EEG Background Activity Research Articles

Convulsive seizures and some behavioral comorbidities are uncoupled in the Scn1aA1783V Dravet syndrome mouse model.

Dravet syndrome (Dravet) is a severe childhood epileptic encephalopathy. The disease begins with a febrile stage, characterized by febrile seizures with otherwise normal development. Progression to the worsening stage features recurrent intractable seizures and the presentation of additional nonepileptic comorbidities, including global developmental delay, hyperactivity, and motor deficits. Later in life, at the stabilization stage, seizure burden decreases, whereas Dravet-associated comorbidities persist. To date, it remains debated whether the nonepileptic comorbidities result from severe epilepsy or represent an independent phenotypic feature. Dravet mice (DS) faithfully recapitulate many clinical aspects of Dravet. Using wild-type (WT) and DS at different ages, we monitored multiple behavioral features as well as background electroencephalogram (EEG) activity during the different stages of Dravet epilepsy. Behavioral tests of WT and DS demonstrated that some deficits manifest already at the pre-epileptic stage, prior to the onset of convulsive seizures. These include motor impairment and hyperactivity in the open field. Deficits in cognitive functions were detected at the onset of severe spontaneous seizures. Power spectral analysis of background EEG activity, measured through development, showed that DS exhibit normal background oscillations at the pre-epileptic stage, a marked reduction in total power during the onset of severe epilepsy, and a subsequent smaller reduction later in life. Importantly, low EEG power at the stage of severe frequent convulsive seizures correlated with increased risk for premature death. Our data provide a comprehensive developmental trajectory of Dravet epilepsy and Dravet-associated comorbidities in mice, under controlled settings, demonstrating that the convulsive seizures and some nonepileptic comorbidities may be uncoupled. Moreover, we report the existence of an inverse correlation, on average, between the power of background EEG and the severity of epileptic phenotypes, suggesting that such measurements may potentially serve as a biomarker for Dravet severity.

Perampanel Increases Cortical EEG Fast Activity in Child and Adult Patients Affected by Epilepsy: A Quantitative EEG Study.

Quantitative EEG (qEEG) is an established technique used as objective measure for evaluating the effect of antiseizure medications (ASMs) on EEG background activity and monitoring cognitive effects of ASMs. Perampanel (PER) has been associated with relatively more tolerable cognitive effects in patients with epilepsy. The primary aim of the present study was to verify the effect of PER as first add-on ASM on qEEG in child and adult patients affected by epilepsy. The secondary aim of this study was to verify the effectiveness of the drug as first add-on treatment in both child and adult patients with epilepsy. We collected data from 17 adults and 10 children treated with PER as first add-on treatment, who underwent qEEG analysis before starting PER and at 3-month follow-up under stable treatment. PER resulted with significant effectiveness in reducing seizures in both children and adults. Considering qEEG analysis, we observed at follow-up the significant increase in beta1 and beta total bands both in children and adult patients. In particular, children showed the significant increase of beta band frequencies predominantly in the occipital regions, whereas adults showed a widespread increase of beta activity. Moreover, we documented in both child and adult patients the global reduction of delta bands activity. This qEEG study documented the relative increase of cortical EEG fast activity in both children and adult patients affected by epilepsy and treated by PER. This result may suggest a potential less negative impact of PER on cognition in patients affected by epilepsy, other than demonstrating effectiveness of the drug when used as first add-on treatment in both children and adult patients.

Multicenter prospective study on predictors of short-term outcome in disorders of consciousness.

ObjectiveThis international multicenter, prospective, observational study aimed at identifying predictors of short-term clinical outcome in patients with prolonged disorders of consciousness (DoC) due to acquired severe brain injury.MethodsPatients in vegetative state/unresponsive wakefulness syndrome (VS/UWS) or in minimally conscious state (MCS) were enrolled within 3 months from their brain injury in 12 specialized medical institutions. Demographic, anamnestic, clinical, and neurophysiologic data were collected at study entry. Patients were then followed up for assessing the primary outcome, that is, clinical diagnosis according to standardized criteria at 6 months postinjury.ResultsWe enrolled 147 patients (44 women; mean age 49.4 [95% confidence interval 46.1–52.6] years; VS/UWS 71, MCS 76; traumatic 55, vascular 56, anoxic 36; mean time postinjury 59.6 [55.4–63.6] days). The 6-month follow-up was complete for 143 patients (VS/UWS 70; MCS 73). With respect to study entry, the clinical diagnosis improved in 72 patients (VS/UWS 27; MCS 45). Younger age, shorter time postinjury, higher Coma Recovery Scale–Revised total score, and presence of EEG reactivity to eye opening at study entry predicted better outcome, whereas etiology, clinical diagnosis, Disability Rating Scale score, EEG background activity, acoustic reactivity, and P300 on event-related potentials were not associated with outcome.ConclusionsMultimodal assessment could identify patients with higher likelihood of clinical improvement in order to help clinicians, families, and funding sources with various aspects of decision-making. This multicenter, international study aims to stimulate further research that drives international consensus regarding standardization of prognostic procedures for patients with DoC.

