Functional Near-infrared Spectroscopy Data Research Articles

VR rehabilitation system evaluator: A fNIRS-based and LLM-enabled evaluation paradigm for Mild Cognitive Impairment

Virtual Reality (VR) has significant potential for Mild Cognitive Impairment (MCI) rehabilitation by offering dynamic and engaging tasks designed to stimulate various cognitive domains. However, how efficiently evaluating the VR tasks is always challenging. The current effectiveness evaluation methods for task evaluation and optimisation typically rely on post-training metrics like game performance or subjective questionnaires, which cannot directly reflect the comprehensiveness and intensity of cognitive stimulation. To bridge these gaps, we propose a novel approach integrating functional near-infrared spectroscopy (fNIRS) data and a Large Language Model (LLM) for VR rehabilitation task evaluation and optimisation. Firstly, we leverage fundamental cognitive theories to propose a systematic evaluation paradigm for assessing the scope of the cognitive domains stimulated by VR tasks. Secondly, we propose fNIRS-derived graph parameters to objectively evaluate the cognitive stimulation with high-time resolution. Finally, we develop a prompt-generating strategy to facilitate Large Language Model (LLM)-based analysis, which transforms fNIRS-derived metrics combined with the scope of stimulated cognitive domains into easy-to-understand evaluation reports and actionable recommendations for task optimisation. We demonstrate this approach with two VR rehabilitation tasks. Several experts evaluated the LLM-based task evaluation results and task optimisation recommendation and agreed that the LLM-generated results are meaningful and applicable. This approach offers a rapid, objective method to evaluate VR task effectiveness and improves their design, marking a significant step in developing more effective MCI interventions.

Resting-State Functional Connectivity Predicts Cochlear-Implant Speech Outcomes.

Cochlear implants (CIs) have revolutionized hearing restoration for individuals with severe or profound hearing loss. However, a substantial and unexplained variability persists in CI outcomes, even when considering subject-specific factors such as age and the duration of deafness. In a pioneering study, we use resting-state functional near-infrared spectroscopy to predict speech-understanding outcomes before and after CI implantation. Our hypothesis centers on resting-state functional connectivity (FC) reflecting brain plasticity post-hearing loss and implantation, specifically targeting the average clustering coefficient in resting FC networks to capture variation among CI users. Twenty-three CI candidates participated in this study. Resting-state functional near-infrared spectroscopy data were collected preimplantation and at 1 month, 3 months, and 1 year postimplantation. Speech understanding performance was assessed using consonant-nucleus-consonant words in quiet and Bamford-Kowal-Bench sentences in noise 1-year postimplantation. Resting-state FC networks were constructed using regularized partial correlation, and the average clustering coefficient was measured in the signed weighted networks as a predictive measure for implantation outcomes. Our findings demonstrate a significant correlation between the average clustering coefficient in resting-state functional networks and speech understanding outcomes, both pre- and postimplantation. This approach uses an easily deployable resting-state functional brain imaging metric to predict speech-understanding outcomes in implant recipients. The results indicate that the average clustering coefficient, both pre- and postimplantation, correlates with speech understanding outcomes.

Adjusting effective multiplicity ( ) for family-wise error rate in functional near-infrared spectroscopy data with a small sample size.

The advancement of multichannel functional near-infrared spectroscopy (fNIRS) has enabled measurements across a wide range of brain regions. This increase in multiplicity necessitates the control of family-wise errors in statistical hypothesis testing. To address this issue, the effective multiplicity ( ) method designed for channel-wise analysis, which considers the correlation between fNIRS channels, was developed. However, this method loses reliability when the sample size is smaller than the number of channels, leading to a rank deficiency in the eigenvalues of the correlation matrix and hindering the accuracy of calculations. We aimed to reevaluate the effectiveness of the method for fNIRS data with a small sample size. In experiment 1, we used resampling simulations to explore the relationship between sample size and values. Based on these results, experiment 2 employed a typical exponential model to investigate whether valid could be predicted from a small sample size. Experiment 1 revealed that the values were underestimated when the sample size was smaller than the number of channels. However, an exponential pattern was observed. Subsequently, in experiment 2, we found that valid values can be derived from sample sizes of 30 to 40 in datasets with 44 and 52 channels using a typical exponential model. The findings from these two experiments indicate the potential for the effective application of correction in fNIRS studies with sample sizes smaller than the number of channels.

