Specific Electroencephalogram Research Articles

Optimizing anesthesia management based on early identification of electroencephalogram burst suppression risk in non-cardiac surgery patients: a visualized dynamic nomogram

Background Burst suppression (BS) is a specific electroencephalogram (EEG) pattern that may contribute to postoperative delirium and negative outcomes. Few prediction models of BS are available and some factors such as frailty and intraoperative hypotension (IOH) which have been reported to promote the occurrence of BS were not included. Therefore, we look forward to creating a straightforward, precise, and clinically useful prediction model by incorporating new factors, such as frailty and IOH. Materials and methods We retrospectively collected 540 patients and analyzed the data from 418 patients. Univariate analysis and backward stepwise logistic regression were used to select risk factors to develop a dynamic nomogram model, and then we developed a web calculator to visualize the process of prediction. The performance of the nomogram was evaluated in terms of discrimination, calibration, and clinical utility. Results According to the receiver operating characteristic (ROC) analysis, the nomogram showed good discriminative ability (AUC = 0.933) and the Hosmer–Lemeshow goodness-of-fit test demonstrated the nomogram had good calibration (p = 0.0718). Age, Clinical Frailty Scale (CFS) score, midazolam dose, propofol induction dose, total area under the hypotensive threshold of mean arterial pressure (MAP_AUT), and cerebrovascular diseases were the independent risk predictors of BS and used to construct nomogram. The web-based dynamic nomogram calculator was accessible by clicking on the URL: https://eegbsnomogram.shinyapps.io/dynnomapp/ or scanning a converted Quick Response (QR) code. Conclusions Incorporating two distinctive new risk factors, frailty and IOH, we firstly developed a visualized nomogram for accurately predicting BS in non-cardiac surgery patients. The model is expected to guide clinical decision-making and optimize anesthesia management.

A Deep Semi-Supervised Domain Generalization Approach for Epileptic Seizure Prediction using Electro Encephalo Graphy (EEG)

According to the World Health Organization, nearly 50 million people suffer from epilepsy, one of the most common neurological disease. Epilepsy is characterized by abnormal brain activity, leading to recurrent seizures. Each seizure manifests as sudden, uncontrolled bursts of electrical activity in the brain, and the injuries and restrictions on daily life underscores the urgency of finding effective methods for epileptic seizure prediction. With the use of deep learning techniques, early predictions of epileptic seizures, an unsolved problem, are attempted in this paper. Previous research has limitations of being sensitive to noise as it is dependent on specific electroencephalogram (EEG) devices and datasets, a serious issue this paper solves. In this paper, a semi-supervised based domain generalization method to develop an accurate seizure prediction system is proposed. It consists of two phases: representation learning and transfer learning phase. To achieve high precision, the proposed method utilizes a representation learning approach. Here, a feature-swapping mechanism that effectively disentangles seizure-related features is introduced. During transfer learning, the pre-trained network is trained to output the probability of whether the input EEG indicates a seizure or not. The proposed model achieves state-of-the-art performance, with an accuracy of 90.53% and 94.88% on the NICU and Epileptic Seizure Recognition datasets respectively in within-dataset evaluations. It outperforms the previous methods by 19.35% in cross-dataset evaluations. This robust improvement opens up promising possibilities for real-world clinical applications. The proposed feature disentangling method is also expected to contribute to developing reliable medical tools.

Neurophysiological isolation of individual rhythmic brain activity arising from auditory-speech load