Influencing electroclinical features and prognostic factors in patients with anti-NMDAR encephalitis: a cohort follow-up study in Chinese patients

The clinical manifestations of patients with anti-N-methyl-d-aspartate receptor (anti-NMDAR) encephalitis in East China and factors associated with prognosis were analyzed. A retrospective study of 106 patients (58 females; 48 males) with anti-NMDAR encephalitis in East China was carried out from June 2015 to February 2019. Clinical features and factors influencing outcomes were reviewed. Behavioral changes were observed in 74.5% (79/106) of patients, and comprised the initial symptoms in 61.3% (65/106). Seizures were observed in 67% (71/106) of patients, and served as initial symptoms in 31.1% (33/106). A total of 54.9% (39/71) of seizures were focal seizures. More clinical symptoms were observed in female patients than in male patients (P = 0.000). Similarly, background activity (BA) with high cerebrospinal fluid (CSF) antibody titers at the peak stage was more severe in female patients than in male patients (P = 0.000). The Binary logistic regression and receiver operating characteristic (ROC) curve analyses revealed the factors associated with poor outcomes included consciousness disturbance (OR 4.907, 95% CI 1.653–14.562, P = 0.004; area: 65.4%, sensitivity: 44.2%, specificity: 86.5%, P = 0.014), EEG BA (OR 3.743, 95% CI 1.766–7.932, P = 0.001; area: 76.6%, sensitivity: 73%, specificity: 75%, P = 0.000), number of symptoms (OR 2.911, 95% CI 1.811–4.679, P = 0.000; area: 77.1%, sensitivity: 59.5%, specificity: 78.6%, P = 0.000) and CSF antibody titer (OR 31.778, 95% CI 8.891–113.57, P = 0.000; area: 83.9%, sensitivity: 89.2%, specificity: 78.6%, P = 0.000). EEG BA and number of symptoms were associated with CSF antibody titers. Consciousness disturbances, EEG BA, number of symptoms and CSF antibody titers served as predictors of poor outcomes.

Stable high frequency background EEG activity distinguishes epileptic from healthy brain regions.

High-frequency oscillations are markers of epileptic tissue. Recently, different patterns of EEG background activity were described from which high-frequency oscillations occur: high-frequency oscillations with continuously oscillating background were found to be primarily physiological, those from quiet background were linked to epileptic tissue. It is unclear, whether these interactions remain stable over several days and during different sleep-wake stages. High-frequency oscillation patterns (oscillatory vs. quiet background) were analysed in 23 patients implanted with depth and subdural grid electrodes. Pattern scoring was performed on every channel in 10 s intervals in three separate day- and night-time EEG segments. An entropy value, measuring variability of patterns per channel, was calculated. A low entropy value indicated a stable occurrence of the same pattern in one channel, whereas a high value indicated pattern instability. Differences in pattern distribution and entropy were analysed for 143 280 10 s intervals with allocated patterns from inside and outside the seizure onset zone, different electrode types and brain regions. We found a strong association between high-frequency oscillations out of quiet background activity, and channels of the seizure onset zone (35.2% inside versus 9.7% outside the seizure onset zone, P < 0.001), no association was found for high-frequency oscillations from continuous oscillatory background (P = 0.563). The type of background activity remained stable over the same brain region over several days and was independent of sleep stage and recording technique. Stability of background activity was significantly higher in channels of the seizure onset zone (entropy mean value 0.56 ± 0.39 versus 0.64 ± 0.41; P < 0.001). This was especially true for the presumed epileptic high-frequency oscillations out of quiet background (0.57 ± 0.39 inside versus 0.72 ± 0.37 outside the seizure onset zone; P < 0.001). In contrast, presumed physiological high-frequency oscillations from continuous oscillatory backgrounds were significantly more stable outside the seizure onset zone (0.72 ± 0.45 versus 0.48 ± 0.53; P < 0.001). The overall low entropy values suggest that interactions between high-frequency oscillations and background activity are a stable phenomenon specific to the function of brain regions. High-frequency oscillations occurring from a quiet background are strongly linked to the seizure onset zone whereas high-frequency oscillations from an oscillatory background are not. Pattern stability suggests distinct underlying mechanisms. Analysing short time segments of high-frequency oscillations and background activity could help distinguishing epileptic from physiologically active brain regions.

