Phase-synchrony evaluation of EEG signals for Multiple Sclerosis diagnosis based on bivariate empirical mode decomposition during a visual task

Raeisi, Khadijeh; Mohebbi, Maryam; Khazaei, Mohammad Reza; Seraji, Masoud; Yoonessi, Ali

doi:10.1016/j.compbiomed.2019.103596

Cited by 16 publications

(13 citation statements)

References 61 publications

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“…To evaluate the extracted results from source localization algorithms, the results obtained need to be compared with the medical results obtained from different modalities. For the localization of SOZ and irritative zone (IZ) in the pre-surgical evaluation of each patient, all the available data such as the comprehensive clinical record, full neurological examination, long-term video-EEG monitoring (144), structural MRI (145), neuropsychological assessment, and other non-invasive investigations such as PET and ictal SPECT (146) are usually reviewed.…”

Section: Long-term Eeg Recordingmentioning

confidence: 99%

Localization of Epileptic Foci Based on Simultaneous EEG–fMRI Data

et al. 2021

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Combining functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) enables a non-invasive investigation of the human brain function and evaluation of the correlation of these two important modalities of brain activity. This paper explores recent reports on using advanced simultaneous EEG–fMRI methods proposed to map the regions and networks involved in focal epileptic seizure generation. One of the applications of EEG and fMRI combination as a valuable clinical approach is the pre-surgical evaluation of patients with epilepsy to map and localize the precise brain regions associated with epileptiform activity. In the process of conventional analysis using EEG–fMRI data, the interictal epileptiform discharges (IEDs) are visually extracted from the EEG data to be convolved as binary events with a predefined hemodynamic response function (HRF) to provide a model of epileptiform BOLD activity and use as a regressor for general linear model (GLM) analysis of the fMRI data. This review examines the methodologies involved in performing such studies, including techniques used for the recording of EEG inside the scanner, artifact removal, and statistical analysis of the fMRI signal. It then discusses the results reported for patients with primary generalized epilepsy and patients with different types of focal epileptic disorders. An important matter that these results have brought to light is that the brain regions affected by interictal epileptic discharges might not be limited to the ones where they have been generated. The developed methods can help reveal the regions involved in or affected by a seizure onset zone (SOZ). As confirmed by the reviewed literature, EEG–fMRI provides information that comes particularly useful when evaluating patients with refractory epilepsy for surgery.

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Section: Long-term Eeg Recordingmentioning

confidence: 99%

Localization of Epileptic Foci Based on Simultaneous EEG–fMRI Data

et al. 2021

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“…Colors were chosen in DKL color space then transformed to RGB. In each trial, the visual stimulus was presented for 1 second, and the screen was gray during the 2 s intertrial interval [ 25 ].…”

Section: Methodsmentioning

confidence: 99%

Multiple sclerosis reduces synchrony of the magnocellular pathway

et al. 2021

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Multiple Sclerosis (MS) is an autoimmune demyelinating disease that damages the insulation of nerve cell fibers in the brain and spinal cord. In the visual system, this demyelination results in a robust delay of visually evoked potentials (VEPs), even in the absence of overt clinical symptoms such as blurred vision. VEPs, therefore, offer an avenue for early diagnosis, monitoring disease progression, and, potentially, insight into the differential impairment of specific pathways. A primary hypothesis has been that visual stimuli driving the magno-, parvo-, and konio-cellular pathways should lead to differential effects because these pathways differ considerably in terms of myelination. Experimental tests of this hypothesis, however, have led to conflicting results. Some groups reported larger latency effects for chromatic stimuli, while others found equivalent effects across stimulus types. We reasoned that this lack of pathway specificity could, at least in part, be attributed to the relatively coarse measure of pathway impairment afforded by the latency of a VEP. We hypothesized that network synchrony could offer a more sensitive test of pathway impairments. To test this hypothesis, we analyzed the synchrony of occipital electroencephalography (EEG) signals during the presentation of visual stimuli designed to bias activity to one of the three pathways. Specifically, we quantified synchrony in the occipital EEG using two graph-theoretic measures of functional connectivity: the characteristic path length (L; a measure of long-range connectivity) and the clustering coefficient (CC; a measure of short-range connectivity). Our main finding was that L and CC were both smaller in the MS group than in controls. Notably, this change in functional connectivity was limited to the magnocellular pathway. The effect sizes (Hedge’s g) were 0.89 (L) and 1.26 (CC) measured with magno stimuli. Together, L and CC define the small-world nature of a network, and our finding can be summarized as a reduction in the small-worldness of the magnocellular network. We speculate that the reduced efficiency of information transfer associated with a reduction in small-worldness could underlie visual deficits in MS. Relating these measures to differential diagnoses and disease progression is an important avenue for future work.

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“…The EEG signals were preprocessed using the EEGLAB toolbox (https://sccn.ucsd.edu/eeglab/). First, the sampling rate of the signal was reduced to 250 Hz, and a Butterworth high-pass filter at 1 Hz was used to suppress the low-frequency components (30)(31)(32). Then, all the channels were reviewed, and those with a standard deviation greater than ±3.1 from the mean standard deviation (across all channels) were excluded as the abnormal channels.…”

Section: Eeg Signal Processing-long Term Monitoringmentioning

confidence: 99%

Localizing Epileptic Foci Using Simultaneous EEG-fMRI Recording: Template Component Cross-Correlation

et al. 2021

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Conventional EEG-fMRI methods have been proven to be of limited use in the sense that they cannot reveal the information existing in between the spikes. To resolve this issue, the current study obtains the epileptic components time series detected on EEG and uses them to fit the Generalized Linear Model (GLM), as a substitution for classical regressors. This approach allows for a more precise localization, and equally importantly, the prediction of the future behavior of the epileptic generators. The proposed method approaches the localization process in the component domain, rather than the electrode domain (EEG), and localizes the generators through investigating the spatial correlation between the candidate components and the spike template, as well as the medical records of the patient. To evaluate the contribution of EEG-fMRI and concordance between fMRI and EEG, this method was applied on the data of 30 patients with refractory epilepsy. The results demonstrated the significant numbers of 29 and 24 for concordance and contribution, respectively, which mark improvement as compared to the existing literature. This study also shows that while conventional methods often fail to properly localize the epileptogenic zones in deep brain structures, the proposed method can be of particular use. For further evaluation, the concordance level between IED-related BOLD clusters and Seizure Onset Zone (SOZ) has been quantitatively investigated by measuring the distance between IED/SOZ locations and the BOLD clusters in all patients. The results showed the superiority of the proposed method in delineating the spike-generating network compared to conventional EEG-fMRI approaches. In all, the proposed method goes beyond the conventional methods by breaking the dependency on spikes and using the outside-the-scanner spike templates and the selected components, achieving an accuracy of 97%. Doing so, this method contributes to improving the yield of EEG-fMRI and creates a more realistic perception of the neural behavior of epileptic generators which is almost without precedent in the literature.

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Phase-synchrony evaluation of EEG signals for Multiple Sclerosis diagnosis based on bivariate empirical mode decomposition during a visual task

Cited by 16 publications

References 61 publications

Localization of Epileptic Foci Based on Simultaneous EEG–fMRI Data

Localization of Epileptic Foci Based on Simultaneous EEG–fMRI Data

Multiple sclerosis reduces synchrony of the magnocellular pathway

Localizing Epileptic Foci Using Simultaneous EEG-fMRI Recording: Template Component Cross-Correlation

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