Search Results (410)

Motor impairment is a critical health issue that restricts disabled people from living their lives normally and with comfort. Detecting motor imagery (MI) in electroencephalography (EEG) signals can make their lives easier. There has been a lot of work on detecting two or four different MI movements, which include bilateral, contralateral, and unilateral upper limb movements. However, there is little research on the challenging problem of detecting more than four motor imagery tasks and unilateral lower limb movements. As a solution to this problem, a spectral-spatio-temporal multiscale network (SSTMNet) has been introduced to detect six imagery tasks. It first performs a spectral analysis of an EEG trial and attends to the salient brain waves (rhythms) using an attention mechanism. Then, the temporal dependency across the entire EEG trial is worked out using a temporal dependency block, resulting in spectral-spatio-temporal features, which are passed to a multiscale block to learn multiscale spectral-–spatio-temporal features. Finally, these features are deeply analyzed by a sequential block to extract high-level features, which are used to detect an MI task. In addition, to deal with the small dataset problem for each MI task, the researchers introduce a data augmentation technique based on Fourier transform, which generates new EEG trials from EEG signals belonging to the same class in the frequency domain, with the idea that the coefficients of the same frequencies must be fused, ensuring label-preserving trials. SSTMNet is thoroughly evaluated on a public-domain benchmark dataset; it achieves an accuracy of 77.52% and an F1-score of 56.19%. t-SNE plots, confusion matrices, and ROC curves are presented, which show the effectiveness of SSTMNet. Furthermore, when it is trained on augmented data generated by the proposed data augmentation method, it results in a better performance, which validates the effectiveness of the proposed technique. The results indicate that its performance is comparable with the state-of-the-art methods. An analysis of the features learned by the model reveals that the block architectural design aids the model in distinguishing between multi-imagery tasks. Full article

Background: ATP-binding cassette (ABC) transporters are expressed in the vascular walls of brain capillaries and remove toxic chemicals from the brain. The expression of ABC transporters in peripheral organs is transcriptionally regulated by clock genes and exhibits 24 h periodic fluctuations. In addition, clock gene outputs diminish with aging. In this study, we evaluated whether the expression of ABC transporters in the blood–brain barrier (BBB) of young mice had a 24 h cycle, and whether the expression of ABC transporters in the BBB decreased with age. Methods: Brain microvascular (BMV) fractions from the cerebral cortex of male C57BL/6J mice were prepared using dextran. BMV fractions from young mice (12 weeks old) were prepared every four hours to evaluate 24 h rhythmicity. BMV fractions from both young and aged mice (85 weeks old) were prepared when protein expression peaked (Zeitgeber Time 5). Protein and mRNA expression of ABC transporters in BMV fractions were measured. Results: In young mice, protein expression of P-glycoprotein, breast cancer resistance protein, and multidrug resistance protein 4 showed time-dependent variations with a peak in the light phase (Zeitgeber Time 5); mRNA expression showed no time-dependent variation. The protein expression of these transporters was lower in the BBB of aged mice than in that of young mice, although mRNA expression did not differ between young and aged mice. Conclusions: ABC transporter protein expression levels in BMV endothelial cells decreased with aging; however, mRNA levels did not change, which suggests changes in protein expression did not result from diminished clock gene output. Further studies are needed to elucidate the mechanisms by which ABC transporter expression in the BBB decreases with aging. Full article

Wearable devices have gained increasing attention for use in multifunctional applications related to health monitoring, particularly in research of the circadian rhythms of cognitive functions and metabolic processes. In this comprehensive review, we encompass how wearables can be used to study circadian rhythms in health and disease. We highlight the importance of these rhythms as markers of health and well-being and as potential predictors for health outcomes. We focus on the use of wearable technologies in sleep research, circadian medicine, and chronomedicine beyond the circadian domain and emphasize actigraphy as a validated tool for monitoring sleep, activity, and light exposure. We discuss various mathematical methods currently used to analyze actigraphic data, such as parametric and non-parametric approaches, linear, non-linear, and neural network-based methods applied to quantify circadian and non-circadian variability. We also introduce novel actigraphy-derived markers, which can be used as personalized proxies of health status, assisting in discriminating between health and disease, offering insights into neurobehavioral and metabolic status. We discuss how lifestyle factors such as physical activity and light exposure can modulate brain functions and metabolic health. We emphasize the importance of establishing reference standards for actigraphic measures to further refine data interpretation and improve clinical and research outcomes. The review calls for further research to refine existing tools and methods, deepen our understanding of circadian health, and develop personalized healthcare strategies. Full article

