data, we compared the rates of true and false positives for several connectivity analysis pipelines. Their performance was scored using receiver operating characteristic analysis. Pipelines included partial correlation and multivariate Granger causality, with and without short-separation measurements, and a modified multivariate causality model that included a non-traditional zeroth-lag cross term. We also examined the effects of pre-whitening and robust statistical estimators on performance. Results: Consistent with previous work on bivariate correlation models, our results demonstrate that robust statistics and pre-whitening are effective methods to correct for motion artifacts and autocorrelation in the fNIRS time series. Moreover, we found that pre-filtering using principal components extracted from short-separation fNIRS channels as part of a partial correlation model was most effective in reducing spurious correlations due to shared systemic physiology when the two signals of interest fluctuated synchronously. However, when there was a temporal lag between the signals, a multivariate Granger causality test incorporating the short-separation channels was better. Since it is unknown if such a lag exists in experimental data, we propose a modified version of Granger causality that includes the non-traditional zeroth-lag term as a compromising solution. Conclusions: A combination of pre-whitening, robust statistical methods, and partial correlation in the processing pipeline to reduce autocorrelation, motion artifacts, and global physiology are suggested for obtaining statistically valid connectivity metrics with RS-fNIRS. Further studies should validate the effectiveness of these methods using human data.