EEG Tracings Research Articles

Electroencephalographic manifestations during propofol and xylazine-ketamine anaesthesia in goats

The use of intravenous anaesthesia for short term surgical procedures in animal husbandry practices is increasing. However, information on the quality of an anaesthetic regime in goats has remained inadequate. Therefore, electroencephalographic studies were conducted on twelve apparently healthy adult female Barbari crossbred goats, aged 2 to 4 years, to assess the anaesthetic quality of a propofol and xylazine-ketamine combination. Quantitative analysis of EEG parameters [Total power, Median Frequency, Spectral Edge Frequency 90 (SEF-90) and Relative Power (RP) of different frequency bands delta (δ), theta (θ), alpha (α) and beta (β)] were assessed pre-experimentally (control), and at one, five, 10, 30 min, one hr, and two hr after intravenous propofol (4 mg/kg) and xylazine (0.05 mg/kg)-ketamine (4 mg/kg) administration. After propofol and xylazine-ketamine administration total power, RP-δ and θ increased significantly (P<0.05) while SEF 90, MF, RP-α and RP-β decreased. Most of the EEG changes were adequately depicted in vertex and parietal channels. Spectral analysis of EEG tracings suggested that propofol produced minimum anaesthetic stress and is a safer and better choice for short term anaesthesia in goats.

Comparison of awake Electroencephalography, Electroencephalography after Sleep Deprivation, and Melatonin-Induced Sleep Electroencephalography Sensitivity in the Diagnosis of Epilepsy in Adults

Introduction: The aim of this study was to compare routine awake electroencephalography (r-EEG), melatonin-induced sleep EEG (m-EEG) and EEG (d-EEG) after sleep deprivation studies in terms of epileptiform anomalies (EA), and to compare d-EEG and m-EEG studies in terms of sleep induction in patients requiring differential diagnosis of epileptic seizure/nonepileptic seizure. Methods: The study included 45 patients aged 18–45 years who had at least one seizure suspected to be epileptic but could not be diagnosed with epilepsy with clinical and laboratory findings. Each patient underwent r-EEG on the 1st day, d-EEG on the 2nd day after 24 h of sleeplessness, and m-EEG on the 3rd day after the administration of 6 mg melatonin following 7 h night sleep. Three separate EEG tracings of the patients were compared for EA. The d-EEG and m-EEG methods were examined for their ability to achieve sleep, total sleep time (ST), and sleep latency (SL). Results: When the detection rate of EA in d-EEG and m-EEG was compared with that of r-EEG, it was found to be significantly higher (P < 0.001) (73.3% with d-EEG, 75.6% with m-EEG, and 35.6% with r-EEG). Sleep was achieved at a rate of 100% after receiving melatonin and at a rate of 97.8% with sleep deprivation. There was no significant difference between d-EEG and m-EEG in terms of mean ST and SL (ST = 58.6 ± 12.6 min and 59.7 ± 8.3 min, respectively; SL = 287.6 ± 484.3 s and 152.2 ± 178.7 s after the start of the EEG, respectively). Conclusions: Sleep EEG is superior to awake EEG in terms of detecting EA. In an EEG study, where melatonin was used to induce sleep, the sleep rate and SL were similar to those of d-EEG, and melatonin did not have an EA increasing or suppressing effect on EEG. Given the ease of application and low side effect profile, it is thought that m-EEG may be an applicable method in the diagnosis of epilepsy.

How often is EEG used as part of routine dementia evaluation in community practice?

