- The Characteristics and Long-Term Course of Epilepsy in Lipoid Proteinosis: A Spectrum From Mild to Severe Seizures in Relation to ECM1 Mutations. [Journal Article]
- CEClin EEG Neurosci 2017 Apr 01; :1550059417705280
- Lipoid proteinosis (LP) is a rare autosomal recessive disease characterized by deposition of hyaline material in skin and mucosae. Epilepsy, as an extracutaneous manifestation associated with typical...
Lipoid proteinosis (LP) is a rare autosomal recessive disease characterized by deposition of hyaline material in skin and mucosae. Epilepsy, as an extracutaneous manifestation associated with typical mesial temporal calcifications, has already been identified, but its characteristics and long-term prognosis have not been thoroughly investigated. We included 7 consecutive patients with LP with typical intracranial calcifications out of 16 patients with ECM1 mutations and investigated the semiologic features, ictal and interictal EEG findings, and long-term prognosis of epilepsy in this genodermatosis. Four of them had seizures (57.1%), and focal seizures with motionless staring were the most common seizure phenotype, originating from bilateral mesial temporal areas, but interictal spikes were scant. Auras were observed in three patients, mostly as epigastric sensation and déjà vu, which indicated mesial temporal lobe origin. Three patients with homozygous mutations in sixth and seventh exons of the ECM1 gene had a drug-resistant course at the end of long-term follow-up. Molecular genetic testing showed a rare compound heterozygous mutation in one patient, which was also associated with seizures but without drug-resistance. Our findings indicated a spectrum for epilepsy with a desperate drug-resistant course for decades in most patients with LP, which is still an underrecognized disease by neurologists.
- Electroencephalographic Correlates of Suicidal Ideation in the Theta Band. [Journal Article]
- CEClin EEG Neurosci 2017 Feb 01; :1550059417692083
- Previous studies have indicated that the abnormalities of brain activity are associated with suicidal behavior. However, few studies have explored neurophysiologic biomarkers of suicidal ideation (SI...
Previous studies have indicated that the abnormalities of brain activity are associated with suicidal behavior. However, few studies have explored neurophysiologic biomarkers of suicidal ideation (SI) in healthy subjects. Here, we studied alterations of theta quantitative EEG (QEEG) in frontal regions associated with SI in young healthy subjects. Resting QEEG data were recorded from 90 young healthy subjects. The subjects were divided into two group based on Scale for Suicidal Ideation (SSI) scores: a high SSI group (n = 33) and a low SSI group (n = 57). Individual frontal electrodes (Fp1, Fp2, F7, F3, Fz, F4, F8) and central midline electrodes (FCz, Cz) were examined for absolute and relative power in the theta band. Clinical state and social support was assessed using the Hospital Anxiety and Depression Scale and Functional Social Support Questionnaire. We found that theta absolute and relative power in all channels was positively correlated with SSI, except Fp1, F7 and F8. The high SSI group showed higher theta relative power at F3, Fz, FCz, and Cz than the low SSI group. Theta relative power in the fronto-central region was significantly increased in the high SSI group compared to that in the low SSI group. Hierarchical regression analysis showed that SSI score was the most powerful predictor of fronto-central theta power. The findings suggest that brain electrical activity at the fronto-central region may be associated with differences in SI in young healthy subjects. EEG activity in theta band has clinical potential as a biomarker for preventing suicide.
- Frontal Intermittent Rhythmic Delta Activity (FIRDA) in the Neurological Intensive Care. [Journal Article]
- CEClin EEG Neurosci 2017 Jan 01; :1550059416688108
- CONCLUSIONS: FIRDA is more commonly encountered in the neurocritical care setting as compared with outpatient EEG clinics. Our findings in stroke patients indicate that involved vascular territories may be related to the generation of FIRDA.
