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Deprivation of sleep (DS) and its effects on circadian rhythm gene expression are not well understood despite their influence on various physiological and psychological processes. This study aimed to elucidate the changes in the expression of circadian rhythm genes following a night of sleep and DS. Their correlation with sleep architecture and physical activity was also examined. The study included 81 participants who underwent polysomnography (PSG) and DS with actigraphy. Blood samples were collected after PSG and DS. Expression levels of brain and muscle ARNT-like 1 (BMAL1), circadian locomotor output cycles kaput (CLOCK), neuronal PAS domain protein 2 (NPAS2), period 1 (PER1), cryptochrome 1 (CRY1) and nuclear receptor subfamily 1 group D member 1 (NR1D1) were analyzed using qRT-PCR. DS decreased the expression of CLOCK and BMAL1 while increasing PER1. PER1 expression correlated positively with total sleep time and non-rapid-eye-movement (NREM) sleep duration and negatively with sleep latency, alpha, beta and delta waves in the O1A2 lead. Physical activity during DS showed positive correlations with CLOCK, BMAL1, and CRY1. The findings highlight the role of PER1 in modulating sleep patterns, suggesting potential targets for managing sleep-related disorders. Further research is essential to deepen the understanding of these relationships and their implications. [ABSTRACT FROM AUTHOR]

Olfactory oscillations may enhance cognitive processing through coupling with beta (β, 15–30 Hz) and gamma (γ, 30–160 Hz) activity in the hippocampus (HPC). We hypothesize that coupling between olfactory bulb (OB) and HPC oscillations is increased by cholinergic activation in control rats and is reduced in kainic‐acid‐treated epileptic rats, a model of temporal lobe epilepsy. OB γ2 (63–100 Hz) power was higher during walking and immobility‐awake (IMM) compared to sleep, while γ1 (30–57 Hz) power was higher during grooming than other behavioral states. Muscarinic cholinergic agonist pilocarpine (25 mg/kg ip) with peripheral muscarinic blockade increased OB power and OB‐HPC coherence at β and γ1 frequency bands. A similar effect was found after physostigmine (0.5 mg/kg ip) but not scopolamine (10 mg/kg ip). Pilocarpine increased bicoherence and cross‐frequency coherence (CFC) between OB slow waves (SW, 1–5 Hz) and hippocampal β, γ1 and γ2 waves, with stronger coherence at CA1 alveus and CA3c than CA1 stratum radiatum. Bicoherence further revealed a nonlinear interaction of β waves in OB with β waves at the CA1‐alveus. Beta and γ1 waves in OB or HPC were segregated at one phase of the OB‐SW, opposite to the phase of γ2 and γ3 (100–160 Hz) waves, suggesting independent temporal processing of β/γ1 versus γ2/γ3 waves. At CA1 radiatum, kainic‐acid‐treated epileptic rats compared to control rats showed decreased theta power, theta‐β and theta‐γ2 CFC during baseline walking, decreased CFC of HPC SW with γ2 and γ3 waves during baseline IMM, and decreased coupling of OB SW with β and γ2 waves at CA1 alveus after pilocarpine. It is concluded that β and γ waves in the OB and HPC are modulated by a slow respiratory rhythm, in a cholinergic and behavior‐dependent manner, and OB‐HPC functional connectivity at β and γ frequencies may enhance cognitive functions. [ABSTRACT FROM AUTHOR]

Background: Long-Covid, characterized by persistent symptoms following acute Covid-19 infection, represents a complex challenge for the scientific community. Among the most common and debilitating manifestations, cognitive fog is a neurological disorder characterized by mental confusion and cognitive difficulties. In this study, we investigated the long-term effects of previous Covid-19 infection on cortical brain activity in patients experiencing cognitive fog symptoms in the medium and long term. Methods: A total of 40 subjects (20 females and 20 males) aged between 45 and 70 years (mean age (M) = 59.78, standard deviation (SD) = 12.93) participated in this study. This sample included individuals with symptoms of cognitive fog, both with and without anosmia, and a control group comprised of healthy subjects. All electroencephalography (EEG) data were collected in two sessions, 1 month and 8 months after recovery from Covid-19, to measure the neurophysiological parameters of P300 and beta band rhythms. Results: The results revealed significant differences in the neurophysiological parameters of P300 and beta band rhythms in subjects affected by cognitive fog, and these alterations persist even 8 months after recovery from Covid-19. Interestingly, no significant differences were observed between the participants with anosmia and without anosmia associated with cognitive fog. Conclusions: These findings provide a significant contribution to understanding the long-term effects of Covid-19 on the brain and have important implications for future interventions aimed at managing and treating brain fog symptoms. The longitudinal assessment of cortical brain activity helps highlight the persistent impact of the virus on the neurological health of Long-Covid patients. [ABSTRACT FROM AUTHOR]

Pilot behavior is crucial for aviation safety. This study aims to investigate the EEG characteristics of pilots, refine training assessment methodologies, and bolster flight safety measures. The collected EEG signals underwent initial preprocessing. The EEG characteristic analysis was performed during left and right turns, involving the calculation of the energy ratio of beta waves and Shannon entropy. The psychological workload of pilots during different flight phases was quantified as well. Based on the EEG characteristics, the pilots' psychological workload was classified through the use of a support vector machine (SVM). The study results showed significant changes in the energy ratio of beta waves and Shannon entropy during left and right turns compared to the cruising phase. Additionally, the pilots' psychological workload was found to have increased during these turning phases. Using support vector machines to detect the pilots' psychological workload, the classification accuracy for the training set was 98.92%, while for the test set, it was 93.67%. This research holds significant importance in understanding pilots' psychological workload. [ABSTRACT FROM AUTHOR]

Recently, there has been a resurgence in experimental and conceptual efforts to understand how brain rhythms can serve to organize visual information. Oscillations can provide temporal structure for neuronal processing and form a basis for integrating information across brain areas. Here, we use a bistable paradigm and a data‐driven approach to test the hypothesis that oscillatory modulations associate with the integration or segregation of visual elements. Spectral signatures of perception of bound and unbound configurations of visual moving stimuli were studied using magnetoencephalography (MEG) in ambiguous and unambiguous conditions. Using a 2 × 2 design, we were able to isolate correlates from visual integration, either perceptual or stimulus‐driven, from attentional and ambiguity‐related activity. Two frequency bands were found to be modulated by visual integration: an alpha/beta frequency and a higher frequency gamma‐band. Alpha/beta power was increased in several early visual cortical and dorsal visual areas during visual integration, while gamma‐band power was surprisingly increased in the extrastriate visual cortex during segregation. This points to an integrative role for alpha/beta activity, likely from top‐down signals maintaining a single visual representation. On the other hand, when more representations have to be processed in parallel gamma‐band activity is increased, which is at odds with the notion that gamma oscillations are related to perceptual coherence. These modulations were confirmed in intracranial EEG recordings and partially originate from distinct brain areas. Our MEG and stereo‐EEG data confirms predictions of binding mechanisms depending on low‐frequency activity for long‐range integration and for organizing visual processing while refuting a straightforward correlation between gamma‐activity and perceptual binding. Practitioner Points: Distinct neurophysiological signals underlie competing bistable percepts.Increased alpha/beta activity correlate with visual integration while gamma correlates with segmentation.Ambiguous percepts drive alpha/beta activity in the posterior cingulate cortex. [ABSTRACT FROM AUTHOR]

