EXPRESS: Simultaneous Measurement of Two-Trace Two-Dimensional (2T2D) Near-Infrared (NIR) Asynchronous Correlation Spectra and Small Angle X-ray Scattering (SAXS) to Characterize Thermally Aged Polypropylene (PP).

In this study, a new system was developed to carry out simultaneous near-infrared (NIR) and small-angle X-ray scattering (SAXS) measurements. Aged PP was examined with the NIR-SAXS system to demonstrate how it can be utilized to derive pertinent information about polymer structure. Pairs of SAXS profiles and NIR spectra of PP in its initial state and after aging were measured to derive an in-depth understanding of the aging phenomenon. The SAXS profiles of the PP samples showed a clear shift of the SAXS peak to the lower q direction induced by the thermal aging, indicating an increase in the length of the long-period structure. Two-trace two-dimensional (2T2D) asynchronous correlation spectra derived from NIR spectra clearly revealed that the aging treatment leads to the substantial increase in the spectral intensity of the regularity bands representing the longer helix present in a folded lamellar structure. In other words, it suggest that the long helix structure is more abundantly present than the short helix structure in the aged PP than in the initial PP. By combining the information derived from the SAXS profiles and NIR spectra, the details of the aging-induced variation were clearly determined. Namely, aging causes additional crystallization of the PP by developing more helix structures, which involves an increase in lamellar thickness as well as a decrease in the amorphous region. The growth of the rigid crystalline phase restricts the elastic deformation in the amorphous structure, which eventually induces the deterioration of PP by making the polymer hard but brittle. Such observation, in turn, implies that the retarding or accelerating the crystallized structure of PP substantially works to control the progress of the aging.

Effect of short-term intensive design-based STEM learning on executive function: an fNIRS study of the left-behind children.

Design-based STEM learning is believed to be an effective cross-disciplinary strategy for promoting children's cognitive development. Yet, its impact on executive functions, particularly for disadvantaged children, still need to be explored. This study investigated the effects of short-term intensive design-based STEM learning on executive function among left-behind children. Sixty-one Grade 4 students from a school dedicated to the left-behind children in China were sampled and randomly assigned to an experimental group (10.70 ± 0.47 years old, n = 30) or a control group (10.77 ± 0.43 years old, n = 31). The experimental group underwent a two-week design-based STEM training program, while the control group participated in a 2-week STEM-related reading program. Both groups were assessed with the brain activation from 4 brain regions of interest using functional near-infrared spectroscopy (fNIRS) and behavioral measures during a Stroop task before and after the training. Analysis disclosed: (i) a significant within-group time effect in the experimental group, with posttest brain activation in Brodmann Area 10 and 46 being notably lower during neutral and word conditions; (ii) a significant between-group difference at posttest, with the experimental group showing considerably lower brain activation in Brodmann Area 10 and Brodmann Area 46 than the control group; and (iii) a significant task effect in brain activity among the three conditions of the Stroop task. These findings indicated that this STEM learning effectively enhanced executive function in left-behind children. The discrepancy between the non-significant differences in behavioral performance and the significant ones in brain activation implies a compensatory mechanism in brain activation. This study enriches current theories about the impact of Science, Technology, Engineering, and Mathematics (STEM) learning on children's executive function development, providing biological evidence and valuable insights for educational curriculum design and assessment.

Development and evaluation of portable NIR technology for the identification and quantification of Australian illicit drugs.

The efficient and accurate analysis of illicit drugs remains a constant challenge in Australia given the high volume of drugs trafficked into and around the country. Portable drug testing technologies facilitate the decentralisation of the forensic laboratory and enable analytical data to be acted upon more efficiently. Near-infrared (NIR) spectroscopy combined with chemometric modelling (machine learning algorithms) has been highlighted as a portable drug testing technology that is rapid and accurate. However, its effectiveness depends upon a database of chemically relevant specimens that are representative of the market. There are chemical differences between drugs in different countries that need to be incorporated into the database to ensure accurate chemometric model prediction. This study aimed to optimise and assess the implementation of NIR spectroscopy combined with machine learning models to rapidly identify and quantify illicit drugs within an Australian context. The MicroNIR (Viavi Solutions Inc.) was used to scan 608 illicit drug specimens seized by the Australian Federal Police comprising of mainly crystalline methamphetamine hydrochloride (HCl), cocaine HCl, and heroin HCl. A number of other traditional drugs, new psychoactive substances and adulterants were also scanned to assess selectivity. The 3673 NIR scans were compared to the identity and quantification values obtained from a reference laboratory in order to assess the proficiency of the chemometric models. The identification of crystalline methamphetamine HCl, cocaine HCl, and heroin HCl specimens was highly accurate, with accuracy rates of 98.4 %, 97.5 %, and 99.2 %, respectively. The sensitivity of these three drugs was more varied with heroin HCl identification being the least sensitive (methamphetamine = 96.6 %, cocaine = 93.5 % and heroin = 91.3 %). For these three drugs, the NIR technology provided accurate quantification, with 99 % of values falling within the relative uncertainty of ±15 %. The MicroNIR with NIRLAB infrastructure has demonstrated to provide accurate results in real-time with clear operational applications. There is potential to improve informed decision-making, safety, efficiency and effectiveness of frontline and proactive policing within Australia.