Connecting the dots: Sensory cueing enhances functional connectivity between pre-motor and supplementary motor areas in Parkinson's disease.

People with Parkinson's disease often exhibit improvements in motor tasks when exposed to external sensory cues. While the effects of different types of sensory cues on motor functions in Parkinson's disease have been widely studied, the underlying neural mechanism of these effects and the potential of sensory cues to alter the motor cortical activity patterns and functional connectivity of cortical motor areas are still unclear. This study aims to compare changes in oxygenated haemoglobin, deoxygenated haemoglobin and correlations among different cortical regions of interest during wrist movement under different external stimulus conditions between people with Parkinson's disease and controls. Ten Parkinson's disease patients and 10 age- and sex-matched neurologically healthy individuals participated, performing repetitive wrist flexion and extension tasks under auditory and visual cues. Changes in oxygenated and deoxygenated haemoglobin in motor areas were measured using functional near-infrared spectroscopy, along with electromyograms from wrist muscles and wrist movement kinematics. The functional near-infrared spectroscopy data revealed significantly higher neural activity changes in the Parkinson's disease group's pre-motor area compared to controls (p = 0.006), and functional connectivity between the supplementary motor area and pre-motor area was also significantly higher in the Parkinson's disease group when external sensory cues were present (p = 0.016). These results indicate that external sensory cues' beneficial effects on motor tasks are linked to changes in the functional connectivity between motor areas responsible for planning and preparation of movements.

Cortical activation for adolescent-onset minor depression and major depressive disorder: an fNIRS study

BackgroundWhile depression is increasing worldwide, some patients are diagnosed as having Major Depressive Disorder (MDD), but others are diagnosed with minor depression, however, the potential neuro mechanism is unknown.MethodsSixty-two patients with minor depression, 44 adolescents with MDD and 54 healthy adolescents participated in this study. Functional near-infrared spectroscopy (fNIRS), both HAMD and HAMA data were collected from all of the participants.ResultsThe result indicates the pervasively decreased activation of BA, 11, 21, 45 and 46 were observed in the MDD group and reduced activation of BA 45 was observed in the minor depression group. However, cortical activation was not observed between the minor depression or MDD groups. Cortical activation was also not correlated with the depressive/anxious score in the minor and MDD groups separately.ConclusionsCortical activation was pervasively decreased in the MDD group and slightly reduced in the minor depression group, which may be a potential neural mechanism. As reduced cortical activation in minor depression, interventions in the early stages of minor depression may help slow or even modify the development of the illness.

Efficacy and executive function of solution-focused brief therapy on adolescent depression.

To investigate the efficacy and impact on executive function of Solution-Focused Brief Therapy (SFBT) in treating Major Depressive Disorder (MDD) in adolescents. A total of 129 adolescents diagnosed with MDD were enrolled in the study. Out of these, 28 adolescents were assigned to the SFBT group, while 25 were part of the Active Control group (AC group), receiving psychodynamic psychotherapy. Executive function, depressive and anxiety symptoms were assessed at baseline, at the time of the third intervention, the sixth intervention, and the 10th intervention. After the third intervention, the scores of the Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7) of the participants in the SFBT group decreased significantly, which had the cumulative effect at the 6th and 10th interventions. The verbal fluency task (VFT) performances of the SFBT group participants yielded significantly higher scores after the third intervention and remained increasing at the 6th and 10th interventions. The AC group steadily decreased after the intervention. Analysis of functional near-infrared spectroscopy (fNIRS) data revealed a progressive and significant increase in the average oxyhemoglobin (oxy-Hb) levels in the dorsolateral prefrontal cortex (DLPFC) in the SFBT group compared to the AC group after the 10th intervention. SFBT might improve depressive and anxiety symptoms as well as executive function of adolescent depression. https://www.chictr.org.cn, identifier ChiCTR2300067909.

