Post-stroke aphasia is associated with a significantly elevated risk of depression, yet the underlying mechanisms remain unclear. This study recorded 64-channel electroencephalogram data and depression scale scores from 12 aphasic patients with depression, 8 aphasic patients without depression, and 12 healthy controls during resting state and an emotional Stroop task. Spectral and microstate analyses were conducted to examine brain activity patterns across conditions. Results showed that depression scores significantly negatively explained the occurrence of microstate class C and positively explained the transition probability from microstate class A to B. Furthermore, aphasic patients with depression exhibited increased alpha-band activation in the frontal region. These findings suggest distinct neural features in aphasic patients with depression and offer new insights into the mechanisms contributing to their heightened vulnerability to depression.
Humans ; Electroencephalography ; Aphasia/etiology* ; Stroop Test ; Emotions/physiology* ; Depression/etiology* ; Male ; Female ; Middle Aged ; Stroke/complications* ; Brain/physiopathology* ; Aged ; Adult ; Rest/physiology*

In recent years, it has become a new direction in the field of neuroscience to explore the mode characteristics, functional significance and interaction mechanism of resting spontaneous electroencephalography (EEG) and task-evoked EEG. This paper introduced the basic characteristics of spontaneous EEG and task-evoked EEG, and summarized the core role of spontaneous EEG in shaping the adaptability of the nervous system. It focused on how the spontaneous EEG interacted with the task-evoked EEG in the process of task processing, and emphasized that the spontaneous EEG could significantly affect the performance of tasks such as perception, cognition and movement by regulating neural activities and predicting external stimuli. These studies provide an important theoretical basis for in-depth understanding of the principle and mechanism of brain information processing in resting and task states, and point out the direction for further exploring the complex relationship between them in the future.
Humans ; Electroencephalography/methods* ; Brain/physiology* ; Rest/physiology* ; Cognition/physiology* ; Evoked Potentials/physiology* ; Task Performance and Analysis

Meditation aims to guide individuals into a state of deep calm and focused attention, and in recent years, it has shown promising potential in the field of medical treatment. Numerous studies have demonstrated that electroencephalogram (EEG) patterns change during meditation, suggesting the feasibility of using deep learning techniques to monitor meditation states. However, significant inter-subject differences in EEG signals poses challenges to the performance of such monitoring systems. To address this issue, this study proposed a novel model-calibrated multi-source adversarial adaptation network (CMAAN). The model first trained multiple domain-adversarial neural networks in a pairwise manner between various source-domain individuals and the target-domain individual. These networks were then integrated through a calibration process using a small amount of labeled data from the target domain to enhance performance. We evaluated the proposed model on an EEG dataset collected from 18 subjects undergoing methamphetamine rehabilitation. The model achieved a classification accuracy of 73.09%. Additionally, based on the learned model, we analyzed the key EEG frequency bands and brain regions involved in the meditation process. The proposed multi-source domain adaptation framework improves both the performance and robustness of EEG-based meditation monitoring and holds great promise for applications in biomedical informatics and clinical practice.
Humans ; Electroencephalography/methods* ; Meditation ; Calibration ; Neural Networks, Computer ; Brain/physiology* ; Rest/physiology* ; Deep Learning ; Signal Processing, Computer-Assisted

Depression is increasingly prevalent among adolescents and can profoundly impact their lives. However, the early detection of depression is often hindered by the time-consuming diagnostic process and the absence of objective biomarkers. In this study, we propose a novel approach for depression detection based on an affective brain-computer interface (aBCI) and the resting-state electroencephalogram (EEG). By fusing EEG features associated with both emotional and resting states, our method captures comprehensive depression-related information. The final depression detection model, derived through decision fusion with multiple independent models, further enhances detection efficacy. Our experiments involved 40 adolescents with depression and 40 matched controls. The proposed model achieved an accuracy of 86.54% on cross-validation and 88.20% on the independent test set, demonstrating the efficiency of multimodal fusion. In addition, further analysis revealed distinct brain activity patterns between the two groups across different modalities. These findings hold promise for new directions in depression detection and intervention.
Humans ; Male ; Female ; Adolescent ; Case-Control Studies ; Depression/diagnosis* ; Early Diagnosis ; Rest ; Electroencephalography/methods* ; Brain-Computer Interfaces ; Models, Psychological ; Reproducibility of Results ; Affect/physiology* ; Photic Stimulation/methods* ; Video Recording ; Brain/physiopathology*

OBJECTIVETo study the changes in cardiopulmonary function induced by mid/long-term simulated microgravity with 6° head down bed rest (HDBR), and the effects of Taikong Yangxin Prescription (, TYP) as a countermeasure.