Mitochondrial epilepsy: a cross-sectional nationwide Italian survey

Many aspects of epilepsy in mitochondrial disorders (MDs) need to be further clarified. To this aim, we explored retrospectively a cohort of individuals with MDs querying the "Nationwide Italian Collaborative Network of Mitochondrial Diseases" (NICNMD) database (1467 patients included since 2010 to December 2016). We collected information on age at epilepsy onset, seizure type and frequency, genetic findings, and antiepileptic drugs (AEDs). At the time of our survey, 147/1467 (10%) patients in the NICNMD database had epilepsy. Complete information was available only for 98 patients, 52 males and 46 females, aged 5-92years (mean age 40.4 ± 18.4; 14/98 children/teenagers and 84 adults). Epilepsy was the presenting feature of MD in 46/98 (47%) individuals, with onset at a median age of 19years (range, 0.2-68; < 3years in 14/97 (14%), 3-19years in 36/97 (37%), > 19years in 47/97 (49%)). Moreover, 91/98 patients (93%) displayed multiple seizures, with daily or weekly frequency in 25/91 (28%). Interictal EEG was abnormal in 70/78 (90%) patients, displaying abnormal background (47/70; 67%) and/or interictal paroxysms (53/70; 76%). Eighty of 90 patients (89%) displayed a 50-100% reduction of seizures on AEDs; levetiracetam was the most commonly used. Forty-one patients (42%) carried the m.3243A>G mutation, 16 (16%) the m.8344A>G, and 9 (9%) nuclear DNA (nDNA) mutations. Individuals with early-onset seizures mainly carried nDNA mutations and had a more severe epilepsy phenotype, higher seizure frequency, and disorganized background EEG activity. A better definition of epilepsy in MDs may foster the diagnostic workup, management, and treatment of affected patients, and allow more homogeneous patient stratification.

Electroencephalography in acute stroke

To determine the incidence of non-convulsive status epilepticus, epileptiform activity, rhythmic and periodic patterns in patients with acute stroke. An analysis of electroencephalography (EEG) in 86 stroke patients in the neurointensive care unit of the tertiary medical center was performed. Criteria for starting EEG recording were epileptic seizures or clinical suspicion of uncontrolled epileptic status. The ictal-interictal continuum biomarkers and the diagnostic value of EEG for prediction of survival and recovery were assessed. Pathological changes on EEG were recorded in 84% of patients. These patients showed the absence of the dominant occipital rhythm (66%) and hemispheric slowing (42%). Diffuse slowing below the theta range was observed in 41% of patients. EEG reactivity was absent in 20%. Sporadic epileptiform discharges were recorded in 36% of patients and rhythmic and periodic patterns in 26%. Reliable predictors of the unfavorable outcome were the absence of dominant occipital rhythm, lack of reactivity, and low amplitude of the background EEG. No association between the recording of epileptiform activity and the probability of death was shown. The most useful EEG biomarkers for predicting survival are amplitude, dominant frequency of background EEG activity and reactivity to external stimulus. Sporadic epileptiform discharges, rhythmic, and periodic patterns are not mandatory associated with a negative prognosis in stroke patients.

Developmental EEG hallmark or biological artifact? Glossokinetic artifact mimicking anterior slow dysrhythmia in two full term newborns