Background: Neuroplasticity, involving cortical and subcortical reorganization, plays a critical role in the adaptation and compensation process post-amputation. However, underlying neurophysiological changes remain unclear, particularly in brain oscillations. Methods: This is a cross-sectional analysis that includes baseline data from 48 individuals with lower limb amputation from our DEFINE Cohort Study project. EEG data were collected using a 64-channel system during a 5-min resting-state period. Preprocessed data were analyzed for delta and alpha oscillations across frontal, central, and parietal regions. Logistic regression models examined associations between EEG oscillations and clinical variables, including cognition (MoCA), functional independence (FIM), and phantom limb sensations (PLS). Results: The multivariate logistic regression analysis revealed distinct patterns of association between EEG oscillations and clinical variables. Delta oscillations were inversely associated with cognitive scores (OR: 0.69; p = 0.048), while higher delta power was related to the absence of PLS (OR: 58.55; p < 0.01). Frontal alpha power was positively linked to cognitive function (OR: 1.55; p = 0.02) but negatively associated with functional independence (OR: 0.75; p = 0.04). Conclusions: These findings suggest that lower frequencies, such as delta oscillations, play a role as potential compensatory brain rhythms. In contrast, alpha oscillations may reflect a more adapted pattern of brain reorganization after amputation. Full article

Sleep disruption and deprivation are epidemic problems in the United States, even among those without a clinically diagnosed sleep disorder. Military service members demonstrate an increased risk of insomnia, which doubles after deployment. This study will investigate the ability of a translational device, Teledyne PeakSleep™ (Teledyne Scientific & Imaging, Durham, NC, USA), to reduce sleep onset latency and the time spent awake after sleep onset, with improvement in the subjective benefits of sleep for patients with insomnia by enhancing the brain rhythms within the frontal lobe implicated in slow wave generation. During this crossover trial, patients will use the wearable neurotechnology prototype headband, which delivers < 14 min of frontal short duration repetitive–transcranial electrical stimulation over a 30 min period immediately before trying to fall asleep. Using active stimulation versus a sham paradigm, we will compare actigraphy data, physiological data, and subjective sleep measures against a pre-treatment baseline in the same patient over the course of the 8-week study. If successful, PeakSleep™ could address the final common pathway in insomnia, namely the onset and maintenance of slow-wave sleep (SWS), and accordingly has the potential to enhance sleep onset in a wide range of individuals, most importantly warfighters in whom efficient sleep onset may be critical for operational success. Full article

Emotion recognition is an advanced technology for understanding human behavior and psychological states, with extensive applications for mental health monitoring, human–computer interaction, and affective computing. Based on electroencephalography (EEG), the biomedical signals naturally generated by the brain, this work proposes a resource-efficient multi-entropy fusion method for classifying emotional states. First, Discrete Wavelet Transform (DWT) is applied to extract five brain rhythms, i.e., delta, theta, alpha, beta, and gamma, from EEG signals, followed by the acquisition of multi-entropy features, including Spectral Entropy (PSDE), Singular Spectrum Entropy (SSE), Sample Entropy (SE), Fuzzy Entropy (FE), Approximation Entropy (AE), and Permutation Entropy (PE). Then, such entropies are fused into a matrix to represent complex and dynamic characteristics of EEG, denoted as the Brain Rhythm Entropy Matrix (BREM). Next, Dynamic Time Warping (DTW), Mutual Information (MI), the Spearman Correlation Coefficient (SCC), and the Jaccard Similarity Coefficient (JSC) are applied to measure the similarity between the unknown testing BREM data and positive/negative emotional samples for classification. Experiments were conducted using the DEAP dataset, aiming to find a suitable scheme regarding similarity measures, time windows, and input numbers of channel data. The results reveal that DTW yields the best performance in similarity measures with a 5 s window. In addition, the single-channel input mode outperforms the single-region mode. The proposed method achieves 84.62% and 82.48% accuracy in arousal and valence classification tasks, respectively, indicating its effectiveness in reducing data dimensionality and computational complexity while maintaining an accuracy of over 80%. Such performances are remarkable when considering limited data resources as a concern, which opens possibilities for an innovative entropy fusion method that can help to design portable EEG-based emotion-aware devices for daily usage. Full article

