ABSTRACT
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.
Subject(s)
Humans , Infant, Newborn , Intensive Care Units, Neonatal , Electroencephalography/methods , Neurophysiological Monitoring/methodsABSTRACT
SUMMARY: Intracranial aneurysm is a common cerebrovascular disease with high mortality. Neurosurgical clipping for the treatment of intracranial aneurysms can easily lead to serious postoperative complications. Studies have shown that intraoperative monitoring of the degree of cerebral ischemia is extremely important to ensure the safety of operation and improve the prognosis of patients. Aim of this study was to probe the application value of combined monitoring of intraoperative neurophysiological monitoring (IONM)-intracranial pressure (ICP)-cerebral perfusion pressure (CPP) in craniotomy clipping of intracranial aneurysms. From January 2020 to December 2022, 126 patients in our hospital with intracranial aneurysms who underwent neurosurgical clipping were randomly divided into two groups. One group received IONM monitoring during neurosurgical clipping (control group, n=63), and the other group received IONM-ICP-CPP monitoring during neurosurgical clipping (monitoring group, n=63). The aneurysm clipping and new neurological deficits at 1 day after operation were compared between the two groups. Glasgow coma scale (GCS) score and national institutes of health stroke scale (NIHSS) score were compared before operation, at 1 day and 3 months after operation. Glasgow outcome scale (GOS) and modified Rankin scale (mRS) were compared at 3 months after operation. All aneurysms were clipped completely. Rate of new neurological deficit at 1 day after operation in monitoring group was 3.17 % (2/63), which was markedly lower than that in control group of 11.11 % (7/30) (P0.05). Combined monitoring of IONM-ICP-CPP can monitor the cerebral blood flow of patients in real time during neurosurgical clipping, according to the monitoring results, timely intervention measures can improve the consciousness state of patients in early postoperative period and reduce the occurrence of early postoperative neurological deficits.
El aneurisma intracraneal es una enfermedad cerebrovascular común con alta mortalidad. El clipaje neuroquirúrgico para el tratamiento de aneurismas intracraneales puede provocar complicaciones posoperatorias graves. Los estudios han demostrado que la monitorización intraoperatoria del grado de isquemia cerebral es extremadamente importante para garantizar la seguridad de la operación y mejorar el pronóstico de los pacientes. El objetivo de este estudio fue probar el valor de la aplicación de la monitorización combinada de la monitorización neurofisiológica intraoperatoria (IONM), la presión intracraneal (PIC) y la presión de perfusión cerebral (CPP) en el clipaje de craneotomía de aneurismas intracraneales. Desde enero de 2020 hasta diciembre de 2022, 126 pacientes de nuestro hospital con aneurismas intracraneales que se sometieron a clipaje neuroquirúrgico se dividieron aleatoriamente en dos grupos. Un grupo recibió monitorización IONM durante el clipaje neuroquirúrgico (grupo de control, n=63) y el otro grupo recibió monitorización IONM-ICP-CPP durante el clipaje neuroquirúrgico (grupo de monitorización, n=63). Se compararon entre los dos grupos el recorte del aneurisma y los nuevos déficits neurológicos un día después de la operación. La puntuación de la escala de coma de Glasgow (GCS) y la puntuación de la escala de accidentes cerebrovasculares de los institutos nacionales de salud (NIHSS) se compararon antes de la operación, 1 día y 3 meses después de la operación. La escala de resultados de Glasgow (GOS) y la escala de Rankin modificada (mRS) se compararon 3 meses después de la operación. Todos los aneurismas fueron cortados por completo. La tasa de nuevo déficit neurológico 1 día después de la operación en el grupo de seguimiento fue del 3,17 % (2/63), que fue notablemente inferior a la del grupo de control del 11,11 % (7/30) (P 0,05). La monitorización combinada de IONM-ICP-CPP puede controlar el flujo sanguíneo cerebral de los pacientes en tiempo real durante el corte neuroquirúrgico; de acuerdo con los resultados de la monitorización, las medidas de intervención oportunas pueden mejorar el estado de conciencia de los pacientes en el período postoperatorio temprano y reducir la aparición de problemas postoperatorios tempranos y déficits neurológicos.
