Idiopathic epilepsies with seizures precipitated by fever and SCN1A abnormalities

Purpose: SCN1A is the most clinically relevant epilepsy gene, most mutations lead to severe myoclonic epilepsy of infancy (SMEI) and generalized epilepsy with febrile seizures plus (GEFS+). We studied 132 patients with epilepsy syndromes with seizures precipitated by fever, and performed phenotype-genotype correlations with SCN1A alterations. Methods: We included patients with SMEI including borderline SMEI (SMEB), GEFS+, febrile seizures (FS), or other seizure types precipitated by fever. We performed a clinical and genetic study focusing on SCN1A, using dHPLC, gene sequencing, and MLPA to detect genomic deletions/duplications on SMEI/SMEB patients. Results: We classified patients as: SMEI/SMEB = 55; GEFS+ = 26; and other phenotypes = 51. SCN1A analysis by dHPLC/sequencing revealed 40 mutations in 37 SMEI/SMEB (67%) and 3 GEFS+ (11.5%) probands. MLPA showed genomic deletions in 2 of 18 SMEI/SMEB. Most mutations were de novo (82%). SMEB patients carrying mutations (8) were more likely to have missense mutations (62.5%), conversely SMEI patients (31) had more truncating, splice site or genomic alterations (64.5%). SMEI/SMEB with truncating, splice site or genomic alterations had a significantly earlier age of onset of FS compared to those with missense mutations and without mutations (p = 0.00007, ANOVA test). None of the remaining patients with seizures precipitated by fever carried SCN1A mutations. Conclusion: We obtained a frequency of 71% SCN1A abnormalities in SMEI/SMEB and of 11.5% in GEFS+ probands. MLPA complements DNA sequencing of SCN1A increasing the mutation detection rate. SMEI/SMEB with truncating, splice site or genomic alterations had a significantly earlier age of onset of FS. This study confirms the high sensitivity of SCN1A for SMEI/SMEB phenotypes. © 2007 International League Against Epilepsy.

Clinical utility of implantable neurostimulation devices as adjunctive treatment of uncontrolled seizures

About one third of patients with epilepsy are refractory to medical treatment. For these patients, alternative treatment options include implantable neurostimulation devices such as vagus nerve stimulation (VNS), deep brain stimulation (DBS), and responsive neurostimulation systems (RNS). We conducted a systematic literature review to assess the available evidence on the clinical efficacy of these devices in patients with refractory epilepsy across their lifespan. VNS has the largest evidence base, and numerous randomized controlled trials and open-label studies support its use in the treatment of refractory epilepsy. It was approved by the US Food and Drug Administration in 1997 for treatment of partial seizures, but has also shown significant benefit in the treatment of generalized seizures. Results in adult populations have been more encouraging than in pediatric populations, where more studies are required. VNS is considered a safe and well-tolerated treatment, and serious side effects are rare. DBS is a well-established treatment for several movement disorders, and has a small evidence base for treatment of refractory epilepsy. Stimulation of the anterior nucleus of the thalamus has shown the most encouraging results, where significant decreases in seizure frequency were reported. Other potential targets include the centromedian thalamic nucleus, hippocampus, cerebellum, and basal ganglia structures. Preliminary results on RNS, new-generation implantable neurostimulation devices which stimulate brain structures only when epileptic activity is detected, are encouraging. Overall, implantable neurostimulation devices appear to be a safe and beneficial treatment option for patients in whom medical treatment has failed to adequately control their epilepsy. Further large-scale randomized controlled trials are required to provide a sufficient evidence base for the inclusion of DBS and RNS in clinical guidelines.

Phenobarbital for neonatal seizures:response rate and predictors of refractoriness