Abnormal prefrontal cortical activation during the GO/NOGO and verbal fluency tasks in adult patients with comorbid generalized anxiety disorder and attention-deficit/hyperactivity disorder: An fNIRS study

Generalized anxiety disorder (GAD) and adult attention-deficit/hyperactivity disorder (ADHD) are commonly reported comorbidities. Adult GAD patients with comorbid ADHD are often underdiagnosed and undertreated. To explore the clinical value of functional near-infrared spectroscopy (fNIRS) data for assisting in the accurate diagnosis of ADHD in individuals with GAD, haemoglobin (HbO) concentration changes in the prefrontal cortex (PFC) were detected via fNIRS in 49 patients with both GAD and ADHD, 46 patients with GAD, and 34 healthy controls (HCs) during a verbal fluency task (VFT) and a GO/NOGO task. The correlations between PFC fNIRS data and the severity of inattention and hyperactivity symptoms assessed using the adult ADHD Self-Report Scale (ASRS) were analyzed. Our results showed that, during the GO/NOGO task, channels in the left dorsolateral PFC (channels 28 and 29) were hyperactivated, while channels in the medial PFC (channels 36, 37, and 47) were hypoactivated in participants with ADHD and GAD compared with those with GAD alone. During the VFT, compared with the HC group, both the ADHD + GAD group and the GAD group exhibited significantly decreased HbO activation in the medial PFC (channels 37, 38, and 48) and in the left ventrolateral PFC (channel 39); moreover, no difference was found between the ADHD + GAD group and the GAD group. Activation in the left dorsolateral PFC (channels 28 and 29) during the GO/NOGO task showed a significant positive correlation with ASRS-inattention scores. Our results indicated that fNIRS data collected during the GO/NOGO task may help to distinguish patients with comorbid GAD and ADHD from those with GAD alone.

Distinct Time-Resolved Brain-Wide Coactivations in Oxygenated and Deoxygenated Hemoglobin.

Human resting-state networks (RSNs) estimated from oxygenated (HbO) and deoxygenated hemoglobin (HbR) data exhibit strong similarities, while task-based studies show different dynamics in HbR and HbO responses. Such a discrepancy might be explained due to time-averaged estimations of RSNs. Our study investigated differences between HbO and HbR on time-resolved brain-wide coactivation patterns (CAPs). Diffuse optical tomography was reconstructed from resting-state whole-head functional near-infrared spectroscopy data of HbR and HbO in individual healthy participants. Time-averaged RSNs were obtained using the group-level independent component analysis. Time-resolved CAPs were estimated using a clustering approach on the time courses of all obtained RSNs. Characteristics of the RSNs and CAPs from HbR and HbO were compared. Spatial patterns of HbR and HbO RSNs exhibited significant similarities. Meanwhile, HbR CAPs revealed much more organized spatial and dynamic characteristics than HbO CAPs. The entire set of HbR CAPs suggests a superstructure resulted from brain-wide neuronal dynamics, which is less evident in the set of HbO CAPs. These differences between HbO and HbR CAPs were consistently replicated in individual session data. Our results suggest that human resting brain-wide neuronal activations are preserved better in time-resolved brain-wide patterns, i.e., CAPs, from HbR than those from HbO, while such a difference is lost between time-averaged HbR and HbO RSNs. Our results reveal, for the first time, HbR concentration fluctuations are more directly coupled with resting dynamics of brain-wide neuronal activations in human brains.

