Brain-Controlled Hand Exoskeleton Based on Augmented Reality-Fused Stimulus Paradigm.

Advancements in brain-machine interfaces (BMIs) have led to the development of novel rehabilitation training methods for people with impaired hand function. However, contemporary hand exoskeleton systems predominantly adopt passive control methods, leading to low system performance. In this work, an active brain-controlled hand exoskeleton system is proposed that uses a novel augmented reality-fused stimulus (AR-FS) paradigm as a human-machine interface, which enables users to actively control their fingers to move. Considering that the proposed AR-FS paradigm generates movement artifacts during hand movements, an enhanced decoding algorithm is designed to improve the decoding accuracy and robustness of the system. In online experiments, participants performed online control tasks using the proposed system, with an average task time cost of 16.27 s, an average output latency of 1.54 s, and an average correlation instantaneous rate (CIR) of 0.0321. The proposed system shows 35.37% better efficiency, 8.03% reduced system delay, and 35.28% better stability than the traditional system. This study not only provides an efficient rehabilitation solution for people with impaired hand function but also expands the application prospects of brain-control technology in areas such as human augmentation, patient monitoring, and remote robotic interaction. The video in Graphical Abstract Video demonstrates the user's process of operating the proposed brain-controlled hand exoskeleton system.

Functional connectivity in people at clinical and familial high risk for schizophrenia.

Patients diagnosed with schizophrenia (SZ) exhibit compromised functional connectivity within extensive brain networks. However, the precise development of this impairment during disease progression in the clinical high-risk (CHR) population and their relatives remains unclear. Our study leveraged data from 128 resting electroencephalography (EEG) channels acquired from 30 SZ patients, 21 CHR individuals, 17 unaffected healthy relatives (RSs; those at heightened SZ risk due to family history), and 31 healthy controls (HCs). These data were harnessed to establish functional connectivity patterns. By calculating the geometric distance between EEG sequences, we unveiled local and global nonlinear relationships within the entire brain. The process of dimensionality reduction led to low-dimensional representations, providing insights into high-dimensional EEG data. Our findings indicated that CHR participants exhibited aberrant functional connectivity across hemispheres, whereas RS individuals showcased anomalies primarily concentrated within hemispheres. In the realm of low-dimensional analysis, RS participants' third-dimensional occipital lobe values lay between those of the CHR individuals and HCs, significantly correlating with scale scores. This low-dimensional approach facilitated the visualization of brain states, potentially offering enhanced comprehension of brain structure, function, and early-stage functional impairment, such as occipital visual deficits, in RS individuals before cognitive decline onset.

Effects of Microstate Dynamic Brain Network Disruption in Different Stages of Schizophrenia.

Schizophrenia is a heterogeneous mental disorder with unknown etiology or pathological characteristics. Microstate analysis of the electroencephalogram (EEG) signal has shown significant potential value for clinical research. Importantly, significant changes in microstate-specific parameters have been extensively reported; however, these studies have ignored the information interactions within the microstate network in different stages of schizophrenia. Based on recent findings, since rich information about the functional organization of the brain can be revealed by functional connectivity dynamics, we use the first-order autoregressive model to construct the functional connectivity of intra- and intermicrostate networks to identify information interactions among microstate networks. We demonstrate that, beyond abnormal parameters, disrupted organization of the microstate networks plays a crucial role in different stages of the disease by 128-channel EEG data collected from individuals with first-episode schizophrenia, ultrahigh-risk, familial high-risk, and healthy controls. According to the characteristics of the microstates of patients at different stages, the parameters of microstate class A are reduced, those of class C are increased, and the transitions from intra- to intermicrostate functional connectivity are gradually disrupted. Furthermore, decreased integration of intermicrostate information might lead to cognitive deficits in individuals with schizophrenia and those in high-risk states. Taken together, these findings illustrate that the dynamic functional connectivity of intra- and intermicrostate networks captures more components of disease pathophysiology. Our work sheds new light on the characterization of dynamic functional brain networks based on EEG signals and provides a new interpretation of aberrant brain function in different stages of schizophrenia from the perspective of microstates.

Altered Neurovascular Coupling for Multidisciplinary Intensive Rehabilitation in Parkinson's Disease.