Methamphetamine is a highly addictive stimulant known to cause neurotoxicity, cognitive deficits, and immune dysregulation in the brain. Despite significant research, the molecular mechanisms driving methamphetamine-induced neurotoxicity and glial cell dysfunction remain poorly understood. This study investigates how methamphetamine disrupts glial cell function and contributes to neurodevelopmental and neurodegenerative processes. Using single-cell RNA sequencing (scRNA-seq), we analyzed the transcriptomes of 4000 glial cell-associated genes from the cortical regions of mice chronically administered methamphetamine. Methamphetamine exposure altered the key pathways in astrocytes, including the circadian rhythm and cAMP signaling; in microglia, affecting autophagy, ubiquitin-mediated proteolysis, and mitophagy; and in oligodendrocytes, disrupting lysosomal function, cytoskeletal regulation, and protein processing. Notably, several transcription factors, such as Zbtb16, Hif3a, Foxo1, and Klf9, were significantly dysregulated in the glial cells. These findings reveal profound methamphetamine-induced changes in the glial transcriptomes, particularly in the cortical regions, highlighting potential molecular pathways and transcription factors as targets for therapeutic intervention. This study provides novel insights into the glial-mediated mechanisms of methamphetamine toxicity, contributing to our understanding of its effects on the central nervous system and laying the groundwork for future strategies to mitigate its neurotoxic consequences. Full article

Melatonin is a critical regulator of biological rhythms across organisms, transducing light signals into neuroendocrine signals that facilitate reproductive regulation in response to environmental cues. However, the precise mechanisms through which melatonin regulates reproduction in fish require further investigation. In this study, we employed molecular and organizational biological techniques to examine the expression patterns of melatonin and its five receptor subtypes (LcMTNR1A1, LcMTNR1A2, LcMTNR1B1, LcMTNR1B2, and LcMTNR1C) in various tissues of the large yellow croaker (Larimichthys crocea). Our results revealed significant expression of all receptors in the pituitary and testes, with distinct gender differences, including a lack of expression in the ovary. Moreover, our data indicate that melatonin and its receptors are primarily expressed during stage III, highlighting their role in sexual maturity. Enzyme- linked immunosorbent assay (ELISA) results further demonstrated that in vitro melatonin incubation in the brain of L. crocea influenced gonadotropin-releasing hormone (GnRH) and testosterone secretion in a dose-dependent manner, suggesting actions beyond the classical hypothalamic–pituitary–gonadal (HPG) axis. Overall, our findings provide new evidence supporting the role of the melatonin system in reproductive regulation in marine teleosts. Full article

Alterations in epigenetic modifications, like DNA methylation, in peripheral blood could serve as a useful, minimally invasive biomarker of the effects of anti-aging interventions. This study explores this potential with a water extract of the botanical Centella asiatica (CAW). Eighteen-month-old mice were treated with CAW in their drinking water for 5 weeks alongside vehicle-treated eighteen-month-old C57BL6 mice. Reduced representation bisulfite sequencing (RRBS) was used to identify genome-wide differential methylation in the blood of CAW-treated aged mice compared to vehicle-treated aged mice. Our results showed a distinct enrichment of differentially methylated regions (DMRs) nearby genes involved in biological processes relevant to aging (i.e., antioxidant response, metabolic regulation, cellular metabolism). A distinct difference was observed between males and females in both the number of methylation sites and the state of methylation. Moreover, genes nearby or overlapping DMRs were found to be enriched for biological processes related to previously described cellular effects of CAW in the mouse brain (i.e., antioxidant response, metabolic regulation, calcium regulation, and circadian rhythm). Together, our data suggest that the peripheral blood methylation signature of CAW in the blood could be a useful, and readily accessible, biomarker of CAW’s effects in aging. Full article

