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Introduction: Removing motion artifacts (MAs) from functional near-infrared spectroscopy (fNIRS) signals is crucial in practical applications, but a standard procedure is not available yet. Artificial neural networks have found applications in diverse domains, such as voice and image processing, while their utility in signal processing remains limited. Method: In this work, we introduce an innovative neural network-based approach for online fNIRS signals processing, tailored to individual subjects and requiring minimal prior experimental data. Specifically, this approach employs one-dimensional convolutional neural networks with a penalty network (1DCNNwP), incorporating a moving window and an input data augmentation procedure. In the training process, the neural network is fed with simulated data derived from the balloon model for simulation validation and semi-simulated data for experimental validation, respectively. Results: Visual validation underscores 1DCNNwP's capacity to effectively suppress MAs. Quantitative analysis reveals a remarkable improvement in signal-to-noise ratio by over 11.08 dB, surpassing the existing methods, including the spline-interpolation, wavelet-based, temporal derivative distribution repair with a 1 s moving window, and spline Savitzky-Goaly methods. Contrast-to-noise ratio (CNR) analysis further demonstrated 1DCNNwP's ability to restore or enhance CNRs for motionless signals. In the experiments of eight subjects, our method significantly outperformed the other approaches (except offline TDDR, t < -3.82, p < 0.01). With an average signal processing time of 0.53 ms per sample, 1DCNNwP exhibited strong potential for real-time fNIRS data processing. Discussion: This novel univariate approach for fNIRS signal processing presents a promising avenue that requires minimal prior experimental data and adapts seamlessly to varying experimental paradigms.
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Background and objectives: This case report investigates the application of intermittent Theta-Burst Stimulation (iTBS) in aphasia rehabilitation following a right hemisphere stroke. Case presentation: A 52-year-old Chinese male with Broca's aphasia post-stroke was treated with iTBS. His progress was evaluated using Functional Near-Infrared Spectroscopy (fNIRS) and behavioral assessments. Significant language function improvement was noted, with fNIRS showing increased activation in right hemisphere language-related cortical areas and altered functional connectivity patterns. Conclusion: The findings indicate that iTBS is effective in facilitating language recovery in right hemisphere stroke-induced aphasia, highlighting the importance of personalized neurorehabilitation strategies. Despite focusing on a single case, the study contributes to understanding neural plasticity mechanisms in right hemisphere stroke-induced aphasia.
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We used 34-channel functional near infrared spectroscopy to investigate and compare changes in oxyhemoglobin concentration of brain networks in bilateral prefrontal cortex, sensorimotor cortex, and occipital lobe of 22 right-handed healthy adults during executive right-handed grasp (motor execution task) and imagined right-handed grasp (motor imagery task). Then calculated lateral index and functional contribution degree, and measured functional connectivity strength between the regions of interest. In the motor executive block task, there was a significant increase in oxyhemoglobin concentration in regions of interest except for right occipital lobe (P<0.05), while in the motor imagery task, all left regions of interest's oxyhemoglobin concentration increased significantly (P<0.05). Except the prefrontal cortex in motor executive task, the left side of the brain was dominant. Left sensorimotor cortex played a major role in these two tasks, followed by right sensorimotor cortex. Among all functional contribution degree, left sensorimotor cortex, right sensorimotor cortex and left occipital lobe ranked top three during these tasks. In continuous acquisition tasks, functional connectivity on during motor imagery task was stronger than that during motor executive task. Brain functions during two tasks of right-hand grasping movement were partially consistent. However, the excitability of brain during motor imagery was lower, and it was more dependent on the participation of left prefrontal cortex, and its synchronous activity of the whole brain was stronger. The trend of functional contribution degree was basically consistent with oxyhemoglobin concentration and lateral index, and can be used as a novel index to evaluate brain function. [ChiCTR2200063792 (2022-09-16)].
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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.