Subject(s)
Humans , Male , Female , Middle Aged , Intracranial Aneurysm/surgery , Intracranial Aneurysm/physiopathology , Cerebrovascular Circulation , Neurosurgical Procedures/methods , Electroencephalography/methods , Blood Pressure , Intracranial Pressure , Glasgow Coma Scale , Intracranial Aneurysm/pathology , Follow-Up Studies , Treatment Outcome , Craniotomy , Glasgow Outcome Scale , Monitoring, Physiologic/methodsABSTRACT
Sensory conflict impacts postural control, yet its effect on cortico-muscular interaction remains underexplored. We aimed to investigate sensory conflict's influence on the cortico-muscular network and postural stability. We used a rotating platform and virtual reality to present subjects with congruent and incongruent sensory input, recorded EEG (electroencephalogram) and EMG (electromyogram) data, and constructed a directed connectivity network. The results suggest that, compared to sensory congruence, during sensory conflict: (1) connectivity among the sensorimotor, visual, and posterior parietal cortex generally decreases, (2) cortical control over the muscles is weakened, (3) feedback from muscles to the cortex is strengthened, and (4) the range of body sway increases and its complexity decreases. These results underline the intricate effects of sensory conflict on cortico-muscular networks. During the sensory conflict, the brain adaptively decreases the integration of conflicting information. Without this integrated information, cortical control over muscles may be lessened, whereas the muscle feedback may be enhanced in compensation.
Subject(s)
Humans , Muscle, Skeletal , Electromyography/methods , Electroencephalography/methods , Brain , Brain MappingABSTRACT
Abstract Introduction: Propofol is a widely used anesthetic and its dose is closely related to aging. Telomere length (TL) is a unique heritable trait, and emerging as a biomarker of aging, health and disease. Telomerase RNA component (TERC) plays an important role in maintaining TL. We proposed a hypothesis that propofol dose in general anesthesia can be predicted by measuring TL before operation, which greatly reduced the risk of anesthesia, especially the elderly. Methods: The association between the propofol dose in anesthesia induction and: TL in the DNA of peripheral blood leukocytes; body weight; sex; difference of the Bispectral Index (BIS) before and after anesthesia induction in patients was evaluated by multivariable linear regression analyses. The mutation at the 5'end or 3'end of TERC was detected. We recruited 100 patients of elective surgery. Results: We found that propofol dose in anesthesia induction was clearly correlated significantly with TL (r = 0.78, p < 0.001), body weight (r = 0.84, p = 0.004), sex (r = 0.83, p= 0.84, p = 0.004), sex (r = 0.83, p = 0.004), and difference of BIS before and after anesthesia induction (r = 0.85, p = 0.029). By comparing the absolute values of standardized regression coefficients (0.58, 0.21, 0.19, and 0.12) of the four variables, it can be seen that TL contributes the most to the propofol dose in anesthesia induction. However, the mutation at the 5' end or 3' end of TERC was not found. Conclusions: These findings provide preliminary evidence that the propofol dose in anesthesia induction was clearly correlated with genetically determined TL. TL may be a promising predictor of the propofol dose, which is beneficial to improve the safety of anesthesia and reduce perioperative complications.
Subject(s)
Humans , Aged , Propofol/pharmacology , Body Weight , DNA , Telomere , Anesthetics, Intravenous/pharmacology , Electroencephalography , Anesthesia, General , LeukocytesABSTRACT
Antecedentes: Según la Organización Mundial de la Salud (OMS) cerca de 70 millones de personas en el mundo padecen epilepsia. Los países de medianos y bajos ingresos presentan 70-80% de los casos; se estima que afecta 4-13% de los niños hasta los 16 años, de los cuales la epilepsia farmacorresistente (EFR) se desarrolla en 10-23%. Objetivo: Determinar factores de riesgo asociados a EFR en pacientes pediátricos atendidos en Hospital María, Especialidades Pediátricas (HMEP), Tegucigalpa, marzo 2017-marzo 2022. Métodos: Estudio de casos-controles. A partir del total de pacientes menores de 18 años con diagnóstico de epilepsia atendidos en el Servicio de Neurología HMEP, se definió Caso como pacientes con diagnóstico de EFR y Controles como pacientes con epilepsia no farmacorresistente (ENFR). A partir de expedientes clínicos, se evaluaron factores sociodemográficos, antecedentes personales y familiares, factores clínicos, estudios de imagen y electroencefalograma. El