Patients with mild cognitive impairment due to Alzheimer’s disease (ADMCI) typically show abnormally high delta (<4 Hz) and low alpha (8–12 Hz) rhythms measured from resting-state eyes-closed electroencephalographic (rsEEG) activity. Here, we hypothesized that the abnormalities in rsEEG activity may be greater in ADMCI patients than in those with MCI not due to AD (noADMCI). Furthermore, they may be associated with the diagnostic cerebrospinal fluid (CSF) amyloid–tau biomarkers in ADMCI patients. An international database provided clinical–demographic–rsEEG datasets for cognitively unimpaired older (Healthy; N = 45), ADMCI (N = 70), and noADMCI (N = 45) participants. The rsEEG rhythms spanned individual delta, theta, and alpha frequency bands. The eLORETA freeware estimated cortical rsEEG sources. Posterior rsEEG alpha source activities were reduced in the ADMCI group compared not only to the Healthy group but also to the noADMCI group (p < 0.001). Negative associations between the CSF phospho-tau and total tau levels and posterior rsEEG alpha source activities were observed in the ADMCI group (p < 0.001), whereas those with CSF amyloid beta 42 levels were marginal. These results suggest that neurophysiological brain neural oscillatory synchronization mechanisms regulating cortical arousal and vigilance through rsEEG alpha rhythms are mainly affected by brain tauopathy in ADMCI patients. Full article

Background: The human sensorimotor system can naturally synchronize with environmental rhythms, such as light pulses or sound beats. Several studies showed that different styles and tempos of music, or other rhythmic stimuli, have an impact on physiological rhythms, including electrocortical brain activity, heart rate, and motor coordination. Such synchronization, also known as the “entrainment effect”, has been identified as a crucial mechanism impacting cognitive, motor, and affective functioning. Objectives: This review examines theoretical and empirical contributions to the literature on entrainment, with a particular focus on the physiological mechanisms underlying this phenomenon and its role in cognitive, motor, and affective functions. We also address the inconsistent terminology used in the literature and evaluate the range of measurement approaches used to assess entrainment phenomena. Finally, we propose a definition of “physiological entrainment” that emphasizes its role as a fundamental mechanism that encompasses rhythmic interactions between the body and its environment, to support information processing across bodily systems and to sustain adaptive motor responses. Methods: We reviewed the recent literature through the lens of the “embodied cognition” framework, offering a unified perspective on the phenomenon of physiological entrainment. Results: Evidence from the current literature suggests that physiological entrainment produces measurable effects, especially on neural oscillations, heart rate variability, and motor synchronization. Eventually, such physiological changes can impact cognitive processing, affective functioning, and motor coordination. Conclusions: Physiological entrainment emerges as a fundamental mechanism underlying the mind–body connection. Entrainment-based interventions may be used to promote well-being by enhancing cognitive, motor, and affective functions, suggesting potential rehabilitative approaches to enhancing mental health. Full article

Circadian rhythms are intrinsic, 24 h cycles that regulate key physiological, mental, and behavioral processes, including sleep–wake cycles, hormone secretion, and metabolism. These rhythms are controlled by the brain’s suprachiasmatic nucleus, which synchronizes with environmental signals, such as light and temperature, and consequently maintains alignment with the day–night cycle. Molecular feedback loops, driven by core circadian “clock genes”, such as Clock, Bmal1, Per, and Cry, are essential for rhythmic gene expression; disruptions in these feedback loops are associated with various health issues. Dysregulated lipid metabolism in the brain has been implicated in the pathogenesis of neurological disorders by contributing to oxidative stress, neuroinflammation, and synaptic dysfunction, as observed in conditions such as Alzheimer’s and Parkinson’s diseases. Disruptions in circadian gene expression have been shown to perturb lipid regulatory mechanisms in the brain, thereby triggering neuroinflammatory responses and oxidative damage. This review synthesizes current insights into the interconnections between circadian rhythms and lipid metabolism, with a focus on their roles in neurological health and disease. It further examines how the desynchronization of circadian genes affects lipid metabolism and explores the potential mechanisms through which disrupted circadian signaling might contribute to the pathophysiology of neurodegenerative disorders. Full article

