Independent Component Analysis in the Study of Focal Seizures

Estimation of seizure onset zone from ictal scalp EEG using independent component analysis in extratemporal lobe epilepsy

OBJECTIVE

The purpose of this study is to localize the seizure onset zone of patients suffering from drug-resistant epilepsy. During the last two decades, multiple studies proposed the use of Independent Component Analysis (ICA) to analyze ictal electroencephalogram (EEG) recordings. This study aims at evaluating ICA potential with quantitative measurements. In particular, we address the challenging step where the components extracted by ICA of an ictal nature must be selected.

APPROACH

We considered a cohort of 10 patients suffering from extratemporal lobe epilepsy who were rendered seizure-free after surgery. Different sets of pre-processing parameters were compared and component features were explored to help distinguish ictal components from others. Quantitative measurements were implemented to determine whether some of the components returned by ICA were located within the resection zone and thus likely to be ictal. Finally, an assistance to the component selection was proposed based on the implemented features.

MAIN RESULTS

For every seizure, at least one component returned by ICA was localized within the resection zone, with the optimal pre-processing parameters. Three features were found to distinguish components localized within the resection zone: the dispersion of their active brain sources, the ictal rhythm power and the contribution to the EEG variance. Using the implemented component selection assistance based on the features, the probability that the first proposed component yields an accurate estimation reaches 51.43% (without assistance: 24.74%). The accuracy reaches 80% when considering the best result within the first five components.

SIGNIFICANCE

This study confirms the utility of ICA for ictal EEG analysis in extratemporal lobe epilepsy, and suggests relevant features to analyze the components returned by ICA. A component selection assistance is proposed to guide clinicians in their choice for ictal components.

Spatio-temporal dynamics of interictal activity in musicogenic epilepsy: Two case reports and a systematic review of the literature

OBJECTIVE

To explore neurophysiological features of musicogenic epilepsy (ME), discussing experimental findings in the framework of a systematic review on ME.

METHODS

Two patients with ME underwent high-density-electroencephalography (hd-EEG) while listening to ictogenic songs. In one case, musicogenic seizures were elicited. Independent component analysis (ICA) was applied to hd-EEG, and components hosting interictal and ictal elements were identified and localized. Finally, the temporal dynamics of spike-density was studied relative to seizures. All findings were compared against the results of a systematic review on ME, collecting 131 cases.

RESULTS

Interictal spikes appeared isolated in specific fronto-temporal independent components, whose cortical generators were located in the anterior temporal and inferior frontal lobe. In the patient undergoing seizure, ictal discharge relied in the same component, with the interictal spike-density decreasing before the seizure onset.

CONCLUSION

Our study shows how ICA can isolate neurophysiological features of ictal and interictal discharges in ME, highlighting a fronto-temporal localization and a suppression of spike-density preceding the seizure onset.

SIGNIFICANCE

While the localization of ME activity could indicate which aspect within the musical stimulus might trigger musicogenic seizures for each patient, the study of ME dynamics could contribute to the development of models for seizure-prediction and their validation.

Resting State EEG in Children With Learning Disabilities: An Independent Component Analysis Approach

In this study, the neurophysiological underpinnings of learning disabilities (LD) in children are examined using resting state EEG. We were particularly interested in the neurophysiological differences between children with learning disabilities not otherwise specified (LD-NOS), learning disabilities with verbal disabilities (LD-Verbal), and healthy control (HC) children. We applied 2 different approaches to examine the differences between the different groups. First, we calculated theta/beta and theta/alpha ratios in order to quantify the relationship between slow and fast EEG oscillations. Second, we used a recently developed method for analyzing spectral EEG, namely the group independent component analysis (gICA) model. Using these measures, we identified substantial differences between LD and HC children and between LD-NOS and LD-Verbal children in terms of their spectral EEG profiles. We obtained the following findings: (a) theta/beta and theta/alpha ratios were substantially larger in LD than in HC children, with no difference between LD-NOS and LD-Verbal children; (b) there was substantial slowing of EEG oscillations, especially for gICs located in frontal scalp positions, with LD-NOS children demonstrating the strongest slowing; (c) the estimated intracortical sources of these gICs were mostly located in brain areas involved in the control of executive functions, attention, planning, and language; and (d) the LD-Verbal children demonstrated substantial differences in EEG oscillations compared with LD-NOS children, and these differences were localized in language-related brain areas. The general pattern of atypical neurophysiological activation found in LD children suggests that they suffer from neurophysiological dysfunction in brain areas involved with the control of attention, executive functions, planning, and language functions. LD-Verbal children also demonstrate atypical activation, especially in language-related brain areas. These atypical neurophysiological activation patterns might provide a helpful guide for rehabilitation strategies to treat the deficiencies in these children with LD.