estudio fue aprobado por el Comité de Ética Institucional. Resultados: Se analizaron 81 casos y 162 controles. La edad más afectada en casos fue preescolar (35.8%), en controles fue edad escolar (41.4%). El sexo masculino presentó similar distribución en ambos grupos (51.8% y 51.2%). La procedencia rural fue más frecuente en los casos que en controles (58.0% versus 48.8%). Se identificaron los siguientes factores asociados a EFR: Antecedentes familiares de epilepsia (ORa 2.32, IC95%1.224.41, p=0.01), alteración focal en examen físico (ORa 2.23, IC95%1.104.55, p=0.02), neurodesarrollo anormal (ORa 2.78, IC95%1.186.54, p=0.02). Discusión: El control adecuado de las crisis epilépticas incide directamente en la calidad de vida y sobrevida de los pacientes. La identificación correcta de los niños con epilepsia con los factores asociados identificados en este estudio, que coinciden con lo descrito internacionalmente, permitirá hacer un mejor tamizaje y priorizar la referencia temprana a un neurólogo pediatra contribuyendo a mejorar la calidad de vida de los pacientes...(AU)
Subject(s)
Drug Resistant Epilepsy , Sociodemographic Factors , Seizures/complications , ElectroencephalographyABSTRACT
Una propiedad fundamental de los sistemas sensoriales es su capacidad para detectar estímulos novedosos en el entorno. El sistema nervioso posee neuronas que disminuyen su respuesta a los estímulos sonoros que se repiten a lo largo del tiempo y otras neuronas que aumentan su frecuencia de disparo ante estímulos novedosos, siendo la diferencia entre ambas respuestas conocida como adaptación-específica a estímulos. En las últimas décadas, se ha propuesto que el cerebro establece, continuamente, predicciones de los estímulos novedosos y del entorno basándose en sus experiencias previas y en modelos de representación internos, teoría denominada codificación predictiva. En esta revisión, abordaremos algunos conceptos de la adaptación-específica a estímulos y codificación predictiva, centrándonos principalmente en el sistema auditivo. Por último, propondremos una explicación teórica basada en el marco de la codificación predictiva para algunas disfunciones neuropsiquiátricas, auditivas y vestibulares.
A fundamental property of sensory systems is their ability to detect novel stimuli in the environment. The nervous system possesses neurons that decrease their response to sound stimuli that are repeated over time and other neurons that increase their firing rate to novel stimuli, the difference between the two responses being known as stimulus-specific adaptation. In recent decades, it has been proposed that the brain continuously makes predictions of novel stimuli and the environment based on its previous experiences and internal representational models, a theory called predictive coding. In this review, we will address some concepts of stimulus-specific adaptation and predictive coding, focusing mainly on the auditory system. Finally, we will propose a theoretical explanation based on the predictive coding framework for some neuropsychiatric, auditory, and vestibular dysfunctions.
Subject(s)
Humans , Auditory Perception/physiology , Evoked Potentials/physiology , Attention/physiology , Electroencephalography/methodsABSTRACT
La epilepsia refractaria tanto generalizada como focal, es una patología sumamente incapacitante, para el tratamiento de la misma se ha establecido a la callosotomía desde hace décadas como primera línea quirúrgica para su control, la cual puede presentar efectos secundarios importantes como síndrome de desconexión y pérdida de memoria, sin embargo, existen pacientes que no responden a la callosotomía y necesitan nuevas líneas de tratamiento, buscando en la estimulación de nervio vago una respuesta a su condición. Descripción del caso de estudio. Se presenta el caso de paciente masculino de 24 años de edad con antecedente patológico de convulsiones tipo tónico clónicas generalizadas confirmadas por video electroencefalograma de 24 horas, de predominio nocturno de 13 años de evolución, es sometido a 2 regímenes farmacológicos antiepilépticos diferentes en un período de 7 años de duración, posteriormente diagnosticado con epilepsia refractaria, por lo que se realiza callosotomía sin control de su cuadro clínico, el mismo año se realiza estimulación de nervio vago, presentando resultados favorables en su evolución. Conclusión. Luego de evidenciar el presente caso de estudio se concluye que el tratamiento de epilepsia refractaria con la colocación de un estimulador de nervio vago izquierdo asociado a un correcto régimen FAE es una alternativa muy eficaz para considerar en estos pacientes.