The aim of this paper is to describe an uncommon physiological EEG artifact in newborns caused by tongue movements (TM), mimicking anterior slow dysrhythmia (ASD). The subjects are two full-term newborns (39 weeks gestational age (GA)), admitted to the Neonatal Intensive Care Unit for respiratory distress. Both underwent polygraphic video-EEG recording in order to better characterize tremor-like movements of all four limbs that appeared 48 hours after birth. Multichannel video-EEG polygraphy was performed using the 10-20 electrode montage modified for neonates. Ninety minutes of EEG was recorded for each subject, capturing different behavioral states. Background EEG activity was normal for both subjects. During active sleep (AS), synchronous and symmetric slow activity was recorded over bifrontal head regions. For subject 1, bursts of monomorphic 2Hz delta waves, with an amplitude between 50-100μV lasting two seconds, were recorded and identified as anterior slow dysrhythmia. For subject 2, polymorphic 1-2Hz delta waves, 50-100μV in amplitude and lasting for 20 seconds, were recorded only during suction. After thorough analysis of simultaneous digital video recording synchronized with the EEG trace, this activity was thought to be compatible with glossokinetic artifact. Interpretation of neonatal EEG can be challenging; the background activity is frequently intermixed with physiological artifacts, such as ocular, muscle and movement artifacts, complicating the interpretation. Even continuous video-recording might not make the diagnosis immediately obvious. Therefore, when a rhythmic monomorphic pattern without evolution in amplitude or frequency is seen, we suggest that tongue movement artifact should be considered.

Resilience, quality of life, and clinical aspects of patients with epilepsy

Clinical and psychosocial factors can influence the quality of life (QoL) of patients with epilepsy (PWE). ObjectiveThe aim of this study was to investigate the association between the Resilience Scale (RS) and the QOLIE-31 (Quality of Life in Epilepsy Inventory), Neurological Disorders Depression Inventory for Epilepsy, and clinical aspects of 137 PWE, at a significance level of p < 0.05. ResultsSeizure control, normal EEG (electroencephalographic) background activity, and antiepileptic drug (AED) monotherapy were associated with greater resilience. There was a correlation between resilience and depressive episodes (Pearson correlation: −0.462; p < 0.000) and performance in the MMSE (Mini-Mental State Examination) (0.221, p = 0.015). Improved QoL was associated with greater resilience, self-sufficiency, equanimity, and perseverance. Greater resilience was significantly related to the absence of depressive symptoms (p = 0.001), normal EEG background activity (p = 0.024), and AED monotherapy (p = 0.049) in the linear regression model. ConclusionClinical, cognitive, and EEG aspects were related to resilience. Depressive symptoms correlate negatively with resilience. Individuals with greater resilience perceive better QoL.

A group sequential test for ABR detection

Objective: To detect the auditory brainstem response (ABR) automatically using an innovative sequentially applied Hotelling’s T 2 test, with the overall goal of optimising test time whilst controlling the false-positive rate (FPR).Design: The stage-wise critical decision boundaries for accepting or rejecting the null hypothesis were found using a new approach called the Convolutional Group Sequential Test (CGST). Specificity, sensitivity, and test time were evaluated using simulations and subject recorded data.Study sample: Data consists of click-evoked ABR threshold series from 12 normal hearing adults, and recordings of EEG background activity from 17 normal hearing adults.Results: Reductions in mean test time of up to 40–45% were observed for the sequential test, relative to a conventional “single shot” test where the statistical test is applied to the data just once. To obtain these results, it will occasionally be necessary to run the test to a higher number of stimuli, i.e. the maximum test time needs to be increased.Conclusions: The CGST can be used to control the specificity of a sequentially applied ABR detection method. Doing so can reduce test time, relative to the “single shot” test, when considered across a cohort of test subjects.

Effect of short-term transcutaneous trigeminal nerve stimulation on EEG activity in drug-resistant epilepsy

BackgroundTranscutaneous trigeminal nerve stimulation (TNS) has antiepileptic effects in patients with drug-resistant epilepsy (DRE). However, whether and how TNS is able to modulate the electroencephalogram (EEG) background activity in patients with DRE is still unknown. ObjectivesTo investigate the effect of short-term TNS on EEG background activity in DRE by qualitative and quantitative analyses. MethodsTwenty-nine DRE patients participated in the study. Twenty-two were randomly divided into a “sham-TNS” or “real-TNS” group; seven patients underwent stimulation of the median nerve (MNS) at the wrist. Real-TNS was delivered bilaterally to the infraorbital nerve (trains of 1–20 mA, 120 Hz, cyclic modality for 20 min). The sham-TNS protocol mimicked the real-TNS one but at a zero intensity. For MNS, the same parameters as real-TNS were used. EEG was continuously acquired for 40 min: 10′ pre, 20′ during and 10′ post stimulation. EEG was visually inspected for interictal epileptiform discharge (IEDs) changes and processed by spectral analysis for changes in mean frequency and absolute power of each frequency band. ResultsA significant increase of EEG absolute alpha power was observed during real-TNS compared with the sham-TNS (F34,680 = 1.748; p = 0.006). Conversely, no significant effects were noticed either for quantitative analysis of other frequency bands or for IEDs detection. MNS proved unable to modulate EEG activity. ConclusionsShort-term TNS induces an acute and specific effect on background EEG of DRE by increasing the absolute alpha band power. EEG alpha rhythm enhancement may index a cortical functional inhibition and act as a seizure-preventing mechanism.