Longitudinal assessment of the effects of passive training on stroke rehabilitation using fNIRS technology

For patients with severe conditions such as stroke, passive exercise is commonly used in the early stages of their rehabilitation training. This study aimed to assess the effect of passive training on stroke rehabilitation and track brain function changes and the patient's rehabilitation progress, by employing a robot glove to perform a passive flexion-extension task. Specifically, functional near-infrared spectroscopy data from 26 patients under resting and right-hand passive interactions (task state) were recorded before and after a one-week interval, respectively, to explore the variations in the brain network of the patients. The results showed a stronger functional connectivity in both states of the two experiments in the left and right homotopic brain regions (p < 0.01). The effective connectivity network between brain regions maintained a consistent trend during the same test. Changes in functional connectivity and effective connectivity networks may represent the advantages of motor rehabilitation tasks and patient treatment duration, providing a perspective for an easy understanding of the mechanisms of stroke-related brain changes. This study demonstrates the feasibility of passive training strategies in the field of intelligent rehabilitation by applying neuroscientific diagnostic methods based on physiological data to the field of human-computer interaction.

B - 66 Functional Near-Infrared Spectroscopy as a Sensitive Marker of Neuropsychological Deficits in Executive Functioning Tasks in Young Adults with a History of Child Abuse.

Research has shown the utility of imaging measures of neural activity in identifying deficits in cognitive functioning in individuals with a history of child abuse. The purpose of this study was to measure differences that may exist between individuals who reported physical, emotional, or sexual abuse as children vs. those who did not using Functional Near Infrared Spectroscopy (fNIRS) during the completion of executive function tasks. The present study recruited 84 students from the University of North Dakota. The participants were administered several prescreening measures, including a measures of child abuse. Based on responses, participants were assigned to either a "no child abuse" or "child abuse" group. Next, the Wisconsin Card Sorting Task, the Operation Span Task, and the Connors Continuous Performance Task were administered while functional near-infrared spectroscopy (fNIRS) data was collected. The results showed a significantly higher rate and number of errors of commission on the Conners CPT in the child abuse group compared to the control group (F(1,57) = 6.604, p = 0.013 partial eta2 = 0.104). Neurological data revealed a statistically significant effect of group (F(1, 69) = 2.934, p = 0.043) across all executive functioning tasks. Additional tests showed these differences exist only during measures of decision-making (t(71) = 2.063, p = 0.043). The results suggest that the child abuse group may show subtle neurological deficits that persist into adulthood that may not manifest on traditional measures of cognitive function. These findings have implications for the development of remediation and treatment strategies in this population.

Prefrontal dysfunction in post-COVID-19 hyposmia: an EEG/fNIRS study.

Subtle cognitive dysfunction and mental fatigue are frequent after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, characterizing the so-called long COVID-19 syndrome. This study aimed to correlate cognitive, neurophysiological, and olfactory function in a group of subjects who experienced acute SARS-CoV-2 infection with persistent hyposmia at least 12 weeks before the observation. For each participant (32 post-COVID-19 patients and 16 controls), electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) data were acquired using an integrated EEG-fNIRS system during the execution of a P300 odd-ball task and a Stroop test. The Sniffin' Sticks test was conducted to assess subjects' olfactory performance. The Montreal Cognitive Assessment (MoCA) and the Frontal Assessment Battery (FAB) were also administered. The post-COVID-19 group consisted of 32 individuals (20 women and 12 men) with an average education level of 12.9 ± 3.12 years, while the control group consisted of 16 individuals (10 women and 6 men) with an average education level of 14.9 ± 3.2 years. There were no significant differences in gender (X2 = 0, p = 1) or age between the two groups (age 44.81 ± 13.9 vs. 36.62 ± 11.4, p = 0.058). We identified a lower concentration of oxyhemoglobin (p < 0.05) at the prefrontal cortical level in post-COVID-19 subjects during the execution of the Stroop task, as well as a reduction in the amplitude of the P3a response. Moreover, we found that post-COVID-19 subjects performed worst at the MoCA screening test (p = 0.001), Sniffin's Sticks test (p < 0.001), and Stroop task response latency test (p < 0.001). This study showed that post-COVID-19 patients with persistent hyposmia present mild deficits in prefrontal function, even 4 months after the end of the infection. These deficits, although subtle, could have long-term implications for quality of life and cognitive wellbeing. It is essential to continue monitoring and evaluating these patients to better understand the extent and duration of cognitive impairments associated with long COVID-19.

