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.

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.

Investigation of the role of the GABRG2 gene variant in migraine

Migraine is the most common neurological disorder worldwide affecting about 12% of the worldwide population. This disorder has been classed into two main types of migraine—with and without aura. While a number of factors can influence the onset of migraine, a major factor is that of genetics. The GABAA gene encodes for the GABAA receptor. Along with other receptors, the GABAA receptor is involved in the mediation of neuronal activities. In this study, a GABRG2 gene (GABAA receptor gamma-2-subunit) SNP (rs211037) was genotyped on a migraine case–control population of 546 (273 affected and an equal number of healthy) individuals. Using specifically designed primers, a high resolution melt (HRM) assay was carried out in the genotyping process. After genotyping, results were compared in the case and control populations. Analysis of results showed no significant differences in the allele frequencies between case and control populations. Similarly no differences were detected for subtypes or for a specific gender of migraine (p > 0.05). Although this gene has been previously found to be involved in febrile seizures and there is some co-morbidity between epilepsy and migraine, we decided to investigate this marker for involvement in migraine. The results did not support a role for the tested GABRG2 variant in migraine.

The effectiveness of health education using the teach-back method on adherence and self-management in chronic disease: A systematic review protocol

Review question/objective What is the effect of using the teach-back method for health education to improve adherence to treatment regimen and self-management in chronic disease? Inclusion criteria Types of participants This review will consider all studies that include adult patients (aged 18 years and over) in any healthcare setting, either as inpatients (eg acute care, medical and surgical wards) or those who attend primary health care, family medical practice, general medical practice, clinics, outpatient departments, rehabilitation or community settings. Participants need to have been diagnosed as having one or more chronic diseases including heart failure, diabetes, cardiovascular disease, cancer, respiratory disease, asthma, chronic obstructive pulmonary disease, chronic kidney disease, arthritis, epilepsy or a mental health condition. Studies that include seriously ill patients, and/or those who have impairments in verbal communication and cognitive function will be excluded. Types of intervention This review will consider studies that investigate the use of the teach-back method alone or in combination with other supporting education, either in routine or research intervention education programs; regardless of how long the programs were and whether or not a follow-up was conducted. The intervention could be delivered by any healthcare professional. The comparator will be any health education for chronic disease that does not include the teach-back method. Types of outcomes Primary outcomes of interest are disease-specific knowledge, adherence, and self-management knowledge, behavior and skills measured using patient report, nursing observation or validated measurement scales. Secondary outcomes include knowledge retention, self-efficacy, hospital readmission, hospitalization, and quality of life, also measured using patient report, nursing observation, hospital records or validated measurement scales.

Lying in all honesty : capturing truth in women’s confessional memoir

This paper explores the slippery nature of illness and diagnosis in Lauren Slater’s memoir, Lying: a Metaphorical Memoir (2000). Speaking from the shadowy intersection of childhood and adolescence, Slater’s narrator, Lauren, uses the metaphor of epilepsy to describe her own predilection for exaggeration. In exploiting the fallibility of the first-person narrator, Slater insists on the legitimacy of metaphor in accounts of childhood illness that are more concerned with narrative truth than historical accuracy. The result of this playfulness and general misrule is that Slater writes herself into a double bind: on one side, she is the child narrator who inadvertently misrepresents events and misdirects readers, and on the other side, she is the untrustworthy author who employs metaphor as a licence to lie.

Medial temporal lobe roles in human path integration

Path integration is a process in which observers derive their location by integrating self-motion signals along their locomotion trajectory. Although the medial temporal lobe (MTL) is thought to take part in path integration, the scope of its role for path integration remains unclear. To address this issue, we administered a variety of tasks involving path integration and other related processes to a group of neurosurgical patients whose MTL was unilaterally resected as therapy for epilepsy. These patients were unimpaired relative to neurologically intact controls in many tasks that required integration of various kinds of sensory self-motion information. However, the same patients (especially those who had lesions in the right hemisphere) walked farther than the controls when attempting to walk without vision to a previewed target. Importantly, this task was unique in our test battery in that it allowed participants to form a mental representation of the target location and anticipate their upcoming walking trajectory before they began moving. Thus, these results put forth a new idea that the role of MTL structures for human path integration may stem from their participation in predicting the consequences of one's locomotor actions. The strengths of this new theoretical viewpoint are discussed.

