Optical imaging and spectroscopy for the study of the human brain: status report

Cerebral, systemic physiological and behavioral responses to colored light exposure during a cognitive task: A SPA-fNIRS study

Colored light has important implications for human health and well-being, as well as for the aesthetics and function of various environments. In addition to its effects on visual function, colored light has significant effects on cognitive performance, behavior and systemic physiology. The aim of the current study was to comprehensively investigate how colored light exposure (CLE) combined with a cognitive task (2-back) affects performance, cerebral hemodynamics, oxygenation, and systemic physiology as assessed by systemic physiology augmented functional near-infrared spectroscopy (SPA-fNIRS). 36 healthy subjects (22 female, 14 male, age 26.3 ± 5.7 years) were measured twice on two different days. They were exposed to the sequence of blue and red light or vice versa in a randomized crossover design. During the CLE, the subjects were asked to perform a 2-back task. The 2-back task performance was correlated with changes in the concentration of oxygenated hemoglobin in the prefrontal cortex (red: r = -0.37, p = 0.001; blue: r = -0.33, p = 0.004) and the high-frequency component of the heart rate variability (red: r = 0.35, p = 0.003; blue: r = 0.25, p = 0.04). These changes were independent of the CLE. Sequence-dependent effects were observed for fNIRS signals at the visual cortex (VC) and for electrodermal activity (EDA). While both colors caused relatively similar changes in the VC and EDA at the position of the first exposure, blue and red light caused greater changes in the VC and EDA, respectively, in the second exposure. There was no significant difference in the subjects' 2-back task performance between the CLE (p = 0.46). The results of this study provide new insights into how human physiology and behavior respond to colored light exposure. Our findings are important for understanding the impact of colored light in our daily lives and its potential applications in a variety of settings, including education, the workplace and healthcare.

Mental workload assessment by monitoring brain, heart, and eye with six biomedical modalities during six cognitive tasks

Introduction

The efficiency and safety of complex high precision human-machine systems such as in aerospace and robotic surgery are closely related to the cognitive readiness, ability to manage workload, and situational awareness of their operators. Accurate assessment of mental workload could help in preventing operator error and allow for pertinent intervention by predicting performance declines that can arise from either work overload or under stimulation. Neuroergonomic approaches based on measures of human body and brain activity collectively can provide sensitive and reliable assessment of human mental workload in complex training and work environments.

Methods

In this study, we developed a new six-cognitive-domain task protocol, coupling it with six biomedical monitoring modalities to concurrently capture performance and cognitive workload correlates across a longitudinal multi-day investigation. Utilizing two distinct modalities for each aspect of cardiac activity (ECG and PPG), ocular activity (EOG and eye-tracking), and brain activity (EEG and fNIRS), 23 participants engaged in four sessions over 4 weeks, performing tasks associated with working memory, vigilance, risk assessment, shifting attention, situation awareness, and inhibitory control.

Results

The results revealed varying levels of sensitivity to workload within each modality. While certain measures exhibited consistency across tasks, neuroimaging modalities, in particular, unveiled meaningful differences between task conditions and cognitive domains.

Discussion

This is the first comprehensive comparison of these six brain-body measures across multiple days and cognitive domains. The findings underscore the potential of wearable brain and body sensing methods for evaluating mental workload. Such comprehensive neuroergonomic assessment can inform development of next generation neuroadaptive interfaces and training approaches for more efficient human-machine interaction and operator skill acquisition.

A compact and cost-effective laser-powered speckle visibility spectroscopy (SVS) device for measuring cerebral blood flow

In the realm of cerebrovascular monitoring, primary metrics typically include blood pressure, which influences cerebral blood flow (CBF) and is contingent upon vessel radius. Measuring CBF non-invasively poses a persistent challenge, primarily attributed to the difficulty of accessing and obtaining signal from the brain. This study aims to introduce a compact speckle visibility spectroscopy (SVS) device designed for non-invasive CBF measurements, offering cost-effectiveness and scalability while tracking CBF with remarkable sensitivity and temporal resolution. The wearable hardware has a modular design approach consisting solely of a laser diode as the source and a meticulously selected board camera as the detector. They both can be easily placed on a subject's head to measure CBF with no additional optical elements. The SVS device can achieve a sampling rate of 80 Hz with minimal susceptibility to external disturbances. The device also achieves better SNR compared with traditional fiber-based SVS devices, capturing about 70 times more signal and showing superior stability and reproducibility. It is designed to be paired and distributed in multiple configurations around the head, and measure signals that exceed the quality of prior optical CBF measurement techniques. Given its cost-effectiveness, scalability, and simplicity, this laser-centric tool offers significant potential in advancing non-invasive cerebral monitoring technologies.

Cortical Correlates of Visuospatial Switching Processes Between Egocentric and Allocentric Frames of Reference: A fNIRS Study

Human beings represent spatial information according to egocentric (body-to-object) and allocentric (object-to-object) frames of reference. In everyday life, we constantly switch from one frame of reference to another in order to react effectively to the specific needs of the environment and task demands. However, to the best of our knowledge, no study to date has investigated the cortical activity of switching and non-switching processes between egocentric and allocentric spatial encodings. To this aim, a custom-designed visuo-spatial memory task was administered and the cortical activities underlying switching vs non-switching spatial processes were investigated. Changes in concentrations of oxygenated and deoxygenated haemoglobin were measured using functional near-infrared spectroscopy (fNIRS). Participants were asked to memorize triads of geometric objects and then make two consecutive judgments about the same triad. In the non-switching condition, both spatial judgments considered the same frame of reference: only egocentric or only allocentric. In the switching condition, if the first judgment was egocentric, the second one was allocentric (or vice versa). The results showed a generalized activation of the frontal regions during the switching compared to the non-switching condition. Additionally, increased cortical activity was found in the temporo-parietal junction during the switching condition compared to the non-switching condition. Overall, these results illustrate the cortical activity underlying the processing of switching between body position and environmental stimuli, showing an important role of the temporo-parietal junction and frontal regions in the preparation and switching between egocentric and allocentric reference frames.

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.

Statistics of maximum photon penetration depth in a two-layer diffusive medium

We present numerical results for the probability density function f(z) and for the mean value of photon maximum penetration depth ‹zmax› in a two-layer diffusive medium. Both time domain and continuous wave regime are considered with several combinations of the optical properties (absorption coefficient, reduced scattering coefficient) of the two layers, and with different geometrical configurations (source detector distance, thickness of the upper layer). Practical considerations on the design of time domain and continuous wave systems are derived. The methods and the results are of interest for many research fields such as biomedical optics and advanced microscopy.