METHODSFourteen healthy male volunteers were randomly divided into a control group and a Chinese medicine (CM) group (7 in each group) by a random digital table based on their body weight. Both groups underwent 6° HDBR for 60 days. Subjects in the CM group received daily TYP pills and subjects in the control group received daily placebo pills. Cardiac systolic and pumping functions were measured by echocardiography before HDBR; on days 20, 42, and 57 of HDBR; and on day 3 of recovery after HDBR (R+3). Cardiopulmonary functional reserve and exercise capacity were evaluated before HDBR, on day 29, and on day R+3 by exercise testing.

RESULTSThe heart rate (HR) increased gradually during HDBR. The HR was significantly higher on day 57 than before HDBR in the control group (P<0.05), but did not increase significantly in the CM group. The stroke volume/stroke volume index, ejection fraction, and left ventricular fractional shortening tended to decrease over time in the control group, but not in the CM group. These parameters were significantly higher in the CM group than in the control group on day 42 (P<0.05 or <0.01). Exercise testing showed that maximum O2 consumption (VO2max), metabolic equivalents, relative O2 consumption (VO2), O2 pulse, and exercise duration were significantly lower on day 29 than before HDBR in the control group, but not in the CM group.

CONCLUSIONSSixty days of 6° HDBR induced a reduction in cardiac systolic and pumping functions, and reduced cardiopulmonary functional reserve and exercise capacity. Administration of TYP significantly improved cardiac systolic and pumping functions, and maintained cardiopulmonary functional reserve and exercise capacity.

Adult ; Bed Rest ; Drugs, Chinese Herbal ; Exercise Test ; Heart ; physiology ; Humans ; Lung ; physiology ; Male

OBJECTIVETo investigate whether the neural representations underlying alternating two acupoint combinations (ACs) are the same or not.

METHODSIn this functional magnetic resonance imaging study, two sets of analgesia ACs were utilized, including Waiguan (TE5) and Qiuxu (GB40) for Group A, and Neiguan (PC6) and Taichong (LR3) for Group B, which are the most commonly adopted in clinical treatment. Each group had 20 healthy subjects. An experimental design was proposed, which consisted of a pre-needling resting phase, a needling phase and a post-needling resting phase. This paradigm optimally mimics the clinical protocol as well as focuses on both the stimulation and the resting periods. The results were subjected to general linear model analysis, conjunction analysis and the functional connectivity analysis.

RESULTSThe rostral anterior cingulated cortex was engaged in the initiative period of the acupuncture effect in both groups, and it was chosen as the seed region for the functional connectivity analysis for the following resting period. The results showed that several shared brain regions were involved in both groups, in particular the insula, amygdala and hypothalamus. Moreover, significant differences were located at the posterior cingulated cortex as revealed by a two sample -test (P<0.05, corrected). Other regions showed no significant differences. This finding was further supported by the spatial correlation analysis that the two groups were significantly correlated (r =0.51, P<0.01).

CONCLUSIONThis preliminary research helps us understand the neurophysiological mechanisms of acupuncture when following clinical guidelines on ACs, as well as provides an important opportunity to develop better treatment strategies for reducing, or even preventing pain.

Acupuncture Points ; Acupuncture Therapy ; Female ; Gyrus Cinguli ; physiology ; Humans ; Magnetic Resonance Imaging ; Male ; Nerve Net ; physiology ; Nervous System Physiological Phenomena ; Psychophysics ; Rest ; Signal Processing, Computer-Assisted ; Statistics as Topic ; Young Adult

OBJECTIVETo investigate the age-related changes in resting functional connectivity of the marginal division (MrD) of the neostriatum in healthy adults detected using resting-state functional magnetic resonance imaging (rs-fMRI).

METHODSForty-four healthy volunteers aged between 22 and 44 years (mean 30.36∓6.31 years) and 20 elderly volunteers aged between 48-83 years (mean 61.4∓10.25 years) underwent conventional MRI, 3D structural MRI and rs-fMRI. MrD was defined manually on the structural images for computation of the functional connectivity maps. The single group data were analyzed with independent sample t test, and the data of the two-group were examined by analysis of covariance with gender as the covariance.

RESULTSIn the young volunteers, the brain regions of functional connectivity related with the MrD were located in bilateral middle cingulate gyri, putamen, thalamus and amygdala, as compared with the brain regions of the bilateral putamen, thalamus, amygdala, insular cortex, rolandic operculum and right supramarginal gyrus in the elderly volunteers. Compared with the young volunteers, the elderly volunteers showed decreased functional connectivity related with the MrD in the bilateral middle cingulate gyri, parahippocampal gyri and left hippocampus.

