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Background To evaluate the diagnostic value of transcranial Doppler (TCD) and electroencephalography (EEG) in patients with vertebrobasilar insufficiency (VBI) during clinical diagnosis and treatment Methods Eighty patients diagnosed with VBI in our hospital from June 2018 to December 2019 were randomly selected as the observation group, and 80 healthy people who received physical examination in the same period were selected as the control group. The abnormal rate, main performance and results, and the peak velocity of blood flow and vertebrobasilar artery blood flow of the two groups were compared. Results The abnormal rate of EEG and TCD in VBI patients was 38.75% (31/80) and the 93.75% (75/80), respectively. In TCD examination, ACA, PCA, MCA, and VA of both sides of the observation group were higher than those of the control group, while BA was lower than that of the control group ( P < 0.05). The Vs, Vd, and Vm on both sides of BA and VA in the observation group were lower than those in the control group, while PI and RI were higher than those in the control group ( P < 0.05). Conclusions TCD examination is highly sensitive to the degree and pattern of cerebral ischemia in VBI patients. EEG examination will define the changes of brain cell function after cerebral ischemia. Therefore, EEG and TCD have their own advantages. The application of TCD and EEG can be considered in the early diagnosis, curative effect, and prognosis evaluation of VBI patients, so as to improve the accuracy of diagnosis and prognosis.

PurposeTo assess the ability of clinical examination, blood biomarkers, electrophysiology or neuroimaging assessed within 7 days from return of spontaneous circulation (ROSC) to predict good neurological outcome, defined as no, mild, or moderate disability (CPC 1–2 or mRS 0–3) at discharge from intensive care unit or later, in comatose adult survivors from cardiac arrest (CA).MethodsPubMed, EMBASE, Web of Science and the Cochrane Database of Systematic Reviews were searched. Sensitivity and specificity for good outcome were calculated for each predictor. The risk of bias was assessed using the QUIPS tool.ResultsA total of 37 studies were included. Due to heterogeneities in recording times, predictor thresholds, and definition of some predictors, meta-analysis was not performed. A withdrawal or localisation motor response to pain immediately or at 72–96 h after ROSC, normal blood values of neuron-specific enolase (NSE) at 24 h-72 h after ROSC, a short-latency somatosensory evoked potentials (SSEPs) N20 wave amplitude > 4 µV or a continuous background without discharges on electroencephalogram (EEG) within 72 h from ROSC, and absent diffusion restriction in the cortex or deep grey matter on MRI on days 2–7 after ROSC predicted good neurological outcome with more than 80% specificity and a sensitivity above 40% in most studies. Most studies had moderate or high risk of bias.ConclusionsIn comatose cardiac arrest survivors, clinical, biomarker, electrophysiology, and imaging studies identified patients destined to a good neurological outcome with high specificity within the first week after cardiac arrest (CA).

The brainstem conveys sensory and motor inputs between the spinal cord and the brain, and contains nuclei of the cranial nerves. It controls the sleep-wake cycle and vital functions via the ascending reticular activating system and the autonomic nuclei, respectively. Brainstem dysfunction may lead to sensory and motor deficits, cranial nerve palsies, impairment of consciousness, dysautonomia, and respiratory failure. The brainstem is prone to various primary and secondary insults, resulting in acute or chronic dysfunction. Of particular importance for characterizing brainstem dysfunction and identifying the underlying etiology are a detailed clinical examination, MRI, neurophysiologic tests such as brainstem auditory evoked potentials, and an analysis of the cerebrospinal fluid. Detection of brainstem dysfunction is challenging but of utmost importance in comatose and deeply sedated patients both to guide therapy and to support outcome prediction. In the present review, we summarize the neuroanatomy, clinical syndromes, and diagnostic techniques of critical illness-associated brainstem dysfunction for the critical care setting.

Emotion is a natural instinctive state of mind that greatly influences human physiological activities and daily life decisions. Electroencephalogram (EEG) signals created from the central nervous system are very useful for emotion recognition and classification. In this study, EEG signals of individuals are analyzed by the variational mode decomposition (VMD) for frequency domain features to recognize visual stimuli-based evoked emotions (happy, sad, fear). After cleaning EEG signals from artifacts, VMD is employed to decompose the signal into its respective intrinsic mode functions (IMFs). A sliding windowing approach is adopted to calculate the power distributions in each of the predefined frequency bands. The results reveal that extracting frequency domain features using a sliding window of 3 s significantly enhances the efficiency of analyzing induced emotions in subjects. The random forest model shows promising results in classifying various emotions, achieving an accuracy of 99.57% for validation and 99.36% for testing. Moreover, it is observed that the fifth IMF has a strong relationship with emotion elicited from visual stimuli. In addition, the features of the trained model are analyzed by Shapley additive explanations.