Near-infrared spectroscopy (NIRS) in vivo assessment of skeletal muscle oxidative capacity: a comparison of results from short versus long exercise protocols and reproducibility in non-athletic adults.

Background: Near-infrared spectroscopy (NIRS) provides a non-invasive, cost-effective method for assessing skeletal muscle oxidative capacity when combined with a short exercise protocol and arterial occlusions. However, the impact of different exercise protocols and reproducibility of the method in non-athletic adults have not previously been assessed. Methods: Young, non-athletic adults (YA) were invited to perform a short duration, fast frequency contraction (SF) exercise protocol and a long duration slow frequency (LS) contraction protocol, combined with NIRS measurements and arterial occlusions to assess skeletal muscle oxidative capacity. YA and older non-athletic adults (OA; >65 years old) were invited to perform the SF exercise protocol twice to assess the reproducibility of this oxidative capacity measurement. Results: We included 25 participants (14 male (56%), age range: 18-86 years) in the analyses. There was a strong positive correlation and good agreement between time constants derived following the SF and LS exercise protocols (Lin's concordance correlation coefficient: 0.69, p-value < 0.001 mean bias [LoA]: -3.2 [-31.0, 24.4] seconds. There was a strong positive correlation and good agreement between time constants derived from the SF exercise protocol in the YA & OA group (Lin's concordance correlation coefficient: 0.63, p-value < 0.001; mean bias [LoA] -6.4 [-34.0, 21.3] seconds). Conclusion: These data provide evidence to suggest that NIRS is a reliable in vivo method for the assessment of skeletal muscle oxidative capacity irrespective of exercise protocol duration or muscle contraction frequency. NIRS-measured oxidative capacity via the SF exercise protocol was reproducible in non-athletic adults with a wide range in age.

Regional cerebral oxygen saturation variability and brain injury in preterm infants.

Objective: To examine whether variation of regional cerebral oxygen saturation (rScO2) within three days after delivery predicts development of brain injury (intraventricular/cerebellar hemorrhage or white matter injury) in preterm infants. Study design: A prospective study of neonates <32 weeks gestational age with normal cranial ultrasound admitted between 2018 and 2022. All received rScO2 monitoring with near-infrared spectroscopy at admission up to 72 h of life. To assess brain injury a magnetic resonance imaging was performed at term-equivalent age. We assessed the association between rScO2 variability (short-term average real variability, rScO2ARV, and standard deviation, rScO2SD), mean rScO2 (rScO2MEAN), and percentage of time rScO2 spent below 60% (rScO2TIME<60%) during the first 72 h of life and brain injury. Results: The median [IQR] time from birth to brain imaging was 68 [59-79] days. Of 81 neonates, 49 had some form of brain injury. Compared to neonates without injury, in those with injury rScO2ARV was higher during the first 24 h (P = 0.026); rScO2SD was higher at 24 and 72 h (P = 0.029 and P = 0.030, respectively), rScO2MEAN was lower at 48 h (P = 0.042), and rScO2TIME<60% was longer at 24, 48, and 72 h (P = 0.050, P = 0.041, and P = 0.009, respectively). Similar results were observed in multivariable logistic regression. Although not all results were statistically significant, increased rScO2 variability (rScO2ARV and rScO2SD) and lower mean values of rScO2 were associated with increased likelihood of brain injury. Conclusions: In preterm infants increased aberration of rScO2 in early postdelivery period was associated with an increased likelihood of brain injury diagnosis at term-equivalent age.

PFC/M1 activation and excitability: a longitudinal cohort study on fatigue symptoms in healthcare workers post-COVID-19.