Background : Phenobarbital is the first-line choice for neonatal seizures treatment, despite a response rate of approximately 45%. Failure to respond to acute anticonvulsants is associated with poor neurodevelopmental outcome, but knowledge on predictors of refractoriness is limited. Objective : To quantify response rate to phenobarbital and to establish variables predictive of its lack of efficacy. Methods : We retrospectively evaluated newborns with electrographically confirmed neonatal seizures admitted between January 1999 and December 2012 to the neonatal intensive care unit of Parma University Hospital (Italy), excluding neonates with status epilepticus. Response was categorized as complete (cessation of clinical and electrographic seizures after phenobarbital administration), partial (reduction but not cessation of electrographic seizures with the first bolus, response to the second bolus), or absent (no response after the second bolus). Multivariate analysis was used to identify independent predictors of refractoriness. Results : Out of 91 newborns receiving phenobarbital, 57 (62.6%) responded completely, 15 (16.5%) partially, and 19 (20.9%) did not respond. Seizure type (p = 0.02), background electroencephalogram (EEG; p ≤ 0.005), and neurologic examination (p ≤ 0.005) correlated with response to phenobarbital. However, EEG (p ≤ 0.02) and seizure type (p ≤ 0.001) were the only independent predictors. Conclusion : Our results suggest a prominent role of neurophysiological variables (background EEG and electrographic-only seizure type) in predicting the absence of response to phenobarbital in high-risk newborns.

Phenobarbital reduces EEG amplitude and propagation of neonatal seizures but does not alter performance of automated seizure detection

Objective: Phenobarbital increases electroclinical uncoupling and our preliminary observations suggest it may also affect electrographic seizure morphology. This may alter the performance of a novel seizure detection algorithm (SDA) developed by our group. The objectives of this study were to compare the morphology of seizures before and after phenobarbital administration in neonates and to determine the effect of any changes on automated seizure detection rates. Methods: The EEGs of 18 term neonates with seizures both pre- and post-phenobarbital (524 seizures) administration were studied. Ten features of seizures were manually quantified and summary measures for each neonate were statistically compared between pre- and post-phenobarbital seizures. SDA seizure detection rates were also compared. Results: Post-phenobarbital seizures showed significantly lower amplitude (p < 0.001) and involved fewer EEG channels at the peak of seizure (p < 0.05). No other features or SDA detection rates showed a statistical difference. Conclusion: These findings show that phenobarbital reduces both the amplitude and propagation of seizures which may help to explain electroclinical uncoupling of seizures. The seizure detection rate of the algorithm was unaffected by these changes. Significance: The results suggest that users should not need to adjust the SDA sensitivity threshold after phenobarbital administration.

Initial approach to irst-time seizures in pediatrics

Objective: Prove that conducting complementary studies at laboratories and imaging studies are unnecessary in irst-time unprovoked seizures, since there is no change in the evolution and prognosis of the disease, as well as the study of our population, the incidence rate and the proportion of our patients that have been studied and given maintenance treatment, so it can be determined whether or not our population should follow the suggestions of the American Academy of Pediatrics and the Spanish Pediatric Association. Methods: An observational study, including patients diagnosed with irst-time unprovoked seizures. They were followed up on by the emergency department and information was collected from their clinical history and compared with the results of the different studies between patients that suffered just one seizure and the ones that had recurrent seizures. Results: Thirty one patients were included, 14 males and 17 females. The average age was 5.5 years old. The 100% of patients were studied, and the groups were compared. The signiicant study was the electroencephalogram (EEG) with a p=0.02 (signiicance p<0.05), incidence of 41%. Conclusions: The study and diagnosis of irst-time unprovoked seizures is based on clinical manifestations. The EEG is important in the study and classiication of unprovoked seizures. Our population has an incidence and recurrence rate similar to that in the bibliography, and for that reason, this study suggests that the diagnostic and therapeutic guidelines of the American Academy of Pediatrics and the Spanish Pediatric Association should be followed.

Absence of LPA1 receptor results in altered pattern of limbic activation after tail suspension test

Stress serves as an adaptive mechanism and helps organisms to cope with life-threatening situations. However, individual vulnerability to stress and dysregulation of this system may precipitate stress-related disorders such as depression. The neurobiological circuitry in charge of dealing with stressors has been widely studied in animal models. Recently our group has demonstrated a role for lysophosphatidic acid (LPA) through the LPA1 receptor in vulnerability to stress, in particular the lack of this receptor relates to robust decrease of adult hippocampal neurogenesis and induction of anxious and depressive states. Nevertheless, the specific abnormalities in the limbic circuit in reaction to stress remains unclear. The aim of this study is to examine the differences in the brain activation pattern in the presence or absence of LPA1 receptor after acute stress. For this purpose, we have studied the response of maLPA1-null male mice and normal wild type mice to an intense stressor: Tail Suspension Test. Activation induced by behaviour of brain regions involved in mood regulation was analysed by stereological quantification of c-Fos immunoreactive positive cells. We also conducted multidimensional scaling analysis in order to unravel coativation between structures. Our results revealed hyperactivity of stress-related structures such as amygdala and paraventricular nucleus of the hypothalamus in the knockout model and different patterns of coactivation in both genotypes using a multidimensional map. This data provides further evidence to the engagement of the LPA1 receptors in stress regulation and sheds light on different neural pathways under normal and vulnerability conditions that can lead to mood disorders.

