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La electroencefalografía (EEG) siempre ha sido considerada una materia especializada, que amerita de entrenamiento para su aplicación e interpretación; esto ha provocado que el acceso a estos estudios quedara confinado a neurólogos y neurofisiólogos. El recién nacido ingresado en la unidad de cuidados intensivos neonatales (UCIN) amerita de monitorización neurológica para establecer diagnóstico y pronóstico, por lo que se necesita una herramienta sencilla y accesible para el personal de la UCIN. Estas características han sido cubiertas por el electroencefalograma de amplitud integrada (aEEG) que, a través de patrones visuales simples de la actividad cerebral, permite el abordaje de la condición neurológica. El objetivo de este ensayo se orienta al manejo de mnemotecnias que faciliten la identificación de patrones visuales normales y patológicos en el aEEG. La nomenclatura empleada, aunque puede parecer simple, pretende crear una idea fácilmente asimilable de los conceptos básicos para la aplicación e interpretación de la neuromonitorización con aEEG.
An electroencephalography (EEG) has always been considered a specialized field, whose use and interpretation requires training. For this reason, access to these monitoring studies has been restricted to neurologists and neurophysiologists. Newborn infants admitted to the neonatal intensive care unit (NICU) require neurophysiological monitoring to establish their diagnosis and prognosis, so a simple and accessible tool is required for NICU staff. Such features have been covered by amplitude-integrated electroencephalography (aEEG), which, through simple visual patterns of brain activity, allows to approach neurological conditions. The objective of this study is to help with the management of mnemonics that facilitate the identification of normal and pathological visual patterns in an aEEG. Although simple in appearance, this nomenclature is intended to create an easy-to-understand idea of basic concepts for the use and interpretation of neurophysiological monitoring with aEEG.
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Humanos , Recém-Nascido , Unidades de Terapia Intensiva Neonatal , Eletroencefalografia/métodos , Monitorização Neurofisiológica/métodosRESUMO
Seizures are neurological disorders triggered by an imbalance in the activity of excitatory and inhibitory neurotransmitters in the brain. When triggered chronically, this imbalance can lead to epilepsy. Critically, many of the affected individuals are refractory to treatment. Given this, anti-inflammatory drugs, in particular glucocorticoids, have been considered as a potential antiepileptogenic therapy. Glucocorticoids are currently used in the treatment of refractory patients, although there have been contradictory results in terms of their use in association with antiepileptic drugs, which reinforces the need for a more thorough investigation of their effects. In this context, the present study evaluated the effects of dexamethasone (DEX, 0.6 mg/kg) on the electroencephalographic (EEG) and histopathological parameters of male Wistar rats submitted to acute seizure induced by pentylenetetrazol (PTZ). The EEG monitoring revealed that DEX reduced the total brainwave power, in comparison with PTZ, in 12 h after the convulsive episode, exerting this effect in up to 36 h (p < 0.05 for all comparisons). An increase in the accommodation of the oscillations of the delta, alpha, and gamma frequencies was also observed from the first 12 h onwards, with the accommodation of the theta frequency occurring after 36 h, and that of the beta frequency 24 h after the seizure. The histopathological analyses showed that the CA3 region and hilum of the hippocampus suffered cell loss after the PTZ-induced seizure (control vs. PTZ, p < 0.05), although DEX was not able to protect these regions against cell death (PTZ vs. DEX + PTZ, p > 0.05). While DEX did not reverse the cell damage caused by PTZ, the data indicate that DEX has beneficial properties in the EEG analysis, which makes it a promising candidate for the attenuation of the epileptiform wave patterns that can precipitate refractory seizures.
