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Current Psychiatry Reports Nov 2014Electroencephalography (EEG) has, historically, played a focal role in the assessment of neural function in children with attention deficit hyperactivity disorder... (Review)
Review
Electroencephalography (EEG) has, historically, played a focal role in the assessment of neural function in children with attention deficit hyperactivity disorder (ADHD). We review here the most recent developments in the utility of EEG in the diagnosis of ADHD, with emphasis on the most commonly used and emerging EEG metrics and their reliability in diagnostic classification. Considering the clinical heterogeneity of ADHD and the complexity of information available from the EEG signals, we suggest that considerable benefits are to be gained from multivariate analyses and a focus towards understanding of the neural generators of EEG. We conclude that while EEG cannot currently be used as a diagnostic tool, vast developments in analytical and technological tools in its domain anticipate future progress in its utility in the clinical setting.
Topics: Attention Deficit Disorder with Hyperactivity; Electroencephalography; Evoked Potentials; Humans
PubMed: 25234074
DOI: 10.1007/s11920-014-0498-0 -
Sensors (Basel, Switzerland) Apr 2022An electroencephalography (EEG)-based brain-computer interface (BCI) is a system that provides a pathway between the brain and external devices by interpreting EEG.... (Review)
Review
An electroencephalography (EEG)-based brain-computer interface (BCI) is a system that provides a pathway between the brain and external devices by interpreting EEG. EEG-based BCI applications have initially been developed for medical purposes, with the aim of facilitating the return of patients to normal life. In addition to the initial aim, EEG-based BCI applications have also gained increasing significance in the non-medical domain, improving the life of healthy people, for instance, by making it more efficient, collaborative and helping develop themselves. The objective of this review is to give a systematic overview of the literature on EEG-based BCI applications from the period of 2009 until 2019. The systematic literature review has been prepared based on three databases PubMed, Web of Science and Scopus. This review was conducted following the PRISMA model. In this review, 202 publications were selected based on specific eligibility criteria. The distribution of the research between the medical and non-medical domain has been analyzed and further categorized into fields of research within the reviewed domains. In this review, the equipment used for gathering EEG data and signal processing methods have also been reviewed. Additionally, current challenges in the field and possibilities for the future have been analyzed.
Topics: Brain; Brain-Computer Interfaces; Electroencephalography; Humans; Signal Processing, Computer-Assisted
PubMed: 35591021
DOI: 10.3390/s22093331 -
Minerva Anestesiologica Nov 2019Individual response to sedatives and hypnotics is characterized by high variability and the identification of a personalized dose during anesthesia in the operating room... (Review)
Review
Individual response to sedatives and hypnotics is characterized by high variability and the identification of a personalized dose during anesthesia in the operating room and during sedation in the intensive care unit may have beneficial effects. Although the brain is the main target of general intravenous and inhaled anesthetic agents, electroencephalography (EEG) is not routinely utilized to explore cerebral response to sedation and anesthesia probably because EEG trace reading is complex and requires encephalographers' skills. Automated processing algorithms (processed EEG, pEEG) of raw EEG traces provide easy-to-use indices that can be utilized to optimize anesthetic management. A large number of high-quality studies and the recommendations of international scientific societies have confirmed the deleterious consequences of inadequate or excessively deep anesthesia (and sedation) level. In this context, anesthesia in the operating rooms and moderate/deep sedation in intensive care units driven by pEEG monitors could become a standard practice in the near future. The aim of the present review was to provide an overview of current knowledge and debate on available technologies for pEEG monitoring and their role in clinical practice for anesthesia and sedation.
Topics: Anesthesia; Critical Care; Deep Sedation; Electroencephalography; Humans; Intraoperative Neurophysiological Monitoring; Operating Rooms; Seizures; Status Epilepticus
PubMed: 31630505
DOI: 10.23736/S0375-9393.19.13478-5 -
Bosnian Journal of Basic Medical... Aug 2019Electroencephalographic neurofeedback (EEG-NFB) represents a broadly used method that involves a real-time EEG signal measurement, immediate data processing with the... (Review)
Review
Electroencephalographic neurofeedback (EEG-NFB) represents a broadly used method that involves a real-time EEG signal measurement, immediate data processing with the extraction of the parameter(s) of interest, and feedback to the individual in a real-time. Using such a feedback loop, the individual may gain better control over the neurophysiological parameters, by inducing changes in brain functioning and, consequently, behavior. It is used as a complementary treatment for a variety of neuropsychological disorders and improvement of cognitive capabilities, creativity or relaxation in healthy subjects. In this review, various types of EEG-NFB training are described, including training of slow cortical potentials (SCPs) and frequency and coherence training, with their main results and potential limitations. Furthermore, some general concerns about EEG-NFB methodology are presented, which still need to be addressed by the NFB community. Due to the heterogeneity of research designs in EEG-NFB protocols, clear conclusions on the effectiveness of this method are difficult to draw. Despite that, there seems to be a well-defined path for the EEG-NFB research in the future, opening up possibilities for improvement.