BACKGROUND: Fatigue is one of the most common neurological symptoms reported post coronavirus disease 2019 (COVID-19) infection. In order to establish effective early intervention strategies, more emphasis should be placed on the correlation between fatigue and cortical neurophysiological changes, especially in healthcare workers, who are at a heightened risk of COVID-19 infection. METHODS: A prospective cohort study was conducted involving 29 COVID-19 medical workers and 24 healthy controls. The assessment included fatigue, sleep and health quality, psychological status, and physical capacity. Functional near-infrared spectroscopy (fNIRS) was employed to detect activation of brain regions. Bilateral primary motor cortex (M1) excitabilities were measured using single- and paired-pulse transcranial magnetic stimulation. Outcomes were assessed at 1, 3, and 6 months into the disease course. RESULTS: At 1-month post-COVID-19 infection, 37.9% of patients experienced severe fatigue symptoms, dropping to 10.3% at 3 months. Interestingly, the remarkable decreased activation/excitability of bilateral prefrontal lobe (PFC) and M1 were closely linked to fatigue symptoms after COVID-19. Notably, greater increase in M1 region excitability correlated with more significant fatigue improvement. Re-infected patients exhibited lower levels of brain activation and excitability compared to single-infection patients. CONCLUSIONS: Both single infection and reinfection of COVID-19 lead to decreased activation and excitability of the PFC and M1. The degree of excitability improvement in the M1 region correlates with a greater recovery in fatigue. Based on these findings, targeted interventions to enhance and regulate the excitability of M1 may represent a novel strategy for COVID-19 early rehabilitation. TRIAL REGISTRATION: The Ethics Review Committee of Xijing Hospital, No. KY20232051-F-1; www.chictr.org.cn , ChiCTR2300068444.

Cardiac vagal activity changes moderated the association of cognitive and cerebral hemodynamic variations in the prefrontal cortex.

Phasic cardiac vagal activity (CVA), reflecting ongoing, moment-to-moment psychophysiological adaptations to environmental changes, can serve as a predictor of individual difference in executive function, particularly executive performance. However, the relationship between phasic CVA and executive function demands requires further validation because of previous inconsistent findings. Moreover, it remains unclear what types of phasic changes of CVA may be adaptive in response to heightened executive demands. This study used the standard N-back task to induce different levels of working memory (WM) load and combined functional Near-Infrared Spectroscopy (fNIRS) with a multipurpose polygraph to investigate the variations of CVA and its interactions with cognitive and prefrontal responses as executive demands increased in fifty-two healthy young subjects. Our results showed phasic decreases in CVA as WM load increased (t (51) = -3.758, p < 0.001, Cohen's d = 0.526). Furthermore, phasic changes of CVA elicited by increased executive demands moderated the association of cognitive and cerebral hemodynamic variations in the prefrontal cortex (B = 0.038, SE = 0.014, p < 0.05). Specifically, as executive demands increased, individuals with larger phasic CVA withdrawal showed a positive relationship between cognitive and hemodynamic variations in the prefrontal cortex (ß = 0.281, p = 0.031). No such significant relationship was observed in individuals with smaller phasic CVA withdrawal. The current findings demonstrate a decrease in CVA with increasing executive demands and provide empirical support for the notion that a larger phasic CVA withdrawal can be considered adaptive in situations requiring high executive function demands.

Application of adaptive chaotic dung beetle optimization algorithm to near-infrared spectral model transfer.

