Brain Hemodynamic Responses Research Articles

Brain hemodynamic responses and fall prediction in older adults with multiple sclerosis.

We examined whether brain hemodynamic responses, gait, and cognitive performances under single- and dual-task conditions predict falls during longitudinal follow-up in older adults with multiple sclerosis (OAMS) with relapsing-remitting and progressive subtypes. Participants with relapsing-remitting (n = 53, mean age = 65.02 ± 4.17 years, %female = 75.5) and progressive (n = 28, mean age = 64.64 ± 4.31 years, %female = 50) multiple sclerosis (MS) subtypes completed a dual-task-walking paradigm and reported falls during longitudinal follow-up using a monthly structured telephone interview. We used functional near-infrared spectroscopy (fNIRS) to assess oxygenated hemoglobin (HbO) in the prefrontal cortex during active walking and while performing a cognitive test under single- and dual-task conditions. Adjusted general estimating equations models indicated that higher HbO under dual-task walking was significantly associated with a reduction in the odds of reporting falls among participants with relapsing-remitting (odds ratio (OR) = 0.472, p = 0.004, 95% confidence interval (CI) = 0.284-0.785), but not progressive (OR = 1.056, p = 0.792, 95% CI = 0.703-1.588) MS. In contrast, faster stride velocity under dual-task walking was significantly associated with a reduction in the odds of reporting falls among progressive (OR = 0.658, p = 0.004, 95% CI = 0.495-0.874), but not relapsing-remitting (OR = 0.998, p = 0.995, 95% CI = 0.523-1.905) MS. Findings suggest that higher prefrontal cortex activation levels during dual-task walking, which may represent compensatory reallocation of brain resources, provide protection against falls for OAMS with relapsing-remitting subtype.

Exploring the Non-Invasive Methods of Brain- Computer Interface: A Comprehensive Review of their Advances and Applications

The brain-computer interface technology allows the human brain to control external devices directly without using the brain’s output channels or peripheral nerves. It helps individuals with motor impairments to use mechanical and external devices to communicate with the outside world. Non-invasive BCIs allow communication between the human brain and external devices without the need for surgeries or invasive procedures. Methods like EEG, MEG, fMRI, and fNIRS are used. EEG enables the acquisition of electrical activity along the scalp by measuring voltage fluctuations and neurotransmission activity in the brain. The electrodes are attached to a cap-like device and are placed on the scalp to record the electrical current generated by the brain. Unlike MEG, which necessitates specially constructed rooms, EEG is portable. Lab-grade EEG is expensive but cheaper than other forms of BCI. MEG uses magnetometers to measure magnetic fields produced by electric currents occurring naturally in the brain. MEG is better than EEG at measuring high-frequency activity. MEG signals are less distorted by the skull layer. FMRI records blood oxygen level-dependent (BOLD) signals with high spatial resolution across the entire brain. It does this by tracking the hemodynamic response, which is the increase in blood flow to active brain areas. It does this using the principle of nuclear magnetic resonance, where hydrogen atoms in water molecules in the blood emit signals when subjected to a strong magnetic field. It has an advantage over EEG due to its superior spatial specificity and resolution. FNIRS measures the blood flow and oxygenation in the blood associated with neural activity. It gains insight into the brain's hemodynamic response, which is essential for understanding neural functioning during BCI tasks.

Cortical processes of multisensory plausibility modulation of vibrotactile perception in virtual environments in middled-aged and older adults

Digital technologies, such as virtual or augmented reality, can potentially support neurocognitive functions of the aging populations worldwide and complement existing intervention methods. However, aging-related declines in the frontal-parietal network and dopaminergic modulation which progress gradually across the later periods of the adult lifespan may affect the processing of multisensory congruence and expectancy based contextual plausibility. We assessed hemodynamic brain responses while middle-aged and old adults experienced car-riding virtual-reality scenarios where the plausibility of vibrotactile stimulations was manipulated by delivering stimulus intensities that were either congruent or incongruent with the digitalized audio-visual contexts of the respective scenarios. Relative to previous findings observed in young adults, although highly plausible vibrotactile stimulations confirming with contextual expectations also elicited higher brain hemodynamic responses in middle-aged and old adults, this effect was limited to virtual scenarios with extreme expectancy violations. Moreover, individual differences in plausibility-related frontal activity did not correlate with plausibility violation costs in the sensorimotor cortex, indicating less systematic frontal context-based sensory filtering in older ages. These findings have practical implications for advancing digital technologies to support aging societies.