AbstractBackgroundRecommendations for evaluation of patients with dementia have changed little in the last thirty years. The guideline for diagnosis of dementia published by the American Academy of Neurology (AAN) in 1984 recommended against routine use of EEG for evaluation of dementia, and in the updated guideline from 2001 EEG is not specifically mentioned. Some authors continue to argue for use of EEG in dementia research, though mostly this focuses on specialized EEG techniques like quantitative EEG. There are few reports, however, on the frequency of EEG use in community neurological evaluations for dementia.MethodAll new patient referrals to the Novant Health Memory Clinic in Charlotte, NC, for 2020 were reviewed. Information was tabulated for those patients who had been previously evaluated by a neurologist in the community, specifically to determine how often EEG was included as part of the routine evaluation. Results of the EEG as taken from the clinician’s report were tabulated, though there was no opportunity to examined the EEG tracing itself. The author made a judgement as to whether the results of the EEG affected the clinical diagnosis or provided useful information for management of the patient in each case, and these data were tabulated.ResultDuring the year of observation, there were a total of 845 new patient evaluations in the Memory Clinic. Of those, 274 patients met clinical criteria for “Probable” Alzheimer Disease, 237 met criteria for Mild Cognitive Impairment, and 207 for Subjective Cognitive Decline. Out of these patients, 89 had been previously evaluated by a community neurologist. In 63 of the evaluations, EEG was obtained as part of the routine evaluation. Of these, 16 were read as “normal,” and 47 were read as “abnormal” due to slowing of background rhythm. In 2 of the 47, the reader also reported finding “sharp waves” in temporal leads, and these 2 patients were treated by the reading neurologist with anticonvulsants, later discontinued in both cases. In no case did the EEG provide useful information for either diagnosis of management of dementia.ConclusionThese data support the AAN guideline’s recommendation against routine use of EEG for dementia evaluation.

Functional Connectivity of EEG in Encephalitis during Slow Biphasic Complexes

The electroencephalogram (EEG) of patients suffering from inflammatory diseases of the brain may show specific waveforms called slow biphasic complexes (SBC). Recent studies indicated a correlation between the severity of encephalitis and some features of SBCs, such as location, amplitude and frequency of appearance. Moreover, EEG rhythms were found to vary before the onset of an SBC, as if the brain was preparing to the discharge (actually with a slowing down of the EEG oscillation). Here, we investigate possible variations of EEG functional connectivity (FC) in EEGs from pediatric patients with different levels of severity of encephalitis. FC was measured by the maximal crosscorrelation of EEG rhythms in different bipolar channels. Then, the indexes of network patterns (namely strength, clustering coefficient, efficiency and characteristic path length) were estimated to characterize the global behavior when they are measured during SBCs or far from them. EEG traces showed statistical differences in the two conditions: clustering coefficient, efficiency and strength are higher close to an SBC, whereas the characteristic path length is lower. Moreover, for more severe conditions, an increase in clustering coefficient, efficiency and strength and a decrease in characteristic path length were observed in the delta–theta band. These outcomes support the hypothesis that SBCs result from the anomalous coordination of neurons in different brain areas affected by the inflammation process and indicate FC as an additional key for interpreting the EEG in encephalitis patients.

Numerical estimation of the B1 transmit field distortion in a copper EEG trace comparison with the thin-film based resistive trace "NeoNet".

This study investigates the effects of EEG traces in B1 transmit field distortion in a 3T MRI. EEG is a non-invasive method to monitor brain activities. Although EEG monitors brain activities with a high temporal resolution, it has trouble localizing the signal source. The EEG-fMRI is the multimodal imaging method, but care is needed to use EEG while in MRI as EEG traces create the signal distortion to the MRI. To tackle this problem, resistive traces are developed using thin-film technology to reduce the signal distortion during MRI. Numerical simulation was used to estimate the amount of B1 transmit field distortion of NeoNet and copper-based EEG nets (CuNet - with and without current limiting resistors) compared with the case without EEG net (NoNet). The reduced B1 transmit field distortion is estimated in the case of NeoNet compared to the CuNets. NeoNet is an MR-compatible high-density EEG net designed for pediatric subjects. The proposed NeoNet traces will facilitate/enable such EEG/fMRI pediatric studies with mitigated artifacts, which in turn will help to move the pediatric EEG/fMRI field forward.Clinical Relevance-This study estimates the benefit of the thin-film based EEG net with reduced B1 transmit artifact for the multimodal study of EEG-fMRI. The results are compared with commercial EEG trace made with copper metal with current limiting resistors. It is reported that about 470,000 children are suffering from Epilepsy. The MR-compatible resistive EEG traces se EEG-fMRI has potential to be a valuable tool to help understand pediatric Epilepsy and move the pediatric EEG-fMRI field forward.