Regional activity and effective connectivity within the frontoparietal network during precision walking with visual cueing: an fNIRS study.

Precision walking (PW) incorporates precise step adjustments into regular walking patterns to navigate challenging surroundings. However, the brain processes involved in PW control, which encompass cortical regions and interregional interactions, are not fully understood. This study aimed to investigate the changes in regional activity and effective connectivity within the frontoparietal network associated with PW. Functional near-infrared spectroscopy data were recorded from adult subjects during treadmill walking tasks, including normal walking (NOR) and PW with visual cues, wherein the intercue distance was either fixed (FIX) or randomly varied (VAR) across steps. The superior parietal lobule (SPL), dorsal premotor area (PMd), supplementary motor area (SMA), and dorsolateral prefrontal cortex (dlPFC) were specifically targeted. The results revealed higher activities in SMA and left PMd, as well as left-to-right SPL connectivity, in VAR than in FIX. Activities in SMA and right dlPFC, along with dlPFC-to-SPL connectivity, were higher in VAR than in NOR. Overall, these findings provide insights into the roles of different brain regions and connectivity patterns within the frontoparietal network in facilitating gait control during PW, providing a useful baseline for further investigations into brain networks involved in locomotion.

Classification of fNIRS signals from adolescents with MDD in suicide high- and low-risk groups using machine learning

Prefrontal cortex activation is attenuated during cognitive tasks in patients with suicidal ideation or major depressive disorder (MDD). However, the apparent relationship between patients with MDD, especially suicide high-risk (SHR) adolescents, and the characteristics of their hemodynamic responses has not yet been elucidated. To investigate this relationship, we recruited 30 patients with MDD aged 13−19. Functional near-infrared spectroscopy (fNIRS) data were collected for all patients during a Stroop test. Through a ten-time iterative leave-one-out cross-validation via 1000 iterative random search-based feature selections, we achieved a generalized classification accuracy of 70.3±5.0 % (from min. 63.3 % to max. 76.7 %). From the results of random search-based feature selection, Ch08oxy and Ch09deoxy were identified as the two most relevant fNIRS channels. This finding implies that these fNIRS channels can be used as neurological biomarkers to distinguish SHR adolescents with MDD from suicide low-risk (SLR) adolescents. In addition, we determined the oxy-Hb channels of the SHR group, except for Ch01oxy, Ch02oxy, Ch11oxy, and Ch14oxy, were hyperactivated compared to the SLR group.

Partner's emotions are associated with preschoolers' prefrontal activation under joint attention: An fNIRS evidence.

Emotions and joint attention are highly associated and mutually influenced during preschool, the critical period for early emotional and cognitive development. However, few studies have explored the neuropsychological mechanism of joint attention with preschoolers and their partners under different emotions. This study has examined the prefrontal activation under a comprehensive emotional joint attention task in 45 preschoolers (25 boys, Mage = 58 ± 9.02 months) to compare the different influences of partners' positive, neutral, and negative emotions. Analysis of the functional near-infrared spectroscopy data indicated that the participants' prefrontal activation triggered by joint attention in positive and negative emotions was significantly higher than in neutral emotions. Moreover, their brain synchronization intensity was significantly higher in positive emotions of joint attention than in negative emotions. These findings advance our understanding of the neural mechanism of early childhood emotional processing under joint attention and provide a neural perspective to explain the effects of different emotions on preschoolers' social cognition.