Background and purpose: In late December 2019, pneumonia originating from nCOV-2019 spread rapidly around the world, and in March 2020, the World Health Organization officially declared it a pandemic and chose the name "COVID-19" for the resulting disease. A significant proportion of COVID-19 patients experience severe pulmonary complications and life-threatening conditions that necessitate respiratory support and admission to the intensive care unit (ICU). Since the detection of the first case of COVID-19 in Iran, the country has experienced several waves, with different strains of the coronavirus prevailing in each wave. According to the studies conducted in this field, in the first wave, the alpha strain (B.1.1) 7), the second wave of the beta strain (B.1.351), the third wave of the gamma strain (P.1), the fourth wave of the delta strain (B.1.617.2) and in the fifth wave the Amicron strain (B.1.1.529) of the strain were dominant in patients. This study aims to evaluate the clinical and paraclinical findings, as well as the outcomes, of COVID-19 patients admitted to the intensive care units at a referral teaching hospital in northern Iran during the first through fifth waves of the pandemic. Materials and methods: This research is a descriptive-analytical retrospective study that was conducted on all patients with COVID-19 who were hospitalized in the ICU of Razi Qaemshahr Hospital (Infectious Diseases Referral Center of Mazandaran Province) in first to fifth waves. Personal information, underlying diseases, time from the onset of symptoms to a hospital visit, laboratory tests, and length of stay of the patient in the intensive care unit was collected through dossier reading and spss25 software was used for statistical analysis. Results: Out of the 304 patients admitted to the ICU during the first through fifth waves of the COVID-19 outbreak, 50.3% were male. The age range of the patients was from 22 years to 98 years with an average of 65.14±15.08. 244 patients had at least one underlying disease. So 41% of the patients had diabetes and 50% had blood HTN. Among 244 patients with underlying disease, only 28 patients recovered and 216 patients died, which difference was significant (P=0.01). The second wave had the highest number of patients (25.7%), while the third wave had the lowest (16.4%). The average hemoglobin level differed significantly between the second and fourth waves, being 1.37 units lower in the fourth wave. The mortality rates varied significantly across the different waves (P<0.001), with a rate of 100% in wave 1, 85.9% in wave 2, 82% in wave 3, 64.3% in wave 4, and 93% in wave 5. Regarding underlying health conditions, no significant differences were observed among patients across waves 1 to 5. Notably, among the 244 patients with underlying diseases, only 28 recovered, while 216 passed away (P= 0.01). Conclusion: Male Gender and underlying conditions, particularly diabetes and heart failure, are influential factors in determining the prognosis and severity of the disease. The mortality in the fourth wave has decreased significantly and the maximum rate of recovery of patients was in this wave. [ABSTRACT FROM AUTHOR]

Brain development from infancy through childhood involves complex structural and functional changes influenced by both internal and external factors. This review provides a comprehensive analysis of event and task-related brain oscillations, focusing on developmental changes across different frequency bands, including delta, theta, alpha, beta, and gamma. Electroencephalography (EEG) studies highlight that these oscillations serve as functional building blocks for sensory and cognitive processes, with significant variations observed across different developmental stages. Delta oscillations, primarily associated with deep sleep and early cognitive demands, gradually diminish as children age. Theta rhythms, crucial for attention and memory, display a distinct pattern in early childhood, evolving with cognitive maturation. Alpha oscillations, reflecting thalamocortical interactions and cognitive performance, increase in complexity with age. Beta rhythms, linked to active thinking and problem-solving, show developmental differences in motor and cognitive tasks. Gamma oscillations, associated with higher cognitive functions, exhibit notable changes in response to sensory stimuli and cognitive tasks. This review underscores the importance of understanding oscillatory dynamics to elucidate brain development and its implications for sensory and cognitive processing in childhood. The findings provide a foundation for future research on developmental neuroscience and potential clinical applications. [ABSTRACT FROM AUTHOR]

Objective: To investigate whether Infra-low frequency Neurofeedback (ILF-NFB) training can improve brain electrical activity in children with autism spectrum disorders ASD. Method: This single arm pre and post intervention study was carried out at IBMS (Institute of Basic Medical Sciences), Khyber Medical University, Peshawar and Shaheed Zulfiqar Ali Bhutto Medical University (SZABMU), Islamabad from January 2021 to December 2022. A purposive sampling technique was used. Thirty-five ASD children (male=24; female=11; 7-17 years) were provided with 30 sessions of infra low frequency (ILF) neurofeedback training for 15-20 minutes, during 10 weeks. Childhood Autism Rating Scale (CARS) scoring was done and electroencephalogram (EEG) activity was compared before and after ILF-NF training sessions. Results: Around 62.9% participants had mild-moderate autism and 37.1% had severe autism. Wilcoxon Signed rank test revealed a significant decline in delta (Pre-test=47.31±19.22, Post-test=22.07±6.83; p=<0.001), theta (Pretest= 24.75±16.62, Post-test=12.37±3.59; p=<0.001) and alpha (Pre-test=12.01±9.81, Post-test=4.03±1.61; p=< 0.001) waves. Mann Whitney U test exhibited no significant gender differences in EEG pattern before and after neurofeedback except in theta waves (p=0.03) before the intervention. Conclusion: Decline in delta, theta, beta and alpha waves propose that ILF-NF training can be effective in improving the EEG activity. ILF-NFB can be perceived as a valuable non-invasive, non-pharmacological intervention for improving EEG pattern via reintegration of brain activity resulting in increased the attention and focus, enhanced mental stability and cognitive engagement. [ABSTRACT FROM AUTHOR]

Electroencephalography (EEG) wearable devices are particularly suitable for monitoring a subject's engagement while performing daily cognitive tasks. EEG information provided by wearable devices varies with the location of the electrodes, the suitable location of which can be obtained using standard multi-channel EEG recorders. Cognitive engagement can be assessed during working memory (WM) tasks, testing the mental ability to process information over a short period of time. WM could be impaired in patients with epilepsy. This study aims to evaluate the cognitive engagement of nine patients with epilepsy, coming from a public dataset by Boran et al., during a verbal WM task and to identify the most suitable location of the electrodes for this purpose. Cognitive engagement was evaluated by computing 37 engagement indexes based on the ratio of two or more EEG rhythms assessed by their spectral power. Results show that involvement index trends follow changes in cognitive engagement elicited by the WM task, and, overall, most changes appear most pronounced in the frontal regions, as observed in healthy subjects. Therefore, involvement indexes can reflect cognitive status changes, and frontal regions seem to be the ones to focus on when designing a wearable mental involvement monitoring EEG system, both in physiological and epileptic conditions. [ABSTRACT FROM AUTHOR]

Wave trains propagating across Eurasia at both high and low latitudes in winter are key to the climate variation over East Asia via modulating the cold surge and moisture supply, with different configurations inducing diverse impacts. In this study, the combined impacts of the Eurasian (EU) pattern and South Asian jet wave train (SAJW) at a 10–30-day timescale are compared when they work in phase (indices of same signs) and out of phase (indices of opposite signs). Different configuration is defined by considering whether they induce a concurrent or reversing center of action over East Asia–Japan. The in-phase configuration induces a strong outbreak of the East Asian winter monsoon by intensifying the East Asian trough. In contrast, the out-of-phase configuration restricts the cold air over North China and enhances the moisture supply from the low latitudes by intensifying the India-Burma (now Myanmar) trough and an anomalous anticyclone over East Asia-the western North Pacific, inducing abnormal precipitation over Southwest and North China. In in-phase configuration, the EU pattern and SAJW are excited by abnormal disturbances over the western North Atlantic. The disturbance energy splits over Europe and joins over East Asia, intensifying the East Asian trough concurrently. In out-of-phase configuration, the two teleconnections do not share a common upstream source; they develop individually over the eastern North Atlantic in high and subtropical latitudes. They join north of the Bay of Bengal, resulting in a deepened India-Burma trough and an onward western North Pacific anticyclone anomaly. Both the EU pattern and SAJW influence the East Asian trough and the India-Burma trough in different configurations mainly via the advection of abnormal vorticity along wave trains by the subtropical westerly jet stream, with the anticyclonic Rossby wave source and Beta effect playing a negative role. [ABSTRACT FROM AUTHOR]

An analysis of changes in sensorimotor rhythms of the electroencephalogram (EEG) and features of the restoration of motor functions during a course of neurorehabilitation using a non-invasive brain-computer-hand exoskeleton interface was carried out in 50 children aged 7–15 years of both sexes suffering from cerebral palsy (CP). EEG was recorded in 32 leads under conditions of rest and kinesthetic imagination of hand extension movements. Depending on the success of the classifier program in determining imaginary states based on the EEG pattern, the children were divided into two groups—with high and low success when imagining movements. In children of the studied groups, when undergoing a course of neurorehabilitation, differences were revealed in the nature of changes in EEG amplitude in the sensorimotor mu (8–13 Hz) and beta (15–25 Hz) rhythms frequency ranges. When imagining movements of the right hand, intergroup differences for the mu rhythm reached the level of statistical significance in the medial electrodes of the fronto-central and parietal areas of the neocortex, for the beta rhythm—in the medial lead of the parietal region. Children in the group with high success showed a decrease or slight increase in the amplitude of the mu- and beta rhythm in these brain areas at the last session of the course compared to the first. We hypothesize that children in this group are not only better able to kinesthetically imagine movements throughout the course of neurorehabilitation, but also, based on feedback signals, learn to effectively adjust their strategies for movement imagination. Children in the group with low success showed an increase in the amplitude of sensorimotor rhythms in these brain areas, indicating the development of inhibition in the frontoparietal motor network. Patients, whose conditions were determined more accurately by the classifier, achieved higher rates of motor rehabilitation. The results of the study are important for clarifying the brain mechanisms of motor functions restoration in patients with cerebral palsy under the influence of a course of neurorehabilitation. [ABSTRACT FROM AUTHOR]