Corticothalamic Connectivity in Aneurysmal Subarachnoid Hemorrhage: Relationship with Disordered Consciousness and Clinical Outcomes.

We present an exploratory analysis of the occurrence of early corticothalamic connectivity disruption after aneurysmal subarachnoid hemorrhage (SAH) and its correlation with clinical outcomes. We conducted a retrospective study of patients with acute SAH who underwent continuous electroencephalography (EEG) for impairment of consciousness. Only patients undergoing endovascular aneurysm treatment were included. Continuous EEG tracings were reviewed to obtain artifact-free segments. Power spectral analyses were performed, and segments were classified as A (only delta power), B (predominant delta and theta), C (predominant theta and beta), or D (predominant alpha and beta). Each incremental category from A to D implies greater preservation of corticothalamic connectivity. We dichotomized categories as AB for poor connectivity and CD for good connectivity. The modified Rankin Scale score at follow-up and in-hospital mortality were used as outcome measures. Sixty-nine patients were included, of whom 58 had good quality EEG segments for classification: 28 were AB and 30 were CD. Hunt and Hess and World Federation of Neurological Surgeons grades were higher and the initial Glasgow Coma Scale score was lower in the AB group compared with the CD group. AB classification was associated with an adjusted odds ratio of 5.71 (95% confidence interval 1.61-20.30; p < 0.01) for poor outcome (modified Rankin Scale score 4-6) at a median follow-up of 4months (interquartile range 2-6) and an odds ratio of 5.6 (95% confidence interval 0.98-31.95; p = 0.03) for in-hospital mortality, compared with CD. EEG spectral-power-based classification demonstrates early corticothalamic connectivity disruption following aneurysmal SAH and may be a mechanism involved in early brain injury. Furthermore, the extent of this disruption appears to be associated with functional outcome and in-hospital mortality in patients with aneurysmal SAH and appears to be a potentially useful predictive tool that must be validated prospectively.

Unified Retrospective EEG Motion Educated Artefact Suppression for EEG-fMRI to Suppress Magnetic Field Gradient Artefacts During Motion.

The data quality of simultaneously acquired electroencephalography and functional magnetic resonance imaging (EEG-fMRI) can be strongly affected by motion. Recent work has shown that the quality of fMRI data can be improved by using a Moiré-Phase-Tracker (MPT)-camera system for prospective motion correction. The use of the head position acquired by the MPT-camera-system has also been shown to correct motion-induced voltages, ballistocardiogram (BCG) and gradient artefact residuals separately. In this work we show the concept of an integrated framework based on the general linear model to provide a unified motion informed model of in-MRI artefacts. This model (retrospective EEG motion educated gradient artefact suppression, REEG-MEGAS) is capable of correcting voltage-induced, BCG and gradient artefact residuals of EEG data acquired simultaneously with prospective motion corrected fMRI. In our results, we have verified that applying REEG-MEGAS correction to EEG data acquired during subject motion improves the data quality in terms of motion induced voltages and also GA residuals in comparison to standard Artefact Averaging Subtraction and Retrospective EEG Motion Artefact Suppression. Besides that, we provide preliminary evidence that although adding more regressors to a model may slightly affect the power of physiological signals such as the alpha-rhythm, its application may increase the overall quality of a dataset, particularly when strongly affected by motion. This was verified by analysing the EEG traces, power spectra density and the topographic distribution from two healthy subjects. We also have verified that the correction by REEG-MEGAS improves higher frequency artefact correction by decreasing the power of Gradient Artefact harmonics. Our method showed promising results for decreasing the power of artefacts for frequencies up to 250Hz. Additionally, REEG-MEGAS is a hybrid framework that can be implemented for real time prospective motion correction of EEG and fMRI data. Among other EEG-fMRI applications, the approach described here may benefit applications such as EEG-fMRI neurofeedback and brain computer interface, which strongly rely on the prospective acquisition and application of motion artefact removal.