Predicting driver fatigue degree is crucial for traffic safety. This study proposes a deep learning model utilizing electroencephalography (EEG) signals and multi-step temporal data to predict the next time-step fatigue degree indicator percentage of eyelid closure (PERCLOS) while exploring the impact of different EEG features on prediction performance. A CTL-ResFNet model integrating CNN, Transformer Encoder, LSTM, and residual connections is proposed. Its effectiveness is validated through two experimental paradigms, Leave-One-Out Cross-Validation (LOOCV) and pretraining-finetuning, with comparisons against baseline models. Additionally, the performance of four EEG features-differential entropy, α/β band power ratio, wavelet entropy, and Hurst exponent-is evaluated, using RMSE and MAE as metrics. The combined input of EEG and PERCLOS significantly outperforms using PERCLOS alone validated by LSTM, and CTL-ResFNet surpasses baseline models under both experimental paradigms. In LOOCV experiments, the α/β band power ratio performs best, whereas differential entropy excels in pretraining-finetuning. This study presents a high-performance hybrid deep learning framework for predicting driver fatigue degree and reveals the applicability differences in EEG features across experimental paradigms, offering guidance for feature selection and model deployment in practical applications.

Abstract Background A standardized protocol for electroencephalography (EEG) under standing sedation for the investigation of epilepsy in foals is needed. Hypothesis/Objectives To evaluate a modified standardized EEG protocol under standing sedation using sublingual detomidine hydrochloride in Egyptian Arabian foals. Animals Nineteen foals (controls, 9; juvenile idiopathic epilepsy [JIE], 10). Methods Descriptive clinical study. Foals were classified as controls or epileptic based on history or witnessed seizures and neurological examination. Foals were sedated using sublingual detomidine hydrochloride at a dosage of 0.08 mg/kg to avoid stress associated with injectable sedation. Once foals appeared sedated with their heads low to the ground and with wide base stance (30 minutes), topical lidocaine hydrochloride was applied at the determined locations of EEG electrodes. Fifteen minutes were allowed for absorption and electrodes were placed, protected, and EEG recording performed. Results Level of sedation was considered excellent with no need of redosing. The EEG recording lasted from 27 to 51 minutes and provided interpretable data. Epileptic discharges (ED) were noted predominantly in the central-parietal region in 9 of 10 epileptic foals. Photic stimulation triggered ED in 7 of 10 epileptic foals and in none of the controls. Foals were not oversedated and recovered uneventfully. Conclusions and Clinical Importance Sublingual detomidine hydrochloride is a safe, painless, simple, and effective method of sedation for EEG recording in foals. Sublingual sedation allowed the investigation of cerebral electrical activity during states of sleep and arousal, and during photic stimulation for the investigation of epilepsy in foals.

: Approximately 17 million individuals worldwide experience stroke annually. Stroke-induced cerebral hypoxia or infarction can impair multiple cognitive domains. This study aims to monitor the cognitive abilities of patients with acute stroke through the intervention of electroencephalogram (EEG) devices. : Patients from the neurology ward were invited to participate after obtaining study approval from the research ethics committees of a medical center in northern Taiwan. Participation was explained to the eligible individuals, and only those who met the criteria and signed the informed consent form were included. The participants were those who agreed to undergo 10 sessions of the EEG training. Ultimately, 30 valid samples were collected. The effectiveness of the intervention was analyzed using the pre- and post-test results of the Mini-Mental State Examination (MMSE) and Conners' Continuous Performance Test (CPT3). : After 10 EEG intervention sessions, the patients showed significant differences in the pre- and post-test results of the MMSE and CPT3 ( = 0.0001 and = 0.007, respectively). The EEG training suggests a possible association with changes in cognitive performance following stroke. : EEG-based interventions may be potentially associated with cognitive improvement. The effects appeared similar across patient subgroups; however, given the pilot nature of this study and the absence of a control group, the findings should be interpreted cautiously. Further well-designed controlled studies are needed to confirm these preliminary observations and evaluate their clinical applicability.