Knowledge about the rhythmic activity of neural networks associated with the implementation of a particular brain function can be used to construct diagnostic systems for objective analyses of cognitive dysfunctions. The aim of this study was to identify specific frequency-based electroencephalogram phenomena associated with speech processing. The study included data from 40 clinically healthy volunteers aged 30 to 50 years (median 32.5 years), including 23 men and 17 women. While listening to a speech stimulus, changes in bioelectrical activity over the speech centers were recorded in 23 subjects (58%). During active speech production, similar changes were recorded in 12 subjects (30%). A pairwise comparison of electroencephalogram frequencies recorded during background recording and listening to the stimuli revealed statistically significant differences in changes in rhythmic activity over Broca’s area during listening and over Wernicke's area during active speech production, while changes in rhythmic activity over Broca’s area during active speech production and over Wernicke's area during listening were less significant. The most characteristic changes in the bioelectrical activity over the speech centers during listening and speaking were fluctuations with a frequency (on average) of 17.5–17.7 Hz. This may reflect a specific electroencephalogram rhythm associated with activity in the speech areas of the brain, which could allow these regions to be more accurately identified during auditory-verbal processing.

Specific electroencephalogram features in the very early phases of sporadic Creutzfeldt–Jakob disease

Studies on the very early electroencephalography (EEG) features prior to the emergence of generalized periodic discharges (GPDs, generally known as periodic sharp-wave complexes) in Creutzfeldt–Jakob disease (CJD) are rare. Fourteen patients with sporadic CJD (sCJD) (eight with MM1/classic and six with MM2c) were included in this study. The predominant findings of the first EEG were categorized as 1) lateralized periodic discharges (LPDs), 2) central sagittal sporadic epileptiform discharges (CSSEDs) showing midline predominant generalized spike-and-wave complexes and/or sharp waves in the central sagittal regions, or 3) focal epileptiform discharges. Clinical records, magnetic resonance imaging (MRI), and changes in EEG were compared between three groups (LPD in MM1/classic, CSSED in MM1/classic, and focal epileptiform discharge in MM2c). Three (37.5%) and five (62.5%) patients with MM1/classic sCJD were classified into the LPD and CSSED groups, respectively. Patients in the LPD group were accompanied by cortical hyperintensities at the corresponding areas on MRI, while those in the CSSED group showed hyperintensities on MRI at unassociated cortical areas. Follow-up EEG of three (100%) patients in the LPD group and four (80%) in the CSSED group showed transitions to GPDs. All patients with MM1/classic sCJD showed myoclonus on initial EEG, and the symptomatic side was opposite to the hemisphere showing LPDs or higher-amplitude central sagittal epileptiform activity. The periodicity after these EEGs likely contributes to the diagnostic confidence of physicians when patients are in the very early stages of MM1/classic sCJD.

The Electroencephalographic Evolution of Electrical Status

Purpose: Electrical status epilepticus during slow sleep (ESES) is an electroclinical syndrome with a specific electroencephalogram (EEG) pattern characterized by epileptic seizures, cognitive decline, and behavioral problems. The EEG pattern is defined by the percentage of the spike-wave index (SWI) in nonrapid eye movement (NREM) sleep without a clear cut-off value. The purpose of this study is to determine the significance of SWI calculation in the first 180 s of the NREM sleep stage. Methods: Patients with tonic seizures and those with SWI levels of <50% were excluded from the study. One hundred patients were enrolled in the study (typical ESES: 85; atypical ESES: 15). EEG findings were evaluated according to the following points: 1-ESES type: atypical ESES for SWI between 50% and 85% or typical ESES for ≥85%; 2-SWI calculation methods: Short method and long conventional method; 3-SWI percentage and spike frequency (SF). Results: A moderate correlation was determined between spike-wave percentage (SWP) and SF (r = 0.628; P < 0.001). A strong positive correlation was determined between the short method and long conventional method (r = 0.888; P < 0.001). In multivariate logistic regression with the SWI short method and the number of spikes in the first 180 s of NREM, only the SWI short method was found to predict typical ESES regardless of other factors (odds ratio: 1.18; P = 0.001). The optimal predictive value of the SWI short method for predicting typical ESES was >85, with sensitivity of 81.2%, and specificity of 73.3% (+PV: 94.5%, −PV: 40.7%; AUC ± SE = 0.850 ± 0.05; P < 0.001). Conclusion: Evaluating EEG epileptiform activities with objective and reproducible well-defined measurements such as SWP and SF allows for the comparison of different patient groups. We think that a shorter method for diagnosing ESES would potentially provide increased cost savings and patient comfort.