A new transfer approach was proposed to share calibration models of the hexamethylenetetramine-acetic acid solution for studying hexamethylenetetramine concentration values across different near-infrared (NIR) spectrometers. This approach combines Savitzky-Golay first derivative (S_G_1) and orthogonal signal correction (OSC) preprocessing, along with feature variable optimization using an adaptive chaotic dung beetle optimization (ACDBO) algorithm. The ACDBO algorithm employs tent chaotic mapping and a nonlinear decreasing strategy, enhancing the balance between global and local search capabilities and increasing population diversity to address limitations observed in traditional dung beetle optimization (DBO). Validated using the CEC-2017 benchmark functions, the ACDBO algorithm demonstrated superior convergence speed, accuracy, and stability. In the context of a partial least squares (PLS) regression model for transferring hexamethylenetetramine-acetic acid solutions using NIR spectroscopy, the ACDBO algorithm excelled over alternative methods such as uninformative variable elimination, competitive adaptive reweighted sampling, cuckoo search, grey wolf optimizer, differential evolution, and DBO in efficiency, accuracy of feature variable selection, and enhancement of model predictive performance. The algorithm attained outstanding metrics, including a determination coefficient for the calibration set (Rc2) of 0.99999, a root mean square error for the calibration set (RMSEC) of 0.00195%, a determination coefficient for the validation set (Rv2) of 0.99643, a root mean squared error for the validation set (RMSEV) of 0.03818%, residual predictive deviation (RPD) of 16.72574. Compared to existing OSC, slope and bias correction (S/B), direct standardization (DS), and piecewise direct standardization (PDS) model transfer methods, the novel strategy enhances the accuracy and robustness of model predictions. It eliminates irrelevant background information about the hexamethylenetetramine concentration, thereby minimizing the spectral discrepancies across different instruments. As a result, this approach yields a determination coefficient for the prediction set (Rp2) of 0.96228, a root mean squared error for the prediction set (RMSEP) of 0.12462%, and a relative error rate (RER) of 17.62331, respectively. These figures closely follow those obtained using DS and PDS, which recorded Rp2, RMSEP, and RER values of 0.97505, 0.10135%, 21.67030, and 0.98311, 0.08339%, 26.33552, respectively. Unlike conventional methods such as OSC, S/B, DS, and PDS, this novel approach does not require the analysis of identical samples across different instruments. This characteristic significantly broadens its applicability for model transfer, which is particularly beneficial for transferring specific measurement samples.

Convolutional neural networks can detect orthostatic hypotension in Parkinson's disease using resting-state functional near-infrared spectroscopy data.

Neurological disorders such as Parkinson's disease (PD) often adversely affect the vascular system, leading to alterations in blood flow patterns. Functional near-infrared spectroscopy (fNIRS) is used to monitor hemodynamic changes via signal measurement. This study investigated the potential of using resting-state fNIRS data through a convolutional neural network (CNN) to evaluate PD with orthostatic hypotension. The CNN demonstrated significant efficacy in analyzing fNIRS data, and it outperformed the other machine learning methods. The results indicate that judicious input data selection can enhance accuracy by over 85%, while including the correlation matrix as an input further improves the accuracy to more than 90%. This study underscores the promising role of CNN-based fNIRS data analysis in the diagnosis and management of the PD. This approach enhances diagnostic accuracy, particularly in resting-state conditions, and can reduce the discomfort and risks associated with current diagnostic methods, such as the head-up tilt test.

Regional brain activity and neural network changes in cognitive-motor dual-task interference: A functional near-infrared spectroscopy study.

Previous neuroimaging studies have reported dual-task interference (DTi) and deterioration of task performance in a cognitive-motor dual task (DT) compared to that in a single task (ST). Greater frontoparietal activity is a neural signature of DTi; nonetheless, the underlying mechanism of cortical network in DTi still remains unclear. This study aimed to investigate the regional brain activity and neural network changes during DTi induced by highly demanding cognitive-motor DT. Thirty-four right-handed healthy young adults performed the spiral-drawing task. They underwent a paced auditory serial addition test (PASAT) simultaneously or independently while their cortical activity was measured using functional near-infrared spectroscopy. Motor performance was determined using the balanced integration score (BIS), a balanced index of drawing speed and precision. The cognitive task of the PASAT was administered with two difficulty levels defined by 1 s (PASAT-1 s) and 2 s (PASAT-2 s) intervals, allowing for the serial addition of numbers. Cognitive performance was determined using the percentage of correct responses. These motor and cognitive performances were significantly reduced during DT, which combined a drawing and a cognitive task at either difficulty level, compared to those in the corresponding ST conditions. The DT conditions were also characterized by significantly increased activity in the right dorsolateral prefrontal cortex (DLPFC) compared to that in the ST conditions. Multivariate Granger causality (GC) analysis of cortical activity in the selected frontoparietal regions of interest further revealed selective top-down causal connectivity from the right DLPFC to the right inferior parietal cortex during DTs. Furthermore, changes in the frontoparietal GC connectivity strength between the PASAT-2 s DT and ST conditions significantly correlated negatively with changes in the percentage of correct responses. Therefore, DTi can occur even in cognitively proficient young adults, and the right DLPFC and frontoparietal network being crucial neural mechanisms underlying DTi. These findings provide new insights into DTi and its underlying neural mechanisms and have implications for the clinical utility of cognitive-motor DTs applied to clinical populations with cognitive decline, such as those with psychiatric and brain disorders.