Topics: Brain-Computer Interfaces; Electroencephalography; Humans; Nervous System Diseases; Neurofeedback; Signal Processing, Computer-Assisted; Treatment Outcome
PubMed: 30465705
DOI: 10.17305/bjbms.2018.3785 -
British Journal of Clinical Pharmacology Jan 2014To assess centrally mediated analgesic mechanisms in clinical trials with pain patients, objective standardized methods such as electroencephalography (EEG) has many... (Review)
Review
To assess centrally mediated analgesic mechanisms in clinical trials with pain patients, objective standardized methods such as electroencephalography (EEG) has many advantages. The aim of this review is to provide the reader with an overview of present findings in analgesics assessed with spontaneous EEG and evoked brain potentials (EPs) in humans. Furthermore, EEG methodologies will be discussed with respect to translation from animals to humans and future perspectives in predicting analgesic efficacy. We searched PubMed with MeSH terms 'analgesics', 'electroencephalography' and 'evoked potentials' for relevant articles. Combined with a search in their reference lists 15 articles on spontaneous EEG and 55 papers on EPs were identified. Overall, opioids produced increased activity in the delta band in the spontaneous EEG, but increases in higher frequency bands were also seen. The EP amplitudes decreased in the majority of studies. Anticonvulsants used as analgesics showed inconsistent results. The N-methyl-D-aspartate receptor antagonist ketamine showed an increase in the theta band in spontaneous EEG and decreases in EP amplitudes. Tricyclic antidepressants increased the activity in the delta, theta and beta bands in the spontaneous EEG while EPs were inconsistently affected. Weak analgesics were mainly investigated with EPs and a decrease in amplitudes was generally observed. This review reveals that both spontaneous EEG and EPs are widely used as biomarkers for analgesic drug effects. Methodological differences are common and a more uniform approach will further enhance the value of such biomarkers for drug development and prediction of treatment response in individual patients.
Topics: Analgesics; Animals; Brain Waves; Electroencephalography; Evoked Potentials; Humans
PubMed: 23593934
DOI: 10.1111/bcp.12137 -
Sensors (Basel, Switzerland) Jul 2014Electroencephalography (EEG) emerged in the second decade of the 20th century as a technique for recording the neurophysiological response. Since then, there has been... (Review)
Review
Electroencephalography (EEG) emerged in the second decade of the 20th century as a technique for recording the neurophysiological response. Since then, there has been little variation in the physical principles that sustain the signal acquisition probes, otherwise called electrodes. Currently, new advances in technology have brought new unexpected fields of applications apart from the clinical, for which new aspects such as usability and gel-free operation are first order priorities. Thanks to new advances in materials and integrated electronic systems technologies, a new generation of dry electrodes has been developed to fulfill the need. In this manuscript, we review current approaches to develop dry EEG electrodes for clinical and other applications, including information about measurement methods and evaluation reports. We conclude that, although a broad and non-homogeneous diversity of approaches has been evaluated without a consensus in procedures and methodology, their performances are not far from those obtained with wet electrodes, which are considered the gold standard, thus enabling the former to be a useful tool in a variety of novel applications.
Topics: Electric Impedance; Electrodes; Electroencephalography; Equipment Design; Humans
PubMed: 25046013
DOI: 10.3390/s140712847 -
The Journal of Comparative Neurology Dec 2020The presence of dreams in human sleep, especially in REM sleep, and the detection of physiologically similar states in mammals has led many to ponder whether animals... (Review)
Review
The presence of dreams in human sleep, especially in REM sleep, and the detection of physiologically similar states in mammals has led many to ponder whether animals experience similar sleep mentation. Recent advances in our understanding of the anatomical and physiological correlates of sleep stages, and thus dreaming, allow a better understanding of the possibility of dream mentation in nonhuman mammals. Here, we explore the potential for dream mentation, in both non-REM and REM sleep across mammals. If we take a hard-stance, that dream mentation only occurs during REM sleep, we conclude that it is unlikely that monotremes, cetaceans, and otariid seals while at sea, have the potential to experience dream mentation. Atypical REM sleep in other species, such as African elephants and Arabian oryx, may alter their potential to experience REM dream mentation. Alternatively, evidence that dream mentation occurs during both non-REM and REM sleep, indicates that all mammals have the potential to experience dream mentation. This non-REM dream mentation may be different in the species where non-REM is atypical, such as during unihemispheric sleep in aquatic mammals (cetaceans, sirens, and Otariid seals). In both scenarios, the cetaceans are the least likely mammalian group to experience vivid dream mentation due to the morphophysiological independence of their cerebral hemispheres. The application of techniques revealing dream mentation in humans to other mammals, specifically those that exhibit unusual sleep states, may lead to advances in our understanding of the neural underpinnings of dreams and conscious experiences.
