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:IntroductionElectroencephalographic (EEG) data quality is severely compromised when recorded inside the magnetic resonance (MR) environment. Here we characterized the impact of the ballistocardiographic (BCG) artifact on resting-state EEG spectral properties and compared the effectiveness of seven common BCG correction methods to preserve EEG spectral features. We also assessed if these methods retained posterior alpha power reactivity to an eyes closure-opening (EC-EO) task and compared the results from EEG-informed fMRI analysis using different BCG correction approaches.MethodElectroencephalographic data from 20 healthy young adults were recorded outside the MR environment and during simultaneous fMRI acquisition. The gradient artifact was effectively removed from EEG-fMRI acquisitions using Average Artifact Subtraction (AAS). The BCG artifact was corrected with seven methods: AAS, Optimal Basis Set (OBS), Independent Component Analysis (ICA), OBS followed by ICA, AAS followed by ICA, PROJIC-AAS and PROJIC-OBS. EEG signal preservation was assessed by comparing the spectral power of traditional frequency bands from the corrected rs-EEG-fMRI data with the data recorded outside the scanner. We then assessed the preservation of posterior alpha functional reactivity by computing the ratio between the EC and EO conditions during the EC-EO task. EEG-informed fMRI analysis of the EC-EO task was performed using alpha power-derived BOLD signal predictors obtained from the EEG signals corrected with different methods.ResultsThe BCG artifact caused significant distortions (increased absolute power, altered relative power) across all frequency bands. Artifact residuals/signal losses were present after applying all correction methods. The EEG reactivity to the EC-EO task was better preserved with ICA-based correction approaches, particularly when using ICA feature extraction to isolate alpha power fluctuations, which allowed to accurately predict hemodynamic signal fluctuations during the EEG-informed fMRI analysis.DiscussionCurrent software solutions for the BCG artifact problem offer limited efficiency to preserve the EEG spectral power properties using this particular EEG setup. The state-of-the-art approaches tested here can be further refined and should be combined with hardware implementations to better preserve EEG signal properties during simultaneous EEG-fMRI. Existing and novel BCG artifact correction methods should be validated by evaluating signal preservation of both ERPs and spontaneous EEG spectral power.

Project description:ImportanceTransient global amnesia (TGA) is usually considered a benign event with a low recurrence rate. However, recurrence rates vary considerably among studies and there are no known risk factors for TGA.ObjectiveTo examine risk factors for the recurrence of TGA.Design, setting, and participantsThis retrospective cohort study involved medical record review of patients with isolated or recurrent TGA presenting to the Mayo Clinic in Rochester, Minnesota, between August 1, 1992, and February 28, 2018. A total of 1491 cases were reviewed and 1044 met diagnostic inclusion criteria for TGA, with the remainder excluded owing to indeterminate or alternate diagnoses or limited information available in the medical record.ExposuresSingle vs recurrent episodes of TGA.Main outcomes and measuresDemographics, precipitating factors, migraine history, imaging and electrodiagnostic findings, and family history of TGA were collected. The main outcome measure was TGA recurrence.ResultsOf 1044 included patients, 575 (55.1%) were male, and the mean (SD) age at inclusion was 75.0 (11.5) years. A total of 901 patients (86.3%) had a single episode of TGA and 143 (13.7%) had recurrent episodes of TGA. The 2 groups were similar in age at inclusion, sex, identifiable triggers, and duration of anterograde amnesia. The number of recurrences ranged from 1 to 9, with 137 individuals (95.8%) having 3 or fewer recurrences. The mean (SD) age at first episode of TGA was 65.2 (10.0) years for individuals with a single episode vs 58.8 (10.3) years for those with recurrent episodes (P < .001). There was a personal history of migraine in 180 individuals (20.0%) with a single episode of TGA and 52 individuals (36.4%) with recurrent episodes of TGA (P < .001), and a family history of migraine in 167 individuals (18.5%) with a single episode of TGA and 44 individuals (30.8%) with recurrent episodes of TGA (P = .001). There were no electroencephalographic findings associated with increased risk of TGA recurrence. Acute and subacute temporal lobe abnormalities on results of magnetic resonance imaging were seen rarely and did not require intervention. A family history of TGA was identified in 12 individuals (1.3%) with a single episode of TGA and 4 individuals (2.8%) with recurrent episodes of TGA.Conclusions and relevanceThis study suggests that, in this large cohort of patients with TGA, recurrent TGA was associated with earlier age at the time of first TGA episode and higher prevalence of both personal and family history of migraine compared with isolated cases. These results can be used to counsel patients about risks of recurrence and may have implications for the understanding of TGA pathophysiology.

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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