A calculus of probability or belief? Neural underpinnings of social decision-making in a card game

For decades, the prefrontal cortex (PFC) has been the focus of social neuroscience research, specifically regarding its role in competitive social decision-making. However, the distinct contributions of PFC subregions when making strategic decisions involving multiple types of information (social, non-social, and mixed information) remain unclear. This study investigates decision-making strategies (pure probability calculation vs. mentalizing) and their neural representations using functional near-infrared spectroscopy (fNIRS) data collected during a two-person card game. We observed individual differences in information processing strategy, indicating that some participants relied more on probability than others. Overall, the use of pure probability decreased over time in favor of other types of information (e.g., mixed information), with this effect being more pronounced within-round trials than across rounds. In the brain, (1) the lateral PFC activates when decisions are driven by probability calculations; (2) the right lateral PFC responds to trial difficulty; and (3) the anterior medial PFC is engaged when decision-making involves mentalizing. Furthermore, neural synchrony, which reflects the real-time interplay between individuals' cognitive processes, did not consistently contribute to correct decisions and fluctuated throughout the experiment, suggesting a hierarchical mentalizing mechanism at work.

Identifying ADHD boys by very-low frequency prefrontal fNIRS fluctuations during a rhythmic mental arithmetic task

Objective. Computer-aided diagnosis of attention-deficit/hyperactivity disorder (ADHD) aims to provide useful adjunctive indicators to support more accurate and cost-effective clinical decisions. Deep- and machine-learning (ML) techniques are increasingly used to identify neuroimaging-based features for objective assessment of ADHD. Despite promising results in diagnostic prediction, substantial barriers still hamper the translation of the research into daily clinic. Few studies have focused on functional near-infrared spectroscopy (fNIRS) data to discriminate ADHD condition at the individual level. This work aims to develop an fNIRS-based methodological approach for effective identification of ADHD boys via technically feasible and explainable methods. Approach. fNIRS signals recorded from superficial and deep tissue layers of the forehead were collected from 15 clinically referred ADHD boys (average age 11.9 years) and 15 non-ADHD controls during the execution of a rhythmic mental arithmetic task. Synchronization measures in the time-frequency plane were computed to find frequency-specific oscillatory patterns maximally representative of the ADHD or control group. Time series distance-based features were fed into four popular ML linear models (support vector machine, logistic regression (LR), discriminant analysis and naïve Bayes) for binary classification. A ‘sequential forward floating selection’ wrapper algorithm was adapted to pick out the most discriminative features. Classifiers performance was evaluated through five-fold and leave-one-out cross-validation (CV) and statistical significance by non-parametric resampling procedures. Main results. LR and linear discriminant analysis achieved accuracy, sensitivity and specificity scores of near 100% (p <.001) for both CV schemes when trained with only three key wrapper-selected features, arising from surface and deep oscillatory components of very low frequency. Significance. We provide preliminary evidence that very-low frequency fNIRS fluctuations induced/modulated by a rhythmic mental task accurately differentiate ADHD boys from non-ADHD controls, outperforming other similar studies. The proposed approach holds promise for finding functional biomarkers reliable and interpretable enough to inform clinical practice.

Between-sessions test-retest reliability of prefrontal cortical activity during usual walking in patients with Parkinson’s Disease: A fNIRS study

BackgroundExamining between-sessions test-retest reliability of functional near-infrared spectroscopy (fNIRS) data is crucial to better interpret rehabilitation-related changes in the hemodynamic response. Research questionThis study investigated test-retest reliability of prefrontal activity during usual walking in 14 patients with Parkinson’s Disease with a fixed retest intervals of five weeks. MethodsFourteen patients performed usual walking in two sessions (T0 and T1). Relative changes in cortical activity (oxy and deoxyhemoglobin: ∆HbO2 and ∆HbR, respectively) in the dorsolateral prefrontal cortex (DLPFC) using fNIRS system and gait performance were measured. Test-retest reliability of mean ∆HbO2 for the total DLPFC and for each hemisphere were measured using paired t-test, intraclass correlation coefficient (ICC), and Bland-Altman plots with 95% agreement. Pearson correlations between cortical activity and gait performance were also performed. ResultsModerate reliability was found for ∆HbO2 in the total DLPFC (mean difference of ∆HbO2 between T1 and T0 = −0.005 µmol, p = 0.93; ICC average = 0.72). However, test-retest reliability of ∆HbO2 was poorer when considering each hemisphere. SignificanceFindings suggest that fNIRS may be used as a reliable tool for rehabilitation studies in patients with PD. Test-retest reliability of fNIRS data between 2 sessions during walking tasks should be interpreted respectively of gait performance.