Objective means of predicting treatment responses in patients with schizophrenia using quantitative electroencephalography (qEEG) as an electrophysiological indicator. We obtained qEEG recordings from patients with schizophrenia and explored them for patterns indicative of treatment responsiveness. Patients and Methods: The study included 68 patients had been diagnosed with schizophrenia spectrum disorder. After retrospectively gathering demographic information, clinical data such as qEEG, Positive and Negative Syndrome Scale (PANSS), a multiple regression analysis was performed. This analysis employed baseline qEEG findings as independent variables and PANSS score changes as dependent variables to discern causal relationships. Results: The mean age of the participants was 38.4 years(SD =13.73). The mean PANSS score on admission was 92.97, decreasing to 67.41 at discharge. Multiple regression analysis revealed that delta waves in T4 (β=0.346, t=3.165, p=0.002), and high-beta waves in Fp2 (β=0.231, t=2.361, p=0.021) were associated with PANSS changes in absolute power. In addition, the delta waves of O2 (β=0.250, t=3.288, p=0.002); beta waves of T3 (β=− 1.463, t=− 5.423, p< 0.001) and O2 (β=0.551, t=3.366, p=0.001); high beta waves of Fp1 (β=0.307, t=4.026, p< 0.001), T3 (β=0.855, t=4.414, p< 0.001) and T6 (β=− 0.838, t=− 4.559, p< 0.001) of absolute power using the Z-score were also related to PANSS changes. Pearson's correlation analysis showed that only delta waves at Cz (r= 0.246, p=0.043) in absolute power correlated with changes in the PANSS. Conclusion: We found that certain qEEG wave patterns in patients with schizophrenia prior to antipsychotic treatment were linked to PANSS changes before and after treatment. Delta waves and beta waves, primarily in the frontal and temporal regions, were found to be significantly associated with changes in PANSS scores. In the future, the qEEG indicators identified in this study could serve as electrophysiological markers for predicting antipsychotic treatment responses in patients with schizophrenia. [ABSTRACT FROM AUTHOR]

Low and high beta frequency rhythms were observed in the motor cortex, but their respective sources and behavioral correlates remain unknown. We studied local field potentials (LFPs) during pre-cued reaching behavior in macaques. They contained a low beta band (<20 Hz) dominant in primary motor cortex and a high beta band (>20 Hz) dominant in dorsal premotor cortex (PMd). Low beta correlated positively with reaction time (RT) from visual cue onset and negatively with uninstructed hand postural micro-movements throughout the trial. High beta reflected temporal task prediction, with selective modulations before and during cues, which were enhanced in moments of increased focal attention when the gaze was on the work area. This double-dissociation in sources and behavioral correlates of motor cortical low and high beta, with respect to both task-instructed and spontaneous behavior, reconciles the largely disparate roles proposed for the beta rhythm, by suggesting band-specific roles in both movement control and spatiotemporal attention. Beta oscillations are associated with many aspects of motor behavior and studies often include the entire beta frequency range. This study shows that high and low beta rhythms co-reside in the motor cortex of macaques and have distinct, band-specific roles in movement control and spatio-temporal attention. [ABSTRACT FROM AUTHOR]

This study aims to take higher-education students as examples to understand and compare artistic and engineering mindsets in creative processes using EEG. Fifteen Master of Fine Arts (MFA) visual arts and fifteen Master of Engineering (MEng) design engineering students were recruited and asked to complete alternative uses tasks wearing an EEG headset. The results revealed that (1) the engineering-mindset students responded to creative ideas faster than artistic-mindset students. (2) Although in creative processes both artistic- and engineering-mindset students showed Theta, Alpha, and Beta wave activity, the active brain areas are slightly different. The active brain areas of artistic-mindset students in creative processes are mainly in the frontal and occipital lobes; while the whole brain (frontal, oriental, temporal, and occipital lobes) was active in creative processes of engineering-mindset students. (3) During the whole creative process, the brain active level of artistic-mindset students was higher than that of engineering-mindset students. The results of this study fills gaps in existing research where only active brain areas and band waves were compared between artistic- and engineering-mindset students in creative processes. For quick thinking in terms of fluency of generating creative ideas, engineering students have an advantage in comparison to those from the visual arts. Also, the study provided more evidence that mindset can affect the active levels of the brain areas. Finally, this study provides educators with more insights on how to stimulate students' creative ability. [ABSTRACT FROM AUTHOR]

This study examines the impact of reminiscence therapy on cognitive and emotional well-being in institutionalized older patients with dementia. Conducted at the Long-Term Care Health Facility for the Elderly, the research involved 34 participants who underwent therapy sessions that included personalized discussions of past experiences. Using physiological markers such as electroencephalography alpha and beta waves, along with psychological measures such as the Hasegawa Dementia Scale—Revised, the study aimed to quantify the effects of the therapy. Although the results indicated positive correlations between alpha and beta waves, suggesting enhanced relaxation and cognitive engagement, improvements in Hasegawa Dementia Scale—Revised scores were not statistically significant, pointing to variability in therapeutic effectiveness among patients. Despite these mixed outcomes, the findings support the potential of reminiscence therapy as a non-pharmacological intervention to improve the quality of life of dementia patients, though they also underscore the necessity for further research to refine therapy protocols and enhance applicability. [ABSTRACT FROM AUTHOR]

Current assessments for generalized anxiety disorder (GAD) are often subjective and do not rely on a standardized measure to evaluate the GAD across its severity levels. The lack of objective and multi-level quantitative diagnostic criteria poses as a significant challenge for individualized treatment strategies. To address this need, this study aims to establish a GAD grading and quantification diagnostic model by integrating an electroencephalogram (EEG) and ensemble learning. In this context, a total of 39 normal subjects and 80 GAD patients were recruited and divided into four groups: normal control, mild GAD, moderate GAD, and severe GAD. Ten minutes resting state EEG data were collected for every subject. Functional connectivity features were extracted from each EEG segment with different time windows. Then, ensemble learning was employed for GAD classification studies and brain mechanism analysis. Hence, the results showed that the Catboost model with a 10 s time window achieved an impressive 98.1% accuracy for four-level classification. Particularly, it was found that those functional connections situated between the frontal and temporal lobes were significantly more abundant than in other regions, with the beta rhythm being the most prominent. The analysis framework and findings of this study provide substantial evidence for the applications of artificial intelligence in the clinical diagnosis of GAD. [ABSTRACT FROM AUTHOR]

The central nervous system (CNS) may produce the same endpoint trajectory or torque profile with different muscle activation patterns. What differentiates these patterns is the presence of cocontraction, which does not contribute to effective torque generation but allows to modulate joints' mechanical stiffness. Although it has been suggested that the generation of force and the modulation of stiffness rely on separate pathways, a characterization of the differences between the synaptic inputs to motor neurons (MNs) underlying these tasks is still missing. In this study, participants coactivated the same pair of upper-limb muscles, i.e., the biceps brachii and the triceps brachii, to perform two functionally different tasks: limb stiffness modulation or endpoint force generation. Spike trains of MNs were identified through decomposition of high-density electromyograms (EMGs) collected from the two muscles. Cross-correlogram showed a higher synchronization between MNs recruited to modulate stiffness, whereas cross-muscle coherence analysis revealed peaks in the β-band, which is commonly ascribed to a cortical origin. These peaks did not appear during the coactivation for force generation, thus suggesting separate cortical inputs for stiffness modulation. Moreover, a within-muscle coherence analysis identified two subsets of MNs that were selectively recruited to generate force or regulate stiffness. This study is the first to highlight different characteristics, and probable different neural origins, of the synaptic inputs driving a pair of muscles under different functional conditions. We suggest that stiffness modulation is driven by cortical inputs that project to a separate set of MNs, supporting the existence of a separate pathway underlying the control of stiffness. NEW & NOTEWORTHY: The characterization of the pathways underlying force generation or stiffness modulation are still unknown. In this study, we demonstrated that the common input to motor neurons of antagonist muscles shows a high-frequency component when muscles are coactivated to modulate stiffness but not to generate force. Our results provide novel insights on the neural strategies for the recruitment of multiple muscles by identifying specific spectral characteristics of the synaptic inputs underlying functionally different tasks. [ABSTRACT FROM AUTHOR]