Inhibiting responses under the watch of a recently synchronized peer increases self-monitoring: evidence from functional near-infrared spectroscopy

Developing motor synchrony with a peer (through interventions such as the mirror game) can yield collaborative, cognitive and social benefits. However, it is also well established that observation by an audience can improve cognition. The combined and relative advantages offered by motor synchronization and audience effects are not yet understood. It is important to address this gap to determine the extent to which synchronizing activities might interact with the positive effects of an audience. In this preregistered study, we investigate the extent to which response inhibition may be improved when observed by a peer after motor synchronization with this peer. We compare behavioural and cortical (functional near-infrared spectroscopy; fNIRS) measures of inhibition between synchronized and non-synchronized dyads and find that the presence of a synchronized peer-audience introduces a speed-accuracy trade-off, consisting of slower reaction times and improved accuracy. This co-occurs with cortical activation in bilateral inferior frontal and middle prefrontal cortices, which are implicated in monitoring and maintenance of social alignment. Our findings have implications for carers and support people, who may benefit from synchronizing activities for rehabilitating inhibition and social skills in clinical settings.

Mobile fNIRS for exploring inter-brain synchrony across generations and time

While still relatively rare, longitudinal hyperscanning studies are exceptionally valuable for documenting changes in inter-brain synchrony, which may in turn underpin how behaviors develop and evolve in social settings. The generalizability and ecological validity of this experimental approach hinges on the selected imaging technique being mobile-a requirement met by functional near-infrared spectroscopy (fNIRS). fNIRS has most frequently been used to examine the development of inter-brain synchrony and behavior in child-parent dyads. In this position paper, we contend that dedicating attention to longitudinal and intergenerational hyperscanning stands to benefit the fields of social and cognitive neuroscience more broadly. We argue that this approach is particularly relevant for understanding the neural mechanisms underpinning intergenerational social dynamics, and potentially for benchmarking progress in psychological and social interventions, many of which are situated in intergenerational contexts. In line with our position, we highlight areas of intergenerational research that stand to be enhanced by longitudinal hyperscanning with mobile devices, describe challenges that may arise from measuring across generations in the real world, and offer potential solutions.

Comparing the performance potential of speckle contrast optical spectroscopy and diffuse correlation spectroscopy for cerebral blood flow monitoring using Monte Carlo simulations in realistic head geometries

Significance

The non-invasive measurement of cerebral blood flow based on diffuse optical techniques has seen increased interest as a research tool for cerebral perfusion monitoring in critical care and functional brain imaging. Diffuse correlation spectroscopy (DCS) and speckle contrast optical spectroscopy (SCOS) are two such techniques that measure complementary aspects of the fluctuating intensity signal, with DCS quantifying the temporal fluctuations of the signal and SCOS quantifying the spatial blurring of a speckle pattern. With the increasing interest in the use of these techniques, a thorough comparison would inform new adopters of the benefits of each technique.

Aim

We systematically evaluate the performance of DCS and SCOS for the measurement of cerebral blood flow.

Approach

Monte Carlo simulations of dynamic light scattering in an MRI-derived head model were performed. For both DCS and SCOS, estimates of sensitivity to cerebral blood flow changes, coefficient of variation of the measured blood flow, and the contrast-to-noise ratio of the measurement to the cerebral perfusion signal were calculated. By varying complementary aspects of data collection between the two methods, we investigated the performance benefits of different measurement strategies, including altering the number of modes per optical detector, the integration time/fitting time of the speckle measurement, and the laser source delivery strategy.

Results

Through comparison across these metrics with simulated detectors having realistic noise properties, we determine several guiding principles for the optimization of these techniques and report the performance comparison between the two over a range of measurement properties and tissue geometries. We find that SCOS outperforms DCS in terms of contrast-to-noise ratio for the cerebral blood flow signal in the ideal case simulated here but note that SCOS requires careful experimental calibrations to ensure accurate measurements of cerebral blood flow.

Conclusion

We provide design principles by which to evaluate the development of DCS and SCOS systems for their use in the measurement of cerebral blood flow.

Comparison of diffuse correlation spectroscopy analytical models for measuring cerebral blood flow in adults

Significance

Although multilayer analytical models have been proposed to enhance brain sensitivity of diffuse correlation spectroscopy (DCS) measurements of cerebral blood flow, the traditional homogeneous model remains dominant in clinical applications. Rigorous in vivo comparison of these analytical models is lacking.

Aim

We compare the performance of different analytical models to estimate a cerebral blood flow index (CBFi) with DCS in adults.

Approach

Resting-state data were obtained on a cohort of 20 adult patients with subarachnoid hemorrhage. Data at 1 and 2.5 cm source-detector separations were analyzed with the homogenous, two-layer, and three-layer models to estimate scalp blood flow index and CBFi. The performance of each model was quantified via fitting convergence, fit stability, brain-to-scalp flow ratio (BSR), and correlation with transcranial Doppler ultrasound (TCD) measurements of cerebral blood flow velocity in the middle cerebral artery (MCA).

Results

The homogeneous model has the highest pass rate (100%), lowest coefficient of variation (CV) at rest (median [IQR] at 1 Hz of 0.18 [0.13, 0.22]), and most significant correlation with MCA blood flow velocities (R s = 0.59 , p = 0.010 ) compared with both the two- and three-layer models. The multilayer model pass rate was significantly correlated with extracerebral layer thicknesses. Discarding datasets with non-physiological BSRs increased the correlation between DCS measured CBFi and TCD measured MCA velocities for all models.

Conclusions

We found that the homogeneous model has the highest pass rate, lowest CV at rest, and most significant correlation with MCA blood flow velocities. Results from the multilayer models should be taken with caution because they suffer from lower pass rates and higher coefficients of variation at rest and can converge to non-physiological values for CBFi. Future work is needed to validate these models in vivo, and novel approaches are merited to improve the performance of the multimodel models.

Impaired cerebrovascular reactivity in pediatric sickle cell disease using diffuse correlation spectroscopy

Cerebrovascular reactivity (CVR), defined as the ability of cerebral vasculature to dilate in response to a vasodilatory stimulus, is an integral mechanism in brain homeostasis that is thought to be impaired in sickle cell disease (SCD). This study used diffuse correlation spectroscopy and a simple breath-hold stimulus to quantify CVR non-invasively in a cohort of 12 children with SCD and 14 controls. Median [interquartile range] CVR was significantly decreased in SCD compared to controls (2.03 [1.31, 2.44] versus 3.49 [3.00, 4.11] %/mmHg, p = 0.028). These results suggest DCS may provide a feasible means to routinely monitor CVR impairments in pediatric SCD.