A fNIRS investigation of menopausal-related symptoms and brain cortical activity in menopause.

This study aimed to delineate the association between menopausal-related symptoms and brain cortical hemodynamics in peri-postmenopause women. Cross-sectional data from a total of 358 Han-Chinese women who visited the Menopause Clinic in the Shanghai Sixth People's Hospital from August 2019 to August 2022. Menopausal-related symptoms were analyzed through Kupperman index (KMI) scale and PSQI scale, while cerebral blood flow was measured using a functional near-infrared spectroscopy (fNIRS). Multiple linear regression model was used to assess the risk factors for subregions of brain hemodynamic response. After adjusting for confounding factors, we identified that menopausal symptom (B=-1.575, 95% CI (-2.661, -0.488), p=0.005) and duration of menopause (B=-14.583, 95% CI (-26.753, -4.192), p=0.007) were independently associated with the lower brain hemodynamic response in the prefrontal lobe, while in the temporal lobe, overweight (BMI≥24kg/m2) was negatively associated with the lower brain cortical activity (B=-36.882, 95% CI (-72.708, -1.056), p=0.044) after adjusting for other confounding variables. Our findings proposed that menopausal symptom and overweight should be attached great importance to the postmenopausal women, which provides clinical evidence for the feasible early detection and effective prevention such as menopausal hormone therapy (MHT) of brain health in postmenopausal women.

Disentangling the effects of near-infrared light stimulation and exercise on cognitive function in fNIRS studies

Functional near-infrared spectroscopy (fNIRS) studies often aim to measure changes in the brain's hemodynamic response in relation to a specific intervention. We recently showed how a fNIRS device could induce photobiomodulatory effects on cognition by using its near-infrared (NIR) light. However, so far, fNIRS research has overlooked the stimulatory potential intrinsic to this technique. The work by Kuwamizu et al. (2023) on pupil dynamics during exercise is no exception. Here, we suggest a fix to their experimental design, which could be taken into account in other fNIRS studies, to guarantee an adequate level of control for possible unconsidered photobiomodulatory effects.

Language brain responses and neurodevelopmental outcome in preschoolers with congenital heart disease: A fNIRS study

Neurodevelopmental disabilities affect up to 50% of survivors of congenital heart disease (CHD). Language difficulties are frequently identified during preschool period and can lead to academic, social, behavioral, and emotional difficulties. Structural brain alterations are associated with poorer neurodevelopmental outcomes in patients with CHD during infancy, childhood, and adolescence. However, evidence is lacking about the functional brain activity in children with CHD and its relationship with neurodevelopment. This study therefore aimed to characterize brain responses during a passive story-listening task in 3-year-old children with CHD, and to investigate the relationship between functional brain patterns of language processing and neurodevelopmental outcomes. To do so, we assessed hemodynamic concentration changes, using functional near-infrared spectroscopy (fNIRS), and neurodevelopmental outcomes, using the Wechsler Preschool and Primary Scale of Intelligence – 4th Edition (WPPSI-IV), in children with CHD (n = 19) and healthy controls (n = 23). Compared to their healthy peers, children with CHD had significantly lower scores on the Verbal comprehension index (VCI), the Vocabulary acquisition index (VAI), the General ability index (GAI), and the Information and the Picture Naming subtests of the WPPSI-IV. During the passive story-listening task, healthy controls showed significant hemodynamic brain responses in the temporal and the temporal posterior regions, with stronger activation in the temporal posterior than in the temporal regions. In contrast, children with CHD showed reduced activation in the temporal posterior regions compared to controls, with no difference of activation between regions. Reduced brain responses in the temporal posterior regions were also correlated with lower neurodevelopmental outcomes in both groups. This is the first study that reveals reduced brain functional responses in preschoolers with CHD during a receptive language task. It also suggests that the temporal posterior activation could be a potential brain marker of cognitive development. These findings provide support for the feasibility of identifying brain correlates of neurodevelopmental vulnerabilities in children with CHD.