CONCLUSIONAn increased age is associated with alterations in the functional connectivity related with the MrD in healthy adults.

Adult ; Age Factors ; Aged ; Aged, 80 and over ; Female ; Humans ; Limbic System ; physiology ; Magnetic Resonance Imaging ; methods ; Male ; Middle Aged ; Neural Pathways ; Rest ; Young Adult

Vigilance is defined as the ability to maintain attention or alertness over prolonged periods of time. Since Mid-20th century, following the increasing man-machine communication, high level of vigilance has been demanded in many areas including driving safety, medical care and therapy, aerospace and military affairs, etc. Therefore, finding quick methods to improve the level of vigilance has become a key issue in medical study. Based on physical regulation, chemical regulation and physiological regulation, the research progress has been summarized in this paper. We, furthermore, also try to predict the future trend in this academic area and develop some tentative ideas about seeking more effective and convenient ways to improve the level of brain vigilance.
Arousal ; physiology ; Attention ; Brain ; physiology ; Coffee ; Humans ; Light ; Rest ; physiology ; Sound

OBJECTIVEEnergy metabolism of critically ill children has its own characteristics, especially for those undergoing mechanical ventilation. We tried to assess the energy expenditure status and evaluate the use of predictive equations in such children. Moreover, the characteristics of the energy metabolism among various situation were explored.

METHODFifty critically ill children undergoing mechanical ventilation were selected in this study. Data produced during the 24 hours of mechanical ventilation were collected for computation of severity of illness. Resting energy expenditure (REE) was determined at 24 hours after mechanical ventilation (MREE). Predictive resting energy expenditure (PREE) was calculated for each subject using age-appropriate equations (Schofield-HTWT, White). The study was approved by the hospital medical ethics committee and obtained parental written informed consent.

RESULTThe pediatric risk of mortality score 3 (PRISM3) and pediatric critical illness score (PCIS) were (7 ± 3) and (82 ± 4), respectively. MREE, Schofield-HTWT equation PREE and White equation PREE were (404.80 ± 178.28), (462.82 ± 160.38) and (427.97 ± 152.30) kcal/d, respectively; 70% were hypometabolic and 10% were hypermetabolic. MREE and PREE which were calculated using Schofield-HTWT equation and White equation, both were higher than MREE (P = 0.029). Correlation analysis was performed between PRISM3 and PCIS with MREE. There were no statistically significant correlation (P > 0.05).

CONCLUSIONThe hypometabolic response is apparent in critically ill children with mechanical ventilation; Schofield-HTWT equation and White equation could not predict energy requirements within acceptable clinical accuracy. In critically ill children undergoing mechanical ventilation, the energy expenditure is not correlated with the severity of illness.

Basal Metabolism ; physiology ; Body Weight ; Calorimetry, Indirect ; Child ; Child, Preschool ; Critical Illness ; Energy Metabolism ; physiology ; Female ; Humans ; Infant ; Intensive Care Units, Pediatric ; Male ; Nutritional Requirements ; Oxygen Consumption ; Predictive Value of Tests ; Prospective Studies ; Respiration, Artificial ; Rest ; physiology ; Severity of Illness Index

OBJECTIVE: Resting-state networks (RSNs), including the default mode network (DMN), have been considered as markers of brain status such as consciousness, developmental change, and treatment effects. The consistency of functional connectivity among RSNs has not been fully explored, especially among resting-state-related independent components (RSICs). MATERIALS AND METHODS: This resting-state fMRI study addressed the consistency of functional connectivity among RSICs as well as their spatial consistency between 'at day 1' and 'after 4 weeks' in 13 healthy volunteers. RESULTS: We found that most RSICs, especially the DMN, are reproducible across time, whereas some RSICs were variable in either their spatial characteristics or their functional connectivity. Relatively low spatial consistency was found in the basal ganglia, a parietal region of left frontoparietal network, and the supplementary motor area. The functional connectivity between two independent components, the bilateral angular/supramarginal gyri/intraparietal lobule and bilateral middle temporal/occipital gyri, was decreased across time regardless of the correlation analysis method employed, (Pearson's or partial correlation). CONCLUSION: RSICs showing variable consistency are different between spatial characteristics and functional connectivity. To understand the brain as a dynamic network, we recommend further investigation of both changes in the activation of specific regions and the modulation of functional connectivity in the brain network.
Brain/*physiology ; Brain Mapping ; Humans ; Image Processing, Computer-Assisted ; Magnetic Resonance Imaging/*methods ; Male ; Neural Pathways/*physiology ; Regression Analysis ; Rest/*physiology ; Young Adult