Search Results (115)

Background: The sense of agency (SoA)—the subjective experience of controlling one’s own actions and their consequences—is a fundamental aspect of human cognition, volition, and motor control. Understanding how the SoA arises and is disrupted in neuropsychiatric disorders has significant implications for human–machine interface (HMI) design for neurorehabilitation. Traditional cognitive models of agency often fail to capture its full complexity, especially in dynamic and uncertain environments. Objective: This review synthesizes computational models—particularly predictive coding, Bayesian inference, and optimal control theories—to provide a unified framework for understanding the SoA in both healthy and dysfunctional brains. It aims to demonstrate how these models can inform the design of adaptive HMIs and therapeutic tools by aligning with the brain’s own inference and control mechanisms. Methods: I reviewed the foundational and contemporary literature on predictive coding, Kalman filtering, the Linear–Quadratic–Gaussian (LQG) control framework, and active inference. I explored their integration with neurophysiological mechanisms, focusing on the somato-cognitive action network (SCAN) and its role in sensorimotor integration, intention encoding, and the judgment of agency. Case studies, simulations, and XR-based rehabilitation paradigms using robotic haptics were used to illustrate theoretical concepts. Results: The SoA emerges from hierarchical inference processes that combine top–down motor intentions with bottom–up sensory feedback. Predictive coding frameworks, especially when implemented via Kalman filters and LQG control, provide a mechanistic basis for modeling motor learning, error correction, and adaptive control. Disruptions in these inference processes underlie symptoms in disorders such as functional movement disorder. XR-based interventions using robotic interfaces can restore the SoA by modulating sensory precision and motor predictions through adaptive feedback and suggestion. Computer simulations demonstrate how internal models, and hypnotic suggestions influence state estimation, motor execution, and the recovery of agency. Conclusions: Predictive coding and active inference offer a powerful computational framework for understanding and enhancing the SoA in health and disease. The SCAN system serves as a neural hub for integrating motor plans with cognitive and affective processes. Future work should explore the real-time modulation of agency via biofeedback, simulation, and SCAN-targeted non-invasive brain stimulation. Full article

Falls, a major cause of injury and disability, particularly among older adults, present a significant public-health challenge. Existing methods of balance assessment often lack the sensitivity and specificity needed to identify subtle deviations from normal patterns, hindering early intervention. To address this gap, we introduced a novel artificial intelligence-based tool that leverages anomaly detection to provide a comprehensive assessment of balance performance across all age groups. This study evaluated the tool’s effectiveness in 163 individuals aged 18–85 years who were assessed using a force platform under four conditions: eyes open and eyes closed on firm and foam surfaces. Data analysis, employing an artificial neural network with 19 socio-anthropometric and postural variables, showed the tool’s exceptional accuracy (R = 0.99998) in differentiating among balance profiles. Notably, the model highlighted the significant impact of age and education on balance, with older adults demonstrating increased reliance on visual input, especially when somatosensory information was reduced on foam surfaces. In contrast, younger, more educated individuals exhibited a more integrated sensorimotor approach. These findings demonstrate that our anomaly-detection tool can identify subtle balance impairments often missed by traditional methods, offering valuable insights for personalized fall-risk assessment and intervention. This AI-based approach can provide a holistic assessment of balance, leading to more effective strategies for fall prevention and rehabilitation, particularly in aging populations. Full article

Objective: Patients with bipolar disorder (BD) may exhibit common and significant changes in brain activity across different networks. Our aim was to investigate the changes in functional connectivity (FC) within different brain networks in BD, as well as their neuroimaging homogeneity, heterogeneity, and genetic variation. Methods: In this study, we analyzed the seed points and whole-brain FC of the sensorimotor network (SMN) and visual network (VN) in 83 healthy controls (HCs) and 77 BD patients, along with their genetic neuroimaging associations. Results: The results showed that, compared to HCs, BD patients exhibited abnormal FC in the SMN and VN brain regions. However, after three months of treatment, there were no significant differences in SMN and VN FC in the brain regions of the patients compared to pre-treatment levels. Enrichment analysis indicated that genes associated with changes in FC were shared among different SMN seed points, but no shared genes were found among VN seed points. Conclusions: In conclusion, changes in SMN FC may serve as a potential neuroimaging marker in BD patients. Our genetic neuroimaging association analysis may help to comprehensively understand the molecular mechanisms underlying FC changes in BD patients. Full article