An in-depth characterisation of neonatal seizures by early continuous video-EEG analysis

Introduction Seizures are harmful to the neonatal brain; this compels many clinicians and researchers to persevere further in optimizing every aspects of managing neonatal seizures. Aims To delineate the seizure profile between non-cooled versus cooled neonates with hypoxic-ischaemic encephalopathy (HIE), in neonates with stroke, the response of seizure burden to phenobarbitone and to quantify the degree of electroclinical dissociation (ECD) of seizures. Methods The multichannel video-EEG was used in this research study as the gold standard to detect seizures, allowing accurate quantification of seizure burden to be ascertained in term neonates. The entire EEG recording for each neonate was independently reviewed by at least 1 experienced neurophysiologist. Data were expressed in medians and interquartile ranges. Linear mixed models results were presented as mean (95% confidence interval); p values <0.05 were deemed as significant. Results Seizure burden in cooled neonates was lower than in non-cooled neonates [60(39-224) vs 203(141-406) minutes; p=0.027]. Seizure burden was reduced in cooled neonates with moderate HIE [49(26-89) vs 162(97-262) minutes; p=0.020] when compared with severe HIE. In neonates with stroke, the background pattern showed suppression over the infarcted side and seizures demonstrated a characteristic pattern. Compared with 10 mg/kg, phenobarbitone doses at 20 mg/kg reduced seizure burden (p=0.004). Seizure burden was reduced within 1 hour of phenobarbitone administration [mean (95% confidence interval): -14(-20 to -8) minutes/hour; p<0.001], but seizures returned to pre-treatment levels within 4 hours (p=0.064). The ECD index in cooled, non-cooled neonates with HIE, stroke and in neonates with other diagnoses were 88%, 94%, 64% and 75% respectively. Conclusions Further research exploring the treatment effects on seizure burden in the neonatal brain is required. A change to our current treatment strategy is warranted as we continue to strive for more effective seizure control, anchored with use of the multichannel EEG as the surveillance tool.

Treatment trials for neonatal seizures: the effect of design on sample size

Neonatal seizures are common in the neonatal intensive care unit. Clinicians treat these seizures with several anti-epileptic drugs (AEDs) to reduce seizures in a neonate. Current AEDs exhibit sub-optimal efficacy and several randomized control trials (RCT) of novel AEDs are planned. The aim of this study was to measure the influence of trial design on the required sample size of a RCT. We used seizure time courses from 41 term neonates with hypoxic ischaemic encephalopathy to build seizure treatment trial simulations. We used five outcome measures, three AED protocols, eight treatment delays from seizure onset (Td) and four levels of trial AED efficacy to simulate different RCTs. We performed power calculations for each RCT design and analysed the resultant sample size. We also assessed the rate of false positives, or placebo effect, in typical uncontrolled studies. We found that the false positive rate ranged from 5 to 85% of patients depending on RCT design. For controlled trials, the choice of outcome measure had the largest effect on sample size with median differences of 30.7 fold (IQR: 13.7–40.0) across a range of AED protocols, Td and trial AED efficacy (p<0.001). RCTs that compared the trial AED with positive controls required sample sizes with a median fold increase of 3.2 (IQR: 1.9–11.9; p<0.001). Delays in AED administration from seizure onset also increased the required sample size 2.1 fold (IQR: 1.7–2.9; p<0.001). Subgroup analysis showed that RCTs in neonates treated with hypothermia required a median fold increase in sample size of 2.6 (IQR: 2.4–3.0) compared to trials in normothermic neonates (p<0.001). These results show that RCT design has a profound influence on the required sample size. Trials that use a control group, appropriate outcome measure, and control for differences in Td between groups in analysis will be valid and minimise sample size.