Circadian rhythms are important for maintaining homeostasis, from regulating physiological activities (e.g., sleep–wake cycle and cognitive performance) to cellular processes (e.g., cell cycle and DNA damage repair). Melatonin is a key regulator of circadian rhythms and exerts control by binding to melatonin receptor 1 (MT1), decreasing neuronal firing in the suprachiasmatic nucleus (SCN). Previous work studying effects of melatonin on circadian rhythms utilized in vivo models. Since MT1 is also expressed outside of the brain, it is important to study impacts of melatonin on circadian gene oscillations in vitro. We evaluated the effects of melatonin and an MT1 inverse agonist, UCSF7447, in U2OS circadian reporter cell lines, which facilitate detailed assessments of oscillatory changes. We report that cellular circadian rhythms are responsive to treatment with MT1-targeting molecules; their activities are not dependent upon the SCN. Corroborating in vivo data, both melatonin and UCSF7447 lengthened the periods of BMAL1 and PER2, and while melatonin delayed circadian phases, UCSF7447 advanced them. Compounds were also dosed at two different times, however this did not yield changes. Our findings indicate the importance of utilizing in vitro models and that the direct effects of melatonin likely go beyond the SCN and should be explored further. Full article

Anxiety is a widespread mental health issue, and binaural beats have been explored as a potential non-invasive treatment. EEG data reveal changes in neural oscillation and connectivity linked to anxiety reduction; however, harmonics introduced during signal acquisition and processing often distort these findings. Existing methods struggle to effectively reduce harmonics and capture the fine-grained temporal dynamics of EEG signals, leading to inaccurate feature extraction. Hence, a novel Denoised Harmonic Subtraction and Transient Temporal Feature Extraction is proposed to improve the analysis of the impact of binaural beats on anxiety levels. Initially, a novel Wiener Fused Convo Filter is introduced to capture spatial features and eliminate linear noise in EEG signals. Next, an Intrinsic Harmonic Subtraction Network is employed, utilizing the Attentive Weighted Least Mean Square (AW-LMS) algorithm to capture nonlinear summation and resonant coupling effects, effectively eliminating the misinterpretation of brain rhythms. To address the challenge of fine-grained temporal dynamics, an Embedded Transfo XL Recurrent Network is introduced to detect and extract relevant parameters associated with transient events in EEG data. Finally, EEG data undergo harmonic reduction and temporal feature extraction before classification with a cross-correlated Markov Deep Q-Network (DQN). This facilitates anxiety level classification into normal, mild, moderate, and severe categories. The model demonstrated a high accuracy of 95.6%, precision of 90%, sensitivity of 93.2%, and specificity of 96% in classifying anxiety levels, outperforming previous models. This integrated approach enhances EEG signal processing, enabling reliable anxiety classification and offering valuable insights for therapeutic interventions. Full article

Entropy management, central to the Free Energy Principle, requires a process that temporarily shifts brain activity toward states of lower or higher entropy. Metastable synchronization is a process by which a system achieves entropy fluctuations by intermittently transitioning between states of collective order and disorder. Previous work has shown that collective oscillations, similar to those recorded from the brain, emerge spontaneously from weakly stable synchronization in critically coupled oscillator systems. However, direct evidence linking the formation of collective oscillations to entropy fluctuations is lacking. In this short communication, we demonstrate how the emergence of Metastable Oscillatory Modes (MOMs) is directly associated with a temporary reduction in entropy in the ongoing dynamics. We apply Shannon entropy to the distribution of eigenvalues of phase covariance over sliding time windows, capturing the temporal evolution of entropy at the level of the entire dynamical system. By demonstrating how the formation of MOMs impacts a system’s entropy levels, we bridge theoretical works on the physics of coupled oscillators with the FEP framework, supporting the hypothesis that brain rhythms recorded experimentally are a signature of entropy management. Full article