Microvascular reperfusion during endovascular therapy: the balance of supply and demand

BACKGROUND

Endovascular therapy (EVT) has revolutionized the treatment of acute stroke, but large vessel recanalization does not always result in tissue-level reperfusion. Cerebral blood flow (CBF) is not routinely monitored during EVT. We aimed to leverage diffuse correlation spectroscopy (DCS), a novel transcranial optical imaging technique, to assess the relationship between microvascular CBF and post-EVT outcomes.

METHODS

Frontal lobe CBF was monitored by DCS in 40 patients undergoing EVT. Baseline CBF deficit was calculated as the percentage of CBF impairment on pre-EVT CT perfusion. Microvascular reperfusion was calculated as the percentage increase in DCS-derived CBF that occurred with recanalization. The adequacy of reperfusion was defined by persistent CBF deficit, calculated as: baseline CBF deficit - microvascular reperfusion. A good functional outcome was defined as 90-day modified Rankin Scale score ≤2.

RESULTS

Thirty-six of 40 patients achieved successful recanalization, in whom microvascular reperfusion in itself was not associated with infarct volume or functional outcome. However, patients with good functional outcomes had a smaller persistent CBF deficit (median 1% (IQR -11%-16%)) than patients with poor outcomes (median 28% (IQR 2-50%)) (p=0.02). Smaller persistent CBF deficit was also associated with smaller infarct volume (p=0.004). Multivariate models confirmed that persistent CBF deficit was independently associated with infarct volume and functional outcome.

CONCLUSIONS

CBF augmentation alone does not predict post-EVT outcomes, but when microvascular reperfusion closely matches the baseline CBF deficit, patients experience favorable clinical and radiographic outcomes. By recognizing inadequate reperfusion, bedside CBF monitoring may provide opportunities to personalize post-EVT care aimed at CBF optimization.

Transcranial, Non-Invasive Evaluation of Potential Misery Perfusion During Hyperventilation Therapy of Traumatic Brain Injury Patients

Hyperventilation (HV) therapy uses vasoconstriction to reduce intracranial pressure (ICP) by reducing cerebral blood volume. However, as HV also lowers cerebral blood flow (CBF), it may provoke misery perfusion (MP), in which the decrease in CBF is coupled with increased oxygen extraction fraction (OEF). MP may rapidly lead to the exhaustion of brain energy metabolites, making the brain vulnerable to ischemia. MP is difficult to detect at the bedside, which is where transcranial hybrid, near-infrared spectroscopies are promising because they non-invasively measure OEF and CBF. We have tested this technology during HV (∼30 min) with bilateral, frontal lobe monitoring to assess MP in 27 sessions in 18 patients with traumatic brain injury. In this study, HV did not lead to MP at a group level (p > 0.05). However, a statistical approach yielded 89 events with a high probability of MP in 19 sessions. We have characterized each statistically significant event in detail and its possible relationship to clinical and radiological status (decompressive craniectomy and presence of a cerebral lesion), without detecting any statistically significant difference (p > 0.05). However, MP detection stresses the need for personalized, real-time assessment in future clinical trials with HV, in order to provide an optimal evaluation of the risk-benefit balance of HV. Our study provides pilot data demonstrating that bedside transcranial hybrid near-infrared spectroscopies could be utilized to assess potential MP.

Functional near-infrared spectroscopy-based prefrontal cortex oxygenation during working memory tasks in sickle cell disease

Significance

Sickle cell disease (SCD), characterized by painful vaso-occlusive crises, is associated with cognitive decline. However, objective quantification of cognitive decline in SCD remains a challenge, and the associated hemodynamics are unknown.

Aim

To address this, we utilized functional near-infrared spectroscopy (fNIRS) to measure prefrontal cortex (PFC) oxygenation responses to N -back working memory tasks in SCD patients and compared them with healthy controls.

Approach

We quantified the PFC oxygenation rate as an index of cognitive activity in each group and compared them. In half of the participants, a Stroop test was administered before they started N -back to elevate their baseline stress level.

Results

In SCD compared to healthy controls, we found that (1) under a high baseline stress level, there were significantly greater oxygenation responses during the 2-back task, further elevated with histories of stroke; (2) there was a marginally slower N -back response time, and it was even slower with a history of stroke; and (3) the task accuracy was not different.

Conclusions

Additional requirements for processing time, PFC resources, and PFC oxygenation in SCD patients offer an important basis for understanding their cognitive decline and highlight the potential of fNIRS for evaluating cognitive functions.

scatterBrains: an open database of human head models and companion optode locations for realistic Monte Carlo photon simulations

Significance

Monte Carlo (MC) simulations are currently the gold standard in the near-infrared and diffuse correlation spectroscopy (NIRS/DCS) communities for generating light transport paths through tissue. However, realistic and diverse models that capture complex tissue layers are not easily available to all; moreover, manually placing optodes on such models can be tedious and time consuming. Such limitations may hinder the adoption of representative models for basic simulations and the use of these models for large-scale simulations, e.g., for training machine learning algorithms.

Aim

We aim to provide the NIRS/DCS communities with an open-source, user-friendly database of morphologically and optically realistic head models, as well as a succinct software pipeline to prepare these models for mesh-based Monte Carlo simulations of light transport.

Approach

Sixteen anatomical models were created from segmented T1-weighted magnetic resonance imaging (MRI) head scans and converted to tetrahedral mesh volumes. Approximately 800 companion scalp surface locations were distributed on each model, comprising full head coverage. A pipeline was created to place custom source and optical detectors at each location, and guidance is provided on how to use these parameters to set up MC simulations.

Results

The models, head surface locations, and all associated code are freely available under the scatterBrains project on Github.