- Abstracts of Presentations at the Joint Meeting of the EEG & Clinical Neuroscience Society (ECNS), the International Society for Brain Electromagnetic Topography (ISBET), and the International Society for Neuroimaging in Psychiatry (ISNIP) in Halifax, Nova Scotia, Canada, September 3-7, 2014. [Congresses]
- CEClin EEG Neurosci 2016; 47(4):NP1-NP15
- Local and Widely Distributed EEG Activity in Schizophrenia With Prevalence of Negative Symptoms. [Journal Article]
- CEClin EEG Neurosci 2017 Jan 01; :1550059416683283
- We evaluated EEG frequency abnormalities in resting state (eyes closed and eyes open) EEG in a group of chronic schizophrenia patients as compared with healthy subjects. The study included 3 methods ...
We evaluated EEG frequency abnormalities in resting state (eyes closed and eyes open) EEG in a group of chronic schizophrenia patients as compared with healthy subjects. The study included 3 methods of analysis of deviation of EEG characteristics: genuine EEG, current source density (CSD), and group independent component (gIC). All 3 methods have shown that the EEG in schizophrenia patients is characterized by enhanced low-frequency (delta and theta) and high-frequency (beta) activity in comparison with the control group. However, the spatial pattern of differences was dependent on the type of method used. Comparative analysis has shown that increased EEG power in schizophrenia patients apparently concerns both widely spatially distributed components and local components of signal. Furthermore, the observed differences in the delta and theta range can be described mainly by the local components, and those in the beta range mostly by spatially widely distributed ones. The possible nature of the widely distributed activity is discussed.
- Application and Evaluation of Independent Component Analysis Methods to Generalized Seizure Disorder Activities Exhibited in the Brain. [Journal Article]
- CEClin EEG Neurosci 2016 Nov 11
- EEG records the spontaneous electrical activity of the brain using multiple electrodes placed on the scalp, and it provides a wealth of information related to the functions of brain. Nevertheless, th...
EEG records the spontaneous electrical activity of the brain using multiple electrodes placed on the scalp, and it provides a wealth of information related to the functions of brain. Nevertheless, the signals from the electrodes cannot be directly applied to a diagnostic tool like brain mapping as they undergo a "mixing" process because of the volume conduction effect in the scalp. A pervasive problem in neuroscience is determining which regions of the brain are active, given voltage measurements at the scalp. Because of which, there has been a surge of interest among the biosignal processing community to investigate the process of mixing and unmixing to identify the underlying active sources. According to the assumptions of independent component analysis (ICA) algorithms, the resultant mixture obtained from the scalp can be closely approximated by a linear combination of the "actual" EEG signals emanating from the underlying sources of electrical activity in the brain. As a consequence, using these well-known ICA techniques in preprocessing of the EEG signals prior to clinical applications could result in development of diagnostic tool like quantitative EEG which in turn can assist the neurologists to gain noninvasive access to patient-specific cortical activity, which helps in treating neuropathologies like seizure disorders. The popular and proven ICA schemes mentioned in various literature and applications were selected (which includes Infomax, JADE, and SOBI) and applied on generalized seizure disorder samples using EEGLAB toolbox in MATLAB environment to see their usefulness in source separations; and they were validated by the expert neurologist for clinical relevance in terms of pathologies on brain functionalities. The performance of Infomax method was found to be superior when compared with other ICA schemes applied on EEG and it has been established based on the validations carried by expert neurologist for generalized seizure and its clinical correlation. The results are encouraging for furthering the studies in the direction of developing useful brain mapping tools using ICA methods.
- Toward an Attention-Based Diagnostic Tool for Patients With Locked-in Syndrome. [Journal Article]
- CEClin EEG Neurosci 2016 Nov 07
- Electroencephalography (EEG) has been proposed as a supplemental tool for reducing clinical misdiagnosis in severely brain-injured populations helping to distinguish conscious from unconscious patien...