Interaction between gender and post resuscitation interventions on neurological outcome in an asphyxial rat model of cardiac arrest

PurposePrevious clinical studies have suggested an effect of gender on outcome after out-of-hospital cardiac arrest, but the results are conflicting and there is no uniform agreement regarding gender differences in survival and prognosis. The present study was aimed to investigate the interaction between gender and post resuscitation interventions on neurological outcome in an asphyxial rat model of cardiac arrest.MethodsAsphyxia was induced by blocking the endotracheal tube in 120 adult Sprague–Dawley rats (60 males and 60 females) at the same age. Cardiopulmonary resuscitation (CPR) was started after 5 min of untreated cardiac arrest. Animals were randomized into one of the three post resuscitation care intervention groups (n = 40, 20 males) immediately after resuscitation: (1) normothermic control (NC): ventilated with 2% N2/98% O2 for 1 h under normothermia; (2) targeted temperature management (TTM): ventilated with 2% N2/98% O2 for 1 h under hypothermia; (3) hydrogen inhalation (HI): ventilated with 2% H2/98% O2 for 1 h under normothermia. Physiological variables were recorded during the 5 h post resuscitation monitoring period. Neurological deficit score (NDS) and accumulative survival were used to assess 96 h outcomes. Mutual independence analysis and Mantel–Haenszel stratified analysis were used to explore the associations among gender, intervention and survival.ResultsThe body weights of female rats were significantly lighter than males, but CPR characteristics did not differ between genders. Compared with male rats, females had significantly lower mean arterial pressure, longer onset time of the electroencephalogram (EEG) burst and time to normal EEG trace (TTNT) in the NC group; relatively longer TTNT in the TTM group; and substantially longer TTNT, lower NDSs, and higher survival in the HI group. Mutual independence analysis revealed that both gender and intervention were associated with neurological outcome. Mantel–Haenszel stratified analysis demonstrated that female rats had significantly higher survival rate than males when adjusted for the confounder intervention.ConclusionIn this rat model cardiac arrest and CPR, gender did not affect resuscitation but associated with neurological outcome. The superiority of female rats in neurological recovery was affected by post resuscitation interventions and female rats were more likely to benefit from hydrogen therapy.

Prediction of cortical theta oscillations in humans for phase-locked visual stimulation

Background: The timing of an event within an oscillatory phase is considered to be one of the key strategies used by the brain to code and process neural information. Whereas existing methods of studying this phenomenon are chiefly based on retrospective analysis of electroencephalography (EEG) data, we now present a method to study it prospectively.New method: We present a system that allows for the delivery of visual stimuli at a specific phase of the cortical theta oscillation by fitting a sine to raw surface EEG data to estimate and predict the phase. One noteworthy feature of the method is that it can minimize potentially confounding effects of previous trials by using only a short sequence of past data.Results: In a trial with 10 human participants we achieved a significant phase locking with an inter-trial phase coherence of 0.39. We demonstrated successful phase locking on synthetic signals with a signal-to-noise ratio of less than − 20 dB.Comparison with existing method(s): We compared the new method to an autoregressive method published in the literature and found the new method was superior in mean phase offset, circular standard deviation, and prediction latency.Conclusions: By fitting sine waves to raw EEG traces, we locked visual stimuli to arbitrary phases within the theta oscillatory cycle of healthy humans.