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Ondas Encefálicas , Dexametasona , Eletroencefalografia , Pentilenotetrazol , Ratos Wistar , Convulsões , Animais , Dexametasona/farmacologia , Dexametasona/efeitos adversos , Pentilenotetrazol/toxicidade , Convulsões/tratamento farmacológico , Convulsões/induzido quimicamente , Convulsões/fisiopatologia , Masculino , Ratos , Ondas Encefálicas/efeitos dos fármacos , Encéfalo/efeitos dos fármacos , Encéfalo/patologia , Encéfalo/fisiopatologia , Anticonvulsivantes/farmacologia , Hipocampo/efeitos dos fármacos , Hipocampo/patologia , Hipocampo/fisiopatologiaRESUMO
Sporadic Creutzfeldt-Jakob disease (CJD) is a rare neurodegenerative spongiform encephalopathy that causes neuronal derangement secondary to prion protein. Its initial diagnosis is often complex and challenging due to non-specific clinical presentation, lack of awareness, and low clinical suspicion. This disease is invariably fatal, and most patients die within 12 months of presentation. Definite diagnosis of prion disease requires neuropathological analysis, usually done at autopsy. Here, we present the autopsy findings of a 57-year-old male patient, illustrating the complexity of diagnosing this disease early in the clinical course and the need for a broad differential diagnosis at the onset.
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A data set of clinical studies of electroencephalogram recordings (EEG) following data acquisition protocols in control individuals (Eyes Closed Wakefulness - Eyes Open Wakefulness, Hyperventilation, and Optostimulation) are quantified with information theory metrics, namely permutation Shanon entropy and permutation Lempel Ziv complexity, to identify functional changes. This work implement Linear mixed-effects models (LMEMs) for confirmatory hypothesis testing. The results show that EEGs have high variability for both metrics and there is a positive correlation between them. The mean of permutation Lempel-Ziv complexity and permutation Shanon entropy used simultaneously for each of the four states are distinguishable from each other. However, used separately, the differences between permutation Lempel-Ziv complexity or permutation Shanon entropy of some states were not statistically significant. This shows that the joint use of both metrics provides more information than the separate use of each of them. Despite their wide use in medicine, LMEMs have not been commonly applied to simultaneously model metrics that quantify EEG signals. Modeling EEGs using a model that characterizes more than one response variable and their possible correlations represents a new way of analyzing EEG data in neuroscience.
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Understanding the brain response to thermal stimuli is crucial in the sensory experience. This study focuses on non-painful thermal stimuli, which are sensations induced by temperature changes without causing discomfort. These stimuli are transmitted to the central nervous system through specific nerve fibers and are processed in various regions of the brain, including the insular cortex, the prefrontal cortex, and anterior cingulate cortex. Despite the prevalence of studies on painful stimuli, non-painful thermal stimuli have been less explored. This research aims to bridge this gap by investigating brain functional connectivity during the perception of non-painful warm and cold stimuli using electroencephalography (EEG) and the partial directed coherence technique (PDC). Our results demonstrate a clear contrast in the direction of information flow between warm and cold stimuli, particularly in the theta and alpha frequency bands, mainly in frontal and temporal regions. The use of PDC highlights the complexity of brain connectivity during these stimuli and reinforces the existence of different pathways in the brain to process different types of non-painful warm and cold stimuli.
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Encéfalo , Eletroencefalografia , Humanos , Eletroencefalografia/métodos , Masculino , Encéfalo/fisiologia , Encéfalo/diagnóstico por imagem , Adulto , Feminino , Adulto Jovem , Temperatura Baixa , Mapeamento Encefálico/métodos , Temperatura Alta , Dor , Sensação Térmica/fisiologiaRESUMO
Regarding motor processes, modeling healthy people's brains is essential to understand the brain activity in people with motor impairments. However, little research has been undertaken when external forces disturb limbs, having limited information on physiological pathways. Therefore, in this paper, a nonlinear delay differential embedding model is used to estimate the brain response elicited by externally controlled wrist movement in healthy individuals. The aim is to improve the understanding of the relationship between a controlled wrist movement and the generated cortical activity of healthy people, helping to disclose the underlying mechanisms and physiological relationships involved in the motor event. To evaluate the model, a public database from the Delft University of Technology is used, which contains electroencephalographic recordings of ten healthy subjects while wrist movement was externally provoked by a robotic system. In this work, the cortical response related to movement is identified via Independent Component Analysis and estimated based on a nonlinear delay differential embedding model. After a cross-validation analysis, the model performance reaches 90.21% ± 4.46% Variance Accounted For, and Correlation 95.14% ± 2.31%. The proposed methodology allows to select the model degree, to estimate a general predominant operation mode of the cortical response elicited by wrist movement. The obtained results revealed two facts that had not previously been reported: the movement's acceleration affects the cortical response, and a common delayed activity is shared among subjects. Going forward, identifying biomarkers related to motor tasks could aid in the evaluation of rehabilitation treatments for patients with upper limbs motor impairments.