Analysis of cardiac and epileptic signals using higher order spectra

The theory of nonlinear dyamic systems provides some new methods to handle complex systems. Chaos theory offers new concepts, algorithms and methods for processing, enhancing and analyzing the measured signals. In recent years, researchers are applying the concepts from this theory to bio-signal analysis. In this work, the complex dynamics of the bio-signals such as electrocardiogram (ECG) and electroencephalogram (EEG) are analyzed using the tools of nonlinear systems theory. In the modern industrialized countries every year several hundred thousands of people die due to sudden cardiac death. The Electrocardiogram (ECG) is an important biosignal representing the sum total of millions of cardiac cell depolarization potentials. It contains important insight into the state of health and nature of the disease afflicting the heart. Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computerbased intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and four classes of arrhythmia. This thesis presents some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. Several features were extracted from the HOS and subjected an Analysis of Variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, seven features were extracted from the heart rate signals using HOS and fed to a support vector machine (SVM) for classification. The performance evaluation protocol in this thesis uses 330 subjects consisting of five different kinds of cardiac disease conditions. The classifier achieved a sensitivity of 90% and a specificity of 89%. This system is ready to run on larger data sets. In EEG analysis, the search for hidden information for identification of seizures has a long history. Epilepsy is a pathological condition characterized by spontaneous and unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic early detection of the seizure onsets would help the patients and observers to take appropriate precautions. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, these features are used to train both a Gaussian mixture model (GMM) classifier and a Support Vector Machine (SVM) classifier. Results show that the classifiers were able to achieve 93.11% and 92.67% classification accuracy, respectively, with selected HOS based features. About 2 hours of EEG recordings from 10 patients were used in this study. This thesis introduces unique bispectrum and bicoherence plots for various cardiac conditions and for normal, background and epileptic EEG signals. These plots reveal distinct patterns. The patterns are useful for visual interpretation by those without a deep understanding of spectral analysis such as medical practitioners. It includes original contributions in extracting features from HRV and EEG signals using HOS and entropy, in analyzing the statistical properties of such features on real data and in automated classification using these features with GMM and SVM classifiers.

Chlorzoxazone, an SK-type potassium channel activator used in humans, reduces excessive alcohol intake in rats

Background Alcoholism imposes a tremendous social and economic burden. There are relatively few pharmacological treatments for alcoholism, with only moderate efficacy, and there is considerable interest in identifying additional therapeutic options. Alcohol exposure alters SK-type potassium channel (SK) function in limbic brain regions. Thus, positive SK modulators such as chlorzoxazone (CZX), a US Food and Drug Administration–approved centrally acting myorelaxant, might enhance SK function and decrease neuronal activity, resulting in reduced alcohol intake. Methods We examined whether CZX reduced alcohol consumption under two-bottle choice (20% alcohol and water) in rats with intermittent access to alcohol (IAA) or continuous access to alcohol (CAA). In addition, we used ex vivo electrophysiology to determine whether SK inhibition and activation can alter firing of nucleus accumbens (NAcb) core medium spiny neurons. Results Chlorzoxazone significantly and dose-dependently decreased alcohol but not water intake in IAA rats, with no effects in CAA rats. Chlorzoxazone also reduced alcohol preference in IAA but not CAA rats and reduced the tendency for rapid initial alcohol consumption in IAA rats. Chlorzoxazone reduction of IAA drinking was not explained by locomotor effects. Finally, NAcb core neurons ex vivo showed enhanced firing, reduced SK regulation of firing, and greater CZX inhibition of firing in IAA versus CAA rats. Conclusions The potent CZX-induced reduction of excessive IAA alcohol intake, with no effect on the more moderate intake in CAA rats, might reflect the greater CZX reduction in IAA NAcb core firing observed ex vivo. Thus, CZX could represent a novel and immediately accessible pharmacotherapeutic intervention for human alcoholism. Key Words: Alcohol intake; intermittent; neuro-adaptation; nucleus accumbens; SK potassium channel

Application of higher order spectra to identify epileptic EEG

Epilepsy is characterized by the spontaneous and seemingly unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic system that detects seizure onsets would allow patients or the people near them to take appropriate precautions, and could provide more insight into this phenomenon. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, we made a comparative study of the performance of Gaussian mixture model (GMM) and Support Vector Machine (SVM) classifiers using the features derived from HOS and from the power spectrum. Results show that the selected HOS based features achieve 93.11% classification accuracy compared to 88.78% with features derived from the power spectrum for a GMM classifier. The SVM classifier achieves an improvement from 86.89% with features based on the power spectrum to 92.56% with features based on the bispectrum.