Electroencephalogram Spectrum in Children with Neurological Disorders an Experience of Tertiary Care Hospital

Background and Objective: For evaluation of brain function in medical and psychiatric disorders one of the important investigative tool is Electroencephalogram (EEG) . There are limited studies overall related to use of EEG however in pediatric population there is scarcity of standard data related to topic Therefore, the objective of this study is to evaluate the prevalence of abnormal EEG and related neurological disorders in children. Methods: A retrospective analysis of 664 EEG was done. One year record from 1st October 2020 to 30th September 2021 was reviewed .EEG request forms and reports were retrieved from neurophysiology lab data of the institute. A structured Pre-designed questionnaire used for collection of data information collected include demographics , history and conclusion were noted on the proforma. Results: Total of 664 childrens has complete Electroencephalogram and bio-demographic records. The Mean age was 5.5 ± 4 SD at presentation was . Males 375( 63.5%) and 290(43.6%) were females. Males to female ratio was. Among total ,375 (56%) EEG were normal, while 408(61.4%) patients had history of seizure. whereas 256 ( 38.5%) had provisional diagnosis other than seizure and 61 (29%) of them abnormal EEG tracing. Conclusion: In developing countries EEG yet plays an essential role in the evaluation of neurological disorder particularly epilepsy. Therefore efforts needed to establish fully equipped neurophysiology facilities at least in tertiary care pediatric hospitals for early diagnosis and optimum prognosis. Keywords: Electroencephalogram, Neurological Disorders, patterns

Prospective evaluation of interrater agreement between EEG technologists and neurophysiologists

We aim to prospectively investigate, in a large and heterogeneous population, the electroencephalogram (EEG)-reading performances of EEG technologists. A total of 8 EEG technologists and 5 certified neurophysiologists independently analyzed 20-min EEG recordings. Interrater agreement (IRA) for predefined EEG pattern identification between EEG technologists and neurophysiologits was assessed using percentage of agreement (PA) and Gwet-AC1. Among 1528 EEG recordings, the PA [95% confidence interval] and interrater agreement (IRA, AC1) values were as follows: status epilepticus (SE) and seizures, 97% [96–98%], AC1 kappa = 0.97; interictal epileptiform discharges, 78% [76–80%], AC1 = 0.63; and conclusion dichotomized as “normal” versus “pathological”, 83.6% [82–86%], AC1 = 0.71. EEG technologists identified SE and seizures with 99% [98–99%] negative predictive value, whereas the positive predictive values (PPVs) were 48% [34–62%] and 35% [20–53%], respectively. The PPV for normal EEGs was 72% [68–76%]. SE and seizure detection were impaired in poorly cooperating patients (SE and seizures; p < 0.001), intubated and older patients (SE; p < 0.001), and confirmed epilepsy patients (seizures; p = 0.004). EEG technologists identified ictal features with few false negatives but high false positives, and identified normal EEGs with good PPV. The absence of ictal features reported by EEG technologists can be reassuring; however, EEG traces should be reviewed by neurophysiologists before taking action.

Neurovascular coupling (NVC) in newborns using processed EEG versus amplitude-EEG

There is a critical need for development of real time physiological biomarkers for birth asphyxia that constitutes a major global public health burden. Our recent study (Scientific Reports, V10:9183, 2020) established a novel non-invasive neurovascular coupling (NVC) assessment in newborns using dynamic wavelet transform coherence (WTC) analysis irrespective of different aEEG algorithms. As an extended study, the current paper examines whether the variability in processed EEG and amplitude-EEG (aEEG) outputs would impact the determination of NVC in newborns with encephalopathy. Concurrent processed EEG tracings and regional near infrared spectroscopy (NIRS)-based cerebral tissue oxygen saturation (SctO2) readings during a period of twenty hours in their first day of life were selected and processed in this study. After bandpass-filtered in 2–15 Hz, rectified, and down-sampled at 0.21 Hz, the processed EEG tracings along with NIRS-SctO2 (0.21 Hz) were used to perform WTC analysis, followed by comparison of WTC-metrics between SctO2-processed EEG coherence and SctO2-aEEG coherence using Bland–Altman statistics. Our results demonstrated high and significant correlation (R2 = 0.96, p < 0.001) between NVC assessments by SctO2-processed EEG and SctO2-aEEG coherence, confirming that band-passed, rectified, and down-sampled processed EEG, or aEEG, can be paired with NIRS-SctO2 to assess NVC in newborns with encephalopathy. Findings indicate the feasibility of a simpler approach to NVC in neonates by using directly processed EEG, instead of aEEG.