Intrinsic connectivity of the fusiform face area (FFA) was assessed using resting-state functional magnetic resonance imaging (fMRI) to compare adults with autism spectrum disorder (ASD; n = 17) and age-, sex-, and IQ-matched typically developing controls (TD; n = 22). The FFA seed region was delineated in each participant using a functional localizer task. Whole brain analyses of FFA connectivity revealed increased connectivity between the right FFA and the vermis, sensorimotor cortex, and extended face-processing network in individuals with ASD compared to TD participants; the TD group did not demonstrate increased functional connectivity. No group differences were observed from the left FFA. The relationship between FFA connectivity and the ability to remember faces significantly differed between the groups. Better face memory performance was positively correlated with increased connectivity within general visual processing areas in the ASD participants; whereas for the TD group, better face memory performance was associated with increased connectivity with brain regions related to face encoding, recognition, and retrieval. FFA overconnectivity with face, emotion, and memory processing areas, along with atypical relationships between FFA–occipito-temporal connections and face memory performance highlights a possible mechanism underlying social dysfunction in individuals with ASD. Full article

Background/Objectives: Precise stepping control is fundamental to human mobility, and impairments increase fall risk in older adults and individuals with neurological conditions. This study investigated the cortical networks underlying stepping accuracy using mobile brain/body imaging with electroencephalography (EEG)-based exact low-resolution electromagnetic tomography-independent component analysis (eLORETA-ICA) and microstate segmentation analysis (MSA). Methods: Sixteen healthy male participants performed a precision stepping task while wearing a mobile EEG system. Step performance was quantified using error distance, measuring deviation between target and heel contact points. Preprocessed EEG data were analyzed using eLORETA-ICA and MSA, with participants categorized into high- and low-performing groups. Results: Seven microstate clusters were identified, with the anterior cingulate cortex (ACC) showing the highest microstate probability (21.15%). The high-performing group exhibited amplified theta-band activity in the ACC, enhanced activity in the precuneus and postcentral gyrus, and suppressed mu- and beta-band activity in the paracentral lobules. Conclusions: Stepping accuracy relies on a distributed neural network, with the ACC playing a central role in performance monitoring. We propose an integrated framework comprising the following systems: error monitoring (ACC), sensorimotor integration (paracentral lobules), and visuospatial processing (precuneus and occipital regions). These findings highlight the importance of neural oscillatory mechanisms in precise motor control and offer insights for rehabilitation strategies and fall prevention programs. Full article

Background: In functional magnetic resonance imaging (fMRI), functional network connectivity (FNC) captures temporal coupling among intrinsic connectivity networks (ICNs). Traditional FNC analyses often rely on linear models, which may overlook complex nonlinear interactions. We propose a multi-layered neural network that generates nonlinear heatmaps from FNC matrices, which we visualize at multiple layers, enabling us to better characterize multi-level interactions and improve interpretability. Methods: Our approach consists of two training stages. In the first, a deep convolutional neural network (DCNN) is trained to produce heatmaps from multiple convolution layers. In the second, a t-test-based feature selection identifies relevant heatmaps that help distinguish different groups. In addition, we introduce ‘source-based features’ which summarize the multi-layer model output using an independent component analysis-based procedure that provides valuable, interpretable insights into the specific layer outputs. We tested this approach on a large dataset of schizophrenia patients and healthy controls, split into training and validation sets. Furthermore, this method clarifies how underlying neural mechanisms differ between schizophrenia patients and healthy controls, revealing crucial patterns in the default mode and visual networks. Results: The results indicate increased default mode network connectivity with itself and cognitive control regions in patients, while controls showed stronger visual and sensorimotor connectivity. Our DCNN approach achieved 92.8% cross-validated classification accuracy, outperforming competing methods. We also separated individuals into three cognitive performance groups based on cognitive scores and showed that the model can accurately predict the cognitive level using the FNC data. Conclusion: Our novel approach demonstrates the advantage of employing more sophisticated models in characterizing complex brain connectivity patterns while enhancing the interpretability of results. These findings underscore the significance of modeling nonlinear dynamics in fMRI analysis, shedding new light on the intricate interplays underlying cognitive and psychiatric phenomena. Full article

Background: Motor learning can occur through active reaching with the arm hidden from view, leading to improvements in somatosensory acuity and modulation of functional connectivity in sensorimotor and reward networks. In this proof-of-principle study, we assess if the same paradigm benefits stroke survivors using a compact end-effector robot with integrated gaming elements. Methods: Nine community-dwelling chronic hemiplegic stroke survivors with persistent somatosensory deficits participated in 15 training sessions, each lasting 1 h. Every session comprised a robotic-based joint approximation block, followed by 240 repetitions of training using a forward-reaching task with the affected forearm covered from view. During movement, the robot provided haptic guidance along the movement path as enhanced sensory cues. Augmented reward feedback was given following every successful movement as positive reinforcement. Baseline, post-intervention, and 1-month follow-up assessments were conducted, with the latter two sessions occurring after the final training day. Results: Training led to reliable improvements in endpoint accuracy, faster completion times, and smoother movements. Acceptability and feasibility analyses were performed to understand the viability of the intervention. Significant improvement was observed mainly in robotic-based sensory outcomes up to a month post training, suggesting that training effects were predominantly sensory, rather than motor. Conclusions: The study outcomes provide preliminary evidence supporting the feasibility of this intervention for future adoption in neurorehabilitation. Full article