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Executive Function , Learning , Spectroscopy, Near-Infrared , Humans , Executive Function/physiology , Male , Female , Spectroscopy, Near-Infrared/methods , Child , Learning/physiology , Brain/physiology , Brain/diagnostic imaging , Reading , Mathematics , Stroop Test , Functional Laterality/physiology , ChinaABSTRACT
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.
Subject(s)
COVID-19 , Fatigue , Health Personnel , Motor Cortex , Prefrontal Cortex , Transcranial Magnetic Stimulation , Humans , COVID-19/physiopathology , Fatigue/physiopathology , Male , Female , Longitudinal Studies , Adult , Prefrontal Cortex/physiopathology , Prefrontal Cortex/diagnostic imaging , Motor Cortex/physiopathology , Middle Aged , SARS-CoV-2/isolation & purification , Prospective Studies , Spectroscopy, Near-Infrared , Cohort StudiesABSTRACT
BACKGROUND: Neuroimaging studies suggest alterations in prefrontal cortex (PFC) activity in healthy adults under stress. Adolescents with non-suicidal self-injury (NSSI) report difficulties in stress and emotion regulation, which may be dependent on their level of borderline personality disorder (BPD). AIMS: The aim was to examine alterations in the PFC in adolescents with NSSI during stress. METHOD: Adolescents (13-17 years) engaging in non-suicidal self-injury (n = 30) and matched healthy controls (n = 29) performed a task with low cognitive demand and the Trier Social Stress Test (TSST). Mean PFC oxygenation across the PFC was measured with an eight-channel near-infrared spectroscopy system. Alongside self-reports on affect, dissociation and stress, BPD pathology was assessed via clinical interviews. RESULTS: Mixed linear-effect models revealed a significant effect of time on PFC oxygenation and a significant time×group interaction, indicating increased PFC activity in patients engaging in NSSI at the beginning of the TSST compared with healthy controls. Greater BPD symptoms overall were associated with an increase in PFC oxygenation during stress. In exploratory analyses, mixed models addressing changes in PFC connectivity over time as a function of BPD symptoms were significant only for the left PFC. CONCLUSIONS: Results indicate differences in the neural stress response in adolescents with NSSI in line with classic neuroimaging findings in adults with BPD. The link between PFC oxygenation and measures of BPD symptoms emphasises the need to further investigate adolescent risk-taking and self-harm across the spectrum of BPD, and maybe overall personality pathology, and could aid in the development of tailored therapeutic interventions.
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BACKGROUND: Mobility and cognitive impairment are prevalent and co-occurring in older adults with multiple sclerosis (OAMS), yet there is limited research concerning the role of disability status in the cognitive control of gait among OAMS. OBJECTIVE: We investigated the levels of prefrontal cortex (PFC) activation, using oxygenated hemoglobin (HbO2), during cognitively-demanding tasks in OAMS with lower and higher disability using functional near-infrared spectroscopy (fNIRS) to: (1) identify PFC activation differences in single task walk and cognitively-demanding tasks in OAMS with different levels of disability; and (2) evaluate if disability may moderate practice-related changes in neural efficiency in OAMS. METHODS: We gathered data from OAMS with lower (n = 51, age = 65 ± 4 years) or higher disability (n = 48, age = 65 ± 5 years), using a cutoff of 3 or more, in the Patient Determined Disease Steps, for higher disability, under 3 different conditions (single-task walk, Single-Task-Alpha, and Dual-Task-Walk [DTW]) administered over 3 counterbalanced, repeated trials. RESULTS: OAMS who had a lower disability level exhibited decreased PFC activation levels during Single-Task-Walk (STW) and larger increases in PFC activation levels, when going from STW to a cognitively-demanding task, such as a DTW, than those with higher disability. OAMS with a lower disability level exhibited greater declines in PFC activation levels with additional within session practice than those with a higher disability level. CONCLUSIONS: These findings suggest that disability moderates brain adaptability to cognitively-demanding tasks and demonstrate the potential for fNIRS-derived outcome measures to complement neurorehabilitation outcomes.
