Dataset Information

Power Spectral Differences between Transient Epileptic and Global Amnesia: An eLORETA Quantitative EEG Study.

ABSTRACT: Transient epileptic amnesia (TEA) is a rare epileptic condition, often confused with transient global amnesia (TGA). In a real-life scenario, differential diagnosis between these two conditions can be hard. In this study we use power spectral analysis empowered by exact Low Resolution Brain Electromagnetic Tomography (eLORETA) to evidence the differences between TEA and TGA. Fifteen patients affected by TEA (64.2 ± 5.2 y.o.; 11 female/4 male; 10 left and 5 right temporal epileptic focus) and 15 patients affected by TGA (65.8 ± 7.2 y.o.; 11 females/4 males) were retrospectively identified in our clinical records. All patients recorded EEGs after symptoms offset. EEGs were analyzed with eLORETA to evidence power spectral contrast between the two conditions. We used an inverse problem solution to localize the source of spectral differences. We found a significant increase in beta band power over the affected hemisphere of TEA patients. Significant results corresponded to the uncus and para-hippocampal gyrus, respectively Brodmann's Areas: 36, 35, 28, 34. We present original evidence of an increase in beta power in the affected hemisphere (AH) of TEA as compared to TGA. These differences involve key areas of the memory network located in the mesial temporal lobe. Spectral asymmetries could be used in the future to recognize cases of amnesia with a high risk of epilepsy.

SUBMITTER: Lanzone J

PROVIDER: S-EPMC7563784 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Power Spectral Differences between Transient Epileptic and Global Amnesia: An eLORETA Quantitative EEG Study.

Lanzone Jacopo J Imperatori Claudio C Assenza Giovanni G Ricci Lorenzo L Farina Benedetto B Di Lazzaro Vincenzo V Tombini Mario M

Brain sciences 20200906 9

Transient epileptic amnesia (TEA) is a rare epileptic condition, often confused with transient global amnesia (TGA). In a real-life scenario, differential diagnosis between these two conditions can be hard. In this study we use power spectral analysis empowered by exact Low Resolution Brain Electromagnetic Tomography (eLORETA) to evidence the differences between TEA and TGA. Fifteen patients affected by TEA (64.2 ± 5.2 y.o.; 11 female/4 male; 10 left and 5 right temporal epileptic focus) and 15 ...[more]

PMID: 32899970

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Project description:There has been a growing interest in computational electroencephalogram (EEG) signal processing in a diverse set of domains, such as cortical excitability analysis, event-related synchronization, or desynchronization analysis. In recent years, several inconsistencies were found across different EEG studies, which authors often attributed to methodological differences. However, the assessment of such discrepancies is deeply underexplored. It is currently unknown if methodological differences can fully explain emerging differences and the nature of these differences. This study aims to contrast widely used methodological approaches in EEG processing and compare their effects on the outcome variables. To this end, two publicly available datasets were collected, each having unique traits so as to validate the results in two different EEG territories. The first dataset included signals with event-related potentials (visual stimulation) from 45 subjects. The second dataset included resting state EEG signals from 16 subjects. Five EEG processing steps, involved in the computation of power and phase quantities of EEG frequency bands, were explored in this study: artifact removal choices (with and without artifact removal), EEG signal transformation choices (raw EEG channels, Hjorth transformed channels, and averaged channels across primary motor cortex), filtering algorithms (Butterworth filter and Blackman-Harris window), EEG time window choices (-750 ms to 0 ms and -250 ms to 0 ms), and power spectral density (PSD) estimation algorithms (Welch's method, Fast Fourier Transform, and Burg's method). Powers and phases estimated by carrying out variations of these five methods were analyzed statistically for all subjects. The results indicated that the choices in EEG transformation and time-window can strongly affect the PSD quantities in a variety of ways. Additionally, EEG transformation and filter choices can influence phase quantities significantly. These results raise the need for a consistent and standard EEG processing pipeline for computational EEG studies. Consistency of signal processing methods cannot only help produce comparable results and reproducible research, but also pave the way for federated machine learning methods, e.g., where model parameters rather than data are shared.

Project description:OBJECTIVE:While olfactory hallucinations are relatively rare in epilepsy, a high prevalence (up to 42%) has been reported in one form - Transient Epileptic Amnesia (TEA). TEA is characterized by recurring amnestic seizures and is commonly associated with persistent interictal memory deficits. Despite reports of changes in smell, olfactory ability has not been objectively assessed in this group. The aim of this study was to measure olfactory ability in patients with TEA and explore whether olfactory symptoms relate to other clinical variables. METHODS:Fifty-five participants with TEA were recruited from The Impairment of Memory in Epilepsy project database. The presence of olfactory symptoms was obtained via case notes and clinical interview. Participants completed questionnaires to evaluate their olfaction and memory function subjectively. Olfactory ability was measured using the University of Pennsylvania Smell Identification Test (UPSIT). TEA participants' performance was compared to 50 matched healthy control participants. A subset of TEA participants (n=26) also completed a battery of memory tests including standard neuropsychological measures, and assessment of accelerated long-term forgetting and autobiographical memory. RESULTS:Olfactory hallucinations were reported in 55% of patients with TEA. A significant reduction in smell identification (UPSIT) was found between patients with TEA and healthy controls (p<0.001). Epilepsy variables, including history of olfactory hallucinations, were not predictive of olfactory ability. Patients reported ongoing memory difficulties and performed below normative values on objective tests. While no correlation was found between objective measures of memory and olfactory performance, subjective complaints of route finding difficulty was associated with UPSIT score. CONCLUSIONS:Impairments in odor identification are common in patients with TEA and exceed changes that occur in normal aging. Olfactory hallucinations occurs in approximately half of patients with TEA, but do not always coincide with reduced sense of smell. Olfactory impairment and interictal memory problems both occur frequently in TEA but are not closely associated.

Dataset Information

Power Spectral Differences between Transient Epileptic and Global Amnesia: An eLORETA Quantitative EEG Study.

Publications

Power Spectral Differences between Transient Epileptic and Global Amnesia: An eLORETA Quantitative EEG Study.

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