Abstract TP190: Higher Pre-Hospital Blood Pressure is Associated With Lower Mismatch Volume and Poorer Collateral Status in Patients With Acute Ischemic Stroke Due to Large Vessel Occlusions

Introduction: Immediately after AIS onset, blood pressure variability (BPV) arises as the result of a complex interplay between brain and systemic physiological hemodynamic responses. In this study, we examined the effect of BPV on early infarct growth in patients with large vessel occlusions (LVO) during their prehospital transfer. Methods: We included consecutive patients with AIS-LVO from 2 large comprehensive stroke centers. We collected the BP values from emergency medical services arrival to hospital admission. Patients with <3 BP recordings were excluded. BPV was assessed using the standard deviation (SD) of the systolic (SBPv), diastolic (DBPv), and mean BP (MBPv). Initial infarct volume (IIV) was defined as rCBF <30%, penumbra area as time to maximum concentration (Tmax) >6s, and mismatch volume as the difference between these two volumes (Tmax 6 - rCBF<30%). Collateral status was evaluated using the hypoperfusion intensity ratio (HIR), defined as the Tmax>10s/Tmax>6s ratio. We used linear regression to investigate associations between these variables, using log-transformation to achieve normality, and final exponentiation for a better interpretability of the results. Results: We included 171 patients, mean age was 70.9± 13.7, 51.5% female, 88.3% white, median NIHSS was 15. Mean BP: SBP=12.37 + 6.8, DBP=10.2 + 7.1, and MBP=8.9 + 5.9. CTP values: rCBF >30% (5 [IQR 0.001 - 22]), Tmax >6s (103 [60.5 - 158.5]), and HIR (0.38 [0.17 - 0.54]). Higher SBP variability was significantly associated with lower mismatch volumes. Furthermore, higher SBP tertiles were associated with worse collaterals (high HIR) (Figure) . Conclusion: Pre-hospital BPV is associated with lower mismatch volume, likely mediated by the effect of BP on collateral status. Our findings are consistent with previous studies; the association between higher pre-treatment blood pressure and poorer collaterals might be due to an imbalance in the need of increasing perfusion to the ischemic tissue.

Integrating fNIRS and machine learning: shedding light on Parkinson's disease detection.

The purpose of this research is to introduce an approach to assist the diagnosis of Parkinson's disease (PD) by classifying functional near-infrared spectroscopy (fNIRS) studies as PD positive or negative. fNIRS is a non-invasive optical signal modality that conveys the brain's hemodynamic response, specifically changes in blood oxygenation in the cerebral cortex; and its potential as a tool to assist PD detection deserves to be explored since it is non-invasive and cost-effective as opposed to other neuroimaging modalities. Besides the integration of fNIRS and machine learning, a contribution of this work is that various approaches were implemented and tested to find the implementation that achieves the highest performance. All the implementations used a logistic regression model for classification. A set of 792 temporal and spectral features were extracted from each participant's fNIRS study. In the two best performing implementations, an ensemble of feature-ranking techniques was used to select a reduced feature subset, which was subsequently reduced with a genetic algorithm. Achieving optimal detection performance, our approach reached 100 % accuracy, precision, and recall, with an F1 score and area under the curve (AUC) of 1, using 14 features. This significantly advances PD diagnosis, highlighting the potential of integrating fNIRS and machine learning for non-invasive PD detection.