Background Delirium is a common postoperative complication in patients undergoing cardiac surgery and is associated with prolonged hospitalization and persistent cognitive impairment. This study aimed to assess the predictive value of alpha power in various brain regions at different time points for postoperative delirium. Methods Patients scheduled for routine cardiac surgery were prospectively enrolled. All participants underwent 12-hour ambulatory electroencephalography (EEG) monitoring immediately upon admission to the intensive care unit (ICU). Delirium was assessed daily using the CAM-ICU criteria for five postoperative days. Alpha power in the frontal, parietal, and occipital lobes was analyzed at three time points: immediately (T0), at 6 h, and at 12 h postoperatively. Results Among the 106 patients in the training cohort, 45 developed postoperative delirium. These patients had a higher incidence of hypertension and prolonged extracorporeal circulation and aortic clamping times. Alpha power in the frontal lobe at T0 was identified as the most accurate predictor of delirium, with an area under the curve (AUC) of 0.91 (95% CI: 0.84–0.97). The validation cohort ( n  = 74) showed consistent results with an AUC of 0.9188 (95% CI: 0.87–0.99; P  < 0.001). Conclusion Frontal lobe alpha power measured immediately postoperatively could be a reliable neurophysiological biomarker for predicting delirium after cardiac surgery, outperforming conventional clinical predictors (AUC 0.91 vs. 0.70). Graphical Abstract

ObjectivesTo research the relationship between quantitative electroencephalogram (qEEG) and impaired cognitive function patients who have obstructive sleep apnea (OSA) but no dementia.MethodsSubjects who complained of snoring between March 2020 and April 2021 in the Sleep Medicine Center of Weihai Municipal Hospital were included. All subjects underwent overnight in-laboratory polysomnography (PSG) and were assessed using a neuropsychological scale. Standard fast fourier transform (FFT) was used to obtain the electroencephalogram (EEG) power spectral density curve, and to calculate the delta, theta, alpha, and beta relative power and the ratio between slow and fast frequencies. Binary logistic regression was used to assess the risk factors for cognitive impairment in patients who had OSA but no dementia. Correlation analysis was performed to determine the relationship between qEEG and cognitive impairment.ResultsA total of 175 participants without dementia who met the inclusion criteria were included in this study. There were 137 patients with OSA, including 76 with mild cognitive impairment (OSA + MCI), 61 without mild cognitive impairment (OSA-MCI), and 38 participants without OSA (non-OSA). The relative theta power in the frontal lobe in stage 2 of non-rapid eye movement sleep (NREM 2) in OSA + MCI was higher than that in OSA-MCI (P = 0.038) and non-OSA (P = 0.018). Pearson correlation analysis showed that the relative theta power in the frontal lobe in NREM 2 was negatively correlated with Mini-Mental State Examination (MMSE) scores, Montreal Cognitive Assessment (MoCA) Beijing version scores, and MoCA subdomains scores (visual executive function, naming, attention, language, abstraction, delayed recall and orientation) outside language.ConclusionsIn patients who had OSA but no dementia, the EEG slower frequency power increased. The relative theta power in the frontal lobe in NREM 2 was associated with MCI of patients with OSA. These results suggest that the slowing of theta activity may be one of the neurophysiological changes in the early stage of cognitive impairment in patients with OSA.

Alzheimer's disease (AD) is the most widely recognized type of dementia. It is associated with cell cycle abnormalities including genomic instability and increased micronuclei (MNi) which usually evolve many years before the appearance of the clinical manifestations. Digital electroencephalogram (EEG) has a role in perceiving brain changes in dementia and in early detection of cognitive decline. This study aimed to assess the competency of using neurophysiological markers including absolute power of alpha waves and a cytogenetic marker which comprises scoring of MNi as a step toward early and preclinical diagnosis of AD. The study was conducted on 27 subjects; they were 15 patients diagnosed as sporadic AD and a group of 12 age and sex-matched controls. All subjects were subjected to Mini-Mental State Examination (MMSE), conventional EEG, digital EEG, and cytokinesis-block micronucleus assay (CBMN) in peripheral blood lymphocytes. Conventional EEG showed a normal background activity with no abnormal epileptogenic discharges in both groups. Digital EEG showed significant reduction of the absolute power of alpha waves for AD patients as compared to the control group (P < 0.0001). Score of MNi showed statistical significant difference between the two groups (P < 0.0001). By linking scores of both cognitive state using MMSE and MNi among the group of patients, a significant negative correlation was detected (r = -0.6066). The correlations between cognitive state and the absolute power of alpha wave among the patients revealed a positive correlation (r = 0.2235). The combination of both cytogenetic and neurophysiological markers can be beneficial for early detection of cognitive decline and may lead to preclinical identification of individuals at increased risk for AD, where at this stage treatment is constructive. The negative correlation between the scores of MNi and MMSE is suggestive for the impact of genomic instability on the cognitive state.