Electroencephalography (EEG) has been proposed as a supplemental tool for reducing clinical misdiagnosis in severely brain-injured populations helping to distinguish conscious from unconscious patients. We studied the use of spectral entropy as a measure of focal attention in order to develop a motor-independent, portable, and objective diagnostic tool for patients with locked-in syndrome (LIS), answering the issues of accuracy and training requirement. Data from 20 healthy volunteers, 6 LIS patients, and 10 patients with a vegetative state/unresponsive wakefulness syndrome (VS/UWS) were included. Spectral entropy was computed during a gaze-independent 2-class (attention vs rest) paradigm, and compared with EEG rhythms (delta, theta, alpha, and beta) classification. Spectral entropy classification during the attention-rest paradigm showed 93% and 91% accuracy in healthy volunteers and LIS patients respectively. VS/UWS patients were at chance level. EEG rhythms classification reached a lower accuracy than spectral entropy. Resting-state EEG spectral entropy could not distinguish individual VS/UWS patients from LIS patients. The present study provides evidence that an EEG-based measure of attention could detect command-following in patients with severe motor disabilities. The entropy system could detect a response to command in all healthy subjects and LIS patients, while none of the VS/UWS patients showed a response to command using this system.
- Serial EEG Monitoring in a Patient With Anti-NMDA Receptor Encephalitis. [Journal Article]
- CEClin EEG Neurosci 2016 Nov 07
- Electroencephalogram (EEG) abnormalities are very common in anti-N-methyl-d-aspartate receptor (anti-NMDAR) encephalitis. Extreme delta brush (EDB) is a distinctive EEG pattern that is can be suggest...
Electroencephalogram (EEG) abnormalities are very common in anti-N-methyl-d-aspartate receptor (anti-NMDAR) encephalitis. Extreme delta brush (EDB) is a distinctive EEG pattern that is can be suggestive of the diagnosis; however, the etiology of the EDB remains unclear. Furthermore, there is question with regard to its ictal or interictal nature. We report a 20-year-old woman with anti-NMDAR encephalitis whose serial video-EEG monitoring was obtained at 2, 2.5, 4, and 6 months after admission. There was a long-standing EDB lasting up to several hours, with no evolution in frequency, amplitude, or morphology, and without clear association her frequent orofacial dyskinesia. Intravenous benzodiazepine administrations did not change the EDB pattern. As her clinical symptoms improved, the EDB gradually became less prominent and less frequent, with complete resolution at 6 months after admission. These findings suggest that EDB is more likely a marker of the severity of the disease in contrast to an epileptic seizure and is useful for diagnosis and monitoring of treatment response in conjunction with clinical improvement.
- Frederic Andrews Gibbs, M.D., EEG Pioneer. [Historical Article]
- CEClin EEG Neurosci 2016; 47(4):255-259
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- Beta Responses in Healthy Elderly and in Patients With Amnestic Mild Cognitive Impairment During a Task of Temporal Orientation of Attention. [Journal Article]
- CEClin EEG Neurosci 2016 Nov 02
- Recent studies demonstrated that beta oscillations are elicited during cognitive processes. To investigate their potential as electrophysiological markers of amnestic mild cognitive impairment (aMCI)...
Recent studies demonstrated that beta oscillations are elicited during cognitive processes. To investigate their potential as electrophysiological markers of amnestic mild cognitive impairment (aMCI), we recorded beta EEG activity during resting and during an omitted tone task in patients and healthy elderly. Thirty participants were enrolled (15 patients, 15 healthy controls). In particular, we investigated event-related spectral perturbation and intertrial coherence indices. Analyses showed that (a) healthy elderly presented greater beta power at rest than patients with aMCI patients; (b) during the task, healthy elderly were more accurate than aMCI patients and presented greater beta power than aMCI patients; (c) both groups showed qualitatively similar spectral perturbation responses during the task, but different spatiotemporal response patterns; and (d) aMCI patients presented greater beta phase locking than healthy elderly during the task. Results indicate that beta activity in healthy elderly differs from that of patients with aMCI. Furthermore, the analysis of task-related EEG activity extends evidences obtained during resting and suggests that during the prodromal phase of Alzheimer's disease there is a reduced efficiency in information exchange by large-scale neural networks. The study for the first time shows the potential of task-related beta responses as early markers of aMCI impairments.