Introductions: Medical students are required to lifelong learning. Therefore, it is important for them to have self-regulated learning skills that involve cognitive function processes. Electroencephalography is a neuroscience tool that can be used to record brain wave activity related to a person’s cognitive function. Objective: This study was conducted to see the relationship between self-regulated learning and cognitive function with quantitative electroencephalogram (qEEG) parameters. Methods: This study used an observational analytic approach to assess self-regulated learning and cognitive function using the MSLQ and MoCA-INA questionnaires. qEEG recording to see brain wave activity was done when the eyes were open and closed and seen in alpha and beta waves. The sample of this study amounted to 32 respondents who were willing to carry out each research procedure. The Kruskal-Wallis correlation test was used to see the relationship between variables. Results: The study findings reveal a significant correlation between SRL and qEEG parameters. In the open-eye condition, such a correlation exists in the frontal and central regions with regard to alpha waves (P = 0.046 and P = 0.047). In contrast, in the closed-eye condition, it exists in the occipital, central, and parietal regions with alpha waves (P = 0.005, P = 0.021, and P = 0.049) and the central region with beta waves (P = 0.030). There is a significant correlation between cognitive function and qEEG parameters observed in both open and closed-eye conditions within the frontal region beta waves (P = 0.024, P = 0.044, and P = 0.021). Conclusions: There is a relationship between SRL and cognitive function with alpha and beta wave activity on qEEG recording. [ABSTRACT FROM AUTHOR]

The prevalence of electronic screens in modern society has significantly increased our exposure to high-energy blue and violet light wavelengths. Accumulating evidence links this exposure to adverse visual and cognitive effects and sleep disturbances. To mitigate these effects, the optical industry has introduced a variety of filtering glasses. However, the scientific validation of these glasses has often been based on subjective reports and a narrow range of objective measures, casting doubt on their true efficacy. In this study, we used electroencephalography (EEG) to record brain wave activity to evaluate the effects of glasses that filter multiple wavelengths (blue, violet, indigo, and green) on human brain activity. Our results demonstrate that wearing these multi-colour light filtering glasses significantly reduces beta wave power (13–30 Hz) compared to control or no glasses. Prior research has associated a reduction in beta power with the calming of heightened mental states, such as anxiety. As such, our results suggest that wearing glasses such as the ones used in this study may also positively change mental states, for instance, by promoting relaxation. This investigation is innovative in applying neuroimaging techniques to confirm that light-filtering glasses can induce measurable changes in brain activity. [ABSTRACT FROM AUTHOR]

The brain often switches freely between focused attention and divergent thinking, and the Default Mode Network (DMN) is activated during brain rest. Since its discovery, the DMN, together with its function and characteristics, indicates that learning does not stop when the brain "rests". Therefore, DMN plays an important role in learning. Neural activities such as beta wave rhythm regulation, "subconscious" divergence thinking mode initiation, hippocampal function, and neural replay occur during default mode, all of which explains that "rest" promotes learning. This paper summarized the function and neural mechanism of DMN in learning and proposed that the DMN plays an essential role in learning, which is that it enables rest to promote learning. [ABSTRACT FROM AUTHOR]

Background: Parkinson's disease is one of the most common neurodegenerative disorders. While a definitive cure for Parkinson's disease remains elusive, a range of treatments are available to slow its progression and counteract its symptoms. Transcranial direct current stimulation (tDCS) represents a non-invasive method to induce brain plasticity. The aim of this study was to examine the effects of two weeks of tDCS on the left dorsolateral prefrontal cortex (DLPFC) on the neurophysiological functioning of Parkinson's patients. Methods: Thirty patients aged between 67 and 82 years with Parkinson's disease participated to the experiment. Fifteen underwent tDCS on the left DLPFC, while fifteen underwent sham tDCS. Neurophysiological functions were assessed before and after tDCS using electroencephalogram methods for alpha and beta band rhythms and P300 event-related potential latency. Results: tDCS led to a reduction in the onset latency of the P300 response and an increase in the power spectrum of the alpha and beta band rhythms. Conclusions: This research enhances our understanding of the potential effects of tDCS in the context of Parkinson's disease treatment, as the reduction in P300 latency and the increase in alpha and beta bands are associated with improvements in cognitive aspects. [ABSTRACT FROM AUTHOR]

Brain–computer interfaces (BCIs) can provide a non-muscular channel of control to stroke patients for motor rehabilitation. This can be achieved through the use of motor imagery (MI) training, involving the modulation of sensorimotor rhythms. The practice of MI has been shown to be able to strengthen key motor pathways when reinforced with rewarding feedback. Recently, there has been a growing evidence of the positive impact of embodied virtual reality (VR) and vibrotactile feedback in MI training. Nonetheless, it is not yet clear what the optimal MI-BCI setup is for evoking stronger sensorimotor rhythms in VR. In this study, we investigate the impact of head-mounted VR, and vibrotactile feedback during MI-BCI training in the induced sensorimotor rhythms. To achieve this, 19 healthy subjects performed MI training with embodied VR between four conditions: head-mounted vs. screen VR, with and without vibrotactile feedback; and two control conditions: abstract MI without embodied feedback, and motor execution. The event-related desynchronization (ERD) and the lateralization indices (LI) of the Alpha and Beta EEG rhythms were analyzed in a within-subject design. Results show that the combination of vibrotactile feedback and embodied VR can induce stronger and more lateralized Alpha ERD; nonetheless, LI was not significantly different across conditions. [ABSTRACT FROM AUTHOR]

Individuals' phenotypes, including the brain's structure and function, are largely determined by genes and their interplay. The resting brain generates salient rhythmic patterns that can be characterized noninvasively using functional neuroimaging such as magnetoencephalography (MEG). One of these rhythms, the somatomotor (rolandic) beta rhythm, shows intermittent high amplitude "events" that predict behavior across tasks and species. Beta rhythm is altered in neurological disease. The aperiodic (1/f) signal present in electrophysiological recordings is also modulated by some neurological conditions and aging. Both sensorimotor beta and aperiodic signal could thus serve as biomarkers of sensorimotor function. Knowledge about the extent to which these brain functional measures are heritable could shed light on the mechanisms underlying their generation. We investigated the heritability and variability of human spontaneous sensorimotor beta rhythm events and aperiodic activity in 210 healthy male and female adult siblings' spontaneous MEG activity. The most heritable trait was the aperiodic 1/f signal, with a heritability of 0.87 in the right hemisphere. Time-resolved beta event amplitude parameters were also highly heritable, whereas the heritabilities for overall beta power, peak frequency, and measures of event duration remained nonsignificant. Human sensorimotor neural activity can thus be dissected into different components with variable heritability. We postulate that these differences partially reflect different underlying signalgenerating mechanisms. The 1/f signal and beta event amplitude measures may depend more on fixed, anatomical parameters, whereas beta event duration and its modulation reflect dynamic characteristics, guiding their use as potential disease biomarkers. [ABSTRACT FROM AUTHOR]

Aging often leads to awareness decline and psychological stress. Meditation, a method of modulating consciousness, may help individuals improve overall awareness and increase emotional resilience toward stress. This study explored the potential influence of the Awareness Training Program (ATP), a form of consciousness modulation, on age-related brain wave changes and psychological stress in middle-aged adults. Eighty-five participants with mild stress were recruited and randomly assigned to ATP (45.00 ± 8.00 yr) or control (46.67 ± 7.80 yr) groups, matched by age and gender. Ten-minute resting-state EEG data, obtained while the participants' eyes were closed, were collected using a 128-channel EEG system (EGI). A strong positive Pearson correlation was found between fast-wave (beta wave, 12–25 Hz; gamma wave, 25–40 Hz) EEG and age. However, after the 7-week ATP intervention, this correlation became insignificant in the ATP group. Furthermore, there was a significant reduction in stress levels, as measured by the Chinese version of the 10 item Perceived Stress Scale (PSS-10), in the ATP group. These results suggest that ATP may help modulate age-related effects on fast brain waves, as evidenced by the reduced correlation magnitude between age and gamma waves, and lower psychological stress. This suggests that ATP, as a form of consciousness modulation, may improve stress resilience and modulate age-related gamma wave changes. [ABSTRACT FROM AUTHOR]

