2020
DOI: 10.1038/s41598-020-66279-0
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Frontoparietal connectivity correlates with working memory performance in multiple sclerosis

Abstract: Working Memory (WM) impairment is the most common cognitive deficit of patients with Multiple Sclerosis (MS). However, evidence of its neurobiological mechanisms is scarce. Here we recorded electroencephalographic activity of twenty patients with relapsing-remitting MS and minimal cognitive deficit, and 20 healthy control (HC) subjects while they solved a WM task. In spite of similar performance, the HC group demonstrated both a correlation between temporoparietal theta activity and memory load, and a correlat… Show more

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Cited by 29 publications
(33 citation statements)
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“…In this context, it is relevant to mention reported working memory deficits in children with ADHD (Nikolas and Nigg, 2013). Working memory crucially depends on theta oscillation (Billeke et al, 2017;Larrain-Valenzuela et al, 2017;Figueroa-Vargas et al, 2020), and its impairment can preclude the adequate information maintaining necessary to exert general proactive cognitive control. In a broad sense, these functional results can be related to the functional differences observed in children with ADHD in prefrontal areas when compared to TD children (Nakao et al, 2011;Frodl and Skokauskas, 2012) and the difference between TD children according to age (Bruin et al, 2001;Jonkman, 2006;Spronk et al, 2008).…”
Section: Discussionmentioning
confidence: 99%
“…In this context, it is relevant to mention reported working memory deficits in children with ADHD (Nikolas and Nigg, 2013). Working memory crucially depends on theta oscillation (Billeke et al, 2017;Larrain-Valenzuela et al, 2017;Figueroa-Vargas et al, 2020), and its impairment can preclude the adequate information maintaining necessary to exert general proactive cognitive control. In a broad sense, these functional results can be related to the functional differences observed in children with ADHD in prefrontal areas when compared to TD children (Nakao et al, 2011;Frodl and Skokauskas, 2012) and the difference between TD children according to age (Bruin et al, 2001;Jonkman, 2006;Spronk et al, 2008).…”
Section: Discussionmentioning
confidence: 99%
“…When the data did not meet the normal assumption, we used nonparametric tests. For the EEG statistical analysis, we rst tted a general linear model (GLM) of the power of the oscillatory activity per trial in each participant ( rst-level analysis, see [45][46][47][48] ) using the following equation:…”
Section: Discussionmentioning
confidence: 99%
“…A similar study in broad autism phenotype reports an effect size of f η 2 = 0.09 [ 68 ], which is a large effect [ 69 ]. Taking into account the publication bias, and our previous experience in effect size in electrophysiological measure in our experimental setting between clinical and subclinical populations [e.g., 70 , 71 ], we set an intermediated effect size of η 2 = 0.06. Thus, for the between-within factor interaction in a 2x4 mixed ANOVA with a power of (1-β) = 0.95 and a significant level of α = 0.05, the minimum sample size to find the expected effect was n = 36.…”
Section: Methodsmentioning
confidence: 99%