Conclusions

The NIRS/DCS community benefits from having shared resources for conducting MC simulations on realistic head geometries. We hope this will make MRI-based head models and virtual optode placement easily accessible to all. Contributions to the database are welcome and encouraged.

fNIRS Studies of Individuals with Speech and Language Impairment Underreport Sociodemographics: A Systematic Review

Functional near-infrared spectroscopy (fNIRS) is a promising tool for scientific discovery and clinical application. However, its utility depends upon replicable reporting. We evaluate reporting of sociodemographics in fNIRS studies of speech and language impairment and asked the following: (1) Do refereed fNIRS publications report participant sociodemographics? (2) For what reasons are participants excluded from analysis? This systematic review was preregistered with PROSPERO (CRD42022342959) and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol. Searches in August 2022 included the terms: (a) fNIRS or functional near-infrared spectroscopy or NIRS or near-infrared spectroscopy, (b) speech or language, and (c) disorder or impairment or delay. Searches yielded 38 qualifying studies from 1997 to present. Eight studies (5%) reported at least partial information on race or ethnicity. Few studies reported SES (26%) or language background (47%). Most studies reported geographic location (100%) and gender/sex (89%). Underreporting of sociodemographics in fNIRS studies of speech and language impairment hinders the generalizability of findings. Replicable reporting is imperative for advancing the utility of fNIRS.

Non-invasive estimation of in vivo optical properties and hemodynamic parameters of domestic animals: a preliminary study on horses, dogs, and sheep

Biosensors applied in veterinary medicine serve as a noninvasive method to determine the health status of animals and, indirectly, their level of welfare. Near infrared spectroscopy (NIRS) has been suggested as a technology with this application. This study presents preliminary in vivo time domain NIRS measurements of optical properties (absorption coefficient, reduced scattering coefficient, and differential pathlength factor) and hemodynamic parameters (concentration of oxygenated hemoglobin, deoxygenated hemoglobin, total hemoglobin, and tissue oxygen saturation) of tissue domestic animals, specifically of skeletal muscle (4 dogs and 6 horses) and head (4 dogs and 19 sheep). The results suggest that TD NIRS in vivo measurements on domestic animals are feasible, and reveal significant variations in the optical and hemodynamic properties among tissue types and species. In horses the different optical and hemodynamic properties of the measured muscles can be attributed to the presence of a thicker adipose layer over the muscle in the Longissimus Dorsi and in the Gluteus Superficialis as compared to the Triceps Brachii. In dogs the absorption coefficient is higher in the head (temporalis musculature) than in skeletal muscles. The smaller absorption coefficient for the head of the sheep as compared to the head of dogs may suggest that in sheep we are indeed reaching the brain cortex while in dog light penetration can be hindered by the strongly absorbing muscle covering the cranium.

Epilepsy: Mitochondrial connections to the 'Sacred' disease

Over 65 million people suffer from recurrent, unprovoked seizures. The lack of validated biomarkers specific for myriad forms of epilepsy makes diagnosis challenging. Diagnosis and monitoring of childhood epilepsy add to the need for non-invasive biomarkers, especially when evaluating antiseizure medications. Although underlying mechanisms of epileptogenesis are not fully understood, evidence for mitochondrial involvement is substantial. Seizures affect 35%-60% of patients diagnosed with mitochondrial diseases. Mitochondrial dysfunction is pathophysiological in various epilepsies, including those of non-mitochondrial origin. Decreased ATP production caused by malfunctioning brain cell mitochondria leads to altered neuronal bioenergetics, metabolism and neurological complications, including seizures. Iron-dependent lipid peroxidation initiates ferroptosis, a cell death pathway that aligns with altered mitochondrial bioenergetics, metabolism and morphology found in neurodegenerative diseases (NDDs). Studies in mouse genetic models with seizure phenotypes where the function of an essential selenoprotein (GPX4) is targeted suggest roles for ferroptosis in epilepsy. GPX4 is pivotal in NDDs, where selenium protects interneurons from ferroptosis. Selenium is an essential central nervous system micronutrient and trace element. Low serum concentrations of selenium and other trace elements and minerals, including iron, are noted in diagnosing childhood epilepsy. Selenium supplements alleviate intractable seizures in children with reduced GPX activity. Copper and cuproptosis, like iron and ferroptosis, link to mitochondria and NDDs. Connecting these mechanistic pathways to selenoproteins provides new insights into treating seizures, pointing to using medicines including prodrugs of lipoic acid to treat epilepsy and to potential alternative therapeutic approaches including transcranial magnetic stimulation (transcranial), photobiomodulation and vagus nerve stimulation.

Test-retest reliability of fNIRS in resting-state cortical activity and brain network assessment in stroke patients

Resting-state functional near infrared spectroscopy (fNIRS) scanning has attracted considerable attention in stroke rehabilitation research in recent years. The aim of this study was to quantify the reliability of fNIRS in cortical activity intensity and brain network metrics among resting-state stroke patients, and to comprehensively evaluate the effects of frequency selection, scanning duration, analysis and preprocessing strategies on test-retest reliability. Nineteen patients with stroke underwent two resting fNIRS scanning sessions with an interval of 24 hours. The haemoglobin signals were preprocessed by principal component analysis, common average reference and haemodynamic modality separation (HMS) algorithm respectively. The cortical activity, functional connectivity level, local network metrics (degree, betweenness and local efficiency) and global network metrics were calculated at 25 frequency scales × 16 time windows. The test-retest reliability of each fNIRS metric was quantified by the intraclass correlation coefficient. The results show that (1) the high-frequency band has higher ICC values than the low-frequency band, and the fNIRS metric is more reliable than at the individual channel level when averaged within the brain region channel, (2) the ICC values of the low-frequency band above the 4-minute scan time are generally higher than 0.5, the local efficiency and global network metrics reach high and excellent reliability levels after 4 min (0.5 < ICC < 0.9), with moderate or even poor reliability for degree and betweenness (ICC < 0.5), (3) HMS algorithm performs best in improving the low-frequency band ICC values. The results indicate that a scanning duration of more than 4 minutes can lead to high reliability of most fNIRS metrics when assessing low-frequency resting brain function in stroke patients. It is recommended to use the global correction method of HMS, and the reporting of degree, betweenness and single channel level should be performed with caution. This paper provides the first comprehensive reference for resting-state experimental design and analysis strategies for fNIRS in stroke rehabilitation.