High-temporal resolution functional PET/MRI reveals coupling between human metabolic and hemodynamic brain response

PurposePositron emission tomography (PET) provides precise molecular information on physiological processes, but its low temporal resolution is a major obstacle. Consequently, we characterized the metabolic response of the human brain to working memory performance using an optimized functional PET (fPET) framework at a temporal resolution of 3 s.MethodsThirty-five healthy volunteers underwent fPET with [18F]FDG bolus plus constant infusion, 19 of those at a hybrid PET/MRI scanner. During the scan, an n-back working memory paradigm was completed. fPET data were reconstructed to 3 s temporal resolution and processed with a novel sliding window filter to increase signal to noise ratio. BOLD fMRI signals were acquired at 2 s.ResultsConsistent with simulated kinetic modeling, we observed a constant increase in the [18F]FDG signal during task execution, followed by a rapid return to baseline after stimulation ceased. These task-specific changes were robustly observed in brain regions involved in working memory processing. The simultaneous acquisition of BOLD fMRI revealed that the temporal coupling between hemodynamic and metabolic signals in the primary motor cortex was related to individual behavioral performance during working memory. Furthermore, task-induced BOLD deactivations in the posteromedial default mode network were accompanied by distinct temporal patterns in glucose metabolism, which were dependent on the metabolic demands of the corresponding task-positive networks.ConclusionsIn sum, the proposed approach enables the advancement from parallel to truly synchronized investigation of metabolic and hemodynamic responses during cognitive processing. This allows to capture unique information in the temporal domain, which is not accessible to conventional PET imaging.

EarGenie, an innovative test to measure speech discrimination using functional near-infrared spectroscopy

EarGenie is an innovative hearing test utilizing fNIRS (functional near-infrared light) technology to measure the brain's response to sound. By detecting variations in the brain's hemodynamic response to auditory stimuli, EarGenie can effectively assess a baby's hearing capabilities. Current audiology practices primarily rely on electrophysiology measures to determine hearing thresholds in infants. This approach poses limitations when it comes to accurately assessing infants with auditory neuropathy. There is no measure of speech discrimination for the paediatric population currently in the clinical setting, which can lead to uncertainties and challenges in providing appropriate care. The EarGenie will fulfill this unmet need to provide clinicians with an objective measure of speech discrimination. Improved clarity for clinicians and families of the diagnosis and management of infants with hearing loss is required to optimize audiology practices.

How Do Drivers Perceive Risks During Automated Driving Scenarios? An fNIRS Neuroimaging Study.

Using brain haemodynamic responses to measure perceived risk from traffic complexity during automated driving. Although well-established during manual driving, the effects of driver risk perception during automated driving remain unknown. The use of fNIRS in this paper for assessing drivers' states posits it could become a novel method for measuring risk perception. Twenty-three volunteers participated in an empirical driving simulator experiment with automated driving capability. Driving conditions involved suburban and urban scenarios with varying levels of traffic complexity, culminating in an unexpected hazardous event. Perceived risk was measured via fNIRS within the prefrontal cortical haemoglobin oxygenation and from self-reports. Prefrontal cortical haemoglobin oxygenation levels significantly increased, following self-reported perceived risk and traffic complexity, particularly during the hazardous scenario. This paper has demonstrated that fNIRS is a valuable research tool for measuring variations in perceived risk from traffic complexity during highly automated driving. Even though the responsibility over the driving task is delegated to the automated system and dispositional trust is high, drivers perceive moderate risk when traffic complexity builds up gradually, reflected in a corresponding significant increase in blood oxygenation levels, with both subjective (self-reports) and objective (fNIRS) increasing further during the hazardous scenario. Little is known regarding the effects of drivers' risk perception with automated driving. Building upon our experimental findings, future work can use fNIRS to investigate the mental processes for risk assessment and the effects of perceived risk on driving behaviours to promote the safe adoption of automated driving technology.