Neural dynamics of delayed feedback in robot teleoperation: insights from fNIRS analysis.

Introduction: As robot teleoperation increasingly becomes integral in executing tasks in distant, hazardous, or inaccessible environments, operational delays remain a significant obstacle. These delays, inherent in signal transmission and processing, adversely affect operator performance, particularly in tasks requiring precision and timeliness. While current research has made strides in mitigating these delays through advanced control strategies and training methods, a crucial gap persists in understanding the neurofunctional impacts of these delays and the efficacy of countermeasures from a cognitive perspective. Methods: This study addresses the gap by leveraging functional Near-Infrared Spectroscopy (fNIRS) to examine the neurofunctional implications of simulated haptic feedback on cognitive activity and motor coordination under delayed conditions. In a human-subject experiment (N = 41), sensory feedback was manipulated to observe its influences on various brain regions of interest (ROIs) during teleoperation tasks. The fNIRS data provided a detailed assessment of cerebral activity, particularly in ROIs implicated in time perception and the execution of precise movements. Results: Our results reveal that the anchoring condition, which provided immediate simulated haptic feedback with a delayed visual cue, significantly optimized neural functions related to time perception and motor coordination. This condition also improved motor performance compared to the asynchronous condition, where visual and haptic feedback were misaligned. Discussion: These findings provide empirical evidence about the neurofunctional basis of the enhanced motor performance with simulated synthetic force feedback in the presence of teleoperation delays. The study highlights the potential for immediate haptic feedback to mitigate the adverse effects of operational delays, thereby improving the efficacy of teleoperation in critical applications.

Similarity measure method of near-infrared spectrum combined with multi-attribute information.

Due to the high-dimensionality, redundancy, and non-linearity of the near-infrared (NIR) spectra data, as well as the influence of attributes such as producing area and grade of the sample, which can all affect the similarity measure between samples. This paper proposed a t-distributed stochastic neighbor embedding algorithm based on Sinkhorn distance (St-SNE) combined with multi-attribute data information. Firstly, the Sinkhorn distance was introduced which can solve problems such as KL divergence asymmetry and sparse data distribution in high-dimensional space, thereby constructing probability distributions that make low-dimensional space similar to high-dimensional space. In addition, to address the impact of multi-attribute features of samples on similarity measure, a multi-attribute distance matrix was constructed using information entropy, and then combined with the numerical matrix of spectral data to obtain a mixed data matrix. In order to validate the effectiveness of the St-SNE algorithm, dimensionality reduction projection was performed on NIR spectral data and compared with PCA, LPP, and t-SNE algorithms. The results demonstrated that the St-SNE algorithm effectively distinguishes samples with different attribute information, and produced more distinct projection boundaries of sample category in low-dimensional space. Then we tested the classification performance of St-SNE for different attributes by using the tobacco and mango datasets, and compared it with LPP, t-SNE, UMAP, and Fisher t-SNE algorithms. The results showed that St-SNE algorithm had the highest classification accuracy for different attributes. Finally, we compared the results of searching the most similar sample with the target tobacco for cigarette formulas, and experiments showed that the St-SNE had the highest consistency with the recommendation of the experts than that of the other algorithms. It can provide strong support for the maintenance and design of the product formula.

Increased and sex-differentiated medial prefrontal cortex activation during the MATRICS Consensus Cognitive Battery in schizophrenia: A fNIRS study.

Executive impairment in schizophrenia is common, but the mechanism remains unclear. This is the first study to use simultaneously functional near-infrared spectroscopy (fNIRS) to monitor the hemodynamic response in schizophrenia during the MATRICS Consensus Cognitive Battery (MCCB). Here, we monitored relative changes in oxyhemoglobin concentration in the medial prefrontal cortex (mPFC) during Trail Making Test, Symbol Coding Test and Mazes Test of the MCCB in 63 patients (29 females) with schizophrenia and 32 healthy controls (15 females). Results showed that patients with schizophrenia scored lower than healthy controls on all three tests (P < 0.001), but mPFC activation was significantly higher during the test (P < 0.03). Higher activation of the mPFC may reflect abnormal information processing in schizophrenia. In addition, the results also showed sex differences in hemodynamic activation during the task in patients with schizophrenia, and fNIRS has the potential to be a clinical adjunct to screening for cognitive function in schizophrenia.

Effect of near-infrared spectroscopy on postoperative delirium in cardiac surgery with cardiopulmonary bypass: a systematic review and meta-analysis.