Background/Objectives: Synchronized beta-band oscillations (14–30 Hz) are critical for sensorimotor processing and motor performance. Modulating beta activity either locally in targeted brain regions or globally across sensorimotor networks may enhance motor function. This study aimed to explore whether transcranial direct current stimulation (tDCS) and alternating current stimulation (tACS) could enhance sensorimotor responses by modulating beta-band synchronization. Methods: Eight participants performed a stimulus–response task requiring a quick keypress to a visual cue. Response times (RTs) and electroencephalography (EEG) data were recorded during pre-, in-, and post-stimulation sessions for five conditions: motor-anodal tDCS, visual-anodal tDCS, alpha (10 Hz) tACS, beta (20 Hz) tACS, and sham, with a one-week interval between conditions. Results: Significant RT reductions were observed only after motor-anodal tDCS. EEG analysis revealed a positive correlation between these RT reductions and increased beta-phase synchronization between visual and motor areas. In contrast, tACS conditions did not yield significant RT improvements or beta-phase synchronization changes. Conclusions: These findings indicate that motor-anodal tDCS has the potential to enhance sensorimotor performance by facilitating beta-phase synchronization across the visual-motor network. The observed effects likely extend beyond localized neuronal modulation, emphasizing the importance of network-level connectivity in sensorimotor integration. Beta-phase synchronization appears to play a critical role in integrating visual and motor information, contributing to task-related performance improvements. Further research is warranted to build upon these findings and fully elucidate the underlying mechanisms. Full article

Previous EEG studies using graph analysis have revealed altered functional brain networks in children with developmental dyslexia (DD). The influence of sex on these networks within this childhood disorder remains unclear. The study emphasizes the importance of considering sex and individual differences by investigating brain connectivity in 8-year-old children (42 controls and 72 children with DD, half girls) during a task involving low- and high-contrast discrimination of low-spatial frequency illusion (LSFI). Understanding these variations is crucial for elucidating the neurobiological underpinnings of developmental disabilities. Control children showed sex differences in association networks, while children with DD exhibited them in sensorimotor networks. The control boys’ α, β2-frequency functional networks were more integrated than control girls in low-contrast LSFI and in β and γ2-networks in high-contrast LSFI. Boys exhibited stronger anterior connectivity (language, visual motion), while girls showed stronger posterior connectivity (visuospatial, visuomotor attention). There was a notable overlap in association networks between boys and girls. Sex-related differences were pronounced in the γ2 frequency sensorimotor, and association cortical networks exhibited dispersion in both hemispheres for boys and in the left hemisphere for girls (both contrast LSFIs). Boys with DD exhibited hubs in α-sensorimotor networks (low-contrast LSFI) and β1-networks (high-contrast LSFI) in the right brain hemisphere, while girls’ hubs with DD were in the left hemisphere. The differing rates of cortical network maturation between sexes with DD during childhood contribute to variations linked to disruptions in brain network development, even within sensorimotor networks. The study showed that this task enhanced even minor individual differences in functional connectivity characteristics and revealed subtle differences in brain connectivity, especially in children with DD. Full article

Background/Methods: The influence of sex on brain organization was investigated in functional reading networks in 8-year-old children, in those typically developing and those with developmental dyslexia (DD), utilizing the minimum spanning tree model. Results: The word reading task revealed subtle sex differences in brain connectivity and highlighted even small individual variations in functional connectivity characteristics, particularly among boys with DD. In girls, significantly stronger connections and core hubs were identified within and between motor, parietal, and visual networks in posterior brain regions in both hemispheres, particularly in the θ (dyslexics) and δ (normolexics) frequency bands. In contrast, boys showed a more diffuse connectivity pattern, predominantly in the left hemisphere, encompassing anterior heteromodal and sensorimotor networks. Girls exhibited greater network complexity (bigger leaf fraction, kappa, and tree hierarchy), particularly in the θ and δ frequency bands, while boys with DD showed increased network efficiency, except for in the γ2 band (smaller diameter and bigger leaf fraction). Therefore, gender-specific differences in brain network organization may affect reading development and dyslexia. While sex may influence brain network development, its impact on the sensorimotor and frontoparietal networks of 8-year-old children is relatively limited. Significant sex differences were observed in only a small subset of children, primarily in higher (β2-γ2) frequency bands. Conclusions: Interindividual variations were evident only in boys with DD, impacting both sensorimotor and association networks. Different rates of cortical network maturation between sexes with DD during childhood may contribute to variations associated with disruptions in brain network development, even within fundamental networks like the sensorimotor network. Full article