Refractory epilepsy, both generalized and focal, is an extremely disabling pathology. For its treatment, callosotomy has been established for decades as the first surgical line for its control, which can present important side effects such as disconnection and loss syndrome. by heart, however, there are patients who do not respond to callosotomy and need new lines of treatment, looking for an answer to their condition in vagus nerve stimulation. Description of the case study. We present the case of a 24-year-old male patient with a pathological history of generalized tonic-clonic seizures confirmed by a 24-hour video electroencephalogram, predominantly nocturnal for 13 years, undergoing 2 different antiepileptic pharmacological mechanisms over a period of 7 years in duration, later diagnosed with refractory epilepsy, for which callosotomy was performed without control of its clinical picture, the same year vagus nerve stimulation was performed, presenting favorable results in its evolution. Conclution. After evidencing the present case study, it is concluded that the treatment of refractory epilepsy with the placement of a left vagus nerve stimulator associated with a correct AED regimen is a very effective alternative to consider in these patients.
A epilepsia refratária, tanto generalizada quanto focal, é uma patologia extremamente incapacitante. Para seu tratamento, a calosotomia se estabeleceu há décadas como a primeira linha cirúrgica para seu controle, que pode apresentar importantes efeitos colaterais como desconexão e síndrome de perda., há pacientes que não respondem à calosotomia e precisam de novas linhas de tratamento, buscando resposta para sua condição na estimulação do nervo vago. Descrição do estudo de caso. Apresentamos o caso de um doente do sexo masculino, 24 anos, com antecedentes patológicos de crises tónico-clónicas generalizadas confirmadas por videoeletroencefalograma de 24 horas, predominantemente nocturnas há 13 anos, submetido a 2 mecanismos farmacológicos antiepilépticos diferentes ao longo de 7 anos de duração, posteriormente diagnosticada com epilepsia refratária, para a qual foi realizada calosotomia sem controle de seu quadro clínico, no mesmo ano foi realizada estimulação do nervo vago, apresentando resultados favoráveis em sua evolução. Conclusão. Depois de evidenciar o presente estudo de caso, conclui-se que o tratamento da epilepsia refratária com a colocação de um estimulador de nervo vago esquerdo associado a um esquema correto de DEA é uma alternativa muito eficaz a ser considerada nesses pacientes.
Subject(s)
Humans , Male , Adult , ElectroencephalographyABSTRACT
Objective: To analyze the clinical features of children with uridine responsive developmental epileptic encephalopathy 50 (DEE50) caused by CAD gene variants. Methods: A retrospective study was conducted on 6 patients diagnosed with uridine-responsive DEE50 caused by CAD gene variants at Beijing Children's Hospital and Peking University First Hospital from 2018 to 2022. The epileptic seizures, anemia, peripheral blood smear, cranial magnetic resonance imaging (MRI), visual evoked potential (VEP), genotype features and the therapeutic effect of uridine were descriptively analyzed. Results: A total of 6 patients, including 3 boys and 3 girls, aged 3.5(3.2,5.8) years, were enrolled in this study. All patients presented with refractory epilepsy, anemia with anisopoikilocytosis and global developmental delay with regression. The age of epilepsy onset was 8.5 (7.5, 11.0) months, and focal seizures were the most common seizure type (6 cases). Anemia ranged from mild to severe. Four patients had peripheral blood smears prior to uridine administration, showing erythrocytes of variable size and abnormal morphology, and normalized at 6 (2, 8) months after uridine supplementation. Two patients suffered from strabismus, 3 patients had VEP examinations, indicating of suspicious optic nerve involvement, and normal fundus examinations. VEP was re-examined at 1 and 3 months after uridine supplementation, suggesting significant improvement or normalization. Cranial MRI were performed at 5 patients, demonstrating cerebral and cerebellar atrophy. They had cranial MRI re-examined after uridine treatment with a duration of 1.1 (1.0, 1.8) years, indicating significant improvement in brain atrophy. All patients received uridine orally at a dose of 100 mg/(kg·d), the age at initiation of uridine treatment was 1.0 (0.8, 2.5) years, and the duration of treatment was 2.4 (2.2, 3.0) years. Immediate cession of seizures was observed within days to a week after uridine supplementation. Four patients received uridine monotherapy and were seizure free for 7 months, 2.4 years, 2.4 years and 3.0 years respectively. One patient achieved seizure free for 3.0 years after uridine supplementation and had discontinued uridine for 1.5 years. Two patients were supplemented with uridine combined with 1 to 2 anti-seizure medications and had a reduced seizure frequency of 1 to 3 times per year, and they had achieved seizure free for 8 months and 1.4 years respectively. Conclusions: The clinical manifestations of DEE50 caused by CAD gene variants present a triad of refractory epilepsy, anemia with anisopoikilocytosis, and psychomotor retardation with regression, accompanied by suspected optic nerve involvement, all of which respond to uridine treatment. Prompt diagnosis and immediate uridine supplementation could lead to significant clinical improvement.