Effective rehabilitation in Parkinson's disease (PD) is related to brain reorganization with restoration of cortico-subcortical networks and compensation of frontoparietal networks; however, further neural rehabilitation evidence from a multidimensional perspective is needed. To investigate how multidisciplinary intensive rehabilitation treatment affects neurovascular coupling, 31 PD patients (20 female) before and after treatment and 30 healthy controls (17 female) underwent blood oxygenation level-dependent functional magnetic resonance imaging and arterial spin labeling scans. Cerebral blood flow (CBF) was used to measure perfusion, and fractional amplitude of low-frequency fluctuation (fALFF) was used to measure neural activity. The global CBF-fALFF correlation and regional CBF/fALFF ratio were calculated as neurovascular coupling. Dynamic causal modeling (DCM) was used to evaluate treatment-related alterations in the strength and directionality of information flow. Treatment reduced CBF-fALFF correlations. The altered CBF/fALFF exhibited increases in the left angular gyrus and the right inferior parietal gyrus and decreases in the bilateral thalamus and the right superior frontal gyrus. The CBF/fALFF alteration in right superior frontal gyrus showed correlations with motor improvement. Further, DCM indicated increases in connectivity from the superior frontal gyrus and decreases from the thalamus to the inferior parietal gyrus. The benefits of rehabilitation were reflected in the dual mechanism, with restoration of executive control occurring in the initial phase of motor learning and compensation of information integration occurring in the latter phase. These findings may yield multimodal insights into the role of rehabilitation in disease modification and identify the dorsolateral superior frontal gyrus as a potential target for noninvasive neuromodulation in PD.SIGNIFICANCE STATEMENT Although rehabilitation has been proposed as a promising supplemental treatment for PD as it results in brain reorganization, restoring cortico-subcortical networks and eliciting compensatory activation of frontoparietal networks, further multimodal evidence of the neural mechanisms underlying rehabilitation is needed. We measured the ratio of perfusion and neural activity derived from arterial spin labeling and blood oxygenation level-dependent fMRI data and found that benefits of rehabilitation seem to be related to the dual mechanism, restoring executive control in the initial phase of motor learning and compensating for information integration in the latter phase. We also identified the dorsolateral superior frontal gyrus as a potential target for noninvasive neuromodulation in PD patients.

Individual-level functional connectomes predict the motor symptoms of Parkinson's disease.

Abnormalities in functional connectivity networks are associated with sensorimotor networks in Parkinson's disease (PD) based on group-level mapping studies, but these results are controversial. Using individual-level cortical segmentation to construct individual brain atlases can supplement the individual information covered by group-level cortical segmentation. Functional connectivity analyses at the individual level are helpful for obtaining clinically useful markers and predicting treatment response. Based on the functional connectivity of individualized regions of interest, a support vector regression model was trained to estimate the severity of motor symptoms for each subject, and a correlation analysis between the estimated scores and clinical symptom scores was performed. Forty-six PD patients aged 50-75 years were included from the Parkinson's Progression Markers Initiative database, and 63 PD patients were included from the Beijing Rehabilitation Hospital database. Only patients below Hoehn and Yahr stage III were included. The analysis showed that the severity of motor symptoms could be estimated by the individualized functional connectivity between the visual network and sensorimotor network in early-stage disease. The results reveal individual-level connectivity biomarkers related to motor symptoms and emphasize the importance of individual differences in the prediction of the treatment response of PD.

Individual functional parcellation revealed compensation of dynamic limbic network organization in healthy ageing.

Using group-level functional parcellations and constant-length sliding window analysis, dynamic functional connectivity studies have revealed network-specific impairment and compensation in healthy ageing. However, functional parcellation and dynamic time windows vary across individuals; individual-level ageing-related brain dynamics are uncertain. Here, we performed individual parcellation and individual-length sliding window clustering to characterize ageing-related dynamic network changes. Healthy participants (n = 637, 18-88 years) from the Cambridge Centre for Ageing and Neuroscience dataset were included. An individual seven-network parcellation, varied from group-level parcellation, was mapped for each participant. For each network, strong and weak cognitive brain states were revealed by individual-length sliding window clustering and canonical correlation analysis. The results showed negative linear correlations between age and change ratios of sizes in the default mode, frontoparietal, and salience networks and a positive linear correlation between age and change ratios of size in the limbic network (LN). With increasing age, the occurrence and dwell time of strong states showed inverted U-shaped patterns or a linear decreasing pattern in most networks but showed a linear increasing pattern in the LN. Overall, this study reveals a compensative increase in emotional networks (i.e., the LN) and a decline in cognitive and primary sensory networks in healthy ageing. These findings may provide insights into network-specific and individual-level targeting during neuromodulation in ageing and ageing-related diseases.

