UNASSIGNED: Electroencephalography (EEG) is a technique for measuring brain activity that is widely used in neuroscience research. Event-related potentials (ERPs) in the EEG make it possible to study sensory and cognitive processes in the brain. Previous reports have shown that aerobic exercise can have an impact on components of ERPs such as amplitude and latency. However, they focused on the measurement of ERPs after exercise.
UNASSIGNED: The aim of this systematic review was to investigate the feasibility of measuring ERPs during cycling, and to assess the impact of cycling on ERPs during cycling.
UNASSIGNED: We followed the PRISMA guidelines for new systematic reviews. To be eligible, studies had to include healthy adults and measure ERPs during cycling. All articles were found using Google Scholar and by searching references. Data extracted from the studies included: objectives of ERP studies, ERP paradigm, EEG system, study population data, exercise characteristics (duration, intensity, pedaling cadence), and ERP and behavioral outcomes. The Cochrane Risk of Bias 2 tool was used to assess study bias.
UNASSIGNED: Twenty studies were selected. The effect of cycling on ERPs was mainly based on a comparison of P3 wave amplitude between cycling and resting states, using an attentional task. The ERP paradigm most often used was the auditory oddball task. Exercise characteristics and study methods varied considerably.
UNASSIGNED: It is possible to measure ERPs during cycling under conditions that are likely to introduce more artifacts, including a 3-h athletic exercise session and cycling outdoors. Secondly, no assessment of the effect of cycling on ERPs was possible, because the methods differed too widely between studies. In addition, the theories proposed to explain the results sometimes seemed to contradict each other. Although most studies reported significant results, the direction of the effects was inconsistent. Finally, we suggest some areas for improvement for future studies on the subject.

Absence seizures are classically associated with behavioral arrest and transient deficits in consciousness, yet substantial variability exists in the severity of the impairment. Despite several decades of research on the topic, the pathophysiology of absence seizures and the mechanisms underlying behavioral impairment remain unclear. Several rationales have been proposed including widespread cortical deactivation, reduced perception of external stimuli, and transient suspension of the default mode network, among others. This review aims to summarize the current knowledge on the neural correlates of impaired consciousness in absence seizures. We review evidence from studies using animal models of absence epilepsy, electroencephalography, functional magnetic resonance imaging, magnetoencephalography, positron emission tomography, and single photon emission computed tomography.

UNASSIGNED: Stress is one of the main environmental factors involved in the onset of different psychopathologies. In youth, stressful life events can trigger inappropriate and health-damaging behaviors, such as binge drinking. This behavior, in turn, can lead to long-lasting changes in the neurophysiological response to stress and the development of psychological disorders late in life, e.g., alcohol use disorder. Our aim was to analyze the pattern of neurophysiological responses triggered with the exposition to a stressful virtual environment in young binge drinkers.
UNASSIGNED: AUDIT-3 (third question from the full AUDIT) was used to detect binge drinking (BD) in our young sample (age 18-25 years). According to the score, participants were divided into control (CO) and BD group. Next, a standardized virtual reality (VR) scenario (Richie\'s Plank) was used for triggering the stress response while measuring the following neurophysiological variables: brain electrical activity by electroencephalogram (EEG) and cortisol levels through saliva samples both measurements registered before and after the stressful situation. Besides, heart rate (HR) with a pulsometer and electrodermal response (EDA) through electrodes placed on fingers were analyzed before, during and after the VR task.
UNASSIGNED: Regarding the behavior assessed during the VR task, BD group spent significantly less amount of time walking forward the table and a tendency toward more time walking backwards. There was no statistically significant difference between the BD and the CO group regarding time looking down, but when we controlled the variable sex, the BD women group displayed higher amount of time looking down than the rest of the groups. Neurophysiological measurements revealed that there was not any statistically significant difference between groups in any of the EEG registered measures, EDA response and cortisol levels. Sex-related differences were found in HR response to VR scenario, in which BD women displayed the highest peak of response to the stressor. Also, the change in heartbeat was higher in BD women than men.
UNASSIGNED: Unveiling the neurophysiological alterations associated with BD can help us to prevent and detect early onset of alcohol use disorder. Also, from our data we conclude that participants\' sex can modulate some stress responses, especially when unhealthy behaviors such as BD are present. Nevertheless, the moment of registration of the neurophysiological variables respect to the stressor seems to be a crucial variable.