Deep learning-based framework for real-time upper limb motion intention classification using combined bio-signals

This research study proposes a unique framework that takes input from a surface electromyogram (sEMG) and functional near-infrared spectroscopy (fNIRS) bio-signals. These signals are trained using convolutional neural networks (CNN). The framework entails a real-time neuro-machine interface to decode the human intention of upper limb motions. The bio-signals from the two modalities are recorded for eight movements simultaneously for prosthetic arm functions focusing on trans-humeral amputees. The fNIRS signals are acquired from the human motor cortex, while sEMG is recorded from the human bicep muscles. The selected classification and command generation features are the peak, minimum, and mean ΔHbO and ΔHbR values within a 2-s moving window. In the case of sEMG, wavelength, peak, and mean were extracted with a 150-ms moving window. It was found that this scheme generates eight motions with an enhanced average accuracy of 94.5%. The obtained results validate the adopted research methodology and potential for future real-time neural-machine interfaces to control prosthetic arms.

Dissociated coupling between cerebral oxygen metabolism and perfusion in the prefrontal cortex during exercise: a NIRS study

Purpose: The present study used near-infrared spectroscopy to investigate the relationships between cerebral oxygen metabolism and perfusion in the prefrontal cortex (PFC) during exercises of different intensities. Methods: A total of 12 recreationally active men (age 24 ± 6 years) were enrolled. They performed 17 min of low-intensity exercise (ExL), followed by 3 min of moderate-intensity exercise (ExM) at constant loads. Exercise intensities for ExL and ExM corresponded to 30% and 45% of the participants' heart rate reserve, respectively. Cardiovascular and respiratory parameters were measured. We used near-infrared time-resolved spectroscopy (TRS) to measure the cerebral hemoglobin oxygen saturation (ScO2) and total hemoglobin concentration ([HbT]), which can indicate the cerebral blood volume (CBV). As the cerebral metabolic rate for oxygen (CMRO2) is calculated using cerebral blood flow (CBF) and ScO2, we assumed a constant power law relationship between CBF and CBV based on investigations by positron emission tomography (PET). We estimated the relative changes in CMRO2 (rCMRO2) and CBV (rCBV) from the baseline. During ExL and ExM, the rate of perceived exertion was monitored, and alterations in the subjects' mood induced by exercise were evaluated using the Profile of Moods Scale-Brief. Results: Three minutes after exercise initiation, ScO2 decreased and rCMRO2 surpassed rCBV in the left PFC. When ExL changed to ExM, cardiovascular variables and the sense of effort increased concomitantly with an increase in [HbT] but not in ScO2, and the relationship between rCMRO2 and rCBV was dissociated in both sides of the PFC. Immediately after ExM, [HbT], and ScO2 increased, and the disassociation between rCMRO2 and rCBV was prominent in both sides of the PFC. While blood pressure decreased and a negative mood state was less prominent following ExM compared with that at rest, ScO2 decreased 15 min after exercise and rCMRO2 surpassed rCBV in the left PFC. Conclusion: Dissociated coupling between cerebral oxidative metabolism and perfusion in the PFC was consistent with the effort required for increased exercise intensity and associated with post-exercise hypotension and altered mood status after exercise. Our result demonstrates the first preliminary results dealing with the coupling between cerebral oxidative metabolism and perfusion in the PFC using TRS.

Measuring acute effects of subanesthetic ketamine on cerebrovascular hemodynamics in humans using TD-fNIRS

Quantifying neural activity in natural conditions (i.e. conditions comparable to the standard clinical patient experience) during the administration of psychedelics may further our scientific understanding of the effects and mechanisms of action. This data may facilitate the discovery of novel biomarkers enabling more personalized treatments and improved patient outcomes. In this single-blind, placebo-controlled study with a non-randomized design, we use time-domain functional near-infrared spectroscopy (TD-fNIRS) to measure acute brain dynamics after intramuscular subanesthetic ketamine (0.75 mg/kg) and placebo (saline) administration in healthy participants (n = 15, 8 females, 7 males, age 32.4 ± 7.5 years) in a clinical setting. We found that the ketamine administration caused an altered state of consciousness and changes in systemic physiology (e.g. increase in pulse rate and electrodermal activity). Furthermore, ketamine led to a brain-wide reduction in the fractional amplitude of low frequency fluctuations, and a decrease in the global brain connectivity of the prefrontal region. Lastly, we provide preliminary evidence that a combination of neural and physiological metrics may serve as predictors of subjective mystical experiences and reductions in depressive symptomatology. Overall, our study demonstrated the successful application of fNIRS neuroimaging to study the physiological effects of the psychoactive substance ketamine in humans, and can be regarded as an important step toward larger scale clinical fNIRS studies that can quantify the impact of psychedelics on the brain in standard clinical settings.

Experimental demonstration of a new near-infrared spectroscopy technique based on optical dual-comb: DC-NIRS

We present a novel near-infrared spectroscopy technique based on Dual-Comb optical interrogation (DC-NIRS) applied to dispersive media. The technique recovers the frequency response of the medium under investigation by sampling its spectral response in amplitude and phase. The DC-NIRS reference and sample signals are generated using electro-optic modulation which offers a cost-effective, integrable solution while providing high adaptability to the interrogated medium. A careful choice of both line spacing and optical span of the frequency comb ensures that the retrieved information enables the reconstruction of the temporal impulse response of the medium, known as the diffuse-time-of-flight (DTOF), to obtain its optical properties with a 70 µs temporal resolution and 32 ps photon propagation delay resolution. Furthermore, the DC-NIRS technique also offers enhanced penetration due to noiseless optical amplification (interferometric detection). The presented technique was demonstrated on a static bio-mimetic phantom of known optical properties reproducing a typical brain's optical response. The DTOF and optical properties of the phantom were measured, showing the capabilities of this new technique on the estimation of absolute optical properties with a deviation under 3%. Compared to current technologies, our DC-NIRS technique provides enhanced temporal resolution, spatial location capabilities, and penetration depth, with an integrable and configurable cost-effective architecture, paving the way to next-generation, non-invasive and portable systems for functional brain imaging, and brain-computer interfaces, among other. The system is patent pending PCT/ES2022/070176.

Simultaneous fMRI and tDCS for Enhancing Training of Flight Tasks

There is a gap in our understanding of how best to apply transcranial direct-current stimulation (tDCS) to enhance learning in complex, realistic, and multifocus tasks such as aviation. Our goal is to assess the effects of tDCS and feedback training on task performance, brain activity, and connectivity using functional magnetic resonance imaging (fMRI). Experienced glider pilots were recruited to perform a one-day, three-run flight-simulator task involving varying difficulty conditions and a secondary auditory task, mimicking real flight requirements. The stimulation group (versus sham) received 1.5 mA high-definition HD-tDCS to the right dorsolateral prefrontal cortex (DLPFC) for 30 min during the training. Whole-brain fMRI was collected before, during, and after stimulation. Active stimulation improved piloting performance both during and post-training, particularly in novice pilots. The fMRI revealed a number of tDCS-induced effects on brain activation, including an increase in the left cerebellum and bilateral basal ganglia for the most difficult conditions, an increase in DLPFC activation and connectivity to the cerebellum during stimulation, and an inhibition in the secondary task-related auditory cortex and Broca's area. Here, we show that stimulation increases activity and connectivity in flight-related brain areas, particularly in novices, and increases the brain's ability to focus on flying and ignore distractors. These findings can guide applied neurostimulation in real pilot training to enhance skill acquisition and can be applied widely in other complex perceptual-motor real-world tasks.