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Background: Alzheimer's disease has become increasingly prevalent among the older population, leading to significant social and economic burdens. Transcranial photobiomodulation (tPBM) has shown promise as a cognitive intervention for enhancing cognitive efficiency in healthy older adults, and individuals with mild cognitive impairment and Alzheimer's disease. However, determining the optimal tPBM dosage is crucial for ensuring effective and efficient intervention. Objective: This study aimed to compare the effects of different dosages in a single tPBM session on cognitive efficiency in healthy older adults. Methods: In this randomized controlled trial, 88 healthy older participants were assigned to either a single dose (irradianceâ=â30âmW/cm2, fluenceâ=â10.8âJ/cm2; nâ=â44) or a double dose (irradianceâ=â30âmW/cm2, fluenceâ=â21.6âJ/cm2; nâ=â44) tPBM session. Cognitive efficiency was assessed using functional near-infrared spectroscopy during a visual working memory span task. Results: The single dose group exhibited significantly greater cognitive efficiency enhancement, indicated by a more pronounced reduction in oxygenated hemoglobin during a challenging task level (span level 9) (pâ=â0.021, dâ=â0.50), and better working memory task performance (pâ=â0.045, dâ=â0.31). Furthermore, participants with better visuospatial abilities demonstrated greater improvement after a single dose (râ=â-0.42, pâ=â0.004). In contrast, participants with varying cognitive function did not exhibit additional benefits from a double dose (râ=â-0.22-0.15, pâ=â0.16-0.95). Conclusions: These findings suggest that higher tPBM dosages may not necessarily result in superior cognitive improvement in older adults.
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OBJECTIVE: We investigated tinnitus-related cortical networks in cochlear implant users who experience tinnitus and whose perception of tinnitus changes with use of their implant. Tinnitus, the perception of unwanted sounds which are not present externally, can be a debilitating condition. In individuals with cochlear implants, use of the implant is known to modulate tinnitus, often improving symptoms but worsening them in some cases. Little is known about underlying cortical changes with use of the implant, which lead to changes in tinnitus perception. In this study we investigated whether changes in brain networks with the cochlear implant turned on and off, were associated with changes in tinnitus perception, as rated subjectively. Approach: Using functional near-infrared spectroscopy (fNIRS), we recorded cortical activity at rest, from 14 cochlear implant users who experienced tinnitus. Recordings were performed with the cochlear implant turned off and on. For each condition, participants rated the loudness and annoyance of their tinnitus using a visual rating scale. Changes in neural synchrony have been reported in humans and animal models of tinnitus. To assess neural synchrony, functional connectivity networks with the implant turned on and off, were compared using two network features: node strength and diversity coefficient. Main results: Changes in subjective ratings of loudness were significantly correlated with changes in node strength, averaged across occipital channels (r=-0.65,p = 0.01). Changes in both loudness and annoyance were significantly correlated with changes in diversity coefficient averaged across all channels (r=-0.79,p<0.001 and r = -0.86,p<0.001). More distributed connectivity with the implant on, compared to implant off, was associated with a reduction in tinnitus loudness and annoyance. Significance: A better understanding of neural mechanisms underlying tinnitus suppression with cochlear implant use, could lead to their application as a tinnitus treatment and pave the way for effective use of other less invasive stimulation-based treatments. .