Osteopenia in a teenage boy presenting with previously undiagnosed guanidinoacetate methyltransferase (GAMT) deficiency and response to creatine supplementation

A 16 y.o. fully ambulant boy born to consanguineous Indian parents, presented for assessment of a fragility femoral neck fracture sustained against a background of autism and moderately severe intellectual disability. He had a past history of infantile eczema, and epilepsy treated with anticonvulsants from 2 to 10 years of age, with no further seizures following cessation of anticonvulsants. He had a thin body habitus (see Table 1) with long fingers and a high arched palate. He had no speech and negligible social interaction, but physical examination was otherwise unremarkable. Positive investigations revealed an undetectable serum creatinine and a urinary metabolic screen which showed an elevated GUA:Phe of 160 (< 36) and a decreased creatinine of 0.3 mmol/l (1.2–29.5) consistent with the diagnosis of guanidinoacetate methyltransferase(GAMT) deficiency. He was commenced on oral creatine 5 g three times daily. Despite improvement in physical activity, height and bone density, there was no discernable improvement in his intellectual functioning. Proton and phosphorous brain and leg magnetic resonance spectroscopy(MRS) was performed at baseline and showed an increased inorganic phosphorus peak and decreased phosphocreatine synthesis in brain and decreased creatine concentration in muscle. Following creatine treatment total brain creatine(1H-MRS) and phosphocreatine/ATP ratio (31P-MRS) content increased to 30% and 60% of control values, respectively. Brain GUA returned to normal levels.

Benign Epilepsy with Centro-temporal Spikes: Spike Triggered fMRI Shows Somato-sensory Cortex Activity

Summary:  Objective: We performed spike triggered functional MRI (fMRI) in a 12 year old girl with Benign Epilepsy with Centro-temporal Spikes (BECTS) and left-sided spikes. Our aim was to demonstrate the cerebral origin of her interictal spikes. Methods: EEG was recorded within the 3 Tesla MRI. Whole brain fMRI images were acquired, beginning 2–3 seconds after spikes. Baseline fMRI images were acquired when there were no spikes for 20 seconds. Image sets were compared with the Student's t-test. Results: Ten spike and 20 baseline brain volumes were analysed. Focal activiation was seen in the inferior left sensorimotor cortex near the face area. The anterior cingulate was more active during baseline than spikes. Conclusions: Left sided epileptiform activity in this patient with BECTS is associated with fMRI activation in the left face region of the somatosensory cortex, which would be consistent with the facial sensorimotor involvement in BECT seizures. The presence of BOLD signal change in other regions raises the possibility that the scalp recorded field of this patient with BECTs may reflect electrical change in more than one brain region.

Neurological drugs and opioids for pain management

20.1 Epilepsy and an introduction to drugs used to treat 20.1.1 Introduction to epilepsy 20.1.2 Treatment of partial seizures 20.1.3 Treatment of generalised seizures 20.1.4 Treatment of status epilepticus 20.2 Neurodegenerative disorders; principles of treatment 20.2.1 Introduction to neurodegenerative disorders 20.2.2 Parkinson’s disease 20.2.2.1 Introduction to Parkinson’s disease 20.2.2.2 Dopaminergic system 20.2.2.3 Treatment to enhance the dopaminergic system 20.2.2.4 Treatment to inhibit the cholinergic system 20.2.3 Dementia/Alzheimer’s disease 20.2.3.1 Introduction to Alzheimer’s disease 20.2.3.2 Treatment of Alzheimer’s disease 20.2.4 Amyotrophic lateral sclerosis 43.4.1 Introduction 43.4.2 Treatment 20.3. Pain and opioid analgesics 20.3.1 Introduction to pain and analgesia 20.3.2 Introduction to opioids 20.3.3 Tolerance and physical dependence 20.3.4 Effects of opioids 20.3.5 Agonists at opioid μ receptors 20.3.6 Toxicity to opioids This section deals with the neurologic drugs. The neurologic drugs are used to treat epilepsy and neurodegenerative diseases such as Parkinson’s disease and Alzheimer’s disease. The opioids for pain management are also discussed in this section.