Automatic Analysis of EEGs Using Big Data and Hybrid Deep Learning Architectures.

Brain monitoring combined with automatic analysis of EEGs provides a clinical decision support tool that can reduce time to diagnosis and assist clinicians in real-time monitoring applications (e.g., neurological intensive care units). Clinicians have indicated that a sensitivity of 95% with specificity below 5% was the minimum requirement for clinical acceptance. In this study, a high-performance automated EEG analysis system based on principles of machine learning and big data is proposed. This hybrid architecture integrates hidden Markov models (HMMs) for sequential decoding of EEG events with deep learning-based post-processing that incorporates temporal and spatial context. These algorithms are trained and evaluated using the Temple University Hospital EEG, which is the largest publicly available corpus of clinical EEG recordings in the world. This system automatically processes EEG records and classifies three patterns of clinical interest in brain activity that might be useful in diagnosing brain disorders: (1) spike and/or sharp waves, (2) generalized periodic epileptiform discharges, (3) periodic lateralized epileptiform discharges. It also classifies three patterns used to model the background EEG activity: (1) eye movement, (2) artifacts, and (3) background. Our approach delivers a sensitivity above 90% while maintaining a specificity below 5%. We also demonstrate that this system delivers a low false alarm rate, which is critical for any spike detection application.

Transient electroencephalographic alpha power loss during maintenance of general anaesthesia

BackgroundEEG activity in the extended alpha frequency range (7–17 Hz) during maintenance of general anaesthesia is primarily determined by effect-site concentrations of the hypnotic and analgesic drugs used. Intermittent alpha loss during surgery, unexplained by changes in anaesthetic or opioid concentrations, could represent arousal of the cortex as a result of increased surgical stimulation. MethodsA generalised linear model was fitted to alpha power recorded from patients undergoing general anaesthesia from induction until waking using three explanatory variables: age-adjusted volatile anaesthetic effect-site concentration, and estimated effect-site propofol and opioid concentrations. Model residuals were decomposed into uncorrelated white noise and a fluctuating auto-correlated trend. Deviations of this local trend were classified as ‘unexpected alpha dropout events’. To investigate whether these alpha dropouts might be explained by the effect of noxious stimulation, we related their occurrence to whether a patient was undergoing surgery involving the body cavity or not. ResultsAlpha power dropouts occurred in 73 of the 237 patients included in the final analysis (31%, median amplitude of −3.5 dB, duration=103 s). They showed a bimodal or broadly skewed distribution, being more probable soon after initial incision (32%), dropping to around 10% at 1 h, and then again increasing to >30% in operations lasting >3 h. Multivariate analysis showed that alpha dropouts were significantly associated with body cavity surgery (P=0.003) and with longer operations (P<0.001). ConclusionsA loss of alpha power, unexplained by changes in anaesthetic or opioid concentrations, is suggestive of thalamocortical depolarisation induced by body cavity noxious stimuli, and could provide a measure of nociception during surgery.

Changes in background electroencephalographic activity in benign childhood epilepsy with centrotemporal spikes after oxcarbazepine treatment: a standardized low-resolution brain electromagnetic tomography (sLORETA) study