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Academic achievement is a critical measure of intellectual ability, prompting extensive research into cognitive tasks as potential predictors. Neuroimaging technologies, such as functional near-infrared spectroscopy (fNIRS), offer insights into brain hemodynamics, allowing understanding of the link between cognitive performance and academic achievement. Herein, we explored the association between cognitive tasks and academic achievement by analyzing prefrontal fNIRS signals. A novel quantum annealer (QA) feature selection algorithm was applied to fNIRS data to identify cognitive tasks correlated with CSAT scores. Twelve features (signal mean, median, variance, peak, number of peaks, sum of peaks, range, minimum, kurtosis, skewness, standard deviation, and root mean square) were extracted from fNIRS signals at two time windows (10- and 60-s) to compare results from various feature variable conditions. The feature selection results from the QA-based and XGBoost regressor algorithms were compared to validate the former's performance. In a two-step validation process using multiple linear regression models, model fitness (adjusted R2) and model prediction error (RMSE) values were calculated. The quantum annealer demonstrated comparable performance to classical machine learning models, and specific cognitive tasks, including verbal fluency, recognition, and the Corsi block tapping task, were correlated with academic achievement. Group analyses revealed stronger associations between Tower of London and N-back tasks with higher CSAT scores. Quantum annealing algorithms have significant potential in feature selection using fNIRS data, and represents a novel research approach. Future studies should explore predictors of academic achievement and cognitive ability.
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Algorithms , Cognition , Prefrontal Cortex , Spectroscopy, Near-Infrared , Humans , Spectroscopy, Near-Infrared/methods , Cognition/physiology , Male , Female , Prefrontal Cortex/physiology , Prefrontal Cortex/diagnostic imaging , Adult , Young Adult , Machine LearningABSTRACT
Objective: To explore the activation patterns in the frontal cortex of patients with post-stroke cognitive impairment during the execution of working memory tasks. Methods: 15 patients with post-stroke cognitive impairment, 17 patients without cognitive impairment, and 15 healthy controls of similar age and sex were included. All participants under-went immediate recall task testing and near-infrared spectroscopy imaging to measure frontal cortex activation during the task. Results: The healthy control group performed the best in the immediate recall task, followed by the post-stroke non-cognitive impairment group. The post-stroke cognitive impairment group had the poorest performance. The near-infrared spectroscopy results revealed that during the immediate recall task, the healthy control group primarily activated the left frontal lobe region. In contrast, post-stroke patients exhibited reduced activation in the left frontal lobe and increased activation in the right frontal cortex, particularly in the right frontopolar and orbitofrontal regions, with the post-stroke cognitive impairment group displaying the most pronounced changes. Conclusion: Patients with post-stroke cognitive impairment exhibit reduced activation in the left prefrontal cortex during the working memory tasks. They rely on compensatory activation in the right prefrontal cortex, particularly in the frontopolar and orbitofrontal cortex, to successfully complete the task.
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There is broad consensus that listening effort is an important outcome for measuring hearing performance. However, there remains debate on the best ways to measure listening effort. This study sought to measure neural correlates of listening effort using functional near-infrared spectroscopy (fNIRS) in experienced adult hearing aid users. The study evaluated impacts of amplification and signal-to-noise ratio (SNR) on cerebral blood oxygenation, with the expectation that easier listening conditions would be associated with less oxygenation in the prefrontal cortex. Thirty experienced adult hearing aid users repeated sentence-final words from low-context Revised Speech Perception in Noise Test sentences. Participants repeated words at a hard SNR (individual SNR-50) or easy SNR (individual SNR-50 + 10â dB), while wearing hearing aids fit to prescriptive targets or without wearing hearing aids. In addition to assessing listening accuracy and subjective listening effort, prefrontal blood oxygenation was measured using fNIRS. As expected, easier listening conditions (i.e., easy SNR, with hearing aids) led to better listening accuracy, lower subjective listening effort, and lower oxygenation across the entire prefrontal cortex compared to harder listening conditions. Listening accuracy and subjective listening effort were also significant predictors of oxygenation.