Altered brain hemodynamic response and cognitive function after sleep deprivation: a functional near-infrared spectroscopy study

Aim: Acute sleep deprivation has revealed altered executive cognitive functioning, including attention, working memory, and interference resolution. In the present study, we investigated brain hemodynamics and cognitive function measures using functional near-infrared spectroscopy (fNIRS).Methods: fNIRS was used to record cortical brain activity in a resting state scan, flanker task, and n-Back tasks under well-rested (WR, >6.5 h sleep for ≥3 days) and sleep-deprived conditions (SD, 28 h awake) in a repeated-measures study in 20 participants (7 female, mean age 20.1 ± 0.413).Results: Our results indicate decreased accuracy rates in the flanker task in the SD condition, suggesting reduced response inhibition capacity. In the flanker task, a significant increase of beta estimates was observed in the SD condition in the right dl-PFC, suggesting potential compensation (BH-FDR corrected p = 0.0418, t(19) = 3.51). There were no significant differences between WR and SD in n-back task accuracy rates or reaction times or in Flanker task reaction times. Otherwise, functional connectivity strengths were not significantly different between the WR and SD sessions on a group-level analysis for the resting state and all tasks (BH-FDR correction, p > 0.05).Conclusion: Our results provide insight into how insufficient sleep patterns affect interference resolution, and that fNIRS can reveal functional connectivity differences inter- and intra-individually in SD conditions.

Harmonization of repetition time and scanner effects on estimates of brain hemodynamic response function.

Multisite contributions are essential to improve the reliability and statistical power of imaging studies but introduce a complexity because of different acquisition protocols and scanners. The hemodynamic response function (HRF) is the transform that relates neural activity to the measured blood oxygenation level-dependent (BOLD) signal in MRI and contains information about the latency, amplitude, and duration of neuronal activations. Acquisition variabilities, without adding harmonization techniques, can severely limit our ability to characterize spatial effects. To address this problem, we propose to study and remove variabilities of the sampling rate and scanners on estimates of the HRF. We computed the HRF using a blind deconvolution method in 547 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) across 62 sites and 18 scanners. The approach consists of studying the changes of the response according to repetition times (TR) and scanner models. We applied ComBAT, a statistical multi-site harmonization technique, to evaluate and reduce the scanner and repetition time effects and used the Wilcoxon rank sum test to assess the performance of the harmonization. Results show high scanner and repetition time variabilities (|d| ≥ 0.38, p = 4.5 × 10-5) across features, indicating that using harmonization is crucial in multi-site studies. ComBAT successfully removes the sampling effects and reduces the variance between scanners for 7 out of 10 of the HRF features (|d| ≤ 0.05, p = 0.0052). Scanners effects have been characterized on multi-site datasets, but the repetition time impact has been less studied. We showed that the use of different values of repetition time leads to changes in HRF behavior. Regression modeling changes in the HRF on the harmonized data are not significant (p = 0.0401) which does not allow to conclude how HRF changes with aging.

Aging effects on electrical and hemodynamic responses in the sensorimotor network during unilateral proximal upper limb functional tasks

Healthy aging leads to poorer performance in upper limb (UL) daily living movements. Understanding the neural correlates linked with UL functional movements may help to better understand how healthy aging affects motor control. Two non-invasive neuroimaging methods allow for monitoring the movement-related brain activity: functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG), respectively based on the hemodynamic response and electrical activity of brain regions. Coupled, they provide a better spatiotemporal mapping. The aim of this study was to evaluate the effect of healthy aging on the bilateral sensorimotor (SM1) activation patterns of functional proximal UL movements. Twenty-one young and 21 old healthy participants realized two unilateral proximal UL movements during: i) a paced reaching target task and ii) a circular steering task to capture the speed-accuracy trade-off. Combined fNIRS-EEG system was synchronised with movement capture system to record SM1 activation while moving. The circular steering task performance was significantly lower for the older group. The rate of increase in hemodynamic response was longer in the older group with no difference on the amplitude of fNIRS signal for the two tasks. The EEG results showed aging related reduction of the alpha-beta rhythms synchronisation but no desynchronisation modification. In conclusion, this study uncovers the age-related changes in brain electrical and hemodynamic response patterns in the bilateral sensorimotor network during two functional proximal UL movements using two complementary neuroimaging methods. This opens up the possibility to utilise combined fNIRS-EEG for monitoring the movement-related neuroplasticity in clinical practice.

K-means Clustering Machine Learning Approach Reveals Groups of Homogeneous Individuals with Unique Brain Activation, Task, and Performance Dynamics using fNIRS.