Subject(s)
Male , Female , Humans , Child , Infant , Epilepsy/genetics , Retrospective Studies , Drug Resistant Epilepsy , Uridine , Evoked Potentials, Visual , Anemia , Electroencephalography/adverse effects , Neurodegenerative DiseasesABSTRACT
OBJECTIVE@#To explore the biomarkers of tinnitus in vestibular schwannoma patients using electroencephalographic (EEG) microstate technology.@*METHODS@#The EEG and clinical data of 41 patients with vestibular schwannoma were collected. All the patients were evaluated by SAS, SDS, THI and VAS scales. The EEG acquisition time was 10-15 min, and the EEG data were preprocessed and analyzed using MATLAB and EEGLAB software package.@*RESULTS@#Of the 41 patients with vestibular schwannoma, 29 patients had tinnitus and 12 did not have tinnitus, and their clinical parameters were comparable. The average global explanation variances of the non-tinnitus and tinnitus groups were 78.8% and 80.1%, respectively. The results of EEG microstate analysis showed that compared with those without tinnitus, the patients with tinnitus had an increased frequency (P=0.033) and contribution (P=0.028) of microstate C. Correlation analysis showed that THI scale scores of the patients were negatively correlated with the duration of microstate A (R=-0.435, P=0.018) and positively with the frequencies of microstate B (R=0.456, P=0.013) and microstate C (R=0.412, P=0.026). Syntax analysis showed that the probability of transition from microstate C to microstate B increased significantly in vestibular schwannoma patients with tinnitus (P=0.031).@*CONCLUSION@#EEG microstate features differ significantly between vestibular schwannoma patients with and without tinnitus. This abnormality in patients with tinnitus may reflect the potential abnormality in the allocation of neural resources and the transition of brain functional activity.
Subject(s)
Humans , Neuroma, Acoustic/complications , Electroencephalography , Patients , ProbabilityABSTRACT
At present, the incidence of Parkinson's disease (PD) is gradually increasing. This seriously affects the quality of life of patients, and the burden of diagnosis and treatment is increasing. However, the disease is difficult to intervene in early stage as early monitoring means are limited. Aiming to find an effective biomarker of PD, this work extracted correlation between each pair of electroencephalogram (EEG) channels for each frequency band using weighted symbolic mutual information and k-means clustering. The results showed that State1 of Beta frequency band ( P = 0.034) and State5 of Gamma frequency band ( P = 0.010) could be used to differentiate health controls and off-medication Parkinson's disease patients. These findings indicated that there were significant differences in the resting channel-wise correlation states between PD patients and healthy subjects. However, no significant differences were found between PD-on and PD-off patients, and between PD-on patients and healthy controls. This may provide a clinical diagnosis reference for Parkinson's disease.
Subject(s)
Humans , Parkinson Disease/diagnosis , Quality of Life , Cluster Analysis , Electroencephalography , Healthy VolunteersABSTRACT
In clinical, manually scoring by technician is the major method for sleep arousal detection. This method is time-consuming and subjective. This study aimed to achieve an end-to-end sleep-arousal events detection by constructing a convolutional neural network based on multi-scale convolutional layers and self-attention mechanism, and using 1 min single-channel electroencephalogram (EEG) signals as its input. Compared with the performance of the baseline model, the results of the proposed method showed that the mean area under the precision-recall curve and area under the receiver operating characteristic were both improved by 7%. Furthermore, we also compared the effects of single modality and multi-modality on the performance of the proposed model. The results revealed the power of single-channel EEG signals in automatic sleep arousal detection. However, the simple combination of multi-modality signals may be counterproductive to the improvement of model performance. Finally, we also explored the scalability of the proposed model and transferred the model into the automated sleep staging task in the same dataset. The average accuracy of 73% also suggested the power of the proposed method in task transferring. This study provides a potential solution for the development of portable sleep monitoring and paves a way for the automatic sleep data analysis using the transfer learning method.