Subject(s)
Hearing Aids , Spectroscopy, Near-Infrared , Speech Perception , Humans , Male , Female , Speech Perception/physiology , Aged , Middle Aged , Signal-To-Noise Ratio , Acoustic Stimulation/methods , Prefrontal Cortex/physiology , Persons With Hearing Impairments/psychology , Persons With Hearing Impairments/rehabilitation , Noise/adverse effects , Correction of Hearing Impairment/instrumentation , Correction of Hearing Impairment/methods , Adult , Aged, 80 and over , Hearing/physiology , Cerebrovascular Circulation/physiology , Auditory Threshold/physiology , Speech Intelligibility/physiologyABSTRACT
BACKGROUND: There is no diagnostic assessment procedure with moderate or strong evidence of use, and evidence for current means of treating prolonged disorders of consciousness (pDOC) is sparse. This may be related to the fact that the mechanisms of pDOC have not been studied deeply enough and are not clear enough. Therefore, the aim of this study was to explore the mechanism of pDOC using functional near-infrared spectroscopy (fNIRS) to provide a basis for the treatment of pDOC, as well as to explore preclinical markers for determining the arousal of pDOC patients. METHODS: Five minutes resting-state data were collected from 10 pDOC patients and 13healthy adults using fNIRS. Based on the concentrations of oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) in the time series, the resting-state cortical brain functional connectivity strengths of the two groups were calculated, and the functional connectivity strengths of homologous and heterologous brain networks were compared at the sensorimotor network (SEN), dorsal attention network (DAN), ventral attention network (VAN), default mode network (DMN), frontoparietal network (FPN), and visual network (VIS) levels. Univariate binary logistic regression analyses were performed on brain networks with statistically significant differences to identify brain networks associated with arousal in pDOC patients. The receiver operating characteristic (ROC) curves were further analyzed to determine the cut-off value of the relevant brain networks to provide clinical biomarkers for the prediction of arousal in pDOC patients. RESULTS: The results showed that the functional connectivity strengths of oxyhemoglobin (HbO)-based SENâ¼SEN, VISâ¼VIS, DANâ¼DAN, DMNâ¼DMN, SENâ¼VIS, SENâ¼FPN, SENâ¼DAN, SENâ¼DMN, VISâ¼FPN, VISâ¼DAN, VISâ¼DMN, HbR-based SENâ¼SEN, and SENâ¼DAN were significantly reduced in the pDOC group and were factors that could reflect the participants' state of consciousness. The cut-off value of resting-state functional connectivity strength calculated by ROC curve analysis can be used as a potential preclinical marker for predicting the arousal state of subjects. CONCLUSION: Resting-state functional connectivity strength of cortical networks is significantly reduced in pDOC patients. The cut-off values of resting-state functional connectivity strength are potential preclinical markers for predicting arousal in pDOC patients.
Subject(s)
Arousal , Consciousness Disorders , Spectroscopy, Near-Infrared , Humans , Spectroscopy, Near-Infrared/methods , Male , Pilot Projects , Female , Adult , Consciousness Disorders/physiopathology , Consciousness Disorders/diagnostic imaging , Arousal/physiology , Middle Aged , Nerve Net/physiopathology , Nerve Net/diagnostic imaging , Oxyhemoglobins/metabolism , Oxyhemoglobins/analysis , Brain/physiopathology , Brain/diagnostic imaging , Biomarkers , Connectome/methods , Rest/physiology , Young Adult , HemoglobinsABSTRACT
One of the most prevalent psychiatric disorders is major depressive disorder (MDD), which increases the probability of suicidal ideation or untimely demise. Abnormal frontal hemodynamic changes detected by functional near-infrared spectroscopy (fNIRS) during verbal fluency task (VFT) have the potential to be used as an objective indicator for assessing clinical symptoms. However, comprehensive quantitative and objective assessment instruments for individuals who exhibit symptoms suggestive of depression remain undeveloped. Drawing from a total of 467 samples in a large-scale dataset comprising 289 MDD patients and 178 healthy controls, fNIRS measurements were obtained throughout the VFT. To identify unique MDD biomarkers, this research introduced a data representation approach for extracting spatiotemporal features from fNIRS signals, which were subsequently utilized as potential predictors. Machine learning classifiers (e.g., Gradient Boosted Decision Trees (GBDT) and Multilayer Perceptron) were implemented to assess the ability to predict selected features. The mean and standard deviation of the cross-validation indicated that the GBDT model, when combined with the 180-feature pattern, distinguishes patients with MDD from healthy controls in the most effective manner. The accuracy of correct classification for the test set was 0.829 ± 0.053, with an AUC of 0.895 (95 % CI: 0.864-0.925) and a sensitivity of 0.914 ± 0.051. Channels that made the most important contribution to the identification of MDD were identified using Shapley Additive Explanations method, located in the frontopolar area and the dorsolateral prefrontal cortex, as well as pars triangularis Broca's area. Assessment of abnormal prefrontal activity during the VFT in MDD serves as an objectively measurable biomarker that could be utilized to evaluate cognitive deficits and facilitate early screening for MDD. The model suggested in this research could be applied to large-scale case-control fNIRS datasets to detect unique characteristics of MDD and offer clinicians an objective biomarker-based analytical instrument to assist in the evaluation of suspicious cases.