Sleep Phases in Crayfish: Relationship Between Brain Electrical Activity and Autonomic Variables.

In vertebrates like mammals and birds, two types of sleep have been identified: rapid eye movement and non-rapid eye movement sleep. Each one is associated with specific electroencephalogram patterns and is accompanied by variations in cardiac and respiratory frequencies. Sleep has been demonstrated only in a handful of invertebrates, and evidence for different sleep stages remains elusive. Previous results show that crayfish sleeps while lying on one side on the surface of the water, but it is not known if this animal has sleep phases. Heart rate and respiratory frequency are modified by diverse changes in the crayfish environment during wakefulness, and previously, we showed that variations in these variables are present during sleep despite that there are no autonomic anatomical structures described in this animal. Here, we conducted experiments to search for sleep phases in crayfish and the relationships between sleep and cardiorespiratory activity. We used the wavelet transform, grouping analysis with k-means clustering, and principal component analysis, to analyze brain and cardiorespiratory electrical activity. Our results show that (a) crayfish can sleep lying on one side or when it is motionless and (b) the depth of sleep (measured as the power of electroencephalographic activity) changes over time and is accompanied by oscillations in cardiorespiratory signal amplitude and power. Finally, we propose that in crayfish there are at least three phases of sleep.

The unchanging face of Lennox-Gastaut syndrome in adulthood

PurposeLennox-Gastaut syndrome (LGS) is a severe childhood-onset epileptic encephalopathy characterized by the presence of multiple types of intractable seizures, cognitive impairment, and specific electroencephalogram (EEG) patterns. The aim of this study was to investigate the electroclinical features of patients with LGS during adulthood. MethodsWe retrospectively identified the medical records of 20 patients aged over 18 years with a diagnosis of LGS from 3896 patients with epilepsy. ResultsThirteen (65 %) patients were male. The mean age of the patients was 23.4 ± 7.1 (min-max; 18–43) years, and the mean follow-up period was 5.6 ± 4.5 (min-max; 1–14) years. The etiology was identified in 11 (55 %) patients. None of the patients achieved seizure freedom. The most prevalent seizure types were atypical absences in 14 (70 %) patients, tonic seizures in 13 (65 %) patients, and atonic seizures in 11 (55 %) patients. One (5 %) patient was diagnosed as having psychogenic non-epileptic seizures. Mental retardation was reported in all patients and only half of them could walk independently. All patients had drug-resistant seizures and 16 (80 %) patients were on polytherapy. A vagus nerve stimulator was implanted into ten (50 %) patients and five reported 50–80 % seizure reduction. Ketogenic diet was administered to two (10 %) patients and epilepsy surgery was performed in two (10 %) patients with no significant benefit. ConclusionsPaying attention to all factors of seizure outcomes, cognitive impairment, and ambulatory status, all patients were dependent on caregivers for daily living abilities. LGS has life-long persistence with poor outcomes, even during adulthood.

Immune checkpoint inhibitor therapy-associated encephalitis: a case series and review of the literature.