Persistently Elevated Heart Rate Alters EEG Patterns and Locomotor Behavior in Mice

Descending autonomic signaling, traveling from central stations, contributes to regulating heart rate (HR) in response to environmental demands. However, whether and how cardiac rhythm influences central functions in a “bottom-up modality” remains poorly understood. Here, we tested whether persistently elevated HR in mice affects the brain-heart bidirectional communication, the electroencephalographic (EEG) patterns, and behavior. To this end, we used mice with cardiac-selective overexpression of adenylyl cyclase type 8 (TGAC8 mice) that harbor continually heightened HR and autonomic surveillance escape. We implanted them with a double Holter system to obtain ECGs, EEGs, and evaluate changes in the ECG/EEG relationship via the Granger Causality statistical approach. Actigraphy, elevated plus maze, open field, Y-maze, fear conditioning tests served to assess behavior. First, we confirmed that TGAC8s mice have continuously elevated HR, reduced HR variability (HRV), i.e., High (HF) /Low Frequency (LF) components of the ECG, and decreased alpha-DFA. Moreover, as expected, TGAC8 mice isolated atria showed a substantially blunted response to sympathomimetic agents. When EEG rhythms are concerned, TGAC8 mice manifested a marked decrease in theta-2 frequency (in the range of 6-7 Hz), theta-2 wave count, and amplitude. In terms of behavior, TGAC8 mice showed no basal difference in anxiety levels, mood, and memory compared to WT littermates. In contrast, their locomotor activity (i.e. time mobile, total distance traveled, average and maximum speed) was significantly increased, and these changes correlated with the blunting in theta-2 activity. Of relevance, analysis of the informational flow between tachogram and EEG traces in theta-2 range, via Granger analysis, revealed a substantial decrement in the extent of heart/brain bidirectional communication. For the first time, our study shows that persistently elevated cardiac chronotropic activity is penetrant enough to disrupt the brain/heart flow of information, influencing central physiological patterns that control complex activities, such as locomotion.

The Effect of Music on aEEG Cyclicity in Preterm Neonates.

Several methods can be used in the neonatal intensive care unit (NICU) to reduce stress and optimize the quality of life during this period of hospitalization. Among these, music could play an important role. We investigated the effect of different kinds of music therapies on the brain activity of very preterm infants using amplitude-integrated EEG. Sixty-four patients were included and randomly assigned to three different groups: live music group, recorded music group, and control group. In both intervention groups, music was started after the appearance of the first quiet-sleep phase, with a subsequent duration of 20 min. Changes between the first and second quiet-sleep epochs were analyzed using the amplitude-integrated EEG. When looking at single parameters of the amplitude-integrated EEG trace, no differences could be found between the groups when comparing their first and second quiet-sleep phase regarding the parameters of change from baseline, quality of the quiet-sleep epoch, and duration. However, when looking at the total cyclicity score of the second quiet-sleep phase, a difference between both intervention groups and the control group could be found (live music therapy vs. control, p = 0.003; recorded music therapy vs. control, p = 0.006). Improvement within the first and second quiet-sleep epochs were detected in both music groups, but not in the control group. We concluded that our study added evidence of the beneficial effect of music on the amplitude-integrated EEG activity in preterm infants.