Wearable functional near-infrared spectroscopy (fNIRS) for measuring brain function, in terms of hemodynamic responses, is pervading our everyday life and holds the potential to reliably classify cognitive load in a naturalistic environment. However, human's brain hemodynamic response, behavior, and cognitive and task performance vary, even within and across homogeneous individuals (with same training and skill sets), which limits the reliability of any predictive model for human. In the context of high-stakes tasks, such as in military and first-responder operations, the real-time monitoring of cognitive functions and relating it to the ongoing task, performance outcomes, and behavioral dynamics of the personnel and teams is invaluable. In this work, a portable wearable fNIRS system (WearLight) developed by the author was upgraded, and an experimental protocol was designed to image the prefrontal cortex (PFC) area of the brain of 25 healthy homogeneous participants in a naturalistic environment while participants performed n-back working memory (WM) tasks with four difficulty levels. The raw fNIRS signals were processed using a signal processing pipeline to derive the brain's hemodynamic responses. An unsupervised k-means machine learning (ML) clustering approach, utilizing the task-induced hemodynamic responses as input variables, suggested three unique participant groups. Task performance in terms of % correct, % missing, reaction time, inverse efficiency score (IES), and a proposed IES was extensively evaluated for each participant and the three groups. Results showed that, on average, brain hemodynamic response increased, whereas task performance degraded, with increasing WM load. However, the regression and correlation analysis of WM task, performance, and the brain's hemodynamic responses (TPH) revealedinteresting hidden characteristics and the variation in the TPH relationship between groups. The proposed IES also served as a better scoring method that had distinct score ranges for different load levels as opposed to the overlapping scores of the traditional IES method. Results showed that the k-means clustering has the potential to find groups of individuals in an unsupervised manner using the brain's hemodynamic responses and to study the underlying relationship between the TPH in groups. Using the method presented in this paper,real-time monitoring of cognitive and task performance of soldiers, and preferentially forming small units to accomplish tasks based on the insights and goals may be helpful. The results showed that WearLight can image PFC, and this study also suggests future directions for the multi-modal body sensor network (BSN) combining advanced ML algorithms for real-time state classification, cognitive and physical performance prediction, and the mitigation of performance degradation in the high-stakes environment.

Brain Tissue Oxygen and BOLD fMRI Under Different Levels of Neuronal Activity.

Localized increases in neuronal activity are supported by the hemodynamic response, which delivers oxygen to the brain tissue to support synaptic functions, action potentials and other neuronal processes. However, it remains unknown if changes in baseline neuronal activity, which are expected to reflect neuronal metabolic demand, alter the relationship between the local hemodynamic and oxygen behaviour. In order to better characterize this system, we examine here the relationship between brain tissue oxygen (PO2) and hemodynamic responses (BOLD functional MRI) under different levels of neuronal activity. By comparing the stimulus-evoked responses during different levels of baseline neuronal activity, the awake state vs isoflurane anesthesia, we were able to measure how a known change in neuronal demand affected tissue PO2 as well as the hemodynamic response to stimulation. We observed a high correlation between stimulus-evoked PO2 and BOLD responses in the awake state. Moreover, we found that the evoked PO2 and BOLD responses were still present despite the elevated tissue oxygen baseline and decreased baseline of neuronal activity under low concentration isoflurane,and that the magnitudes of these responses decreased by similar proportions but the relationship between these signals was distorted. Our findings point to distortion of the BOLD-PO2 relationship due to anesthesia. The feedback mechanism to adjust the level of brain tissue oxygen, as well as the correlation between BOLD and PO2 responses, are impaired even by a small dose of anesthetics.

2.94 Changes in Brain Hemodynamic Responses in Adolescents After Smartphone Use Restriction: Focusing on Frontal Lobe Activity Changes Using Functional Near-Infrared Spectroscopy

As the smartphone holding rate has exceeded 95% among South Korean teenagers, problematic smartphone use and its profound impact on brain development have come into increasing focus. While previous research has mainly focused on brain changes following heavy smartphone use in adolescents, the goal of this study is to investigate brain changes in adolescents after reducing smartphone use for 10 weeks and to identify its objective benefits.