Normative cerebral microvascular blood flow waveform morphology assessed with diffuse correlation spectroscopy

Microvascular cerebral blood flow exhibits pulsatility at the cardiac frequency that carries valuable information about cerebrovascular health. This study used diffuse correlation spectroscopy to quantify normative features of these waveforms in a cohort of thirty healthy adults. We demonstrate they are sensitive to changes in vascular tone, as indicated by pronounced morphological changes with hypercapnia. Further, we observe significant sex-based differences in waveform morphology, with females exhibiting higher flow, greater area-under-the-curve, and lower pulsatility. Finally, we quantify normative values for cerebral critical closing pressure, i.e., the minimum pressure required to maintain flow in a given vascular region.

The use of novel diffuse optical spectroscopies for improved neuromonitoring during neonatal cardiac surgery requiring antegrade cerebral perfusion

Background

Surgical procedures involving the aortic arch present unique challenges to maintaining cerebral perfusion, and optimal neuroprotective strategies to prevent neurological injury during such high-risk procedures are not completely understood. The use of antegrade cerebral perfusion (ACP) has gained favor as a neuroprotective strategy over deep hypothermic circulatory arrest (DHCA) due to the ability to selectively perfuse the brain. Despite this theoretical advantage over DHCA, there has not been conclusive evidence that ACP is superior to DHCA. One potential reason for this is the incomplete understanding of ideal ACP flow rates to prevent both ischemia from underflowing and hyperemia and cerebral edema from overflowing. Critically, there are no continuous, noninvasive measurements of cerebral blood flow (CBF) and cerebral oxygenation (StO₂) to guide ACP flow rates and help develop standard clinical practices. The purpose of this study is to demonstrate the feasibility of using noninvasive, diffuse optical spectroscopy measurements of CBF and cerebral oxygenation during the conduct of ACP in human neonates undergoing the Norwood procedure.

Methods

Four neonates prenatally diagnosed with hypoplastic left heart syndrome (HLHS) or a similar variant underwent the Norwood procedure with continuous intraoperative monitoring of CBF and cerebral oxygen saturation (StO₂) using two non-invasive optical techniques, namely diffuse correlation spectroscopy (DCS) and frequency-domain diffuse optical spectroscopy (FD-DOS). Changes in CBF and StO₂ due to ACP were calculated by comparing these parameters during a stable 5 min period of ACP to the last 5 min of full-body CPB immediately prior to ACP initiation. Flow rates for ACP were left to the discretion of the surgeon and ranged from 30 to 50 ml/kg/min, and all subjects were cooled to 18°C prior to initiation of ACP.

Results

During ACP, the continuous optical monitoring demonstrated a median (IQR) percent change in CBF of -43.4% (38.6) and a median (IQR) absolute change in StO₂ of -3.6% (12.3) compared to a baseline period during full-body cardiopulmonary bypass (CPB). The four subjects demonstrated varying responses in StO₂ due to ACP. ACP flow rates of 30 and 40 ml/kg/min (n = 3) were associated with decreased CBF during ACP compared to full-body CPB. Conversely, one subject with a higher flow6Di rate of 50 ml/kg/min demonstrated increased CBF and StO₂ during ACP.

Conclusions

This feasibility study demonstrates that novel diffuse optical technologies can be utilized for improved neuromonitoring in neonates undergoing cardiac surgery where ACP is utilized. Future studies are needed to correlate these findings with neurological outcomes to inform best practices during ACP in these high-risk neonates.

Facilitating or disturbing? An investigation about the effects of auditory frequencies on prefrontal cortex activation and postural sway

Auditory stimulation activates brain areas associated with higher cognitive processes, like the prefrontal cortex (PFC), and plays a role in postural control regulation. However, the effects of specific frequency stimuli on upright posture maintenance and PFC activation patterns remain unknown. Therefore, the study aims at filling this gap. Twenty healthy adults performed static double- and single-leg stance tasks of 60s each under four auditory conditions: 500, 1000, 1500, and 2000 Hz, binaurally delivered through headphones, and in quiet condition. Functional near-infrared spectroscopy was used to measure PFC activation through changes in oxygenated hemoglobin concentration, while an inertial sensor (sealed at the L5 vertebra level) quantified postural sway parameters. Perceived discomfort and pleasantness were rated through a 0-100 visual analogue scale (VAS). Results showed that in both motor tasks, different PFC activation patterns were displayed at the different auditory frequencies and the postural performance worsened with auditory stimuli, compared to quiet conditions. VAS results showed that higher frequencies were considered more discomfortable than lower ones. Present data prove that specific sound frequencies play a significant role in cognitive resources recruitment and in the regulation of postural control. Furthermore, it supports the importance of exploring the relationship among tones, cortical activity, and posture, also considering possible applications with neurological populations and people with hearing dysfunctions.

Diffuse Optical Tomography Spatial Prior for EEG Source Localization in Human Visual Cortex

Electroencephalography (EEG) and diffuse optical tomography (DOT) are imaging methods which are widely used for neuroimaging. While the temporal resolution of EEG is high, the spatial resolution is typically limited. DOT, on the other hand, has high spatial resolution, but the temporal resolution is inherently limited by the slow hemodynamics it measures. In our previous work, we showed using computer simulations that when using the results of DOT reconstruction as the spatial prior for EEG source reconstruction, high spatio-temporal resolution could be achieved. In this work, we experimentally validate the algorithm by alternatingly flashing two visual stimuli at a speed that is faster than the temporal resolution of DOT. We show that the joint reconstruction using both EEG and DOT clearly resolves the two stimuli temporally, and the spatial confinement is drastically improved in comparison to reconstruction using EEG alone.