BackgroundSeveral neuroimaging studies have reported neurophysiological alterations in patients with benign childhood epilepsy with centrotemporal spikes (BCECTS). However, reported outcomes have been inconsistent, and the progression of these changes in the brain remains unresolved. Moreover, background electroencephalography (EEG) in cases of BCECTS has not been performed often.MethodsWe investigated background EEG activity changes after six months of oxcarbazepine treatment to better understand the neurophysiological alterations and progression that occur in BCECTS. In 18 children with BCECTS, non-parametric statistical analyses using standardized low resolution brain electromagnetic tomography (sLORETA) were performed to compare the current density distribution of four frequency bands (delta, theta, alpha, and beta) between untreated and treated conditions.ResultsBackground EEG activity for the delta frequency band was significantly decreased in the fronto-temporal and limbic regions of the left hemisphere after oxcarbazepine treatment (threshold log-F-ratio = ±2.729, P < 0.01). The maximum current density difference was found in the parahippocampal gyrus of the left limbic lobe (Montreal Neurological Institute coordinate [x, y, z = 25, − 20, − 10], Brodmann area 28) (log-F-ratio = 3.081, P < 0.01).ConclusionsOur results indicate the involvement of the fronto-temporal and limbic cortices in BCECTS, and limbic lobe involvement, including the parahippocampal gyrus, was noted. In addition to evidence of the involvement of the fronto-temporal and limbic cortices in BCECTS, this study also found that an antiepileptic drug could reduce the delta frequency activity of the background EEG in these regions.

Chapter 1 - Generalized epilepsies

Idiopathic generalized epilepsies (IGE) are characterized by normal background EEG activity and generalized interictal spike-and-wave discharges in the absence of any evidence of brain lesion. Absence epilepsies are the prototypes of IGEs. In childhood and juvenile absence epilepsies, by definition, all patients manifest absence seizures associated with an EEG pattern of generalized spike-wave (GSW) discharges. In juvenile myoclonic epilepsy, myoclonic jerks, usually affecting shoulders and arms bilaterally and appearing upon awakening, are the most characteristic clinical feature. Myoclonic jerks are accompanied on the EEG by generalized spike/polyspike-and-wave (GSW, GPWS) complexes at 3.5-6Hz. Idiopathic generalized epilepsy with generalized tonic-clonic seizures only is a broad and nonspecific category including all patients with generalized tonic-clonic seizures and an interictal EEG pattern of GSW discharges. Despite the strong heritability and the recent advances in genetic technology, the genetic basis of IGEs remains largely elusive and only in a small minority of patients with classic IGE phenotypes is a monogenic cause identified. Early myoclonic encephalopathy (EME), early infantile encephalopathy with suppression bursts, West syndrome, and Lennox-Gastaut syndrome, once classified among the generalized epilepsies, are now considered to be epileptic encephalopathies. Among them, only Lennox-Gastaut syndrome is characterized by prominent generalized clinical and EEG features.

Prognostic Value of Electroencephalography in Hypothermia-Treated Neonates With Hypoxic-Ischemic Encephalopathy: A Meta-Analysis

BackgroundElectroencephalography (EEG) background activity is associated with neurological outcome in neonates with hypoxic-ischemic encephalopathy. There is uncertainty about the prognostic value of EEG background activity after hypothermia was introduced. MethodsSearches were made on Pubmed, Embase, and the Cochrane Library, from inception to March 1, 2018. Pooled sensitivities and specificities were calculated to assess the diagnostic power of burst suppression, low voltage, and flat trace background activities in the prediction of an adverse neurological outcome in the follow-up period in hypothermia-treated neonates with hypoxic-ischemic encephalopathy. I2 was used to assess heterogeneity, and meta-regression was done to explore the source of heterogeneity. ResultsEighteen studies with 940 neonates were included. Pooled sensitivities and specificities in predicting the combination of death and neurodevelopmental impairment were burst suppression (sensitivity 0.87 [95% confidence interval (CI) 0.79 to 0.93], specificity 0.60 [95% CI 0.44 to 0.74]), low voltage (sensitivity 0.84 [0.75 to 0.90], specificity 0.80 [0.58 to 0.92]), and flat trace (sensitivity 0.85 [0.75 to 0.92], specificity 0.94 [0.77 to 0.99]). Subgroup analysis revealed the sensitivities of background patterns obtained after 24 hours of life were higher than those within age 24 hours, whereas the specificities were just the reverse. Flat trace performed best on sensitivity 0.93 (0.60 to 0.99) and specificity 0.90 (0.64 to 0.98) in predicting death. Burst suppression demonstrated the highest sensitivity 0.87 (0.58 to 0.97) and flat trace performed best on specificity 0.85 (0.60 to 0.96) in predicting neurodevelopmental impairment. ConclusionsEEG background activity is predictive of long-term neurological outcome in hypothermia-treated neonates with hypoxic-ischemic encephalopathy. Burst suppression, low voltage, and flat trace are potential predictors of death or neurodevelopmental impairment.