Topics: Animals; Dreams; Electroencephalography; Humans; Sleep Stages
PubMed: 31960424
DOI: 10.1002/cne.24860 -
Journal of Clinical Neurophysiology :... Apr 2015Critical Care Continuous EEG (CCEEG) is a common procedure to monitor brain function in patients with altered mental status in intensive care units. There is significant...
INTRODUCTION
Critical Care Continuous EEG (CCEEG) is a common procedure to monitor brain function in patients with altered mental status in intensive care units. There is significant variability in patient populations undergoing CCEEG and in technical specifications for CCEEG performance.
METHODS
The Critical Care Continuous EEG Task Force of the American Clinical Neurophysiology Society developed expert consensus recommendations on the use of CCEEG in critically ill adults and children.
RECOMMENDATIONS
The consensus panel recommends CCEEG for diagnosis of nonconvulsive seizures, nonconvulsive status epilepticus, and other paroxysmal events, and for assessment of the efficacy of therapy for seizures and status epilepticus. The consensus panel suggests CCEEG for identification of ischemia in patients at high risk for cerebral ischemia; for assessment of level of consciousness in patients receiving intravenous sedation or pharmacologically induced coma; and for prognostication in patients after cardiac arrest. For each indication, the consensus panel describes the patient populations for which CCEEG is indicated, evidence supporting use of CCEEG, utility of video and quantitative EEG trends, suggested timing and duration of CCEEG, and suggested frequency of review and interpretation.
CONCLUSION
CCEEG has an important role in detection of secondary injuries such as seizures and ischemia in critically ill adults and children with altered mental status.
Topics: Adult; Brain Diseases; Child; Critical Care; Critical Illness; Electroencephalography; Female; Humans; Male; Monitoring, Physiologic
PubMed: 25626778
DOI: 10.1097/WNP.0000000000000166 -
Alcohol Research : Current Reviews 2015Electrophysiological measures of brain function are effective tools to understand neurocognitive phenomena and sensitive indicators of pathophysiological processes... (Review)
Review
Electrophysiological measures of brain function are effective tools to understand neurocognitive phenomena and sensitive indicators of pathophysiological processes associated with various clinical conditions, including alcoholism. Individuals with alcohol use disorder (AUD) and their high-risk offspring have consistently shown dysfunction in several electrophysiological measures in resting state (i.e., electroencephalogram) and during cognitive tasks (i.e., event-related potentials and event-related oscillations). Researchers have recently developed sophisticated signal-processing techniques to characterize different aspects of brain dynamics, which can aid in identifying the neural mechanisms underlying alcoholism and other related complex disorders.These quantitative measures of brain function also have been successfully used as endophenotypes to identify and help understand genes associated with AUD and related disorders. Translational research also is examining how brain electrophysiological measures potentially can be applied to diagnosis, prevention, and treatment.
Topics: Alcohol-Related Disorders; Biomedical Research; Brain; Electroencephalography; Electrophysiological Phenomena; Evoked Potentials; Humans
PubMed: 26259089
DOI: No ID Found -
Computers in Biology and Medicine Nov 2022Wearable multi-modal time-series classification applications outperform their best uni-modal counterparts and hold great promise. A modality that directly measures... (Review)
Review
BACKGROUND
Wearable multi-modal time-series classification applications outperform their best uni-modal counterparts and hold great promise. A modality that directly measures electrical correlates from the brain is electroencephalography. Due to varying noise sources, different key brain regions, key frequency bands, and signal characteristics like non-stationarity, techniques for data pre-processing and classification algorithms are task-dependent.
METHOD
Here, a systematic literature review on mental state classification for wearable electroencephalography is presented. Four search terms in different combinations were used for an in-title search. The search was executed on the 29th of June 2022, across Google Scholar, PubMed, IEEEXplore, and ScienceDirect. 76 most relevant publications were set into context as the current state-of-the-art in mental state time-series classification.
RESULTS
Pre-processing techniques, features, and time-series classification models were analyzed. Across publications, a window length of one second was mainly chosen for classification and spectral features were utilized the most. The achieved performance per time-series classification model is analyzed, finding linear discriminant analysis, decision trees, and k-nearest neighbors models outperform support-vector machines by a factor of up to 1.5. A historical analysis depicts future trends while under-reported aspects relevant to practical applications are discussed.
CONCLUSIONS
Five main conclusions are given, covering utilization of available area for electrode placement on the head, most often or scarcely utilized features and time-series classification model architectures, baseline reporting practices, as well as explainability and interpretability of Deep Learning. The importance of a 'test battery' assessing the influence of data pre-processing and multi-modality on time-series classification performance is emphasized.
Topics: Algorithms; Brain; Electroencephalography; Head; Wearable Electronic Devices
PubMed: 36137314
DOI: 10.1016/j.compbiomed.2022.106088