Physiological Noise Filtering in Functional Near-Infrared Spectroscopy Signals Using Wavelet Transform and Long-Short Term Memory Networks

Activated channels of functional near-infrared spectroscopy are typically identified using the desired hemodynamic response function (dHRF) generated by a trial period. However, this approach is not possible for an unknown trial period. In this paper, an innovative method not using the dHRF is proposed, which extracts fluctuating signals during the resting state using maximal overlap discrete wavelet transform, identifies low-frequency wavelets corresponding to physiological noise, trains them using long-short term memory networks, and predicts/subtracts them during the task session. The motivation for prediction is to maintain the phase information of physiological noise at the start time of a task, which is possible because the signal is extended from the resting state to the task session. This technique decomposes the resting state data into nine wavelets and uses the fifth to ninth wavelets for learning and prediction. In the eighth wavelet, the prediction error difference between the with and without dHRF from the 15-s prediction window appeared to be the largest. Considering the difficulty in removing physiological noise when the activation period is near the physiological noise, the proposed method can be an alternative solution when the conventional method is not applicable. In passive brain-computer interfaces, estimating the brain signal starting time is necessary.

Agreement in cerebrovascular reactivity assessed with diffuse correlation spectroscopy across experimental paradigms improves with short separation regression

Significance

Cerebrovascular reactivity (CVR), i.e., the ability of cerebral vasculature to dilate or constrict in response to vasoactive stimuli, is a biomarker of vascular health. Exogenous administration of inhaled carbon dioxide, i.e., hypercapnia (HC), remains the "gold-standard" intervention to assess CVR. More tolerable paradigms that enable CVR quantification when HC is difficult/contraindicated have been proposed. However, because these paradigms feature mechanistic differences in action, an assessment of agreement of these more tolerable paradigms to HC is needed.

Aim

We aim to determine the agreement of CVR assessed during HC, breath-hold (BH), and resting state (RS) paradigms.

Approach

Healthy adults were subject to HC, BH, and RS paradigms. End tidal carbon dioxide (EtCO2) and cerebral blood flow (CBF, assessed with diffuse correlation spectroscopy) were monitored continuously. CVR (%/mmHg) was quantified via linear regression of CBF versus EtCO2 or via a general linear model (GLM) that was used to minimize the influence of systemic and extracerebral signal contributions.

Results

Strong agreement ( CCC ≥ 0.69 ; R ≥ 0.76 ) among CVR paradigms was demonstrated when utilizing a GLM to regress out systemic/extracerebral signal contributions. Linear regression alone showed poor agreement across paradigms ( CCC ≤ 0.35 ; R ≤ 0.45 ).

Conclusions

More tolerable experimental paradigms coupled with regression of systemic/extracerebral signal contributions may offer a viable alternative to HC for assessing CVR.

Predicting poststroke dyskinesia with resting-state functional connectivity in the motor network

SIGNIFICANCE

Motor function evaluation is essential for poststroke dyskinesia rehabilitation. Neuroimaging techniques combined with machine learning help decode a patient's functional status. However, more research is needed to investigate how individual brain function information predicts the dyskinesia degree of stroke patients.

AIM

We investigated stroke patients' motor network reorganization and proposed a machine learning-based method to predict the patients' motor dysfunction.

APPROACH

Near-infrared spectroscopy (NIRS) was used to measure hemodynamic signals of the motor cortex in the resting state (RS) from 11 healthy subjects and 31 stroke patients, 15 with mild dyskinesia (Mild), and 16 with moderate-to-severe dyskinesia (MtS). The graph theory was used to analyze the motor network characteristics.

RESULTS

The small-world properties of the motor network were significantly different between groups: (1) clustering coefficient, local efficiency, and transitivity: MtS > Mild > Healthy and (2) global efficiency: MtS < Mild < Healthy. These four properties linearly correlated with patients' Fugl-Meyer Assessment scores. Using the small-world properties as features, we constructed support vector machine (SVM) models that classified the three groups of subjects with an accuracy of 85.7%.

CONCLUSIONS

Our results show that NIRS, RS functional connectivity, and SVM together constitute an effective method for assessing the poststroke dyskinesia degree at the individual level.

System Derived Spatial-Temporal CNN for High-Density fNIRS BCI

An intuitive and generalisable approach to spatial-temporal feature extraction for high-density (HD) functional Near-Infrared Spectroscopy (fNIRS) brain-computer interface (BCI) is proposed, demonstrated here using Frequency-Domain (FD) fNIRS for motor-task classification. Enabled by the HD probe design, layered topographical maps of Oxy/deOxy Haemoglobin changes are used to train a 3D convolutional neural network (CNN), enabling simultaneous extraction of spatial and temporal features. The proposed spatial-temporal CNN is shown to effectively exploit the spatial relationships in HD fNIRS measurements to improve the classification of the functional haemodynamic response, achieving an average F1 score of 0.69 across seven subjects in a mixed subjects training scheme, and improving subject-independent classification as compared to a standard temporal CNN.

Neurocognitive and psychiatric symptoms following infection with COVID-19: Evidence from laboratory and population studies

Objective

The objective of the current investigation was to examine associations between symptomatic COVID-19 history, neurocognitive function, and psychiatric symptoms using cognitive task performance, functional brain imaging, and a prospective population survey.

Methods

Study 1 was a laboratory study conducted between 3 May 2022 and 16 Nov 2022 involving 120 fully vaccinated community dwelling adults between 18 and 84 years of age (Mage = 31.96 (SD = 20.71), 63.3% female). In this cross-sectional study we examined the association between symptomatic COVID-19 infection history and performance on three computer tasks assessing cognitive function (Flanker interference, delay discounting and simple reaction time) and measured oxygen saturation within the prefrontal cortex using functional near infrared spectroscopy (fNIRS). Study 2 was a 2-wave population survey undertaken between 28 September 2021 and 21 March 2022, examining the prospective relationship between symptomatic COVID-19 and self-reported symptoms of cognitive dysfunction, depressive symptoms, anxiety symptoms, and agitation at 6-month follow up. The sample (N = 2,002, M _age = 37.0, SD = 10.4; 60.8% female) was collected using a quota process to ensure equal numbers of vaccinated and unvaccinated individuals. Structural equation modelling with latent variables was performed on the population-level data, evaluating the fit of the proposed mediational model of symptomatic COVID-19 to psychiatric symptoms through cognitive dysfunction.