Immune checkpoint inhibitors (ICIs) can cause a wide spectrum of immune-related adverse events, including encephalitis. To date, no prospective randomised controlled trials examining the patient characteristics, treatment and outcomes of ICI-associated encephalitis have been published. Therefore, we aimed to review case reports and to provide recommendations for the management of ICI-associated encephalitis. A literature search using Google Scholar and PubMed was performed in December 2019. Published case reports and case series of ICI-associated encephalitis were reviewed, and a case series from the Limmattal Hospital in Schlieren, Switzerland was added. The results are presented as numbers and medians (ranges). Five different ICIs caused encephalitis in the 47 patients included in this case series. Nivolumab was the most frequently involved drug (27/47, 57%). The median time between treatment and onset of symptoms was 65 (4–630) days. Patients presented with rapidly evolving confusion, reduced level of consciousness, headache, seizures and focal neurological deficits. A total of 19 out of the 44 (43%) magnetic resonance imaging (MRI) scans performed revealed findings suggestive of encephalitis. No specific electroencephalogram (EEG) pattern consistent with encephalitis was found, but epileptiform discharges were detected in 7/20 (35%) of all tested patients. Typical findings of cerebrospinal fluid (CSF) analysis were pleocytosis, elevated protein levels and normal glucose concentrations. Forty-four out of 47 (94%) patients received corticosteroids. Intravenous immunoglobulins (IVIG), rituximab and plasma exchange therapy were less frequently prescribed. Nine out of 47 (19%) patients died during the index hospitalisation. Encephalitis should be suspected in patients treated with ICIs who present with rapidly evolving confusion. Blood tests, CSF analysis, cerebral MRI and an EEG should be performed. Therapy with intravenous corticosteroids is recommended. Steroid unresponsiveness is rare and should lead to a review of the diagnosis. Alternative treatment options are IVIG, plasma exchange therapy and rituximab. &nbsp.

005 Electroclinical characteristics of autoimmune encephalitis as outcome biomarkers

IntroductionSeizures are a common characteristic of Autoimmune encephalitis (AIE). The use of the electroclinical characteristics to assist in the diagnosis of AIE has been explored1 however use of specific electroencephalogram (EEG) changes has not been examined with regards to outcome prediction.MethodsPatients with AIE were recruited retrospectively across 4 hospitals in Victoria. Clinical Data was collected during admission and at final follow-up. EEGs of patients were reviewed using an objective proforma. Associations between EEG biomarkers and clinical outcomes were demonstrated using logistic regression modelling.ResultsWe recruited 88 patients with AIE and available EEGs. Presence of rhythmic delta, superimposed fast activity and an abnormal background were significantly more common in N-methyl-D-aspartame receptor (NMDAR) antibody associated AIE patients (p<0.05). ICU admission was associated with rhythmic delta epileptiform activity (OR 3.25, p=0.046), sharp elements in the EEG abnormality (OR 3.55, p=0.05), and an abnormal background rhythm (OR 3.56, p=0.03). Development of drug resistant epilepsy was associated with prolonged duration of abnormality on EEG (OR 11.99, p=0.013), and sharp elements in the EEG abnormality (OR 7.29, p=0.02).ConclusionWe have identified EEG biomarkers that differentiate NMDAR AIE from other subtypes, and likely represents an objective description of extreme delta brush which has previously been described in NMDAR AIE.2 We have also demonstrated biomarkers associated with important outcomes that can be used to help guide treatment and prognosis.ReferencesLimotai C, Denlertchaikul C, Saraya AW, Jirasakuldej S. Predictive values and specificity of electroencephalographic findings in autoimmune encephalitis diagnosis. Epilepsy Behav 2018;84:29–36.Veciana M, Becerra JL, Fossas P, Muriana D, Sansa G, Santamarina E, et al. EEG extreme delta brush: An ictal pattern in patients with anti-NMDA receptor encephalitis. Epilepsy Behav 2015;49:280–5.

Transition of brain networks from an interictal to a preictal state preceding a seizure revealed by scalp EEG network analysis.

Epilepsy is a neurological disorder in the brain that is characterized by unprovoked seizures. Epileptic seizures are attributed to abnormal synchronous neuronal activity in the brain. To detect the seizure as early as possible, the identification of specific electroencephalogram (EEG) dynamics is of great importance in investigating the transition of brain activity as the epileptic seizure approaches. In this study, we investigated the transition of brain activity from interictal to preictal states preceding a seizure by combining EEG network and clustering analyses together in different frequency bands. The findings of this study demonstrated the best clustering performance of k-medoids in the beta band; in addition, compared to the interictal state, the preictal state experienced increased synchronization of EEG network connectivity, characterized by relatively higher network properties. These findings can provide helpful insight into the mechanism of epilepsy, which can also be used in the prediction of epileptic seizures and subsequent intervention.

Brain-Computer Interface Spellers: A Review.