Background: Postoperative delirium (POD) is a common anesthetic side effect in cardiac surgery. However, the role of oxygen saturation monitoring in reducing postoperative delirium has been controversial. Therefore, this meta-analysis aimed to analyze whether NIRS monitoring during cardiac surgery under cardiopulmonary bypass could reduce the incidence of postoperative delirium. Methods: PubMed, Web of Science, Cochrane Library, Embase and China National Knowledge Infrastructure (CNKI) databases were systematically searched using the related keywords for randomized-controlled trials (RCTs) published from their inception to March 16, 2024. This review was conducted by the Preferred Reporting Project and Meta-Analysis Statement (PRISMA) guidelines for systematic review. The primary outcome was postoperative delirium, and the second outcomes included the length of ICU stay, the incidence of kidney-related adverse outcomes, and the incidence of cardiac-related adverse outcomes. Results: The incidence of postoperative delirium could be reduced under the guidance of near-infrared spectroscopy monitoring (OR, 0.657; 95% CI, 0.447-0.965; P = 0.032; I2 = 0%). However, there were no significant differences in the length of ICU stay (SMD, 0.005 days; 95% CI, -0.135-0.146; P = 0.940; I2 = 39.3%), the incidence of kidney-related adverse outcomes (OR, 0.761; 95% CI, 0.386-1.500; P = 0.430; I2 = 0%), and the incidence of the cardiac-related adverse outcomes (OR, 1.165; 95% CI, 0.556-2.442; P = 0.686; I2 = 0%) between the two groups. Conclusion: Near-infrared spectroscopy monitoring in cardiac surgery with cardiopulmonary bypass helps reduce postoperative delirium in patients. Systematic Review Registration: PROSPERO, identifier, CRD42023482675.

Detectability of hemodynamic oscillations in cerebral cortex through functional near-infrared spectroscopy: a simulation study.

Significance: We explore the feasibility of using time-domain (TD) and continuous-wave (CW) functional near-infrared spectroscopy (fNIRS) to monitor brain hemodynamic oscillations during resting-state activity in humans, a phenomenon that is of increasing interest in the scientific and medical community and appears to be crucial to advancing the understanding of both healthy and pathological brain functioning. Aim: Our general object is to maximize fNIRS sensitivity to brain resting-state oscillations. More specifically, we aim to define comprehensive guidelines for optimizing main operational parameters in fNIRS measurements [average photon count rate, measurement length, sampling frequency, and source-detector distance (SSD)]. In addition, we compare TD and CW fNIRS performance for the detection and localization of oscillations. Approach: A series of synthetic TD and CW fNIRS signals were generated by exploiting the solution of the diffusion equation for two different geometries of the probed medium: a homogeneous medium and a bilayer medium. Known and periodical perturbations of the concentrations of oxy- and deoxy-hemoglobin were imposed in the medium, determining changes in its optical properties. The homogeneous slab model was used to determine the effect of multiple measurement parameters on fNIRS sensitivity to oscillatory phenomena, and the bilayer model was used to evaluate and compare the abilities of TD and CW fNIRS in detecting and isolating oscillations occurring at different depths. For TD fNIRS, two approaches to enhance depth-selectivity were evaluated: first, a time-windowing of the photon distribution of time-of-flight was performed, and then, the time-dependent mean partial pathlength (TMPP) method was used to retrieve the hemoglobin concentrations in the medium. Results: In the homogeneous medium case, the sensitivity of TD and CW fNIRS to periodical perturbations of the optical properties increases proportionally with the average photon count rate, the measurement length, and the sampling frequency and approximatively with the square of the SSD. In the bilayer medium case, the time-windowing method can detect and correctly localize the presence of oscillatory components in the TD fNIRS signal, even in the presence of very low photon count rates. The TMPP method demonstrates how to correctly retrieve the periodical variation of hemoglobin at different depths from the TD fNIRS signal acquired at a single SSD. For CW fNIRS, measurements taken at typical SSDs used for short-separation channel regression show notable sensitivity to oscillations occurring in the deep layer, challenging the assumptions underlying this correction method when the focus is on analyzing oscillatory phenomena. Conclusions: We demonstrated that the TD fNIRS technique allows for the detection and depth-localization of periodical fluctuations of the hemoglobin concentrations within the probed medium using an acquisition at a single SSD, offering an alternative to multi-distance CW fNIRS setups. Moreover, we offered some valuable guidelines that can assist researchers in defining optimal experimental protocols for fNIRS studies.