ETIOLOGY, CLINICAL PROFILE AND OUTCOME OF FIRST EPISODE OF SEIZURE IN CHILDREN

Background: Seizure is a commonly encountered problem in pediatric practice. Convulsive disorder constitutes a heterogeneous group with a varied etiology. Arriving at the cause of seizure is important as it plays a vital role in managing the child. Chances of recurrence to be analyzed, after the rst episode of seizure for management. The aim was to study the etiology and the causes of recurrence after a rst episode seizure. A Methods: prospective observational study was done on 135 children for a period of six months admitted in tertiary care center. Proper history, complete neurological and other systemic examinations was done. Blood investigations and imaging with EEG was done when indicated. All children were classied according to International League against epilepsy and followed up for recurrence rate and history leading to recurrence. Co- relation between recurrence and risk factors was analyzed. Electroencephalogram tracing Results: was abnormal in 62 out of 105 children. 19 out of 62 had recurrence while only 2 among 43 normal EEG had recurrence. This was statistically signicant (P value 0.001). Children with remote symptomatic etiology constitutes the majority in those with abnormal EEG tracings. In children with remote symptomatic etiology, only one child had normal EEG. Remote symptomatic had higher number of abnormal EEG when compared to others and was found to have more recurrence. Conclusions: Children with EEG abnormalities after the rst episode of afebrile seizure have more chance of recurrence. Children with seizure secondary to remote symptomatic etiology had more recurrences

Nervous Activity of the Brain in Five Dimensions

The nervous activity of the brain takes place in higher-dimensional functional spaces. It has been proposed that the brain might be equipped with phase spaces characterized by four spatial dimensions plus time, instead of the classical three plus time. This suggests that global visualization methods for exploiting four-dimensional maps of three-dimensional experimental data sets might be used in neuroscience. We asked whether it is feasible to describe the four-dimensional trajectories (plus time) of two-dimensional (plus time) electroencephalographic traces (EEG). We made use of quaternion orthographic projections to map to the surface of four-dimensional hyperspheres EEG signal patches treated with Fourier analysis. Once achieved the proper quaternion maps, we show that this multi-dimensional procedure brings undoubted benefits. The treatment of EEG traces with Fourier analysis allows the investigation the scale-free activity of the brain in terms of trajectories on hyperspheres and quaternionic networks. Repetitive spatial and temporal patterns undetectable in three dimensions (plus time) are easily enlightened in four dimensions (plus time). Further, a quaternionic approach makes it feasible to identify spatially far apart and temporally distant periodic trajectories with the same features, such as, e.g., the same oscillatory frequency or amplitude. This leads to an incisive operational assessment of global or broken symmetries, domains of attraction inside three-dimensional projections and matching descriptions between the apparently random paths hidden in the very structure of nervous fractal signals.

Will MRI replace the EEG for the diagnosis of nonconvulsive status epilepticus, especially focal?

Magnetic resonance imaging (MRI) can now be used to diagnose or to provide confirmation of focal nonconvulsive status epilepticus (NCSE). Approximately half of patients with status epilepticus (SE) have signal changes. MRI can also aid in the differential diagnosis with generalized NCSE when there is a clinical or EEG doubt, e.g. with metabolic/toxic encephalopathies or Creutzfeldt-Jakob disease. With the development of stroke centers, MRI is available 24h/24 in most hospitals. MRI has a higher spatial resolution than electroencephalography (EEG). MRI with hyperintense lesions on FLAIR and DWI provides information related to brain activity over a longer period of time than a standard EEG where only controversial patterns like lateralized periodic discharges (LPDs) may be recorded. MRI may help identify the ictal nature of LPDs. The interpretation of EEG tracings is not easy, with numerous pitfalls and artifacts. Continuous video-EEGs require a specialized neurophysiology unit. The learning curve for MRI is better than for EEG. It is now easy to transfer MRI to a platform with expertise. MRI is more accessible than single photon emission computed tomography (SPECT) or positron emission tomography (PET). For the future, it is more interesting to develop a strategy with MRI than SPECT or PET for the diagnosis of NCSE. With the development of artificial intelligence, MRI has the potential to transform the diagnosis of SE. Additional MRI criteria beyond the classical clinical/EEG criteria of NCSE (rhythmic versus periodic, spatiotemporal evolution of the pattern…) should now be systematically added. However, it is more complicated to move patients to MRI than to perform an EEG in the intensive care unit, and at this time, we do not know how long the signal changes persist after the end of the SE. Studies with MRI at fixed intervals and after SE cessation are necessary.

Wavelet Transform as a Helping Tool During EEG Analysis in Children with Epilepsy.