A Brain–Computer Interface (BCI) provides a novel non-muscular communication method via brain signals. A BCI-speller can be considered as one of the first published BCI applications and has opened the gate for many advances in the field. Although many BCI-spellers have been developed during the last few decades, to our knowledge, no reviews have described the different spellers proposed and studied in this vital field. The presented speller systems are categorized according to major BCI paradigms: P300, steady-state visual evoked potential (SSVEP), and motor imagery (MI). Different BCI paradigms require specific electroencephalogram (EEG) signal features and lead to the development of appropriate Graphical User Interfaces (GUIs). The purpose of this review is to consolidate the most successful BCI-spellers published since 2010, while mentioning some other older systems which were built explicitly for spelling purposes. We aim to assist researchers and concerned individuals in the field by illustrating the highlights of different spellers and presenting them in one review. It is almost impossible to carry out an objective comparison between different spellers, as each has its variables, parameters, and conditions. However, the gathered information and the provided taxonomy about different BCI-spellers can be helpful, as it could identify suitable systems for first-hand users, as well as opportunities of development and learning from previous studies for BCI researchers.

Reseach progress of electroencephalogram features of Angelman syndrome

Angelman syndrome is also called happy puppet syndrome.It is firstly reported by British scientist in 1965.It is a chromosome disorder disease, mainly of chromosome 15q11-13 regional anomaly.The Angelman syndrome patients are often accompanied by mental retardation and special features, 90% with epilepsy and the specific electroencephalogram patterns, and the prognosis is unfavorable.The diagnosis of Angelman syndrome depends mainly on genetic testing, but some patients with genetic testing may show no abnormalities, these patients need referring the clinical diagnosis and the distinctive electroencephalogram.Before the distinctive clinical manifestation and genetic testing, the abnormal electroencephalogram can help diagnose Angelman syndrome in advance, thereby improving the early detection rate of the disease.This review is mainly to summarize the electroencephalogram patterns in Angelman syndrome in recent years. Key words: Angelman syndrome; electroencephalogram; Epilepsy

A CLINICAL CASE OF SYNGAP1 GENE MUTATION IN A GIRL WITH EPILEPSY, MENTAL RETARDATION, AUTISM, AND MOTOR DISORDERS

The introduction of the latest genetic techniques into practice could discover a basis for the comorbidity of genetic epilepsies and behavioral disturbances with cognitive impairments. Some chromosomal syndromes are characterized by a specific electroencephalogram (EEG) pattern, the type of seizures, and the variant of the course of epilepsy. This paper describes a case of synaptic RAS GTP-ase-activating protein 1 (SYNGAP1) gene mutation in a 9-year-old female patient with eyelid myoclonic epilepsy, atypical absences, and atypical autism with mental retardation. The patient’s parents visited a physician for epilepsy (myoclonic absences), markedly delayed psycho-speech development, and specific communication problems in the child. The characteristics of autistic behavior were manifested from birth; routine EEG recorded epileptiform activity at the age of 2 years; epileptic seizures appeared at 5 years. Valproic acid and levetiracetam in this patient exerted a good effect on seizures; however, a clinical and encephalographic remission was achieved by a combination of levetiracetam and ethosuximide. The clinical case including the neurological and psychic statuses, logopedic characteristics, the result of psychological testing, and video-EEG monitoring findings are analyzed in detail. The SYNGAP1 gene is located on chromosome 6p21.3. About 50 cases of SYNGAP1 syndrome are now known worldwide. After normal maternal pregnancy and delivery, the patients show delayed psychomotor development with pronounced regression at 1 to 3 years of age. At this age, there are diffuse polyspike discharges on the EEG or an onset of generalized epileptic seizures (atonic, myoclonic, eyelid myoclonic, and absence seizures), commonly photosensitivity and autoinduction, mental development stops, speech regresses, behavioral disorders that are typical of autism develop. Drug-resistant epilepsy is noted in approximately half of the described cases. There is a correlation between the severity of epilepsy and cognitive deficit.

