A new method for quantifying mfVEP signal intensity in multiple sclerosis

Castillo, Miguel Ortiz del; Santiago, Luis de; Fernández, A.; Blanco, R.; Rodríguez-Ascariz, J. M.; Barea, Rafael; Miguel-Jiménez, J. M.; Sánchez-Morla, Eva María; Boquete, Luciano

doi:10.1016/j.bspc.2015.06.015

Cited by 3 publications

(2 citation statements)

References 45 publications

(52 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…One cohort of patients with clinically definite MS (n = 28) and two other groups at different relative risks of developing MS—classified as RIS (n = 15) and CIS (n = 28)—were included in this study [ 34 ] and compared with a normal, control, age-matched subject group (n = 24) ( Table 1 ).…”

Section: Methodsmentioning

confidence: 99%

Empirical mode decomposition processing to improve multifocal-visual-evoked-potential signal analysis in multiple sclerosis

et al. 2018

View full text Add to dashboard Cite

ObjectiveTo study the performance of multifocal-visual-evoked-potential (mfVEP) signals filtered using empirical mode decomposition (EMD) in discriminating, based on amplitude, between control and multiple sclerosis (MS) patient groups, and to reduce variability in interocular latency in control subjects.MethodsMfVEP signals were obtained from controls, clinically definitive MS and MS-risk progression patients (radiologically isolated syndrome (RIS) and clinically isolated syndrome (CIS)). The conventional method of processing mfVEPs consists of using a 1–35 Hz bandpass frequency filter (XDFT).The EMD algorithm was used to decompose the XDFT signals into several intrinsic mode functions (IMFs). This signal processing was assessed by computing the amplitudes and latencies of the XDFT and IMF signals (XEMD). The amplitudes from the full visual field and from ring 5 (9.8–15° eccentricity) were studied. The discrimination index was calculated between controls and patients. Interocular latency values were computed from the XDFT and XEMD signals in a control database to study variability.ResultsUsing the amplitude of the mfVEP signals filtered with EMD (XEMD) obtains higher discrimination index values than the conventional method when control, MS-risk progression (RIS and CIS) and MS subjects are studied. The lowest variability in interocular latency computations from the control patient database was obtained by comparing the XEMD signals with the XDFT signals. Even better results (amplitude discrimination and latency variability) were obtained in ring 5 (9.8–15° eccentricity of the visual field).ConclusionsFiltering mfVEP signals using the EMD algorithm will result in better identification of subjects at risk of developing MS and better accuracy in latency studies. This could be applied to assess visual cortex activity in MS diagnosis and evolution studies.

show abstract

Section: Methodsmentioning

confidence: 99%

Empirical mode decomposition processing to improve multifocal-visual-evoked-potential signal analysis in multiple sclerosis

et al. 2018

View full text Add to dashboard Cite

show abstract

“…34 The optic radiations that extend from the lateral geniculate to the optic cortex however are commonly involved in MS and contribute to visual impairment. 35,36 In evaluating MRI parameters of demyelination and axonal loss, Reich et al 35 found that those abnormalities in the optic radiations were more pronounced in progressive than in relapsing MS. Visual impairment from the optic radiations correlated better with changes in NAWM than it did from lesional areas.…”

Section: Mfveps As a Potential Biomarker Of Progressive Msmentioning

confidence: 99%

Changing Paradigms and Unmet Needs in Multiple Sclerosis: The Role of Clinical Neurophysiology

Skeen¹

2020

Journal of Clinical Neurophysiology

View full text Add to dashboard Cite

Our increasing understanding of the immunopathogenesis of multiple sclerosis has led to the development of many diseasemodifying therapies that have revolutionized the care of patients with relapsing forms of the disease. Our understanding of the pathophysiologic basis of progressive forms of the disease is much more limited but has dramatically changed over the past several decades. We are now on the verge of developing therapies that promote remyelination, reduce axonal loss, and restore axonal function. This progress is challenged by inadequate animal models of progressive disease and incomplete biomarkers of progression. In measuring central nervous system function, evoked potentials may have an advantage over biomarkers, which measure only pathologic change. Monitoring multifocal visual evoked potential amplitude may be one possible means of monitoring disease progression in multiple sclerosis. Additional clinical studies are required to document whether evoked potentials can adequately serve as effective biomarkers of progression.

show abstract

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

Raeisi

Mohebbi

Khazaei

et al. 2020

Computers in Biology and Medicine

View full text Add to dashboard Cite

A new method for quantifying mfVEP signal intensity in multiple sclerosis

Cited by 3 publications

References 45 publications

Empirical mode decomposition processing to improve multifocal-visual-evoked-potential signal analysis in multiple sclerosis

Empirical mode decomposition processing to improve multifocal-visual-evoked-potential signal analysis in multiple sclerosis

Changing Paradigms and Unmet Needs in Multiple Sclerosis: The Role of Clinical Neurophysiology

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

Contact Info

Product

Resources

About