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Physical activity and mindfulness techniques, such as exercise and Kapalbhati Pranayama, are known to have positive effects on health and well-being. However, limited research has directly compared their impact on physiological and psychological parameters. This study aimed to investigate and compare the effects of exercise and Kapalbhati Pranayama on Heart Rate Variability (HRV) and Electroencephalogram (EEG) activity, shedding light on their contributions to overall health and mental well-being. The study was conducted at All India Institute of Medical Sciences (AIIMS) in Bhopal, India, from 2018 to 2022. A prospective interventional design was employed over two months, involving 20 participants with normal BMI and no respiratory or cardiac conditions. Exclusion criteria included lung or cardiac diseases, smoking history, dyspnoea during physical activity, pedal edema, and high blood pressure. The Kapalbhati Pranayama intervention was supervised and limited to 5 minutes. HRV was assessed using the HRV Brain Tap Neuralchek Machine before, during, and after Kapalbhati. For exercise, a mild-intensity cycling protocol was performed on healthy volunteers aged 20 to 50. HRV was recorded before, during, and after exercise. The EEG analysis revealed notable changes in brain wave patterns. At baseline, participants exhibited higher levels of delta, theta, and alpha waves, indicating a state of relaxation and calmness. During exercise, there was a significant increase in beta waves and a decrease in delta, theta, and alpha waves, reflecting heightened brain activity and alertness. After Kapalbhati, beta wave levels remained elevated, while delta and theta wave suppression was more pronounced, suggesting a stimulating effect on the brain similar to exercise. The changes in beta and gamma EEG waves could be attributed to factors such as exercise intensity, duration, frequency, and the release of endorphins during both exercise and Kapalbhati. The HRV analysis demonstrated distinct responses to exercise and Kapalbhati. Exercise led to a significant reduction in HRV parameters, characterized by increased heart rate and decreased time-domain HRV measures, aligning with the typical sympathetic nervous system dominance during physical activity. In contrast, Kapalbhati\'s impact on HRV parameters was milder, with minor changes in heart rate and subtle alterations in time-domain HRV measures. The high LF/HF ratio during Kapalbhati suggested a potential stimulation of the sympathetic nervous system. More comprehensive research is required to confirm these findings and understand the long-term effects of Kapalbhati on HRV and cardiovascular health. This study contributes to the understanding of how exercise and Kapalbhati Pranayama affect both cognitive and cardiovascular aspects of health. It highlights that both interventions increase brain activity and alertness, but Kapalbhati may have a more potent effect. Exercise significantly reduces HRV parameters, indicating sympathetic nervous system dominance, while Kapalbhati has milder HRV effects. Further research with larger and more diverse populations is essential to confirm and expand on these findings, providing insights into optimizing cognitive function and cardiovascular health through tailored approaches of exercise and Kapalbhati Pranayama.

OBJECTIVE: Transcutaneous auricular vagus nerve stimulation (taVNS), a non-invasive method of stimulating the vagus nerve, simultaneously affects the autonomic nervous system (ANS) and central nervous system (CNS) through efferent and afferent pathways. The purpose of this study is to analyze the effect of taVNS on the ANS and CNS through heart rate variability (HRV) and electroencephalography (EEG) parameters of identified responders.
METHODS: Two sets of data were collected from each of 10 healthy adult male subjects in their 20s, and five HRV parameters from the time domain (RMSSD, pNN50, pNN30, pNN20, ppNNx) and two EEG parameters (power of alpha band, power of delta band) were extracted.
RESULTS: Based on pNN50, responders to taVNS were identified; among them, pNN50 (p = 0.0041) and ppNNx (p = 0.0037) showed significant differences before and after taVNS. At the same time, for alpha power and delta power of EEG, significant difference (p < 0.05) was observed in most channels after taVNS compared to before stimulation.
CONCLUSIONS: This study demonstrated the validity of identifying responders using pNN50 and the influence of taVNS on both the ANS and CNS. We conclude that taVNS can be used to treat a variety of diseases and as a tool to help control the ANS and CNS.

BACKGROUND: Neurofeedback is a non-invasive brain training technique used to enhance and treat hyperactivity disorder by altering the patterns of brain activity. Nonetheless, the extent of enhancement by neurofeedback varies among individuals/patients and many of them are irresponsive to this treatment technique. Therefore, several studies have been conducted to predict the effectiveness of neurofeedback training including the theta/beta protocol with a specific emphasize on slow cortical potential (SCP) before initiating treatment, as well as examining SCP criteria according to age and sex criteria in diverse populations. While some of these studies failed to make accurate predictions, others have demonstrated low success rates. This study explores functional connections within various brain lobes across different frequency bands of electroencephalogram (EEG) signals and the value of phase locking is used to predict the potential effectiveness of neurofeedback treatment before its initiation.
METHODS: This study utilized EEG data from the Mendelian database. In this database, EEG signals were recorded during neurofeedback sessions involving 60 hyperactive students aged 7-14 years, irrespective of sex. These students were categorized into treatable and non-treatable. The proposed method includes a five-step algorithm. Initially, the data underwent preprocessing to reduce noise using a multi-stage filtering process. The second step involved extracting alpha and beta frequency bands from the preprocessed EEG signals, with a particular emphasis on the EEG recorded from sessions 10 to 20 of neurofeedback therapy. In the third step, the method assessed the disparity in brain signals between the two groups by evaluating functional relationships in different brain lobes using the phase lock value, a crucial data characteristic. The fourth step focused on reducing the feature space and identifying the most effective and optimal electrodes for neurofeedback treatment. Two methods, the probability index (p-value) via a t-test and the genetic algorithm, were employed. These methods showed that the optimal electrodes were in the frontal lobe and central cerebral cortex, notably channels C3, FZ, F4, CZ, C4, and F3, as they exhibited significant differences between the two groups. Finally, in the fifth step, machine learning classifiers were applied, and the results were combined to generate treatable and non-treatable labels for each dataset.
RESULTS: Among the classifiers, the support vector machine and the boosting method demonstrated the highest accuracy when combined. Consequently, the proposed algorithm successfully predicted the treatability of individuals with hyperactivity in a short time and with limited data, achieving an accuracy of 90.6% in the neurofeedback method. Additionally, it effectively identified key electrodes in neurofeedback treatment, reducing their number from 32 to 6.
CONCLUSIONS: This study introduces an algorithm with a 90.6% accuracy for predicting neurofeedback treatment outcomes in hyperactivity disorder, significantly enhancing treatment efficiency by identifying optimal electrodes and reducing their number from 32 to 6. The proposed method enables the prediction of patient responsiveness to neurofeedback therapy without the need for numerous sessions, thus conserving time and financial resources.