Background: Sun salutation (Surya namaskar) is an ancient yogic exercise, which is a combination of 12 different postures rhythmically. Yoga practitioners perform this procedure in a slow as well as fast pace manner. Aim: We undertook this study to find out the immediate changes in heart rate variability (HRV) and brain waves spectrum after the practice of fast pace sun salutation (FPSS). Settings and Design: This prospective interventional observational study was conducted on 30 male healthy subjects in the 30–45 years age group from September 2021 to December 2021 after approval from the Institutional Ethics Committee. Participants gave their written consent in the prescribed format. Materials and Methods: Fourteen rounds of FPSS were performed in approximately 10 min under the guidance of a yoga expert. Brain Tap Dinamika Machine (Advanced HRV Test System, Moscow, Russia) was used to assess different HRV and brain waves parameters before and after FPSS. Statistical Analysis Used: Statistical analysis was done by Student’s paired t‑test using GraphPad online software. Results: All independent variables of time and frequency domain analysis of HRV were found to be increased after the intervention. A significant upsurge in low frequency (LF)% as compared to high frequency (HF)% and very low frequency (VLF)% showed a relative increase in sympathetic activity. In brain waves, delta, theta, and alpha were decreased, whereas activities of beta and gamma waves were found to be increased. Conclusions: Increase in both LF and HF components showed that both sympathetic and parasympathetic components have increased. Brain wave analysis suggested increased mental alertness after FPSS. [ABSTRACT FROM AUTHOR]

The main objective of this study was to further understanding of the patterns of spectral connectivity during exercise in low‐ and high‐tolerant individuals. Thirty‐nine healthy individuals (i.e., 17 low‐ and 22 high‐tolerant participants) took part in the present study. A state‐of‐the‐art portable electroencephalography system was used to measure the brain's electrical activity during an incremental exercise test performed until the point of volitional exhaustion on a cycle ergometer. Spectral coherence was used to explore the patterns of connectivity in the frontal, central, and parietal regions of the brain. Physiological, perceptual, and affective responses were assessed throughout the exercise bout. The spontaneous eyeblink rate was also calculated prior to commencement and upon completion of the exercise trial as an indirect assessment of the dopaminergic system. The present findings indicate that high‐tolerant individuals reported lower levels of perceived activation, especially during the preliminary stages of the exercise test. Participants in the high‐tolerance group also reported greater levels of remembered pleasure upon completion of the exercise test. The data also revealed that high‐tolerant individuals exhibited increased connectivity of theta waves between frontal, central, and parietal electrode sites and increased connectivity of beta waves, primarily within the parietal cortex. Correlational analysis indicated the possibility that low‐ and high‐tolerant individuals make use of different neural networks to process and regulate their psychophysiological state during exercise‐related situations. This strategy could potentially represent a conscious decision to downregulate affective arousal and facilitate the neural control of working muscles during situations of physical stress. Brain communication varies substantially during exercise in response to how individuals perceive the physical task. The main objective of the present study was to explore the patterns of brain connectivity during exercise in low‐ and high‐tolerant individuals. The present findings indicate that high‐tolerant individuals are better equipped to regulate their arousal state during exercise, and this cognitive strategy is possibly associated with increased connectivity of beta frequencies within the parietal cortex. [ABSTRACT FROM AUTHOR]

The processing of threat‐related emotional body language (EBL) has been shown to engage sensorimotor cortical areas early on and induce freezing in the observers' motor system, particularly when observing fearful EBL. To provide insights into the interplay between somatosensory and motor areas during observation of EBL, here, we used high‐density electroencephalography (hd‐EEG) in healthy humans while they observed EBL stimuli involving fearful and neutral expressions. To capture early sensorimotor brain response, we focused on P100 fronto‐central event‐related potentials (ERPs) and event‐related desynchronization/synchronization (ERD/ERS) in the mu‐alpha (8–13 Hz) and lower beta (13–20 Hz) bands over the primary motor (M1) and somatosensory (S1) cortices. Source‐level ERP and ERD/ERS analyses were conducted using eLORETA. Results revealed higher P100 amplitudes in motor and premotor channels for 'Neutral' compared with 'Fear'. Additionally, analysis of ERD/ERS showed increased beta band desynchronization in M1 for 'Neutral', and the opposite pattern in S1. Source‐level estimation showed significant differences between conditions mainly observed in the beta band over sensorimotor areas. These findings provide high‐temporal resolution evidence suggesting that seeing fearful EBL induces early activation of somatosensory areas, which in turn could suppress M1 activity. These findings highlight early dynamics within the observer's sensorimotor system and hint at a sensorimotor mechanism supporting freezing during the processing of EBL. By means of hd‐EEG, we provide high‐temporal resolution evidence that seeing fearful emotional body language (EBL) induces early activation of somatosensory areas, which in turn suppress M1 activity. These findings provide high‐temporal resolution evidence suggesting that seeing fearful EBL induces early activation of somatosensory areas, which in turn could suppress M1 activity. [ABSTRACT FROM AUTHOR]

This document contains abstracts from the International Journal of Psychology covering a range of topics. The first abstract discusses the relationship between disgust and sexual behavior, suggesting that sexual arousal can temporarily reduce the disgust response to sexual stimuli. The second abstract explores the use of biofeedback to reduce stress in students. The third abstract focuses on the connection between chronic stress and mental health disorders in students. The fourth abstract presents a study on the prioritization of different textural features for visual attention. The fifth abstract examines the mechanism of mood disorders in depression patients using event-related potentials. The sixth abstract investigates the effects of Snoezelen, a multi-sensory environment, on stress and anxiety using event-related brain potentials. The seventh abstract validates the ability of individuals to voluntarily generate piloerection and explores its potential use in psychophysiological research. Lastly, a study on the effectiveness of Eye Movement Desensitization and Reprocessing (EMDR) therapy on posttraumatic stress disorder (PTSD) in individuals who experienced traffic accidents is presented. The study found that EMDR therapy led to a decrease in PTSD symptoms, as indicated by changes in brain activity. The study suggests that the beta wave of amplitude spectral analysis can be used as an indicator of improvement in PTSD symptoms. [Extracted from the article]

Stroke is a debilitating clinical condition resulting from a brain infarction or hemorrhage that poses significant challenges for motor function restoration. Previous studies have shown the potential of applying transcranial direct current stimulation (tDCS) to improve neuroplasticity in patients with neurological diseases or disorders. By modulating the cortical excitability, tDCS can enhance the effects of conventional therapies. While upper-limb recovery has been extensively studied, research on lower limbs is still limited, despite their important role in locomotion, independence, and good quality of life. As the life and social costs due to neuromuscular disability are significant, the relatively low cost, safety, and portability of tDCS devices, combined with low-cost robotic systems, can optimize therapy and reduce rehabilitation costs, increasing access to cutting-edge technologies for neuromuscular rehabilitation. This study explores a novel approach by utilizing the following processes in sequence: tDCS, a motor imagery (MI)-based brain-computer interface (BCI) with virtual reality (VR), and a motorized pedal end-effector. These are applied to enhance the brain plasticity and accelerate the motor recovery of post-stroke patients. The results are particularly relevant for post-stroke patients with severe lower-limb impairments, as the system proposed here provides motor training in a real-time closed-loop design, promoting cortical excitability around the foot area (Cz) while the patient directly commands with his/her brain signals the motorized pedal. This strategy has the potential to significantly improve rehabilitation outcomes. The study design follows an alternating treatment design (ATD), which involves a double-blind approach to measure improvements in both physical function and brain activity in post-stroke patients. The results indicate positive trends in the motor function, coordination, and speed of the affected limb, as well as sensory improvements. The analysis of event-related desynchronization (ERD) from EEG signals reveals significant modulations in Mu, low beta, and high beta rhythms. Although this study does not provide conclusive evidence for the superiority of adjuvant mental practice training over conventional therapy alone, it highlights the need for larger-scale investigations. [ABSTRACT FROM AUTHOR]