Background: Prolonged confinement in enclosed environments has raised concerns about its effects on both physical and mental health. Although increased rates of depression or anxiety during COVID-19 lockdowns have been reported, the effects of short-term restrictions on social activities and physical on brain function and structure remain poorly known. Methods: This study explored longitudinal changes in brain gray matter volume (GMV) and functional connectivity (FC) immediately after and four months following a short-term lockdown in comparison to pre-lockdown conditions. MRI data were collected from 20 participants before the lockdown, from 29 participants (14 original, 15 new) two months post-lockdown, and from 27 out of the 29 participants four months post-lifting of the lockdown. Results: Results showed significant GMV reductions in the right gyrus rectus and cuneus post-lockdown, with further reductions observed four months after lifting the restrictions, affecting additional brain regions. Longitudinal FC trajectories revealed decreased connectivity between the default mode network (DMN) and sensorimotor/attention networks post-lockdown, and recovery after four months post-lifting of the lockdown. Conclusions: The observed plasticity in brain FC indicates substantial recovery potential with the potential long-term effect of structural changes. Our findings offer insights into the effects of isolation on the human brain, potentially informing rehabilitation mechanisms and interventions for individuals in similar conditions. Full article

Background: Coffee and tea are widely consumed beverages, but their long-term effects on cognitive function and aging remain largely unexplored. Lifestyle interventions, particularly dietary habits, offer promising strategies for enhancing cognitive performance and preventing cognitive decline. Methods: This study utilized data from the UK Biobank cohort (n = 12,025) to examine the associations between filtered coffee, green tea, and standard tea consumption and neural network functional connectivity across seven resting-state networks. We focused on networks spanning prefrontal and occipital areas that are linked to complex cognitive and behavioral functions. Linear mixed models were used to assess the main effects of coffee and tea consumption, as well as their interactions with Apolipoprotein E (APOE) genetic risk—the strongest genetic risk factor for Alzheimer’s disease (AD). Results: Higher filtered coffee consumption was associated with increased functional connectivity in several networks, including Motor Execution, Sensorimotor, Fronto-Cingular, and a Prefrontal + ‘What’ Pathway Network. Similarly, greater green tea intake was associated with enhanced connectivity in the Extrastriate Visual and Primary Visual Networks. In contrast, higher standard tea consumption was linked to reduced connectivity in networks such as Memory Consolidation, Motor Execution, Fronto-Cingular, and the “What” Pathway + Prefrontal Network. The APOE4 genotype and family history of AD influenced the relationship between coffee intake and connectivity in the Memory Consolidation Network. Additionally, the APOE4 genotype modified the association between standard tea consumption and connectivity in the Sensorimotor Network. Conclusions: The distinct patterns of association between coffee, green tea, and standard tea consumption and resting-state brain activity may provide insights into AD-related brain changes. The APOE4 genotype, in particular, appears to play a significant role in modulating these relationships. These findings enhance our knowledge of how commonly consumed beverages may influence cognitive function and potentially AD risk among older adults. Full article