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Movimento , Dinâmica não Linear , Punho , Humanos , Punho/fisiologia , Masculino , Movimento/fisiologia , Adulto , Eletroencefalografia , Feminino , Adulto JovemRESUMO
Motor adaptations are responsible for recalibrating actions and facilitating the achievement of goals in a constantly changing environment. Once consolidated, the decay of motor adaptation is a process affected by available sensory information during deadaptation. However, the cortical response to task error feedback during the deadaptation phase has received little attention. Here, we explored changes in brain cortical responses due to feedback of task-related error during deadaptation. Twelve healthy volunteers were recruited for the study. Right hand movement and EEG were recorded during repetitive trials of a hand reaching movement. A visuomotor rotation of 30° was introduced to induce motor adaptation. Volunteers participated in two experimental sessions organized in baseline, adaptation, and deadaptation blocks. In the deadaptation block, the visuomotor rotation was removed, and visual feedback was only provided in one session. Performance was quantified using angle end-point error, averaged speed, and movement onset time. A non-parametric spatiotemporal cluster-level permutation test was used to analyze the EEG recordings. During deadaptation, participants experienced a greater error reduction when feedback of the cursor was provided. The EEG responses showed larger activity in the left centro-frontal parietal areas during the deadaptation block when participants received feedback, as opposed to when they did not receive feedback. Centrally distributed clusters were found for the adaptation and deadaptation blocks in the absence of visual feedback. The results suggest that visual feedback of the task-related error activates cortical areas related to performance monitoring, depending on the accessible sensory information.
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Adaptação Fisiológica , Eletroencefalografia , Retroalimentação Sensorial , Desempenho Psicomotor , Humanos , Masculino , Feminino , Adulto , Desempenho Psicomotor/fisiologia , Adaptação Fisiológica/fisiologia , Adulto Jovem , Retroalimentação Sensorial/fisiologia , Córtex Cerebral/fisiologia , Mãos/fisiologia , Movimento/fisiologia , Atividade Motora/fisiologiaRESUMO
An electroencephalography (EEG) has always been considered a specialized field, whose use and interpretation requires training. For this reason, access to these monitoring studies has been restricted to neurologists and neurophysiologists. Newborn infants admitted to the neonatal intensive care unit (NICU) require neurophysiological monitoring to establish their diagnosis and prognosis, so a simple and accessible tool is required for NICU staff. Such features have been covered by amplitude-integrated electroencephalography (aEEG), which, through simple visual patterns of brain activity, allows to approach neurological conditions. The objective of this study is to help with the management of mnemonics that facilitate the identification of normal and pathological visual patterns in an aEEG. Although simple in appearance, this nomenclature is intended to create an easy-to-understand idea of basic concepts for the use and interpretation of neurophysiological monitoring with aEEG.
La electroencefalografía (EEG) siempre ha sido considerada una materia especializada, que amerita de entrenamiento para su aplicación e interpretación; esto ha provocado que el acceso a estos estudios quedara confinado a neurólogos y neurofisiólogos. El recién nacido ingresado en la unidad de cuidados intensivos neonatales (UCIN) amerita de monitorización neurológica para establecer diagnóstico y pronóstico, por lo que se necesita una herramienta sencilla y accesible para el personal de la UCIN. Estas características han sido cubiertas por el electroencefalograma de amplitud integrada (aEEG) que, a través de patrones visuales simples de la actividad cerebral, permite el abordaje de la condición neurológica. El objetivo de este ensayo se orienta al manejo de mnemotecnias que faciliten la identificación de patrones visuales normales y patológicos en el aEEG. La nomenclatura empleada, aunque puede parecer simple, pretende crear una idea fácilmente asimilable de los conceptos básicos para la aplicación e interpretación de la neuromonitorización con aEEG.