Multi-centric longitudinal study on electrophysiological diagnostic and prognostic markers in prolonged disorders of consciousness

Diagnostic accuracy and reliable assessment of prognosis are challenging in patients in vegetative state (VS) and in minimally conscious state (MCS). This longitudinal multi-centric study aims to identify neurophysiological patterns with diagnostic and prognostic value. 59 patients in VS and 63 in MCS underwent clinical assessment by Coma Recovery Scale-Revised3 and neurophysiological evaluations of EEG background activity and reactivity, somatosensory evoked potential (SEP) and event related potential (ERP) at ⩽3 months after brain-injury. Clinical outcome was evaluated at 6 months post-injury. EEG background activity and reactivity significantly differed between VS and MCS patients (p

Longitudinal analysis of developmental changes in electroencephalography patterns and sleep-wake states of the neonatal mouse.

The neonatal brain undergoes rapid maturational changes that facilitate the normal development of the nervous system and also affect the pathological response to brain injury. Electroencephalography (EEG) and analysis of sleep-wake vigilance states provide important insights into the function of the normal and diseased immature brain. While developmental changes in EEG and vigilance states are well-described in people, less is known about the normal maturational properties of rodent EEG, including the emergence and evolution of sleep-awake vigilance states. In particular, a number of developmental EEG studies have been performed in rats, but there is limited comparable research in neonatal mice, especially as it pertains to longitudinal EEG studies performed within the same mouse. In this study, we have attempted to provide a relatively comprehensive assessment of developmental changes in EEG background activity and vigilance states in wild-type mice from postnatal days 9–21. A novel EEG and EMG method allowed serial recording from the same mouse pups. EEG continuity and power and vigilance states were analyzed by quantitative assessment and fast Fourier transforms. During this developmental period, we demonstrate the timing of maturational changes in EEG background continuity, frequencies, and power and the emergence of identifiable wake, NREM, and REM sleep states. These results should serve as important control data for physiological studies of mouse models of normal brain development and neurological disease.

Lacosamide on background eeg activity in brain tumor-related epilepsy patients: A case series study.

ObjectiveTherapeutic doses of antiepileptic drugs (AEDs) may alter EEG background activity, which is considered an index of the functional state of the brain. Quantitative analysis (qEEG) of EEG background activity is a valid instrument to assess the effects of many centrally active drugs on the central nervous system, including AEDs. Lacosamide (LCM) is a new AED that could be a valid therapeutic choice in patients with brain tumor‐related epilepsy (BTRE).MethodsWe used qEEG to analyze the possible effect of LCM as an add‐on, on background EEG activity after 4 months in patients with BTRE.ResultsWe consecutively recruited sixteen patients with BTRE: Five dropped out for disease progression, five for scarce compliance, and six completed the study. For these reasons qEEG was performed at first visit and after 4 months only in six patients. For all frequency bands, LCM revealed no changes of mean relative power during rest with eyes closed, hyperpnoea (HP), and mental arithmetic task (MA); significant increment was found only in the theta mean relative power during opening and closing eyes (BR). After four months of therapy with LCM, one patient was seizure free, four had a seizure reduction ≥50%, and one showed a worsening in seizure frequency <50%.ConclusionDespite the limitation of a small series, these findings suggest that LCM seems to have only a mild interference on EEG background activity and confirm that LCM has a good efficacy on seizure control in patients with BTRE. This is the first study that evaluates the effect of LCM on background EEG activity, using qEEG in BTRE patients. Future research in this area could include prospective studies with qEEG for a longer follow‐up period to assess the impact of AEDs on brain functions in this particular fragile patient population.

Seizures in preterm infants

Preterm newborn infants are at risk for cerebral dysfunction and susceptible to seizures in the first weeks of life.Because of less reliable clinical signs, many seizures of preterm neonates are detectable only on electroencephalogram(EEG). Understanding EEG background patterns and features in these preterm infants is vital to provide appropriate treatment.As EEG background activities and patterns significantly depend on gestational age, some physiologic preterm EEG patterns, such as rhythmic temporal theta activity or delta brushes, may be sharply contoured and appear similar to epileptic EEG patterns later in life in preterm infants.Moreover, compared with full-term neonates, ictal patterns in preterm infants are of lower voltage and frequency.This article reviews current incidence of seizures in preterm infants and their typical ictal EEG patterns.It also discusses the influence of seizures on long-term outcome of preterm infants and distinguishes the pitfalls of EEG analysis. Key words: Premature newborn; Seizure; Electroencephalogram