To understand the neural mechanisms of perceptual filling-in at the blind spot (BS), we analyzed neural activity in the region representing the visual field corresponding to the BS (BS region) in the primary visual cortex (V1) of the macaque monkey. We inserted a linear array electrode into the BS region or surrounding region and recorded the multiunit activities (MUAs) and local field potential (LFP). We examined the responses of MUAs and LFP to a large visual stimulus that entirely covered the BS (surface stimuli) while the monkey performed a visual fixation task in either the monocular condition without receiving direct retinal input or the binocular condition receiving retinal information. We observed clear MUA responses in the deep layers within the BS region under monocular conditions, confirming previous reports that V1 neurons in the BS region are activated when perceptual filling-in occurs. Current source density analysis using LFP showed that MUA responses were mainly observed in layer 5. Although LFP responses were generally stronger in the binocular condition than in the monocular condition, a notable exception was observed in the BS region. LFP responses in the low-beta band in the superficial layers were stronger in the monocular condition than in the binocular condition. These results suggest that low-beta activity in the superficial layer is related to the occurrence of perceptual filling-in in the BS. The origin of this activity is considered to be feedback signals from the extrastriate areas to the V1. NEW & NOTEWORTHY Two characteristic activities were induced in the blind spot (BS) region in response to the stimulus, causing perceptual filling-in: 1) beta-band LFP responses in the superficial layers and 2) neuronal responses in the deep layers, mainly in layer 5. These data suggest that the feedback signal from the extrastriate areas to the BS region in V1 is involved in perceptual filling-in. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to investigate the utility of quantitative electroencephalography (QEEG) as a diagnostic tool for migraine and as an indicator of treatment response by comparing QEEG characteristics between migraine patients and controls, and monitoring changes in these characteristics alongside clinical symptoms in response to treatment Background: We hypothesized that patients with migraine exhibit distinctive characteristics in QEEG measurements, which could be used as potential diagnostic biomarkers and as a tool for monitoring treatment response. Methods: A total of 720 patients were included in the study, comprising 619 patients with migraine and 101 subjects as a control group. QEEG measurements were analyzed for absolute power across specific frequency bands: delta wave (0.5–4 Hz), theta wave (4–8 Hz), alpha wave (8–12 Hz), beta wave (12–25 Hz), and high beta wave (25–30 Hz). The absolute power was normalized against a normative dataset from NeuroGuide, with electrodes being highlighted for significance if they exceeded 1.96. Clinical symptoms were also monitored for correlation with QEEG changes. Results: Our analysis showed that patients with migraine exhibited significantly higher absolute power across all frequencies, most markedly within the high beta frequency range. When considering electrodes with z‐scores exceeding the threshold of 1.96 in the high beta range, a significant association with migraine diagnosis was observed (per 1 electrode increase, OR 1.06; 95% CI 1.01–1.11; p =.012). Moreover, pre‐ and posttreatment changes in QEEG measurements corresponded with changes in clinical symptoms. Conclusion: Patients with migraine have distinctive QEEG measurements, particularly regarding absolute power and the number of electrodes that surpassed the z‐score threshold in high beta wave activity. These findings suggest the potential of QEEG as a diagnostic biomarker and as a tool for monitoring treatment response in migraine patients, warranting further large‐scale studies for confirmation and expansion. [ABSTRACT FROM AUTHOR]

• Shifting toward processing external or internal stimuli modulates the brain rhythms. • External visual stimulation can interfere with VMI but not suppress a KMI. • The eye state during MI affects signal classification accuracy used in BCIs. • To control MI perspective-taking, a novel experimental procedure was developed. It is widely recognized that opening and closing the eyes can direct attention to external or internal stimuli processing. This has been confirmed by studies showing the effects of changes in visual stimulation changes on cerebral activity during different tasks, e.g., motor imagery and execution. However, an essential aspect of creating a mental representation of motion, such as imagery perspective, has not yet been investigated in the present context. Our study aimed to verify the effect of brief visual deprivation (under eyes open [EO] and eyes closed [EC] conditions) on brain wave oscillations and behavioral performance during kinesthetic imagery (KMI) and visual-motor imagery (VMI) tasks. We focused on the alpha and beta rhythms from visual- and motor-related EEG activity sources. Additionally, we used machine learning algorithms to establish whether the registered differences in brain oscillations might affect motor imagery brain-computer interface (MI-BCI) performance. The results showed that the occipital areas in the EC condition presented significantly stronger desynchronization during VMI tasks, which is typical for enhanced visual stimuli processing. Furthermore, the stronger desynchronization of alpha rhythms from motor areas in the EO, than EC condition confirmed previous effects obtained during real movements. It was also found that simulating movement under EC/EO conditions affected signal classification accuracy, which has practical implications for MI-BCI effectiveness. These findings suggest that shifting processing toward external or internal stimuli modulates brain rhythm oscillations associated with different perspectives on the mental representation of movement. [ABSTRACT FROM AUTHOR]

Natural speech perception requires processing the ongoing acoustic input while keeping in mind the preceding one and predicting the next. This complex computational problem could be handled by a dynamic multi-timescale hierarchical inferential process that coordinates the information flow up and down the language network hierarchy. Using a predictive coding computational model (Precoss-β) that identifies online individual syllables from continuous speech, we address the advantage of a rhythmic modulation of up and down information flows, and whether beta oscillations could be optimal for this. In the model, and consistent with experimental data, theta and low-gamma neural frequency scales ensure syllable-tracking and phoneme-level speech encoding, respectively, while the beta rhythm is associated with inferential processes. We show that a rhythmic alternation of bottom-up and top-down processing regimes improves syllable recognition, and that optimal efficacy is reached when the alternation of bottom-up and top-down regimes, via oscillating prediction error precisions, is in the beta range (around 20–30 Hz). These results not only demonstrate the advantage of a rhythmic alternation of up- and down-going information, but also that the low-beta range is optimal given sensory analysis at theta and low-gamma scales. While specific to speech processing, the notion of alternating bottom-up and top-down processes with frequency multiplexing might generalize to other cognitive architectures. Author summary: During speech perception, our brain achieves continuous acoustic analysis of the ongoing speech signal, its transformation into linguistic representations, and the prediction of the most likely next words or syllables. In this computational study, we address the biological mechanisms underpinning the coordination of these operations during natural speech processing. Using a model that recognizes on-line syllables in natural sentences, we show that neural activity at specific rhythms is dedicated to specific operations, and that while the theta and low-gamma rhythms are engaged in speech features signaling and encoding, the more endogenous low-beta rhythm drives the rhythmic and coordinated modulation of prediction errors across levels of hierarchy. [ABSTRACT FROM AUTHOR]

Brain–computer interfaces (BCIs) based on steady-state visually evoked potentials (SSVEPs) are inexpensive and do not require user training. However, the highly personalized reaction to visual stimulation is an obstacle to the wider application of this technique, as it can be ineffective, tiring, or even harmful at certain frequencies. In our experimental study, we proposed a new approach to the selection of optimal frequencies of photostimulation. By using a custom photostimulation device, we covered a frequency range from 5 to 25 Hz with 1 Hz increments, recording the subjects' brainwave activity (EEG) and analyzing the signal-to-noise ratio (SNR) changes at the corresponding frequencies. The proposed set of SNR-based coefficients and the discomfort index, determined by the ratio of theta and beta rhythms in the EEG signal, enables the automation of obtaining the recommended stimulation frequencies for use in SSVEP-based BCIs. [ABSTRACT FROM AUTHOR]

Cranial electrotherapy stimulation (CES) is a form of neurostimulation that delivers alternating microcurrent via electrodes on the head. We investigated the effectiveness of CES in reducing stress. Participants who experienced subjective stress combined with subclinical depression or insomnia were recruited based on interviews and questionnaires. The subjects were randomly assigned to the active CES or sham groups and asked to use the device for 30 min twice a day for three weeks. Psychological rating scales, quantitative electroencephalography (QEEG), and serial salivary cortisol levels were measured before and after the intervention. Sixty-two participants (58 females, mean age = 47.3 ± 8.2 years) completed the trial. After intervention, the depression scores improved significantly to a nearly normal level (Beck depression inventory-II, 31.3 ± 11.6 to 10.8 ± 7.2, p < 0.001) in the CES group, which were greater improvement compared to the sham group (p = 0.020). There were significant group-by-visit interactions in absolute delta power in the temporal area (p = 0.033), and theta (p = 0.038), beta (p = 0.048), and high beta power (p = 0.048) in the parietal area. CES led to a flattening of the cortisol slope (p = 0.011) and an increase in bedtime cortisol (p = 0.036) compared to the sham group. Bias may have been introduced during the process because device use and sample collection were self-conducted by participants at home. CES can alleviate depressive symptoms and stress response, showing a potential as an adjunctive therapy for stress. • Cranial electrotherapy stimulation is effective in reducing depressive symptoms in people with stress. • Cranial electrotherapy stimulation reduces theta, delta, and beta waves in people with stress. • Cranial electrotherapy stimulation flattens the diurnal cortisol slope in people with stress. [ABSTRACT FROM AUTHOR]