Assuntos
Eletroencefalografia , Unidades de Terapia Intensiva Neonatal , Humanos , Eletroencefalografia/métodos , Recém-Nascido , Monitorização Neurofisiológica/métodosRESUMO
Major Depressive Disorder (MDD) is a global problem. Currently, the most common diagnosis is based on criteria susceptible to the subjectivity of the patient and the clinician. A possible solution to this problem is to look for diagnostic biomarkers that can accurately and early detect this mental condition. Some researchers have focused on electroencephalogram (EEG) analysis to identify biomarkers. In this study we used a dataset composed of EEG recordings from 24 subjects with MDD and 29 healthy controls (HC), during the execution of affective priming tasks with three different emotional stimuli (images): fear, sadness, and happiness. We investigated abnormalities in depressed patients using a novel technique, by directly comparing Event-Related Potential (ERP) waveforms to find statistically significant differences between the MMD and HC groups. Compared to the control group (healthy subjects), we found out that for the emotions fear and happiness there is a decrease in cortical activity at temporal regions in MDD patients. Just the opposite, for the emotion sadness, an increase in MDD brain activity occurs in frontal and occipital regions. Our findings suggest that emotions regulate the attentional control of cognitive processing and are promising for clinical application in diagnosing patients with MDD more objectively.
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Transtorno Depressivo Maior , Eletroencefalografia , Emoções , Potenciais Evocados , Humanos , Transtorno Depressivo Maior/fisiopatologia , Transtorno Depressivo Maior/psicologia , Transtorno Depressivo Maior/diagnóstico , Masculino , Feminino , Potenciais Evocados/fisiologia , Adulto , Emoções/fisiologia , Adulto Jovem , Pessoa de Meia-Idade , Encéfalo/fisiopatologia , Encéfalo/diagnóstico por imagemRESUMO
Aging is generally associated with a decline in important cognitive functions that can be observed in EEG. Physical activity in older adults should be considered one of the main strategies to promote health and prevent disease in the elderly. The present study aimed to systematically review studies of EEG activity and cognitive function changes associated with physical activity in older adults. Records from PubMed, Scopus, and EBSCO databases were searched and, following the PRISMA guidelines, nine studies were included in the present systematic review. A risk of bias assessment was performed using the National Institute of Health Quality Assessment Tool for Case-control Studies instrument. The studies analyzed used two main strategies to determine the effects of physical activity on cognition and EEG: (1) multiscale entropy and power frequencies; and (2) event-related potentials. In terms of EEG activity, it can be concluded that exercise-induced neuroplasticity underlies improvements in cognitive function in healthy older adults.
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In Mexico, shamans are recognized for the gift of entering a deep trance that allows them to know the origin of the diseases and conflicts that afflict people. They commonly treat patients through limpias (cleansing) to extract negative elements sent by a witch or that were "collected" in places that harbor "evil winds." We present a case study of an 81-year-old Mexican shaman who noticed her gift in childhood. Electroencephalographic recordings were made while the shaman performed three activities: reading cards to diagnose a patient and answer the questions he posed; limpia with chicken eggs, stones, and bells to absorb adverse "things"; and the incorporation trance through which the deceased is believed to occupy the shaman's body to use it as a communication channel. Alpha activity was observed when concentrated, suggesting a hypnagogic-like state. Predominant beta and gamma oscillations were observed, suggesting a potential plastic phenomenon that modulates the assimilation of external and internal referents guiding temporal schemes for action, attention, and the integration of mnemonic, sensory, and imaginative elements. We used a neuroanthropological approach to understand shamanic trance as a biological potential of the human brain to induce non-ordinary states of consciousness linked to cultural beliefs and practices.