Why people engage in corrupt collaboration: an observation at the multi-brain level.

Recent studies suggest that corrupt collaboration (i.e. acquiring private benefits with joint immoral acts) represents a dilemma between the honesty and reciprocity norms. In this study, we asked pairs of participants (labeled as A and B) to individually toss a coin and report their outcomes; their collective benefit could be maximized by dishonestly reporting (a corrupt behavior). As expected, the likelihood of corrupt behavior was high; this probability was negatively correlated with player A's moral judgment ability but positively correlated with player B's empathic concern (EC). Functional near-infrared spectroscopy data revealed that the brain-to-brain synchronization in the right dorsolateral prefrontal cortex was associated with fewer corrupt behaviors, and that it mediated the relationship between player A's moral judgment ability and corrupt collaboration. Meanwhile, the right temporal-parietal junction synchronization was associated with more corrupt behaviors, and that it mediated the relationship between player B's EC and corrupt collaboration. The roles of these 2 regions are interpreted according to the influence of the honesty and reciprocity norms on corrupt collaboration. In our opinion, these findings provide insight into the underlying mechanisms and modulating factors of corrupt collaboration.

Disturbed functional connectivity and topological properties of the frontal lobe in minimally conscious state based on resting-state fNIRS.

Patients in minimally conscious state (MCS) exist measurable evidence of consciousness. The frontal lobe is a crucial part of the brain that encodes abstract information and is closely related to the conscious state. We hypothesized that the disturbance of the frontal functional network exists in MCS patients. We collected the resting-state functional near-infrared spectroscopy (fNIRS) data of fifteen MCS patients and sixteen age- and gender-matched healthy controls (HC). The Coma Recovery Scale-Revised (CRS-R) scale of MCS patients was also composed. The topology of the frontal functional network was analyzed in two groups. Compared with HC, the MCS patients showed widely disrupted functional connectivity in the frontal lobe, especially in the frontopolar area and right dorsolateral prefrontal cortex. Moreover, the MCS patients displayed lower clustering coefficient, global efficiency, local efficiency, and higher characteristic path length. In addition, the nodal clustering coefficient and nodal local efficiency in the left frontopolar area and right dorsolateral prefrontal cortex were significantly reduced in MCS patients. Furthermore, the nodal clustering coefficient and nodal local efficiency in the right dorsolateral prefrontal cortex were positively correlated to auditory subscale scores. This study reveals that MCS patients' frontal functional network is synergistically dysfunctional. And the balance between information separation and integration in the frontal lobe is broken, especially the local information transmission in the prefrontal cortex. These findings help us to understand the pathological mechanism of MCS patients better.

A neuroergonomic approach to assessing motor performance in stroke patients using fNIRS and behavioral data

Stroke is characterized by high morbidity and disability, and proposing effective methods for assessing and designing rehabilitation products is an attractive topic in current research. In this study, a hand function rehabilitation aid was developed for stroke patients. Ten stroke patients and 20 healthy older people as a control group were recruited to perform a 600 s task after a 600 s resting by gripping a stick while clicking on a flashing light in an electronic insert in sequence according to a pattern. The functional near-infrared spectroscopy (fNIRS) and behavioral data were collected during their rehabilitation training. Brain function was analyzed using three indicators, namely brain area activation, functional connectivity and effective connectivity, while behavioral performance was analyzed using ten indicators, such as velocity and acceleration, and correlations were made between both. Followed by proposing a quantitative assessment method based on the fusion of multiple data sources. The results showed that the developed rehabilitation tool could effectively stimulate the patient's brain and help recover their cognitive and behavioral capacities. The scientific validity of the proposed assessment approach was further confirmed by contrasting the data results of the stroke group with those of the healthy elderly group. This study has integrated brain function and behavioral data, providing a practical quantitative evaluation method of product ergonomics and data-driven product design concepts for stroke patients.