Simple Summary: The coadministration of ketamine and propofol (ketofol) via constant rate infusion (CRI) was studied as a total intravenous anesthetic in dogs. The study found that ketofol induced a biphasic EEG pattern. Subanesthetic doses during induction and recovery led to high beta EEG activity, reflecting increased brain activity. During maintenance with anesthetic doses, the EEG shifted to low beta activity, merging ketamine and propofol EEG characteristics. Ketofol CRI provided robust antinociception activity and maintained a stable heart rate and blood pressure. Subanesthetic ketofol doses caused behavioral excitement, including nystagmus, tongue flicking, salivation and muscle activity. However, these effects were temporary and not a major concern. Such excitement was absent during high-dose general anesthesia. In summary, ketofol CRI showed promise as a safe and effective total intravenous anesthetic combination for dogs. It featured distinct biphasic EEG patterns, stable cardiovascular function and potent antinociception. The effects of concurrent ketamine and propofol (ketofol) constant rate infusion (CRI) were examined in six dogs. The K:P ratio was 1:2, with an initial CRI of 0.25/0.5 mg/kg/min over ten minutes, followed by a 0.5 mg/kg ketamine bolus for induction. During induction, a comprehensive EEG frequency spectrum from delta to gamma was observed, accompanied by subanesthetic-dose ketofol-induced behavioral excitation, including nystagmus, tongue flicking, salivation and active muscle activity. The dogs were maintained on three 15 min decremental doses of ketofol CRI (0.8/1.6, 0.4/0.8 and 0.2/0.4 mg/kg/min). This phase featured a significant decrease in the Patient State Index, electromyographic activity and a shift to low beta waves (SEF95: 13–18 Hz). Additionally, profound antinociception to electric stimulation and a stable heart rate and blood pressure (MBP 81.5–110 mmHg) were observed, as well as a merging of ketamine and propofol EEG characteristics during maintenance. In the recovery phase, a return to beta and gamma EEG patterns and excitement behavior occurred, accompanied by a significant reduction in antinociception, highlighting features of low doses of ketofol. This study reveals biphasic EEG dynamic changes, associated behaviors and robust antinociception and cardiovascular function, suggesting the utility of ketofol as a total intravenous anesthetic combination in dogs. [ABSTRACT FROM AUTHOR]

Depressive disorder (DD) has become one of the most common mental diseases, seriously endangering both the affected person's psychological and physical health. Nowadays, a DD diagnosis mainly relies on the experience of clinical psychiatrists and subjective scales, lacking objective, accurate, practical, and automatic diagnosis technologies. Recently, electroencephalogram (EEG) signals have been widely applied for DD diagnosis, but mainly with high-density EEG, which can severely limit the efficiency of the EEG data acquisition and reduce the practicability of diagnostic techniques. The current study attempts to achieve accurate and practical DD diagnoses based on combining frontal six-channel electroencephalogram (EEG) signals and deep learning models. To this end, 10 min clinical resting-state EEG signals were collected from 41 DD patients and 34 healthy controls (HCs). Two deep learning models, multi-resolution convolutional neural network (MRCNN) combined with long short-term memory (LSTM) (named MRCNN-LSTM) and MRCNN combined with residual squeeze and excitation (RSE) (named MRCNN-RSE), were proposed for DD recognition. The results of this study showed that the higher EEG frequency band obtained the better classification performance for DD diagnosis. The MRCNN-RSE model achieved the highest classification accuracy of 98.48 ± 0.22% with 8–30 Hz EEG signals. These findings indicated that the proposed analytical framework can provide an accurate and practical strategy for DD diagnosis, as well as essential theoretical and technical support for the treatment and efficacy evaluation of DD. [ABSTRACT FROM AUTHOR]

One's working memory process is a fundamental cognitive activity which often serves as an indicator of brain disease and cognitive impairment. In this research, the approach to evaluate working memory ability by means of electroencephalography (EEG) analysis was proposed. The result shows that the EEG signals of subjects share some characteristics when performing working memory tasks. Through correlation analysis, a working memory model describes the changes in EEG signals within alpha, beta and gamma waves, which shows an inverse tendency compared to Zen meditation. The working memory ability of subjects can be predicted using multi-linear support vector regression (SVR) with fuzzy C-mean (FCM) clustering and knowledge-based fuzzy support vector regression (FSVR), which reaches the mean square error of 0.6 in our collected data. The latter, designed based on the working memory model, achieves the best performance. The research provides the insight of the working memory process from the EEG aspect to become an example of cognitive function analysis and prediction. [ABSTRACT FROM AUTHOR]

Wireless communication has become an integral part of our lives. The growing number of antennas in our environment and the expanding use of mobile phones (MPs) are increasing the population's exposure to electromagnetic fields. The present study aimed to examine the potential impact of MPs radiofrequency electromagnetic fields (RF-EMF) exposure on the brainwaves of the resting electroencephalogram (EEG) in humans. Twenty-one healthy volunteers were exposed to Global System for Mobile communications (GSM) signal at 900 MHz MP RF-EMF. The maximum specific absorption rate (SAR) of the MP averaged on 10 g tissue and 1 g tissue were measured at 0.49 W/kg, 0.70 W/kg, respectively. Results showed that while delta and beta rhythms of resting EEG were not affected, theta brainwaves were significantly modulated during exposure to RF-EMF related to MPs. For the first time, it was shown that this modulation is dependent on the eye condition, i.e. closed or open. This study strongly suggests that acute exposure to RF-EMF alters the EEG theta rhythm at rest. Long-term exposure studies are required to explore the effect of this disruption in high-risk or sensitive populations. [ABSTRACT FROM AUTHOR]

High-frequency stimulation (HFS) is a crucial therapeutic approach for neurodegenerative conditions, such as epilepsy. However, its underlying mechanism of inhibition remains unclear. In this study, a rat model of epileptiform discharges (EDs) was constructed by perfusing brain slices with magnesium-free artificial cerebrospinal fluid (aCSF), where after HFS was used to stimulate the CA3 area of the hippocampus. The EDs signals of each sub-region of hippocampal slices before and after HFS were recorded based on a multi-electrode Array (MEA). Secondly, the changes of approximate entropy (ApEn) complexity of rhythms in different regions of hippocampal slices before and after HFS were deeply analyzed The results showed that different rhythm characteristics of EDs signals exhibited significant differences before and after HFS. Here HFS significantly inhibited the delta rhythm of field potential and enhanced the beta rhythm. Finally, the changing rhythm of the EDs signal in the propagation path before and after HFS was analyzed, and it was found that the inhibitory target of HFS on EDs signal was in the CA3b sub-region. The rhythm would gradually decline with the propagation of EDs signal in the hippocampal neural pathway. This study shows that HFS can modulate the local field potential, thus inhibiting the pathological rhythm caused by epilepsy, which provides a novel research incentive for HFS to inhibit EDs. • The changes in approximate entropy of EDs induced by low levels of magnesium were analyzed. • High-frequency stimulation can inhibit the delta rhythm of field potential and enhanced the beta rhythm. • The target of high-frequency stimulation for suppressing EDs may be located in the CA3b subregion. [ABSTRACT FROM AUTHOR]

Generalized anxiety disorder (GAD) and depressive disorder (DD) are distinct mental disorders, which are characterized by complex and unique neuroelectrophysiological mechanisms in psychiatric neurosciences. The understanding of the brain functional differences between GAD and DD is crucial for the accurate diagnosis and clinical efficacy evaluation. The aim of this study was to reveal the differences in functional brain imaging between GAD and DD based on multidimensional electroencephalogram (EEG) characteristics. To this end, 10 min resting-state EEG signals were recorded from 38 GAD and 34 DD individuals. Multidimensional EEG features were subsequently extracted, which include power spectrum density (PSD), fuzzy entropy (FE), and phase lag index (PLI). Then, a direct statistical analysis (i.e., ANOVA) and three ensemble learning models (i.e., Random Forest (RF), Light Gradient Boosting Machine (LightGBM), eXtreme Gradient Boosting (XGBoost)) were used on these EEG features for the differential recognitions. Our results showed that DD has significantly higher PSD values in the alpha1 and beta band, and a higher FE in the beta band, in comparison with GAD, along with the aberrant functional connections in all four bands between GAD and DD. Moreover, machine learning analysis further revealed that the distinct features predominantly occurred in the beta band and functional connections. Here, we show that DD has higher power and more complex brain activity patterns in the beta band and reorganized brain functional network structures in all bands compared to GAD. In sum, these findings move towards the practical identification of brain functional differences between GAD and DD. [ABSTRACT FROM AUTHOR]

Stretching is an effective exercise for increasing body flexibility and pain relief. This study investigates the relationship between stretching intensity and relaxation effects, focusing on brainwaves and autonomic nervous system (ANS) activity. We used a crossover design with low- and high-intensity conditions to elucidate the impact of varying stretching intensities on neural activity associated with relaxation in 19 healthy young adults. Participants completed mood questionnaires. Electroencephalography (EEG) and plethysmography measurements were also obtained before, during, and after stretching sessions. The hamstring muscle was targeted for stretching, with intensity conditions based on the Point of Discomfort. Data analysis included wavelet analysis for EEG, plethysmography data, and repeated-measures ANOVA to differentiate mood, ANS activity, and brain activity related to stretching intensity. Results demonstrated no significant differences between ANS and brain activity based on stretching intensity. However, sympathetic nervous activity showed higher activity during the rest phases than in the stretch phases. Regarding brain activity, alpha and beta waves showed higher activity during the rest phases than in the stretch phases. A negative correlation between alpha waves and sympathetic nervous activities was observed in high-intensity conditions. However, a positive correlation between beta waves and parasympathetic nervous activities was found in low-intensity conditions. Our findings suggest that stretching can induce interactions between the ANS and brain activity. [ABSTRACT FROM AUTHOR]