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INTRODUCTION: Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) lack mechanistic biophysical modeling in diverse, underrepresented populations. Electroencephalography (EEG) is a high temporal resolution, cost-effective technique for studying dementia globally, but lacks mechanistic models and produces non-replicable results. METHODS: We developed a generative whole-brain model that combines EEG source-level metaconnectivity, anatomical priors, and a perturbational approach. This model was applied to Global South participants (AD, bvFTD, and healthy controls). RESULTS: Metaconnectivity outperformed pairwise connectivity and revealed more viscous dynamics in patients, with altered metaconnectivity patterns associated with multimodal disease presentation. The biophysical model showed that connectome disintegration and hypoexcitability triggered altered metaconnectivity dynamics and identified critical regions for brain stimulation. We replicated the main results in a second subset of participants for validation with unharmonized, heterogeneous recording settings. DISCUSSION: The results provide a novel agenda for developing mechanistic model-inspired characterization and therapies in clinical, translational, and computational neuroscience settings.
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Doença de Alzheimer , Encéfalo , Eletroencefalografia , Demência Frontotemporal , Humanos , Demência Frontotemporal/fisiopatologia , Demência Frontotemporal/patologia , Encéfalo/fisiopatologia , Encéfalo/patologia , Feminino , Doença de Alzheimer/fisiopatologia , Masculino , Idoso , Conectoma , Pessoa de Meia-Idade , Modelos NeurológicosRESUMO
The present database contains brain activity of subjective tinnitus sufferers at identifying their sound tinnitus. The main objective of this database is to provide spontaneous Electroencephalographic (EEG) activity at rest, and evoked EEG activity when tinnitus sufferers attempt to identify their sound tinnitus among 54 tinnitus sound examples. For the database, 37 volunteers were recruited: 15 ones without tinnitus (Control Group - CG), and 22 ones with tinnitus (Tinnitus Group - TG). For EEG recording, 30 channels were used to record two conditions: 1) basal condition, where the volunteer remained in a state of rest with the open eyes for two minutes; and 2) active condition, where the volunteer must have identified his/her sound stimulus by pressing a key. For the active condition, a sound-tinnitus library was generated in accordance with the most typical acoustic properties of tinnitus. The library consisted in ten pure tones (250 Hz, 500 Hz, 1 kHz, 2 kHz, 3 kHz, 3.5 kHz, 4 kHz, 6 kHz, 8 kHz, 10 kHz), a White Noise (WN), a Narrow Band noise-High frequencies (NBH, 4 kHz-10 kHz), a Narrow Band noise-Medium frequencies (NBM,1 kHz-4 kHz), a Narrow-Band noise Low frequencies (NBL, 250 Hz-1 kHz), ten pure tones combined with WN, ten pure tones superimposed with NBH, ten tones with NBM and ten pure tones combined with NBL. In total, 54 sound-tinnitus were applied for both groups. In the case of CG, volunteers must have identified a sound at 3.5 kHz. In addition to EEG information, a csv-file with audiometric and psychoacoustic information of volunteers is provided. For TG, this information refers to: 1) hearing level, 2) type of tinnitus, 3) tinnitus frequency, 4) tinnitus perception, 5) Hospital Anxiety and Depression Scale (HADS) and 6) Tinnitus Functional Index (TFI). For CG, the information refers to: 1) hearing level, and 2) HADS.
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Stroke is a neurological syndrome that usually causes a loss of voluntary control of lower/upper body movements, making it difficult for affected individuals to perform Activities of Daily Living (ADLs). Brain-Computer Interfaces (BCIs) combined with robotic systems, such as Motorized Mini Exercise Bikes (MMEB), have enabled the rehabilitation of people with disabilities by decoding their actions and executing a motor task. However, Electroencephalography (EEG)-based BCIs are affected by the presence of physiological and non-physiological artifacts. Thus, movement discrimination using EEG become challenging, even in pedaling tasks, which have not been well explored in the literature. In this study, Common Spatial Patterns (CSP)-based methods were proposed to classify pedaling motor tasks. To address this, Filter Bank Common Spatial Patterns (FBCSP) and Filter Bank Common Spatial-Spectral Patterns (FBCSSP) were implemented with different spatial filtering configurations by varying the time segment with different filter bank combinations for the three methods to decode pedaling tasks. An in-house EEG dataset during pedaling tasks was registered for 8 participants. As results, the best configuration corresponds to a filter bank with two filters (8-19 Hz and 19-30 Hz) using a time window between 1.5 and 2.5 s after the cue and implementing two spatial filters, which provide accuracy of approximately 0.81, False Positive Rates lower than 0.19, andKappaindex of 0.61. This work implies that EEG oscillatory patterns during pedaling can be accurately classified using machine learning. Therefore, our method can be applied in the rehabilitation context, such as MMEB-based BCIs, in the future.