Multimodal analysis of cortical activation in young male adults with internet gaming disorder: A resting state EEG-fNIRS study.

BACKGROUND: Internet gaming disorder (IGD) has become increasingly prevalent worldwide and is recognized as a significant public health concern because of its negative consequences on individuals mental and physical health, social relationships, academic performance and overall well-being. While research on IGD has gained significant momentum in the past decade, the neural substrates underlying this disorder remains unclear. This study aims to investigate resting-state cortical activation in male subjects with IGD using a concurrent functional near infrared spectroscopy (fNIRS) and electroencephalography (EEG) hybrid system. METHODS: Twenty-two male individuals with IGD (18-23 years old) and twenty-two male healthy, age-matched healthy controls were included in the study. Mean oxygenation of the prefrontal cortex (PFC) and whole head neural activity were measured using fNIRS and EEG respectively, during eyes-open and eyes-closed conditions at the resting state. EEG signals were decomposed into distinct frequency sub-bands with wavelet transform, followed by the analysis of the power spectral density within each band. Mean oxygenation of PFC is measured using a multichannel fNIRS system. RESULTS: Results revealed that the individuals with IGD had significantly higher beta power in the frontal region compared to the control group. Individuals with IGD showed significantly increased PFC oxygenation compared to healthy controls. Additionally, both frontal beta power and PFC oxygenation were significantly correlated with IGD severity. However, there were no significant correlations observed between oxygenation and beta powers. CONCLUSION: This study is the first to examine resting-state cortical activation using multimodal EEG-fNIRS system in young adults with IGD. Moreover, it provides an important contribution to the understanding of the underlying neural mechanisms of IGD and offer new insights for the diagnosis and intervention of the disorder using multimodal EEG-fNIRS system. Further studies should aim to replicate the findings of this study using a larger and more culturally diverse sample to support the neurophysiological basis of IGD.

Cerebral Synchronization Between Mothers and Their Newborns During Breastfeeding.

Introduction: Breastfeeding is a fundamental biological function in mammals, allowing the progeny to develop in a physiological way. A physical and emotional dialog between mothers and offspring during breastfeeding has been described as part of the attachment relationship, and a synchronicity between maternal and neonatal brains can be hypothesized. This study aimed to assess if neonatal and maternal cortical areas activated during breastfeeding are functionally synchronized since the second day of life. Materials and Methods: Twenty mothers and their term newborns were enrolled. Cortical activation during breastfeeding was identified by multichannel near-infrared spectroscopy, which detects changes in haemoglobin concentration from multiple cortical regions. Functional activity was simultaneously detected (hyperscanning) in mothers and newborns' frontal and motor/primary somatosensory cortical areas during the first 5 minutes of breastfeeding. Cluster analysis and Student's t test were used to detect oxygenated haemoglobin increase, as cortical activation estimate. Wavelet transform coherence (WTC) analysis was used to identify a possible synchronization between maternal and neonatal activated cortical regions. Results: Mothers showed an activation of the central motor/primary somatosensory cortex, above the sagittal fissure. In newborns, the bilateral frontal cortex was activated. WTC analysis revealed two different cyclical synchronizations between mothers and infants' activated cortical regions. Conclusions: Such evidence may reflect a very early common sharing of experiences, possibly associated with reciprocal dynamic motor adjustments, hormonal coregulation, and somatic stimulations and sensations. The observed cyclical neural synchronization, between the mother and her newborn's cortex during breastfeeding, may play an important role in promoting their bonding.

Ecological momentary assessment and cue-elicited drug craving as primary endpoints: study protocol for a randomized, double-blind, placebo-controlled clinical trial testing the efficacy of a GLP-1 receptor agonist in opioid use disorder.