BACKGROUND: In this study, we used electroencephalogram (EEG) to investigate the activity pattern of the cerebral cortex related to visual pursuit and saccade strategies to predict the arrival position of a visual target. In addition, we clarified the differences in the EEG of those who could predict the arrival position well using the saccade strategy compared to those who were not proficient.
METHODS: Sixteen participants performed two tasks: the \"Pursuit Strategy Task (PST)\" and the \"Saccade Strategy Task (SST)\" while undergoing EEG. For the PST, the participants were instructed to follow the target with their eyes throughout its trajectory and indicate when it reached the final point. For the SST, the participants were instructed to shift their gaze to the end point of arrival once they had predicted it.
RESULTS: Low beta EEG activity at the Oz, Cz, and CP2 electrodes was significantly higher during the SST than during the PST. In addition, low beta EEG activity at P7 electrode was significantly higher in the group showing a small position error (PE) than in the group showing a large PE at response.
CONCLUSIONS: EEG activity at the Oz, Cz, and CP2 electrodes during the SST may reflect visuospatial attention to the moving target, the tracking of moving targets, and the focus on the final destination position. In addition, EEG activity at P7 electrode may more accurately detect the speed and direction of the moving target by the small PE group at response.

CONCLUSIONS: Stereo-EEG is a widely used method to improve the diagnostic precision of presurgical workup in patients with refractory epilepsy. Its ability to detect epileptic activity and identify epileptic networks largely depends on the chosen implantation strategy. Even in an ideal situation, electrodes record activity generated in <10% of the brain and contacts only record from brain tissue in their immediate proximity. In this article, the authors discuss how recording stereo-EEG simultaneously with other diagnostic methods can improve its diagnostic value in clinical and research settings. It can help overcome the limited spatial coverage of intracranial recording and better understand the sources of epileptic activity. Simultaneous scalp EEG is the most widely available method, often used to understand large epileptic networks, seizure propagation, and EEG activity occurring on the contralateral hemisphere. Simultaneous magnetoencephalography allows for more precise source localization and identification of deep sources outside the stereo-EEG coverage. Finally, simultaneous functional MRI can highlight metabolic changes following epileptic activity and help understand the widespread network changes associated with interictal activity. This overview highlights advantages and methodological challenges for all these methods. Clinical use and research applications are presented for each approach.

CONCLUSIONS: Although the role of sleep in modulating epileptic activity is well established, many epileptologists overlook the significance of considering sleep during presurgical epilepsy evaluations in cases of drug-resistant epilepsy. Here, we conducted a comprehensive literature review from January 2000 to May 2023 using the PubMed electronic database and compiled evidence to highlight the need to revise the current clinical approach. All articles were assessed for eligibility by two independent reviewers. Our aim was to shed light on the clinical value of incorporating sleep monitoring into presurgical evaluations with stereo-electroencephalography. We present the latest developments on the important bidirectional interactions between sleep and various forms of epileptic activity observed in stereo-electroencephalography recordings. Specifically, epileptic activity is modulated by different sleep stages, peaking in non-rapid eye movement sleep, while being suppressed in rapid eye movement sleep. However, this modulation can vary across different brain regions, underlining the need to account for sleep to accurately pinpoint the epileptogenic zone during presurgical assessments. Finally, we offer practical solutions, such as automated sleep scoring algorithms using stereo-electroencephalography data alone, to seamlessly integrate sleep monitoring into routine clinical practice. It is hoped that this review will provide clinicians with a readily accessible roadmap to the latest evidence concerning the clinical utility of sleep monitoring in the context of stereo-electroencephalography and aid the development of therapeutic and diagnostic strategies to improve patient surgical outcomes.