Subject(s)
Sleep , Sleep Stages , Arousal , Data Analysis , ElectroencephalographyABSTRACT
Electroencephalogram (EEG) is characterized by high temporal resolution, and various EEG analysis methods have developed rapidly in recent years. The EEG microstate analysis method can be used to study the changes of the brain in the millisecond scale, and can also present the distribution of EEG signals in the topological level, thus reflecting the discontinuous and nonlinear characteristics of the whole brain. After more than 30 years of enrichment and improvement, EEG microstate analysis has penetrated into many research fields related to brain science. In this paper, the basic principles of EEG microstate analysis methods are summarized, and the changes of characteristic parameters of microstates, the relationship between microstates and brain functional networks as well as the main advances in the application of microstate feature extraction and classification in brain diseases and brain cognition are systematically described, hoping to provide some references for researchers in this field.
Subject(s)
Electroencephalography , Brain , CognitionABSTRACT
OBJECTIVES@#To study the factors influencing the short-term (28 days) efficacy of initial adrenocorticotropic hormone (ACTH) therapy for infantile epileptic spasms syndrome (IESS), as well as the factors influencing recurrence and prognosis.@*METHODS@#The clinical data were collected from the children with IESS who received ACTH therapy for the first time in the Department of Pediatric Neurology, Xiangya Hospital of Central South University, from April 2008 to January 2018 and were followed up for ≥2 years. The multivariate logistic regression analysis was used to evaluate the factors influencing the short-term efficacy of ACTH therapy, recurrence, and long-term prognosis.@*RESULTS@#ACTH therapy achieved a control rate of seizures of 55.5% (111/200) on day 28 of treatment. Of the 111 children, 75 (67.6%) had no recurrence of seizures within 12 months of follow-up. The possibility of seizure control on day 28 of ACTH therapy in the children without focal seizures was 2.463 times that in those with focal seizures (P<0.05). The possibility of seizure control on day 28 of ACTH therapy in the children without hypsarrhythmia on electroencephalography on day 14 of ACTH therapy was 2.415 times that in those with hypsarrhythmia (P<0.05). The possibility of recurrence within 12 months after treatment was increased by 11.8% for every 1-month increase in the course of the disease (P<0.05). The possibility of moderate or severe developmental retardation or death in the children without seizure control after 28 days of ACTH therapy was 8.314 times that in those with seizure control (P<0.05). The possibility of moderate or severe developmental retardation or death in the children with structural etiology was 14.448 times that in those with unknown etiology (P<0.05).@*CONCLUSIONS@#Presence or absence of focal seizures and whether hypsarrhythmia disappears after 14 days of treatment can be used as predictors for the short-term efficacy of ACTH therapy, while the course of disease before treatment can be used as the predictor for recurrence after seizure control by ACTH therapy. The prognosis of IESS children is associated with etiology, and early control of seizures after ACTH therapy can improve long-term prognosis.
Subject(s)
Child , Humans , Infant , Adrenocorticotropic Hormone/therapeutic use , Spasms, Infantile/drug therapy , Treatment Outcome , Seizures , Electroencephalography/adverse effects , Spasm/drug therapyABSTRACT
Neonatal hypoxic-ischemic encephalopathy (HIE) is a common disease that affects brain function in neonates. At present, mild hypothermia and hyperbaric oxygen therapy are the main methods for the treatment of neonatal HIE; however, they are independent of each other and cannot be combined for synchronous treatment, without monitoring of brain function-related physiological information. In addition, parameter setting of hyperbaric oxygen chamber and mild hypothermia mattress relies on the experience of the medical practitioner, and the parameters remain unchanged throughout the medical process. This article proposes a new device for the treatment of neonatal HIE, which has the modules of hyperbaric oxygen chamber and mild hypothermic mattress, so that neonates can receive the treatment of hyperbaric oxygen chamber and/or mild hypothermic mattress based on their conditions. Meanwhile, it can realize the real-time monitoring of various physiological information, including amplitude-integrated electroencephalogram, electrocardiogram, and near-infrared spectrum, which can monitor brain function, heart rate, rhythm, myocardial blood supply, hemoglobin concentration in brain tissue, and blood oxygen saturation. In combination with an intelligent control algorithm, the device can intelligently regulate parameters according to the physiological information of neonates and give recommendations for subsequent treatment.