Characterizing cortical responses to short-term multidisciplinary intensive rehabilitation treatment in patients with Parkinson's disease: A transcranial magnetic stimulation and electroencephalography study.

Combined transcranial magnetic stimulation and electroencephalography (TMS-EEG) is a powerful non-invasive tool for qualifying the neurophysiological effects of interventions by recording TMS-induced cortical activation with high temporal resolution and generates reproducible and reliable waves of activity without participant cooperation. Cortical dysfunction contributes to the pathogenesis of the clinical symptoms of Parkinson's disease (PD). Here, we examined changes in cortical activity in patients with PD following multidisciplinary intensive rehabilitation treatment (MIRT). Forty-eight patients with PD received 2 weeks of MIRT. The cortical response was examined following single-pulse TMS over the primary motor cortex by 64-channel EEG, and clinical symptoms were assessed before and after MIRT. TMS-evoked potentials were quantified by the global mean field power, as well as oscillatory power in theta, alpha, beta, and gamma bands, and their clinical correlations were calculated. After MIRT, motor and non-motor symptoms improved in 22 responders, and only non-motor function was enhanced in 26 non-responders. Primary motor cortex stimulation reduced global mean field power amplitudes in responders but not significantly in non-responders. Oscillations exhibited attenuated power in the theta, beta, and gamma bands in responders but only reduced gamma power in non-responders. Associations were observed between beta oscillations and motor function and between gamma oscillations and non-motor symptoms. Our results suggest that motor function enhancement by MIRT may be due to beta oscillatory power modulation and that alterations in cortical plasticity in the primary motor cortex contribute to PD recovery.

Abnormal Dynamic Functional Networks in Subjective Cognitive Decline and Alzheimer's Disease.

Subjective cognitive decline (SCD) is considered to be the preclinical stage of Alzheimer's disease (AD) and has the potential for the early diagnosis and intervention of AD. It was implicated that CSF-tau, which increases very early in the disease process in AD, has a high sensitivity and specificity to differentiate AD from normal aging, and the highly connected brain regions behaved more tau burden in patients with AD. Thus, a highly connected state measured by dynamic functional connectivity may serve as the early changes of AD. In this study, forty-five normal controls (NC), thirty-six individuals with SCD, and thirty-five patients with AD were enrolled to obtain the resting-state functional magnetic resonance imaging scanning. Sliding windows, Pearson correlation, and clustering analysis were combined to investigate the different levels of information transformation states. Three states, namely, the low state, the middle state, and the high state, were characterized based on the strength of functional connectivity between each pair of brain regions. For the global dynamic functional connectivity analysis, statistically significant differences were found among groups in the three states, and the functional connectivity in the middle state was positively correlated with cognitive scales. Furthermore, the whole brain was parcellated into four networks, namely, default mode network (DMN), cognitive control network (CCN), sensorimotor network (SMN), and occipital-cerebellum network (OCN). For the local network analysis, statistically significant differences in CCN for low state and SMN for middle state and high state were found in normal controls and patients with AD. Meanwhile, the differences were also found in normal controls and individuals with SCD. In addition, the functional connectivity in SMN for high state was positively correlated with cognitive scales. Converging results showed the changes in dynamic functional states in individuals with SCD and patients with AD. In addition, the changes were mainly in the high strength of the functional connectivity state.

Task-induced activation transmitted by structural connectivity is associated with behavioral performance.