The present study aimed to determine a multimodal brain empowerment (MBE) program to mitigate the modifiable risk factors in mild cognitive impairment (MCI), and its therapeutic effects are unknown. MBE encompassing (1) tDCS, light therapy, computerized cognitive therapy (TLC) and (2) robot-assisted gait training, music therapy, and core exercise (REM) interventions were randomly assigned to 20 healthy young adults and 20 older adults with MCI. The electroencephalography (EEG) power spectrum and topographic event-related synchronization (ERS) analysis were used to assess intervention-related changes in neural activity during the MBE program. Outcome: The EEG results demonstrated that both multimodal TLC and REM decreased delta waves and increased theta, alpha, and beta waves (p < 0.001). ERS showed increased neural activation in the frontal, temporal, and parietal lobes during TLC and REM. Such enhanced neural activity in the region of interest supports potential clinical benefits in empowering cognitive function in both young adults and older adults with MCI. [ABSTRACT FROM AUTHOR]

Neural oscillatory activity in the beta band (13–30 Hz) is prominent in the brain and it is transmitted partly linearly to the spinal cord and muscles. Multiple views on the functional relevance of beta activity in the motor system have been proposed. Previous simulation work suggested that pools of spinal motoneurons (MNs) receiving a common beta input could demodulate this activity, transforming it into low‐frequency neural drive that could alter force production in muscles. This may suggest that common beta inputs to muscles have a direct role in force modulation. Here we report the experimental average levels and ranges of common beta activity in spinal MNs projecting to single muscles and use a computational model of a MN pool to test if the experimentally observed beta levels in MNs can influence force. When beta was modelled as a continuous activity, the amplitude needed to produce non‐negligible changes in force corresponded to beta representation in the MN pool that was far above the experimental observations. On the other hand, when beta activity was modelled as short‐lived events (i.e. bursts of beta activity separated by intervals without beta oscillations), this activity approximated levels that could cause small changes in force with estimated average common beta inputs to the MNs compatible with the experimental observations. Nonetheless, bursting beta is unlikely to be used for force control due to the temporal sparsity of this activity. It is therefore concluded that beta oscillations are unlikely to contribute to the voluntary modulation of force. Key points: It has been previously proposed that beta (13–30 Hz) common inputs to a motor neuron pool may have a non‐linear effect in voluntary force control.The needed strength of beta oscillations to modulate forces has not been analysed yet.Based on computer simulations, we show that sustained beta inputs to a spinal motoneuron pool at physiologically reported levels have minimal effect on force.Levels of sustained beta rhythmic activity that can cause a significant change in force are not compatible with experimental observations of intramuscular coherence in human skeletal muscles. [ABSTRACT FROM AUTHOR]

The purpose of this research is to examine and assess the relation between a pilot's concentration and reaction time with specific brain activity during short-haul flights. Participants took part in one-hour long flight sessions performed on the FNPT II class flight simulator. Subjects were instructed to respond to unexpected events that occurred during the flight. The brainwaves of each participant were recorded with the Emotiv EPOC+ Scientific Contextual EEG device. The majority of participants showed a statistically significant, positive correlation between Theta Power in the frontal lobe and response time. Additionally, most subjects exhibited statistically significant, positive correlations between band-power and reaction times in the Theta range for the temporal and parietal lobes. Statistically significant event-related changes (ERC) were observed for the majority of subjects in the frontal lobe for Theta frequencies, Beta waves in the frontal lobe and in all lobes for the Gamma band. Notably, significant ERC was also observed for Theta and Beta frequencies in the temporal and occipital Lobes, Alpha waves in the frontal, parietal and occipital lobes for most participants. A difference in brain activity patterns was observed, depending on the performance in time-restricted tasks. [ABSTRACT FROM AUTHOR]

This study aimed to measure the spectral power differences in the brain rhythms among a group of hospital doctors before and after an overnight on-call duty. Thirty-two healthy doctors who performed regular on-call duty in a tertiary hospital in Sarawak, Malaysia were voluntarily recruited into this study. All participants were interviewed to collect relevant background information, followed by a self-administered questionnaire using Chalder Fatigue Scale and electroencephalogram test before and after an overnight on-call duty. The average overnight sleep duration during the on-call period was 2.2 hours (p<0.001, significantly shorter than usual sleep duration) among the participants. The mean (SD) Chalder Fatigue Scale score of the participants were 10.8 (5.3) before on-call and 18.4 (6.6) after on-call (p-value < 0.001). The theta rhythm showed significant increase in spectral power globally after an overnight on-call duty, especially when measured at eye closure. In contrast, the alpha and beta rhythms showed reduction in spectral power, significantly at temporal region, at eye closure, following an overnight on-call duty. These effects are more statistically significant when we derived the respective relative theta, alpha, and beta values. The finding of this study could be useful for development of electroencephalogram screening tool to detect mental fatigue. [ABSTRACT FROM AUTHOR]

Propofol-mediated unconsciousness elicits strong alpha/low-beta and slow oscillations in the electroencephalogram (EEG) of patients. As anesthetic dose increases, the EEG signal changes in ways that give clues to the level of unconsciousness; the network mechanisms of these changes are only partially understood. Here, we construct a biophysical thalamocortical network involving brain stem influences that reproduces transitions in dynamics seen in the EEG involving the evolution of the power and frequency of alpha/low-beta and slow rhythm, as well as their interactions. Our model suggests that propofol engages thalamic spindle and cortical sleep mechanisms to elicit persistent alpha/low-beta and slow rhythms, respectively. The thalamocortical network fluctuates between two mutually exclusive states on the timescale of seconds. One state is characterized by continuous alpha/low-beta-frequency spiking in thalamus (C-state), whereas in the other, thalamic alpha spiking is interrupted by periods of co-occurring thalamic and cortical silence (I-state). In the I-state, alpha colocalizes to the peak of the slow oscillation; in the Cstate, there is a variable relationship between an alpha/beta rhythm and the slow oscillation. The C-state predominates near loss of consciousness; with increasing dose, the proportion of time spent in the I-state increases, recapitulating EEG phenomenology. Cortical synchrony drives the switch to the I-state by changing the nature of the thalamocortical feedback. Brain stem influence on the strength of thalamocortical feedback mediates the amount of cortical synchrony. Our model implicates loss of low-beta, cortical synchrony, and coordinated thalamocortical silent periods as contributing to the unconscious state. [ABSTRACT FROM AUTHOR]

Although the disruptive effects of spinal cord injury (SCI) on the hippocampus have been confirmed in some animal studies, no study has investigated its retrograde manifestations in the hippocampus of aged subjects. Herein, we compared the aged rats with young ones 3 weeks after the induction of SCI (Groups: Sham.Young, SCI.Young, Sham.Aged, SCI.Aged). The locomotion, hippocampal apoptosis, hippocampal rhythms (Delta, Theta, Beta, Gamma) max frequency (Max.rf) and power, hippocampal neurogenesis, and hippocampal receptors (NMDA, GABA A, Muscarinic1/M1), which are important in the generation of rhythms and neurogenesis, were compared in aged rats in contrast to young rats. At the end of the third week, the number of apoptotic (Tunel+) cells in the hippocampus (CA1, DG) of SCI animals was significantly higher compared to the sham animals, and also, it was significantly higher in the SCI.Aged group compared to SCI.Young group. Moreover, the rate of neurogenesis (DCX+, BrdU+ cells) and expression of M1 and NMDA receptors were significantly lower in the SCI.Aged group compared to SCI.Young group. The power and Max.fr of all rhythms were significantly lower in SCI groups compared to sham groups. Despite the decrease in the power of rhythms in the SCI.Aged group compared to SCI.Young group, there was no significant difference between them, and in terms of Max.fr index, only the Max.fr of theta and beta rhythms were significantly lower in the SCI.Aged group compared to SCI.Young group. This study showed that SCI could cause more neurodegeneration in the hippocampus of aged animals compared to young animals. [ABSTRACT FROM AUTHOR]