Electroencephalogram Variations in Pediatric Migraines and Tension-Type Headaches

This study evaluates specific electroencephalogram abnormalities in pediatric migraine and tension-type headaches, and demonstrates the clinical value of these abnormalities. We studied 50 migraine patients and 50 tension-type headache patients. Their mean age ± SD was 10.62 ± 3.21 (range, 5-16) years in the migraine group, and 13.00 ± 2.37 (7-16) years in the tension-type headache group. Diagnoses were rendered according to the International Classification of Headache Disorders, 2nd Edition, First Revision, of the International Headache Society. All patients underwent two waking-state electroencephalograms, one during a headache, and the other when headache-free. Thirty-six percent (18/50) of migraine patients and 12% (6/50) of tension-type headache patients revealed specific electroencephalogram abnormalities in headache attack electroencephalograms (P < 0.05). In headache-free period electroencephalograms, 16% (8/50) of the migraine group and 2% (1/50) of the tension-type headache group revealed abnormalities (P < 0.05). Our results indicate that electroencephalogram abnormalities are particularly prevalent in migraines, especially during headache attacks. This study is the first, to the best of our knowledge, on electroencephalographic evaluation of pediatric migraine and tension-type headache patients during both headache attacks and headache-free periods.

Cardiac Vagal Activation by Adrenocorticotropic Hormone Treatment in Infants with West Syndrome

West syndrome (WS) is a generalized epileptic syndrome of infancy and early childhood with various etiologies, and consists of a triad of infantile spasm, arrest or regress of psychomotor development and specific electroencephalogram (EEG) pattern of hypsarrhythmia. WS had been believed to be refractory, but recent evidence supports effectiveness of adrenocorticotropic hormone (ACTH) treatment. The ACTH treatment, however, has a problem that it is often accompanied by adverse autonomic symptoms. We therefore examined heart rate variability (HRV) for assessing cardiac autonomic functions in WS and prospectively observed the changes during ACTH treatment. We studied 15 patients with WS and 9 age-matched controls during sleep (EEG stage 2). Compared with controls, the patients with WS were greater in the low-frequency component (LF) of HRV, an index reflecting sympatho-vagal interaction (p = 0.02), but were comparable for high-frequency component (HF) and LF-to-HF ratio (LF/HF), indices reflecting cardiac vagal activity and sympathetic predominance, respectively. During ACTH treatment, heart rate decreased (p < 0.01), LF and HF increased (p < 0.01), and LF/HF did not differ significantly. These results indicate that WS might be accompanied by autonomic changes and that ACTH treatment enhances parasympathetic function and causes bradycardia.

Spontaneous slow and fast MEG activity in male schizophrenics treated with clozapine

The atypical neuroleptic clozapine induces specific electroencephalogram changes, which have not been investigated by the use of the technique of Magnetoencephalography (MEG). A 2∗37 channel biomagnetic system (Magnes II, Biomagnetic Technologies, San Diego, CA) was used to record spontaneous magnetic activity for the frequency ranges (2–6 Hz), (7.5–12 Hz), (12.5–30 Hz) in schizophrenic patients and controls in two trials within 3 weeks. Our results lend strong support to the assumption of a significant elevation of absolute dipole values (dipole density maximum [ D max], dipole number [ D total], absolute and relative dipole density) in the fast frequency range (12.5–30 Hz) over the left hemisphere, especially in the temporoparietal region by clozapine.

Spontaneous slow and fast MEG activity in male schizophrenics treated with clozapine.