Mechanisms Responsible for Cognitive Impairment in Epilepsy

Epilepsy is often associated with cognitive and behavioral impairments that can have profound impact on the quality of life of patients. Although the mechanisms of cognitive impairment are not completely understood, we make an attempt to describe, from a systems perspective, how information processing is affected in epilepsy disorders. The aim of this review is to (1) define the nature of cognitive deficits associated with epilepsy, (2) review fundamental systems-level mechanisms underlying information processing, and (3) describe how information processing is dysfunctional in epilepsy and investigate the relative contributions of etiology, seizures, and interictal discharges (IDs). We conclude that these mechanisms are likely to be important and deserve more detailed scrutiny in the future.

Mapping interictal epileptic discharges using mutual information between concurrent EEG and fMRI

OBJECTIVE

The mapping of haemodynamic changes related to interictal epileptic discharges (IED) in simultaneous electroencephalography (EEG) and functional MRI (fMRI) studies is usually carried out by means of EEG-correlated fMRI analyses where the EEG information specifies the model to test on the fMRI signal. The sensitivity and specificity critically depend on the accuracy of EEG detection and the validity of the haemodynamic model. In this study we investigated whether an information theoretic analysis based on the mutual information (MI) between the presence of epileptic activity on EEG and the fMRI data can provide further insights into the haemodynamic changes related to interictal epileptic activity. The important features of MI are that: 1) both recording modalities are treated symmetrically; 2) no requirement for a-priori models for the haemodynamic response function, or assumption of a linear relationship between the spiking activity and BOLD responses, and 3) no parametric model for the type of noise or its probability distribution is necessary for the computation of MI.

METHODS

Fourteen patients with pharmaco-resistant focal epilepsy underwent EEG-fMRI and intracranial EEG and/or surgical resection with positive postoperative outcome (seizure freedom or considerable reduction in seizure frequency) was available in 7/14 patients. We used nonparametric statistical assessment of the MI maps based on a four-dimensional wavelet packet resampling method. The results of MI were compared to the statistical parametric maps obtained with two conventional General Linear Model (GLM) analyses based on the informed basis set (canonical HRF and its temporal and dispersion derivatives) and the Finite Impulse Response (FIR) models.

RESULTS

The MI results were concordant with the electro-clinically or surgically defined epileptogenic area in 8/14 patients and showed the same degree of concordance as the results obtained with the GLM-based methods in 12 patients (7 concordant and 5 discordant). In one patient, the information theoretic analysis improved the delineation of the irritative zone compared with the GLM-based methods.

DISCUSSION

Our findings suggest that an information theoretic analysis can provide clinically relevant information about the BOLD signal changes associated with the generation and propagation of interictal epileptic discharges. The concordance between the MI, GLM and FIR maps support the validity of the assumptions adopted in GLM-based analyses of interictal epileptic activity with EEG-fMRI in such a manner that they do not significantly constrain the localization of the epileptogenic zone.

Involvement of GABA in mirror focus: a case report

Mirror focus (MF) is a cortical epileptogenic lesion that is posited to develop in the contralateral site to a cortical primary focus (PF) by secondary epileptogenic mechanisms. Previous animal evidence supports the implication of gamma-aminobutyric acid (GABA) in this phenomenon, but this contention has not yet been substantiated by clinical findings. Here we report for the first time clinical evidence suggesting the involvement of GABAergic cortical transmission in MF pathogenesis, in a 37-year-old man affected by a lesional PF in the right frontal lobe and a homotopic MF in the contralateral hemisphere, triggered by hyperventilation. One year after surgical excision of the PF, the electric activity of the MF remained unchanged, but was accompanied by a significant increase in the density of GABA(A)/benzodiazepine receptor binding in the left frontal lobe, as measured by (123)I-Iomazenil SPECT. These results extend previous evidence on the involvement of GABAergic signaling in MF pathophysiology.

Source localization of temporal lobe epilepsy using PCA-LORETA analysis on ictal EEG recordings

Localizing the source of an epileptic seizure using noninvasive EEG suffers from inaccuracies produced by other generators not related to the epileptic source. The authors isolated the ictal epileptic activity, and applied a source localization algorithm to identify its estimated location. Ten ictal EEG scalp recordings from five different patients were analyzed. The patients were known to have temporal lobe epilepsy with a single epileptic focus that had a concordant MRI lesion. The patients had become seizure-free following partial temporal lobectomy. A midinterval (approximately 5 seconds) period of ictal activity was used for Principal Component Analysis starting at ictal onset. The level of epileptic activity at each electrode (i.e., the eigenvector of the component that manifest epileptic characteristic), was used as an input for low-resolution tomography analysis for EEG inverse solution (Zilberstain et al., 2004). The algorithm accurately and robustly identified the epileptic focus in these patients. Principal component analysis and source localization methods can be used in the future to monitor the progression of an epileptic seizure and its expansion to other areas.