Applying functional near-infrared spectroscopy and eye-tracking in a naturalistic educational environment to investigate physiological aspects that underlie the cognitive effort of children during mental rotation tests.

Spatial cognition is related to academic achievement in science, technology, engineering, and mathematics (STEM) domains. Neuroimaging studies suggest that brain regions’ activation might be related to the general cognitive effort while solving mental rotation tasks (MRT). In this study, we evaluate the mental effort of children performing MRT tasks by measuring brain activation and pupil dilation. We use functional near-infrared spectroscopy (fNIRS) concurrently to collect brain hemodynamic responses from children’s prefrontal cortex (PFC) and an Eye-tracking system to measure pupil dilation during MRT. Thirty-two healthy students aged 9–11 participated in this experiment. Behavioral measurements such as task performance on geometry problem-solving tests and MRT scores were also collected. The results were significant positive correlations between the children’s MRT and geometry problem-solving test scores. There are also significant positive correlations between dorsolateral PFC (dlPFC) hemodynamic signals and visuospatial task performances (MRT and geometry problem-solving scores). Moreover, we found significant activation in the amplitude of deoxy-Hb variation on the dlPFC and that pupil diameter increased during the MRT, suggesting that both physiological responses are related to mental effort processes during the visuospatial task. Our findings indicate that children with more mental effort under the task performed better. The multimodal approach to monitoring students’ mental effort can be of great interest in providing objective feedback on cognitive resource conditions and advancing our comprehension of the neural mechanisms that underlie cognitive effort. Hence, the ability to detect two distinct mental states of rest or activation of children during the MRT could eventually lead to an application for investigating the visuospatial skills of young students using naturalistic educational paradigms.

Comparison of Hemodynamic Brain Responses Between Big Wave Surfers and Non-big Wave Surfers During Affective Image Presentation.

BackgroundBig wave surfers are extreme sports athletes who expose themselves to life-threatening risk when training and competing. Little is known about how and why extreme sports athletes choose to participate in their chosen sports. This exploratory study investigated potential neurophysiological and psychometric differences between big and non-big wave surfers.MethodsThirteen big wave surfers (BWS) and 10 non-big wave surfers (CON) viewed a series of images from the International Affective Picture System (IAPS) while undergoing brain functional magnetic resonance imaging (fMRI). The Fear Schedule Survey-III, Arnett Inventory of Sensation Seeking, Discrete Emotions Questionnaire, and Positive and Negative Affect Schedule were also completed.ResultsThe BWS group demonstrated higher blood-oxygen level-dependent (BOLD) signal change in the insula, visual cortex, and periaqueductal gray, whereas the CON group displayed increased hypothalamus activation in response to high amplitude negative-valence (HAN) image presentation. Psychophysiological interaction (PPI) analyses found CON showed significant interactions between frontal and temporal cortical regions as well as between the hypothalamus and the insula, frontal, and temporal cortices during HAN image presentation that were not seen in BWS. No differences between groups were found in their responses to the questionnaires.ConclusionOur findings demonstrate significant differences in brain activation between BWS and CON in response to the presentation of HAN IAPS images, despite no significant differences in scores on psychometric questionnaires.

Experimental Study on Panic during Simulated Fire Evacuation Using Psycho- and Physiological Metrics.

Under circumstances of fire, panic usually brings uncertainty and unpredictability to evacuation. Therefore, a deep understanding of panic is desired. This study aims to dig into the underlying mechanism of fire evacuation panic by measuring and analysing psycho- and physiological indicators. In the experiment, participants watched a simulated train station within which three sets of stimuli were triggered separately. Eye movement and brain haemodynamic responses were collected during the watch, while questionnaires and interviews of emotions were conducted after. The analysed physiological indicators include the amplitude of pupil dilation, the time ratios of fixation and saccade, the binned entropy of gaze location, and the brain activation coefficients. The results of this research indicate that fire evacuation panic can be broken down into two elements. (1) Unawareness of situation: less knowledge of the situation leads to a higher level of panic; (2) Intensity of visual stimulation: the panic level is escalated with increased severity of fire that is perceived.