It is thought that brain structure is the primary determinant of functions of brain regions. For example, cortical areas with functional differences also have different structural connectivity (SC) patterns. We used SCs derived from diffusion tensor imaging (DTI) data in 100 healthy adults included in the Human Connectome Project (HCP) to successfully predict cortical activation responses across distinct cognitive tasks and found that predictive performance varied among tasks. We also observed that predictive performance could be used to characterize task load in both relational reasoning and N-back working memory tasks and was significantly positively associated with behavioral performance. Moreover, we found that the default mode network (DMN) played a more dominant role in both activation prediction and behavioral performance than was found for other functional networks. These results support our hypothesis that individuals who performed tasks better might exhibit a more accurate predicted activation pattern as task-evoked activities are more inclined to flow over inherent structural networks than over more flexible paths. In the high difficulty condition, the decreased correlation between predicted and empirical activation may be associated with the more random brain activity in these conditions/participants due to the lack of engagement. Together, our findings highlight the feasibility of using SCs to estimate various cognitive task activations and thus further facilitate the exploration of the relationship between the brain and behavior by providing strong evidence for the relevance of structure to function in the human brain.

Enhancing Working Memory Based on Mismatch Negativity Neurofeedback in Subjective Cognitive Decline Patients: A Preliminary Study.

Mismatch negativity (MMN) is suitable for studies of preattentive auditory discriminability and the auditory memory trace. Subjective cognitive decline (SCD) is an ideal target for early therapeutic intervention because SCD occurs at preclinical stages many years before the onset of Alzheimer's disease (AD). According to a novel lifespan-based model of dementia risk, hearing loss is considered the greatest potentially modifiable risk factor of dementia among nine health and lifestyle factors, and hearing impairment is associated with cognitive decline. Therefore, we propose a neurofeedback training based on MMN, which is an objective index of auditory discriminability, to regulate sensory ability and memory as a non-pharmacological intervention (NPI) in SCD patients. Seventeen subjects meeting the standardized clinical evaluations for SCD received neurofeedback training. The auditory frequency discrimination test, the visual digital N-back (1-, 2-, and 3-back), auditory digital N-back (1-, 2-, and 3-back), and auditory tone N-back (1-, 2-, and 3-back) tasks were used pre- and post-training in all SCD patients. The intervention schedule comprised five 60-min training sessions over 2 weeks. The results indicate that the subjects who received neurofeedback training had successfully improved the amplitude of MMN at the parietal electrode (Pz). A slight decrease in the threshold of auditory frequency discrimination was observed after neurofeedback training. Notably, after neurofeedback training, the working memory (WM) performance was significantly enhanced in the auditory tone 3-back test. Moreover, improvements in the accuracy of all WM tests relative to the baseline were observed, although the changes were not significant. To the best of our knowledge, our preliminary study is the first to investigate the effects of MMN neurofeedback training on WM in SCD patients, and our results suggest that MMN neurofeedback may represent an effective treatment for intervention in SCD patients and the elderly with aging memory decline.

Effects of an Integrated Neurofeedback System with Dry Electrodes: EEG Acquisition and Cognition Assessment.

Electroencephalogram (EEG) neurofeedback improves cognitive capacity and behaviors by regulating brain activity, which can lead to cognitive enhancement in healthy people and better rehabilitation in patients. The increased use of EEG neurofeedback highlights the urgent need to reduce the discomfort and preparation time and increase the stability and simplicity of the system's operation. Based on brain-computer interface technology and a multithreading design, we describe a neurofeedback system with an integrated design that incorporates wearable, multichannel, dry electrode EEG acquisition equipment and cognitive function assessment. Then, we evaluated the effectiveness of the system in a single-blind control experiment in healthy people, who increased the alpha frequency band power in a neurofeedback protocol. We found that upregulation of the alpha power density improved working memory following short-term training (only five training sessions in a week), while the attention network regulation may be related to other frequency band activities, such as theta and beta. Our integrated system will be an effective neurofeedback training and cognitive function assessment system for personal and clinical use.

Disordered high-frequency oscillation in face processing in schizophrenia patients.