BACKGROUND: Despite continuing advancements in treatments for opioid use disorder (OUD), continued high rates of relapse indicate the need for more effective approaches, including novel pharmacological interventions. Glucagon-like peptide 1 receptor agonists (GLP-1RA) provide a promising avenue as a non-opioid medication for the treatment of OUD. Whereas GLP-1RAs have shown promise as a treatment for alcohol and nicotine use disorders, to date, no controlled clinical trials have been conducted to determine if a GLP-1RA can reduce craving in individuals with OUD. The purpose of the current protocol was to evaluate the potential for a GLP-1RA, liraglutide, to safely and effectively reduce craving in an OUD population in residential treatment. METHOD: This preliminary study was a randomized, double-blinded, placebo-controlled clinical trial designed to test the safety and efficacy of the GLP-1RA, liraglutide, in 40 participants in residential treatment for OUD. Along with taking a range of safety measures, efficacy for cue-induced craving was evaluated prior to (Day 1) and following (Day 19) treatment using a Visual Analogue Scale (VAS) in response to a cue reactivity task during functional near-infrared spectroscopy (fNIRS) and for craving. Efficacy of treatment for ambient craving was assessed using Ecological Momentary Assessment (EMA) prior to (Study Day 1), across (Study Days 2-19), and following (Study Days 20-21) residential treatment. DISCUSSION: This manuscript describes a protocol to collect clinical data on the safety and efficacy of a GLP-1RA, liraglutide, during residential treatment of persons with OUD, laying the groundwork for further evaluation in a larger, outpatient OUD population. Improved understanding of innovative, non-opioid based treatments for OUD will have the potential to inform community-based interventions and health policy, assist physicians and health care professionals in the treatment of persons with OUD, and to support individuals with OUD in their effort to live a healthy life. TRIAL REGISTRATION: ClinicalTrials.gov: NCT04199728. Registered 16 December 2019, https://clinicaltrials.gov/study/NCT04199728?term=NCT04199728 . PROTOCOL VERSION: 10 May 2023.

Cerebrovascular Autoregulation in Preterm Infants Using Heart Rate or Blood Pressure: A Pilot Study.

BACKGROUND: Cerebrovascular autoregulation (CAR) is often impaired in preterm infants but requires invasive mean arterial blood pressure (MABP) measurements for continuous assessment. We aimed to assess whether using heart rate (HR) results in different CAR assessment compared with using MABP. METHODS: We compared CAR (moving window correlation-coefficient with cerebral oxygenation saturation (rcSO2)), and percentage of time with impaired CAR (%timeCARi) calculated by either HR (TOHRx, tissue oxygenation heart rate reactivity index) or MABP (COx, cerebral oximetry index) during the first 72 h after birth, and its association with short-term cerebral injury. RESULTS: We included 32 infants, median gestational age of 25 + 5/7 weeks (interquartile range 24 + 6/7-27 + 5/7). COx and TOHRx correlation coefficients (cc) were significantly different in the first two days after birth (individual means ranging from 0.02 to 0.07 and -0.05 to 0.01). %TimeCARi using MABP (cc cut-off 0.3), was higher on day 1 (26.1% vs. 17.7%) and day 3 (23.4% vs. 16.9%) compared with HR (cc cutoff -0.3). During 65.7-69.6% of the time, both methods indicated impaired CAR simultaneously. The aforementioned calculations were not associated with early cerebral injury. CONCLUSIONS: In conclusion, HR and MABP do not seem interchangeable when assessing CAR in preterm infants.

Combined Metabolomic and NIRS Analyses Reveal Biochemical and Metabolite Changes in Goat Milk Kefir under Different Heat Treatments and Fermentation Times.

Dairy products are an important source of protein and other nutrients in the Mediterranean diet. In these countries, the most common sources of milk for producing dairy products are cow, goat, sheep, and buffalo. Andalusia is traditionally the largest producer of goat milk in Spain. Kefir is a fermented product made from bacteria and yeasts and has health benefits beyond its nutritional properties. There is a lack of knowledge about the molecular mechanisms and metabolites that bring about these benefits. In this work, the combination of analytical techniques (GC-FID, UHPLC-MS-QToF, GC-QqQ-MS, and GC-ToF-MS) resulted in the detection of 105 metabolites in kefir produced with goat milk from two different thermal treatments (raw and pasteurized) fermented at four time points (12, 24, 36, and 48 h, using 0 h as the control). Of these, 27 metabolites differed between kefir produced with raw and pasteurized milk. These changes could possibly be caused by the effect of pasteurization on the microbial population in the starting milk. Some interesting molecules were identified, such as shikimic acid, dehydroabietic acid, GABA, and tyramine, which could be related to antibacterial properties, strengthening of the immune system, and arterial pressure. Moreover, a viability assay of the NIRS technique was performed to evaluate its use in monitoring the fermentation and classification of samples, which resulted in a 90% accuracy in comparison to correctly classified samples according to their fermentation time. This study represents the most comprehensive metabolomic analysis of goat milk kefir so far, revealing the intricate changes in metabolites during fermentation and the impact of milk treatment.