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How well autistic children can imitate movements and how their brain activity synchronizes with the person they are imitating have been understudied. The current study adopted functional near-infrared spectroscopy (fNIRS) hyperscanning and employed a task involving real interactions involving meaningful and meaningless movement imitation to explore the fundamental nature of imitation as a dynamic and interactive process. Experiment 1 explored meaningful and meaningless gesture imitation. The results revealed that autistic children exhibited lower imitation accuracy and behavioral synchrony than non-autistic children when imitating both meaningful and meaningless gestures. Specifically, compared to non-autistic children, autistic children displayed significantly higher interpersonal neural synchronization (INS) in the right inferior parietal lobule (r-IPL) (channel 12) when imitating meaningful gestures but lower INS when imitating meaningless gestures. Experiment 2 further investigated the imitation of four types of meaningless movements (orofacial movements, transitive movements, limb movements, and gestures). The results revealed that across all four movement types, autistic children exhibited significantly lower imitation accuracy, behavioral synchrony, and INS in the r-IPL (channel 12) than non-autistic children. This study is the first to identify INS as a biomarker of movement imitation difficulties in autistic individuals. Furthermore, an intra- and interindividual imitation mechanism model was proposed to explain the underlying causes of movement imitation difficulties in autistic individuals.
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BACKGROUND: Structural and functional neurobiological abnormalities have been observed in schizophrenia. Previous studies have concentrated on specific illness stages, obscuring relationships between functional/structural changes and disorder progression. The present study aimed to quantify structural and functional abnormalities across different clinical stages using functional near-infrared spectroscopy (fNIRS) and structural magnetic resonance imaging (sMRI). METHODS: Fifty-four participants with first-episode schizophrenia (FES), 120 with clinically high risk of psychosis (CHR), and 111 healthy controls (HCs) underwent functional near-infrared spectroscopy (fNIRS) to measure oxyhemoglobin (Oxy-Hb) during the verbal fluency task. Among them, 28FES, 64CHR and 55HC also finished sMRI. Oxy-Hb and gray matter volume (GMV) were compared among the three groups while controlling for covariates, including age, sex, years of education, and task performance. Mediation analysis was utilized to determine the mediating effect of GMV on Oxy-Hb and cognition. RESULTS: Compared with the HC group, CHR and FES groups showed significantly reduced brain activity. However, there were no significant differences between the FES and CHR. Pronounced GMV increase in the right frontal pole area (F = 4.234, p = 0.016) was identified in the CHR and FES groups. Mediation analysis showed a significant mediation effect of the right frontal pole GMV between Channel 31 Oxy-Hb and processing speed (z = 2.105, p = 0.035) and attention/vigilance (z = 1.992, p = 0.046). CONCLUSIONS: Brain activation and anatomical deficits were observed in different brain regions, suggesting that anatomical and functional abnormalities are dissociated in the early stages of psychosis. The relationship between neural activity and anatomy may reflect a specific pathophysiology related to cognitive deterioration in schizophrenia.
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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.
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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.
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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.