Subject(s)
Infant, Newborn , Humans , Hypothermia, Induced/methods , Hypothermia/therapy , Hyperbaric Oxygenation , Brain , Electroencephalography , Hypoxia-Ischemia, Brain/therapyABSTRACT
OBJECTIVES@#To explore a new method for electroencephalography (EEG) background analysis in neonates with hypoxic-ischemic encephalopathy (HIE) and its relationship with clinical grading and head magnetic resonance imaging (MRI) grading.@*METHODS@#A retrospective analysis was performed for the video electroencephalography (vEEG) and amplitude-integrated electroencephalography (aEEG) monitoring data within 24 hours after birth of neonates diagnosed with HIE from January 2016 to August 2022. All items of EEG background analysis were enrolled into an assessment system and were scored according to severity to obtain the total EEG score. The correlations of total EEG score with total MRI score and total Sarnat score (TSS, used to evaluate clinical gradings) were analyzed by Spearman correlation analysis. The total EEG score was compared among the neonates with different clinical gradings and among the neonates with different head MRI gradings. The receiver operating characteristic (ROC) curve and the area under thecurve (AUC) were used to evaluate the value of total EEG score in diagnosing moderate/severe head MRI abnormalities and clinical moderate/severe HIE, which was then compared with the aEEG grading method.@*RESULTS@#A total of 50 neonates with HIE were included. The total EEG score was positively correlated with the total head MRI score and TSS (rs=0.840 and 0.611 respectively, P<0.001). There were significant differences in the total EEG score between different clinical grading groups and different head MRI grading groups (P<0.05). The total EEG score and the aEEG grading method had an AUC of 0.936 and 0.617 respectively in judging moderate/severe head MRI abnormalities (P<0.01) and an AUC of 0.887 and 0.796 respectively in judging clinical moderate/severe HIE (P>0.05). The total EEG scores of ≤6 points, 7-13 points, and ≥14 points were defined as mild, moderate, and severe EEG abnormalities respectively, which had the best consistency with clinical grading and head MRI grading (P<0.05).@*CONCLUSIONS@#The new EEG background scoring method can quantitatively reflect the severity of brain injury and can be used for the judgment of brain function in neonates with HIE.
Subject(s)
Infant, Newborn , Humans , Hypoxia-Ischemia, Brain/diagnostic imaging , Retrospective Studies , Brain Injuries , Electroencephalography , ROC CurveABSTRACT
OBJECTIVE@#To propose a semi-supervised epileptic seizure prediction model (ST-WGAN-GP-Bi-LSTM) to enhance the prediction performance by improving time-frequency analysis of electroencephalogram (EEG) signals, enhancing the stability of the unsupervised feature learning model and improving the design of back-end classifier.@*METHODS@#Stockwell transform (ST) of the epileptic EEG signals was performed to locate the time-frequency information by adaptive adjustment of the resolution and retaining the absolute phase to obtain the time-frequency inputs. When there was no overlap between the generated data distribution and the real EEG data distribution, to avoid failure of feature learning due to a constant JS divergence, Wasserstein GAN was used as a feature learning model, and the cost function based on EM distance and gradient penalty strategy was adopted to constrain the unsupervised training process to allow the generation of a high-order feature extractor. A temporal prediction model was finally constructed based on a bi-directional long short term memory network (Bi-LSTM), and the classification performance was improved by obtaining the temporal correlation between high-order time-frequency features. The CHB-MIT scalp EEG dataset was used to validate the proposed patient-specific seizure prediction method.@*RESULTS@#The AUC, sensitivity, and specificity of the proposed method reached 90.40%, 83.62%, and 86.69%, respectively. Compared with the existing semi-supervised methods, the propose method improved the original performance by 17.77%, 15.41%, and 53.66%. The performance of this method was comparable to that of a supervised prediction model based on CNN.@*CONCLUSION@#The utilization of ST, WGAN-GP, and Bi-LSTM effectively improves the prediction performance of the semi-supervised deep learning model, which can be used for optimization of unsupervised feature extraction in epileptic seizure prediction.