Background and Purpose: activities-based locomotor training (AB-LT) is a restorative therapeutic approach to the treatment of movement deficits in people with non-progressive neurological conditions, including cerebral palsy (CP). Transcutaneous spinal stimulation (TSS) is an emerging tool in the rehabilitation of individuals with sensorimotor deficits caused by neurological dysfunction. This non-invasive technique delivers electrical stimulation over the spinal cord, leading to the modulation of spinal sensorimotor networks. TSS has been used in combination with AB-LT and has been shown to improve muscle activation patterns and enhance motor recovery. However, there are no published studies comparing AB-LT + TSS to AB-LT alone in children with CP. The purpose of this case study was to compare the impact of AB-LT alone versus AB-LT combined with TSS on functional movement and quality of life in a child with CP. Methods: A 13-year-old male with quadriplegic CP participated in this pilot study. He was classified in the Gross Motor Function Classification System (GMFCS) at Level III. He completed 20 sessions of AB-LT (5x/week), then a 2-week washout period, followed by 20 sessions of body-AB-LT + TSS. Treatment sessions consisted of 1 h of locomotor training with body weight support and manual facilitation and 30 min of overground play-based activities. TSS was applied using the RTI Xcite^®, with stimulation at the T11 and L1 vertebral levels. Assessments including the Gross Motor Function Measure (GMFM), 10-m walk test (10 MWT), and Pediatric Balance Scale (PBS) were performed, while spatiotemporal gait parameters were assessed using the Zeno Walkway^®. All assessments were performed at three time points: before and after AB-LT, as well as after AB-LT + TSS. OUTCOMES: After 19/20 sessions of AB-LT alone, the participant showed modest improvements in the GMFM scores (from 86.32 to 88), 10 MWT speed (from 1.05 m/s to 1.1 m/s), and PBS scores (from 40 to 42). Following the AB-LT combined with TSS, scores improved to an even greater extent compared with AB-LT alone, with the GMFM increasing to 93.7, 10 MWT speed to 1.43 m/s, and PBS to 44. The most significant gains were observed in the GMFM and 10 MWT. Additionally, improvements were noted across all spatiotemporal gait parameters, particularly at faster walking speeds. Perhaps most notably, the child transitioned from the GMFCS level III to level II by the end of the study. Discussion: Higher frequency and intensity interventions aimed at promoting neuroplasticity to improve movement quality in children with CP are emerging as a promising alternative to traditional physical therapy approaches. This case study highlights the potential of TSS to augment neuroplasticity-driven treatment approaches, leading to improvements in neuromotor function in children with CP. These findings suggest that TSS could be a valuable addition to rehabilitation strategies, warranting further research to explore its efficacy in larger populations. Full article

Background/Objectives: There is a subset of patients with pain who become worse after exercise. To explore this, we examined the responses of people with chronic primary pain to a standardized high intensity exercise protocol used to induce delayed onset muscle soreness (DOMS). Methods: Ten participants with a diagnosis of chronic widespread muscle pain (CWMP) were matched by age and reported gender to ten participants without muscle pain (i.e., no pain (NP)). Participants completed a standardized DOMS protocol. Pain intensity in the arm at rest and with movement was assessed using daily electronic diaries. Peak pain, the timing of peak pain, and the time to recovery were compared between groups. Associations of pain variables with the functional connectivity of the sensorimotor (SMN), cerebellum, frontoparietal control (FPN), and default mode network (DMN) both within network nodes and the rest of the brain was assessed. Results: Significant differences in peak pain, the time to peak pain, and the time to recovery were noted between groups for both pain at rest and pain with movement after controlling for catastrophizing and pain resilience. Connectivity across the SMN, FPN, and DMN was associated with all pain-related variables. Significant group differences were identified between groups. Conclusions: A standardized muscle “injury” protocol resulted in more pain, a longer time to peak pain, and a longer time to resolve pain in the patient group compared to the NP group. These differences were associated with differences in connectivity across brain regions related to sensorimotor integration and appraisal. These findings provide preliminary evidence of the dysregulation of responses to muscle (micro)trauma in people with chronic pain. Full article

Background/Objectives: Driving abilities require the synchronized activity of cerebral networks associated with sensorimotor integration, motricity, and executive functions. Drivers with Parkinson’s disease (DwP) have impaired driving ability, but little is known about the impact of “wearing-off” and therapies in addition to L-DOPA on driving capacities. This study aimed to (i) compare driving performance between DwP during different motor states and healthy controls and (ii) assess the impact of add-on therapies on driving abilities. Methods: DwP (n = 26) were enrolled as individuals experiencing wearing-off symptoms and treated (within 6 months before the enrollment) with add-on therapies to L-DOPA, including MAO inhibitors for DwP-A (n = 12) or opicapone for DwP-B (n = 14). Age- and sex-matched controls (CON, n = 12) were also enrolled. DwP received two driving assessments in a driving simulator during their “best-on” time and during their wearing-off time on different days. An anamnestic driving questionnaire was collected with the assistance of partners. A Virtual Driving Rating Scale (VDRS) was calculated, as well as learning curves (LCs) for driving items calculated in minutes. Results: DwP reported worse driving performance than CON at the driving questionnaire. In line with this, DwP showed worse VDRS (p < 0.01) and LC (p = 0.021) than CON. Lower VDRS was associated with wearing-off (p < 0.01), but DwP-B had better driving performance while in their “best-on” time (p = 0.037) and more items improving with LCs (7 vs. 3) than DwP-A. Conclusions: DwP demonstrated impaired driving compared to controls. Wearing-off symptoms can also affect driving ability, but therapies (opicapone more so than MAO inhibitors) may play a role in preserving specific driving skills, possibly through maintaining learning abilities. Full article