Background:Epilepsy is a brain disorder characterised by unpredictable and excessive nerve cell activity that causes epileptic seizures. Epileptic seizures are more common in children and adolescents than in elderly population. Electroencephalography (EEG) is a diagram of electrical activity of the brain and it is used as a method of choice for diagnosing epilepsy. Despite the accurate EEG tracing of electrical activity in the brain, the disadvantage of this type of analysing is the doctor’s skill to read the EEG correctly.Objective:The aim of this study was ro represents further research presented in our pevious works with wavelet based EEG analysis after masuring a multiresolution as relation between time and frequency resolution.Methods:Signal database set consist of 51 patients: a) healthy patient; b) 50 patients with a diagnosis of epilepsy. Additional characteristics of the analysed data: a) 19 signals-channels of EEG, b) Duration – 20 s or 2688 samples and. Nowadays, we can find dozens of EEG signal analysis papers using mathematical approach and with a focus on identification of epilepsy.Results:This paper represents some results relating to the analysis of EEG in children using Wavelet Transform (WT). The signals was collected and analysed at the Department of neuropediatrics, Pediatric Clinic at the University Clinical Center, University of Sarajevo.Conclusion:Using this approach it is possible to clearly differentiate patients with a diagnosis of epilepsy from healthy ones.

Quantitative EEG During Critical Illness Correlates with Patterns of Long-Term Cognitive Impairment.

Many intensive care unit (ICU) survivors suffer disabling long-term cognitive impairment (LTCI) after critical illness. We compared EEG characteristics during critical illness with patients' 1-year neuropsychological outcomes. We performed a post hoc analysis of patients in the BRAIN-ICU study who had undergone EEG for clinical purposes during admission (n = 10). All survivors underwent formal cognitive assessments at 12-month follow-up. We evaluated EEGs by conventional visual inspection and computed 10 quantitative features. We explored associations between EEG and patterns of LTCI using Wilcoxon rank-sum tests and Spearman's rank correlations. Of 521 Vanderbilt patients enrolled in the parent study, 24 had EEG recordings during admission. Ten survivors had EEG tracings available and completed follow-up cognitive testing. All but one inpatient EEG showed generalized background slowing. All patients demonstrated cognitive impairment in at least one domain at follow-up. The most common deficits occurred in delayed memory (DM-median index 62) and visuospatial/constructional (VC-median index 69) domains. Relative alpha power correlated with VC score (ρ = 0.78, P = .008). Peak interhemispheric coherence correlated negatively with DM (ρ = -0.81, P = .018). Quantitative EEG features during critical illness correlated with domain-specific cognitive performance in our small cohort of ICU survivors. Further study in larger prospective cohorts is required to determine whether these relationships hold. EEG may serve as a prognostic biomarker predicting patterns of long-term cognitive impairment.

Preparatory ERPs in visual, auditory, and somatosensory discriminative motor tasks.

Previous event-related potential (ERP) studies mainly from the present research group showed a novel component, that is, the prefrontal negativity (pN), recorded in visual-motor discriminative tasks during the pre-stimulus phase. This component is concomitant to activity related to motor preparation, that is, the Bereitschaftspotential (BP). The pN component has been reported in experiments based on the visual modality only; for other modalities (acoustic and/or somatosensory) the presence of the pN warrants further investigation. This study represents a first step toward this direction; indeed, we aimed at describing the pN and the BP components in discriminative response tasks (DRTs) for three sensory modalities. In experiment 1 ERPs were recorded in 29 adults in visual and auditory DRT; an additional group of 15 adults participated to a somatosensory DRT (experiment 2). In line with previous results both the pN and the BP were clearly detectable in the visual modality. In the auditory modality the prefrontal pN was not detectable directly; however, the pN could be derived by subtraction of separate EEG traces recorded in a "passive" version of the same auditory task, in which motor responses were not required. In the somatosensory modality both the pN and the BP were detectable, although with lower amplitudes with respect to other two sensory modalities. Overall, regardless of the sensory modality, anticipatory task-related pN and BP components could be detected (or derived by subtraction) over both the prefrontal and motor cortices. These results support the view that anticipatory processes share common components among sensory modalities.