Subject(s)
Humans , Memory, Short-Term , Seizures/diagnosis , ElectroencephalographyABSTRACT
Accurate source localization of the epileptogenic zone (EZ) is the primary condition of surgical removal of EZ. The traditional localization results based on three-dimensional ball model or standard head model may cause errors. This study intended to localize the EZ by using the patient-specific head model and multi-dipole algorithms using spikes during sleep. Then the current density distribution on the cortex was computed and used to construct the phase transfer entropy functional connectivity network between different brain areas to obtain the localization of EZ. The experiment result showed that our improved methods could reach the accuracy of 89.27% and the number of implanted electrodes could be reduced by (19.34 ± 7.15)%. This work can not only improve the accuracy of EZ localization, but also reduce the additional injury and potential risk caused by preoperative examination and surgical operation, and provide a more intuitive and effective reference for neurosurgeons to make surgical plans.
Subject(s)
Humans , Scalp , Brain Mapping/methods , Epilepsy/diagnosis , Electroencephalography/methods , BrainABSTRACT
The method of using deep learning technology to realize automatic sleep staging needs a lot of data support, and its computational complexity is also high. In this paper, an automatic sleep staging method based on power spectral density (PSD) and random forest is proposed. Firstly, the PSDs of six characteristic waves (K complex wave, δ wave, θ wave, α wave, spindle wave, β wave) in electroencephalogram (EEG) signals were extracted as the classification features, and then five sleep states (W, N1, N2, N3, REM) were automatically classified by random forest classifier. The whole night sleep EEG data of healthy subjects in the Sleep-EDF database were used as experimental data. The effects of using different EEG signals (Fpz-Cz single channel, Pz-Oz single channel, Fpz-Cz + Pz-Oz dual channel), different classifiers (random forest, adaptive boost, gradient boost, Gaussian naïve Bayes, decision tree, K-nearest neighbor), and different training and test set divisions (2-fold cross-validation, 5-fold cross-validation, 10-fold cross-validation, single subject) on the classification effect were compared. The experimental results showed that the effect was the best when the input was Pz-Oz single-channel EEG signal and the random forest classifier was used, no matter how the training set and test set were transformed, the classification accuracy was above 90.79%. The overall classification accuracy, macro average F1 value, and Kappa coefficient could reach 91.94%, 73.2% and 0.845 respectively at the highest, which proved that this method was effective and not susceptible to data volume, and had good stability. Compared with the existing research, our method is more accurate and simpler, and is suitable for automation.
Subject(s)
Humans , Random Forest , Bayes Theorem , Sleep Stages , Sleep , Electroencephalography/methodsABSTRACT
The existing automatic sleep staging algorithms have the problems of too many model parameters and long training time, which in turn results in poor sleep staging efficiency. Using a single channel electroencephalogram (EEG) signal, this paper proposed an automatic sleep staging algorithm for stochastic depth residual networks based on transfer learning (TL-SDResNet). Firstly, a total of 30 single-channel (Fpz-Cz) EEG signals from 16 individuals were selected, and after preserving the effective sleep segments, the raw EEG signals were pre-processed using Butterworth filter and continuous wavelet transform to obtain two-dimensional images containing its time-frequency joint features as the input data for the staging model. Then, a ResNet50 pre-trained model trained on a publicly available dataset, the sleep database extension stored in European data format (Sleep-EDFx) was constructed, using a stochastic depth strategy and modifying the output layer to optimize the model structure. Finally, transfer learning was applied to the human sleep process throughout the night. The algorithm in this paper achieved a model staging accuracy of 87.95% after conducting several experiments. Experiments show that TL-SDResNet50 can accomplish fast training of a small amount of EEG data, and the overall effect is better than other staging algorithms and classical algorithms in recent years, which has certain practical value.
Subject(s)
Humans , Sleep Stages , Algorithms , Sleep , Wavelet Analysis , Electroencephalography/methods , Machine LearningABSTRACT
The development and potential application of brain-computer interface (BCI) technology is closely related to the human brain, so that the ethical regulation of BCI has become an important issue attracting the consideration of society. Existing literatures have discussed the ethical norms of BCI technology from the perspectives of non-BCI developers and scientific ethics, while few discussions have been launched from the perspective of BCI developers. Therefore, there is a great need to study and discuss the ethical norms of BCI technology from the perspective of BCI developers. In this paper, we present the user-centered and non-harmful BCI technology ethics, and then discuss and look forward on them. This paper argues that human beings can cope with the ethical issues arising from BCI technology, and as BCI technology develops, its ethical norms will be improved continuously. It is expected that this paper can provide thoughts and references for the formulation of ethical norms related to BCI technology.