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Interfaces Cérebro-Computador , Acidente Vascular Cerebral , Humanos , Atividades Cotidianas , Movimento , Eletroencefalografia/métodosRESUMO
INTRODUCTION: Verbal fluency tasks are common in Alzheimer's disease (AD) assessments. Yet, standard valid response counts fail to reveal disease-specific semantic memory patterns. Here, we leveraged automated word-property analysis to capture neurocognitive markers of AD vis-à-vis behavioral variant frontotemporal dementia (bvFTD). METHODS: Patients and healthy controls completed two fluency tasks. We counted valid responses and computed each word's frequency, granularity, neighborhood, length, familiarity, and imageability. These features were used for group-level discrimination, patient-level identification, and correlations with executive and neural (magnetic resonanance imaging [MRI], functional MRI [fMRI], electroencephalography [EEG]) patterns. RESULTS: Valid responses revealed deficits in both disorders. Conversely, frequency, granularity, and neighborhood yielded robust group- and subject-level discrimination only in AD, also predicting executive outcomes. Disease-specific cortical thickness patterns were predicted by frequency in both disorders. Default-mode and salience network hypoconnectivity, and EEG beta hypoconnectivity, were predicted by frequency and granularity only in AD. DISCUSSION: Word-property analysis of fluency can boost AD characterization and diagnosis. HIGHLIGHTS: We report novel word-property analyses of verbal fluency in AD and bvFTD. Standard valid response counts captured deficits and brain patterns in both groups. Specific word properties (e.g., frequency, granularity) were altered only in AD. Such properties predicted cognitive and neural (MRI, fMRI, EEG) patterns in AD. Word-property analysis of fluency can boost AD characterization and diagnosis.
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Doença de Alzheimer , Demência Frontotemporal , Humanos , Doença de Alzheimer/diagnóstico , Testes Neuropsicológicos , Encéfalo/diagnóstico por imagem , Memória , Imageamento por Ressonância Magnética , Demência Frontotemporal/diagnóstico , Transtornos da MemóriaRESUMO
The Auditory Steady-State Response (ASSR) is a type of auditory evoked potential (AEP) generated in the auditory system that can be automatically detected by means of objective response detectors (ORDs). ASSRs are usually registered on the scalp using electroencephalography (EEG). ORD are univariate techniques, i.e. only uses one data channel. However, techniques involving more than one channel - multi-channel objective response detectors (MORDs) - have been showing higher detection rate (DR) when compared to ORD techniques. When ASSR is evoked by amplitude stimuli, the responses could be detected by analyzing the modulation frequencies and their harmonics. Despite this, ORD techniques are traditionally applied only in its first harmonic. This approach is known as one-sample test. The q-sample tests, however, considers harmonics beyond the first. Thus, this work proposes and evaluates the use of q-sample tests using a combination of multiple EEG channels and multiple harmonics of the stimulation frequencies and compare them with traditional one-sample tests. The database used consists of EEG channels from 24 volunteers with normal auditory threshold collected following a binaural stimulation protocol by amplitude modulated (AM) tone with modulating frequencies near 80 Hz. The best q-sample MORD result showed an increase in DR of 45.25% when compared with the best one-sample ORD test. Thus, it is recommended to use multiple channels and multiple harmonics, whenever available.