The atypical neuroleptic clozapine induces specific electroencephalogram changes, which have not been investigated using the technique of magnetoencephalography (MEG). The present study investigated whether spontaneous magnetoencephalographic (MEG) activity in patients treated with clozapine differs from that in patients treated with haloperidol and untreated control subjects. A 2 x 37 channel biomagnetic system was used to record spontaneous magnetic activity for the frequency ranges (2-6 Hz), (7.5-12 Hz), (12.5-30 Hz) in schizophrenic patients and controls in two trials within 3 weeks. After data acquisition, the processed data were digitally filtered and the spatial distribution of dipoles was determined by a 3-D convolution with a Gaussian envelope. The dipole localisation was calculated by the dipole density plot and the principal component analysis. The target parameters were absolute dipole values and the dipole localisations. The relationship between absolute dipole values, dipole localisations and psychopathological findings (documented by the use of the PANSS, BPRS-scale) during a 3 week period with constant doses of clozapine and haloperidol was investigated using correlation analysis. Our results lend strong support to the assumption of a significant elevation of absolute dipole values [dipole density maximum (Dmax), dipole number (Dtotal), absolute and relative dipole density] in the fast frequency range (12.5-30 Hz) over the left hemisphere, especially in the temporoparietal region by clozapine. In this area, we found a dipole concentration effect only in patients treated with the atypical neuroleptic, whereas the dipole distribution in patients treated with haloperidol and healthy controls was concentrated in the central region. With regard to the absolute dipole values in the frequency ranges 2-6 Hz (delta, theta) and 7.5-12 Hz (alpha), we found no statistically significant differences between the groups investigated. In the slow frequency range (2-6 Hz) no difference was found between the clozapine and haloperidol group for the dipole localisation, which predominated in the temporoparietal region, in contrast to the central dipole distribution in control subjects. The results of an increase in beta activity under clozapine demonstrate a smaller reduction in activity in terms of unspecific sensory and motor paradigms in comparison with typical neuroleptics. The temporoparietal concentration of dipoles, in particular over the left half of the brain, might illustrate either their special role in the disease process, or the effects of the medication. The latter possibility was supported by the differing dipole distribution in the clozapine group with a left temporoparietal centre in both frequency ranges, and a deviating central dipole localisation in the fast activity range in the haloperidol group.

Monitoring of the central nervous system

Clinical studies have shown a close relationship between variables such as hypoxia, increased intracranial pressure, arterial hypotension, or seizures and neurological outcome. This indicates the need for monitoring techniques of the central nervous system including measurements of cerebral blood flow, cerebral oxygenation and neuronal function. Semiquantitative changes in cerebral blood flow can be measured continuously using transcranial Doppler sonography. Measurements of jugular venous oxygen saturation or tissue oxygenation reflect the balance between cerebral oxygen delivery and cerebral oxygen demand. Near-infrared spectroscopy appears to be a technology with potential for non-invasive measurements of cerebral oxygen saturation and mitochondrial oxygen availability. The current technology is, however, of limited clinical utility. Brain electrical monitoring techniques such as electroencephalogram and evoked potentials are sensitive and specific to detect changes in neuronal function caused by cerebral ischaemia. Electroencephalogram and evoked potential measurements of depth of anaesthesia and specific electroencephalogram patterns for pharmacodynamic quantification of drug effects may gear the dosage of anaesthetics according to the anaesthetic effect.

Clozapine-induced electroencephalogram changes as a function of clozapine serum levels

Specific electroencephalogram (EEG) changes during clozapine therapy were prospectively studied in a cohort of 50 chronic state hospital patients with schizophrenia who were randomly assigned to one of three nonoverlapping clozapine serum level ranges (50-150 ng/mL, 200-300 ng/mL, and 350-450 ng/mL). EEGs were obtained before clozapine was instituted, and after 10 weeks of treatment. Fifty-three percent of patients showed EEG changes during the 10-week study period. We observed three seizures (6%), one in a patient on 900 mg (serum level 320 ng/mL) clozapine, and two in patients with lower clozapine serum levels (200-300 ng/mL) who had prior histories of seizures and inadequate valproate coverage. Thirteen percent of patients developed spikes with no relationship to dose or serum level of clozapine. Fifty-three percent of patients developed slowing on EEG. Compared to plasma levels below 300 ng/mL, a clozapine serum level between 350 and 450 ng/mL led to more frequent and more severe slowing. The EEG slowing correlated with observed sleepiness, although this factor was not sufficient to explain the severity of high-dose effects.