Memory and Epileptogenesis in Complex Biological and Simulated Systems

Oscillations of neural activity may bind widespread cortical areas into a neural representation that encodes disparate aspects of an event. In order to test this theory we have turned to data collected from complex partial epilepsy (CPE) patients with chronically implanted depth electrodes. Data from regions critical to word and face information processing was analyzed using spectral coherence measurements. Similar analyses of intracranial EEG (iEEG) during seizure episodes display HippoCampal Formation (HCF)—NeoCortical (NC) spectral coherence patterns that are characteristic of specific seizure stages (Klopp et al. 1996). We are now building a computational memory model to examine whether spatio-temporal patterns of human iEEG spectral coherence emerge in a computer simulation of HCF cellular distribution, membrane physiology and synaptic connectivity. Once the model is reasonably scaled it will be used as a tool to explore neural parameters that are critical to memory formation and epileptogenesis.

Identification of common variants associated with human hippocampal and intracranial volumes

Identifying genetic variants influencing human brain structures may reveal new biological mechanisms underlying cognition and neuropsychiatric illness. The volume of the hippocampus is a biomarker of incipient Alzheimer's disease and is reduced in schizophrenia, major depression and mesial temporal lobe epilepsy. Whereas many brain imaging phenotypes are highly heritable, identifying and replicating genetic influences has been difficult, as small effects and the high costs of magnetic resonance imaging (MRI) have led to underpowered studies. Here we report genome-wide association meta-analyses and replication for mean bilateral hippocampal, total brain and intracranial volumes from a large multinational consortium. The intergenic variant rs7294919 was associated with hippocampal volume (12q24.22; N = 21,151; P = 6.70 × 10 -16) and the expression levels of the positional candidate gene TESC in brain tissue. Additionally, rs10784502, located within HMGA2, was associated with intracranial volume (12q14.3; N = 15,782; P = 1.12 × 10 -12). We also identified a suggestive association with total brain volume at rs10494373 within DDR2 (1q23.3; N = 6,500; P = 5.81 × 10 -7).

Mapping cortical change in Alzheimer's disease, brain development, and schizophrenia

This paper describes algorithms that can identify patterns of brain structure and function associated with Alzheimer's disease, schizophrenia, normal aging, and abnormal brain development based on imaging data collected in large human populations. Extraordinary information can be discovered with these techniques: dynamic brain maps reveal how the brain grows in childhood, how it changes in disease, and how it responds to medication. Genetic brain maps can reveal genetic influences on brain structure, shedding light on the nature-nurture debate, and the mechanisms underlying inherited neurobehavioral disorders. Recently, we created time-lapse movies of brain structure for a variety of diseases. These identify complex, shifting patterns of brain structural deficits, revealing where, and at what rate, the path of brain deterioration in illness deviates from normal. Statistical criteria can then identify situations in which these changes are abnormally accelerated, or when medication or other interventions slow them. In this paper, we focus on describing our approaches to map structural changes in the cortex. These methods have already been used to reveal the profile of brain anomalies in studies of dementia, epilepsy, depression, childhood- and adult-onset schizophrenia, bipolar disorder, attention-deficit/hyperactivity disorder, fetal alcohol syndrome, Tourette syndrome, Williams syndrome, and in methamphetamine abusers. Specifically, we describe an image analysis pipeline known as cortical pattern matching that helps compare and pool cortical data over time and across subjects. Statistics are then defined to identify brain structural differences between groups, including localized alterations in cortical thickness, gray matter density (GMD), and asymmetries in cortical organization. Subtle features, not seen in individual brain scans, often emerge when population-based brain data are averaged in this way. Illustrative examples are presented to show the profound effects of development and various diseases on the human cortex. Dynamically spreading waves of gray matter loss are tracked in dementia and schizophrenia, and these sequences are related to normally occurring changes in healthy subjects of various ages.