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Eletroencefalografia , Humanos , Estimulação Acústica/métodos , Limiar Auditivo/fisiologia , Eletroencefalografia/métodos , Bases de Dados FactuaisRESUMO
PURPOSE: Research describes the existence of a relationship between cortical activity and the regulation of bulbar respiratory centers through the evaluation of the electroencephalographic (EEG) signal during respiratory challenges. For example, we found evidences of a reduction in the frequency of the EEG (alpha band) in both divers and non-divers during apnea tests. For instance, this reduction was more prominent in divers due to the greater physiological disturbance resulting from longer apnea time. However, little is known about EEG adaptations during tests of maximal apnea, a test that voluntarily stops breathing and induces dyspnea. RESULTS: Through this mini-review, we verified that a protocol of successive apneas triggers a significant increase in the maximum apnea time and we hypothesized that successive maximal apnea test could be a powerful model for the study of cortical activity during respiratory distress. CONCLUSION: Dyspnea is a multifactorial symptom and we believe that performing a successive maximal apnea protocol is possible to understand some factors that determine the sensation of dyspnea through the EEG signal, especially in people not trained in apnea.
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Mergulho , Síndrome do Desconforto Respiratório , Humanos , Apneia/diagnóstico , Suspensão da Respiração , Dispneia/diagnóstico , Eletroencefalografia , Mergulho/fisiologiaRESUMO
ABSTRACT Sporadic Creutzfeldt-Jakob disease (CJD) is a rare neurodegenerative spongiform encephalopathy that causes neuronal derangement secondary to prion protein. Its initial diagnosis is often complex and challenging due to non-specific clinical presentation, lack of awareness, and low clinical suspicion. This disease is invariably fatal, and most patients die within 12 months of presentation. Definite diagnosis of prion disease requires neuropathological analysis, usually done at autopsy. Here, we present the autopsy findings of a 57-year-old male patient, illustrating the complexity of diagnosing this disease early in the clinical course and the need for a broad differential diagnosis at the onset.
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Epilepsy is a condition that affects 50 million individuals globally, significantly impacting their quality of life. Epileptic seizures, a transient occurrence, are characterized by a spectrum of manifestations, including alterations in motor function and consciousness. These events impose restrictions on the daily lives of those affected, frequently resulting in social isolation and psychological distress. In response, numerous efforts have been directed towards the detection and prevention of epileptic seizures through EEG signal analysis, employing machine learning and deep learning methodologies. This study presents a methodology that reduces the number of features and channels required by simpler classifiers, leveraging Explainable Artificial Intelligence (XAI) for the detection of epileptic seizures. The proposed approach achieves performance metrics exceeding 95% in accuracy, precision, recall, and F1-score by utilizing merely six features and five channels in a temporal domain analysis, with a time window of 1 s. The model demonstrates robust generalization across the patient cohort included in the database, suggesting that feature reduction in simpler models-without resorting to deep learning-is adequate for seizure detection. The research underscores the potential for substantial reductions in the number of attributes and channels, advocating for the training of models with strategically selected electrodes, and thereby supporting the development of effective mobile applications for epileptic seizure detection.
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Inteligência Artificial , Epilepsia , Humanos , Qualidade de Vida , Convulsões/diagnóstico , Epilepsia/diagnóstico , Eletroencefalografia/métodos , Processamento de Sinais Assistido por Computador , AlgoritmosRESUMO
Abstract More than 100 years of research have passed by and still the human electroencephalogram (EEG) remains a puzzle to be solved. Starting from his studies on plethysmography until his theories on brain thermodynamics, Hans Berger was able to refine his method of recording cortical signs with the apparatus at his disposal in an ordinary neuropsychiatric yard towards an early account of human EEG. This review is an appraisal of his contribution to the field of modern neurophysiology.
Resumo Mais de 100 anos se passaram e o eletroencefalograma humano (EEG) continua sendo um enigma a ser desvendado. A partir de seus estudos sobre pletismografia até suas teorias sobre termodinâmica cerebral, Hans Berger conseguiu refinar seu método de registro da atividade elétrica cortical com os equipamentos a sua disposição em uma ala psiquiátrica comum produzindo uma descrição acurada do EEG humano. Esta revisão é um breve resumo de sua contribuição para o campo da neurofisiologia moderna.