Schizophrenia is a complex disorder characterized by marked social dysfunctions, but the neural mechanism underlying this deficit is unknown. To investigate whether face-specific perceptual processes are influenced in schizophrenia patients, both face detection and configural analysis were assessed in normal individuals and schizophrenia patients by recording electroencephalogram (EEG) data. Here, a face processing model was built based on the frequency oscillations, and the evoked power (theta, alpha, and beta bands) and the induced power (gamma bands) were recorded while the subjects passively viewed face and nonface images presented in upright and inverted orientations. The healthy adults showed a significant face-specific effect in the alpha, beta, and gamma bands, and an inversion effect was observed in the gamma band in the occipital lobe and right temporal lobe. Importantly, the schizophrenia patients showed face-specific deficits in the low-frequency beta and gamma bands, and the face inversion effect in the gamma band was absent from the occipital lobe. All these results revealed face-specific processing in patients due to the disorder of high-frequency EEG, providing additional evidence to enrich future studies investigating neural mechanisms and serving as a marked diagnostic basis.

Correction to: A novel protein derived from lamprey supraneural body tissue with efficient cytocidal actions against tumor cells.

CORRECTION: Unfortunately, following publication of this article [1], it was noticed that the key in Figure 5c incorrectly showed '0 h', '5 h' and '10 h'. The corrected version, showing '0 h', '12 h' and '24 h', can be seen below and the original article has been updated to reflect this.

A novel protein derived from lamprey supraneural body tissue with efficient cytocidal actions against tumor cells.

BACKGROUND: In previous research, we found that cell secretion from the adult lamprey supraneural body tissues possesses cytocidal activity against tumor cells, but the protein with cytocidal activity was unidentified. METHODS: A novel lamprey immune protein (LIP) as defense molecule was first purified and identified in jawless vertebrates (cyclostomes) using hydroxyapatite column and Q Sepharose Fast Flow column. After LIP stimulation, morphological changes of tumor cells were analysed and measured whether in vivo or in vitro. RESULTS: LIP induces remarkable morphological changes in tumor cells, including cell blebbing, cytoskeletal alterations, mitochondrial fragmentation and endoplasmic reticulum vacuolation, and most of the cytoplasmic and organelle proteins are released following treatment with LIP. LIP evokes an elevation of intracellular calcium and inflammatory molecule levels. Our analysis of the cytotoxic mechanism suggests that LIP can upregulate the expression of caspase 1, RIPK1, RIP3 to trigger pyroptosis and necroptosis. To examine the effect of LIP in vivo, tumor xenograft experiments were performed, and the results indicated that LIP inhibits tumor growth without damage to mice. In addition, the cytotoxic action of LIP depended on the phosphatidylserine (PS) content of the cell membrane. CONCLUSIONS: These observations suggest that LIP plays a crucial role in tumor cell survival and growth. The findings will also help to elucidate the mechanisms of host defense in lamprey.

L-C1qDC-1, a novel C1q domain-containing protein from Lethenteron camtschaticum that is involved in the immune response.

The C1q domain-containing (C1qDC) proteins are a family of proteins characterized by a globular C1q (gC1q) domain at their C-terminus. These proteins are involved in various processes in vertebrates and are assumed to serve as important pattern recognition receptors in innate immunity in invertebrates. Here, a novel C1qDC protein from Lethenteron camtschaticum was identified and characterized (designated as L-C1qDC-1). After a partial cDNA sequence of L-C1qDC-1 was identified in a L. camtschaticum liver cDNA library, the full-length cDNA was obtained using 3'- and 5'-rapid amplification of cDNA ends (RACE). L-C1qDC-1 encodes 236 amino acids and contains a signal peptide, a collagen-like sequence with Gly-Xaa-Yaa repeats, and a C-terminal gC1q domain. The L-C1qDC-1 protein was primarily distributed in the gut, liver and supraneural body of L. camtschaticum and was also marginally detectable in leukocytes via real-time PCR and immunofluorescence assays. Furthermore, both immunoprecipitation and immunofluorescence results showed that in L. camtschaticum serum, L-C1qDC-1 could interact with variable lymphocyte receptor (VLR) B and displayed strong colocalization with cancer cell immune responses. These results indicated that the L-C1qDC-1 gene encodes a novel C1qDC protein that may play an important role in the immune responses of L. camtschaticum, providing clues for understanding the universal functions of C1qDC proteins in other species and suggesting that these proteins could serve as pattern recognition molecules in immunotherapy.