Results

Findings from Study 1 revealed significant effects of symptomatic COVID-19 history on Flanker interference and delay discounting. Effects on flanker performance were significantly stronger among older adult women (effect: 9.603, SE = 4.452, t = 2.157, p = .033), and were accompanied by task-related changes cerebral oxygenation at the right superior frontal gyrus (F (1, 143.1) = 4.729, p = .031). Additionally, those with a symptomatic COVID-19 infection history showed evidence of amplified delay discounting (coefficient = 0.4554, SE = 0.2208, t = 2.0629, p = .041). In Study 2, baseline symptomatic COVID-19 history was associated with self-reported cognitive dysfunction and a latent variable reflecting psychiatric symptoms of anxiety, depression and agitation at follow-up. Mediational analyses revealed evidence of cognitive mediation of clinically significant psychiatric outcomes: depression (indirect effect = 0.077, SE = 0.026, p = .003) and generalized anxiety (indirect effect = 0.060, SE = 0.021, p = .004).

Conclusions

Converging findings from laboratory and population survey data support the conclusion that symptomatic COVID-19 infection is associated with task-related, functional imaging and self-reported indices of cognitive dysfunction as well as psychiatric symptoms. In some cases, these findings appear to be more amplified among women than men, and among older women than younger.

Inefficient frontal and parietal brain activation during dual-task walking in a virtual environment in older adults

Walking while performing an additional cognitive task (dual-task walking; DT walking) is a common yet highly demanding behavior in daily life. Previous neuroimaging studies have shown that performance declines from single- (ST) to DT conditions are accompanied by increased prefrontal cortex (PFC) activity. This increment is particularly pronounced in older adults and has been explained either by compensation, dedifferentiation, or ineffective task processing in fronto-parietal circuits. However, there is only limited evidence for the hypothesized fronto-parietal activity changes measured under real life conditions such as walking. In this study, we therefore assessed brain activity in PFC and parietal lobe (PL), to investigate whether higher PFC activation during DT walking in older adults is related to compensation, dedifferentiation, or neural inefficiency. Fifty-six healthy older adults (69.11 ± 4.19 years, 30 female) completed three tasks (treadmill walking at 1 m/s, Stroop task, Serial 3's task) under ST and DT conditions (Walking + Stroop, Walking + Serial 3's), and a baseline Standing task. Behavioral outcomes were step time variability (Walking), Balance Integration Score BIS (Stroop), and number of correct calculations S3_corr (Serial 3's). Brain activity was measured using functional near-infrared spectroscopy (fNIRS) over ventrolateral and dorsolateral PFC (vlPFC, dlPFC) and inferior and superior PL (iPL, sPL). Neurophysiological outcome measures were oxygenated (HbO₂) and deoxygenated hemoglobin (HbR). Linear mixed models with follow-up estimated marginal means contrasts were applied to investigate region-specific upregulations of brain activation from ST to DT conditions. Furthermore, the relationships of DT-specific activations across all brain regions was analyzed as well as the relationship between changes in brain activation and changes in behavioral performance from ST to DT. Data indicated the expected upregulation from ST to DT and that DT-related upregulation was more pronounced in PFC (particularly in vlPFC) than in PL regions. Activation increases from ST to DT were positively correlated between all brain regions, and higher brain activation changes predicted higher declines in behavioral performance from ST to DT. Results were largely consistent for both DTs (Stroop and Serial 3's). These findings more likely suggest neural inefficiency and dedifferentiation in PFC and PL rather than fronto-parietal compensation during DT walking in older adults. Findings have implications for interpreting and promoting efficacy of long-term interventions to improve DT walking in older persons.

Haptic shared control improves neural efficiency during myoelectric prosthesis use

Clinical myoelectric prostheses lack the sensory feedback and sufficient dexterity required to complete activities of daily living efficiently and accurately. Providing haptic feedback of relevant environmental cues to the user or imbuing the prosthesis with autonomous control authority have been separately shown to improve prosthesis utility. Few studies, however, have investigated the effect of combining these two approaches in a shared control paradigm, and none have evaluated such an approach from the perspective of neural efficiency (the relationship between task performance and mental effort measured directly from the brain). In this work, we analyzed the neural efficiency of 30 non-amputee participants in a grasp-and-lift task of a brittle object. Here, a myoelectric prosthesis featuring vibrotactile feedback of grip force and autonomous control of grasping was compared with a standard myoelectric prosthesis with and without vibrotactile feedback. As a measure of mental effort, we captured the prefrontal cortex activity changes using functional near infrared spectroscopy during the experiment. It was expected that the prosthesis with haptic shared control would improve both task performance and mental effort compared to the standard prosthesis. Results showed that only the haptic shared control system enabled users to achieve high neural efficiency, and that vibrotactile feedback was important for grasping with the appropriate grip force. These results indicate that the haptic shared control system synergistically combines the benefits of haptic feedback and autonomous controllers, and is well-poised to inform such hybrid advancements in myoelectric prosthesis technology.

Diffuse correlation spectroscopy: current status and future outlook

Diffuse correlation spectroscopy (DCS) has emerged as a versatile, noninvasive method for deep tissue perfusion assessment using near-infrared light. A broad class of applications is being pursued in neuromonitoring and beyond. However, technical limitations of the technology as originally implemented remain as barriers to wider adoption. A wide variety of approaches to improve measurement performance and reduce cost are being explored; these include interferometric methods, camera-based multispeckle detection, and long path photon selection for improved depth sensitivity. We review here the current status of DCS technology and summarize future development directions and the challenges that remain on the path to widespread adoption.

fNIRS neuroimaging in olfactory research: A systematic literature review

There are a number of key features which make olfaction difficult to study; subjective processes of odor detection, discrimination and identification, and individualistic odor hedonic perception and associated odor memories. In this systematic review we explore the role functional near-infrared spectroscopy (fNIRS) has played in understanding olfactory perception in humans. fNIRS is an optical neuroimaging technique able to measure changes in brain hemodynamics and oxygenation related to neural electrical activity. Adhering to PRISMA guidelines, results of this search found that generally the majority of studies involving healthy adult subjects observed increased activity in response to odors. Other population types were also observed, such as infants, individuals with autism, attention deficit hyperactivity disorder (ADHD), post-traumatic stress disorder (PTSD), mild cognitive impairment (MCI) and dysosmia. fNIRS coverage heavily favored the prefrontal cortex, temporal and parietal regions. This review finds that odor induced cortical activation is dependent on multiple factors, such as odorant type, gender and population type. This review also finds that there is room for improvement in areas such as participant diversity, use of wearable fNIRS systems, physiological monitoring and multi-distance channels.