Cognition in MS correlates with resting-state oscillatory brain activity: An explorative MEG source-space study

Abstract

Clinical and cognitive dysfunction in Multiple Sclerosis (MS) is insufficiently explained by structural damage as identified by traditional magnetic resonance imaging (MRI) of the brain, indicating the need for reliable functional measures in MS. We investigated whether altered resting-state oscillatory power could be related to clinical and cognitive dysfunction in MS. MEG recordings were acquired using a 151-channel whole-head MEG system from 21 relapsing remitting MS patients and 17 healthy age-, gender-, and education-matched controls, using an eyes-closed no-task condition. Relative spectral power was estimated for 78 regions of interest, using an atlas-based beamforming approach, for classical frequency bands; delta, theta, alpha1, alpha2, beta and gamma. These cortical power estimates were compared between groups by means of permutation analysis and correlated with clinical disability (Expanded Disability Status Scale: EDSS), cognitive performance and MRI measures of atrophy and lesion load. Patients showed increased power in the alpha1 band and decreased power in the alpha2 band, compared to controls, mainly in occipital, parietal and temporal areas, confirmed by a lower alpha peak-frequency. Increased power in the alpha1 band was associated with worse overall cognition and especially with information processing speed. Our quantitative relative power analysis of MEG recordings showed abnormalities in oscillatory brain dynamics in MS patients in the alpha band. By applying source-space analyses, this study provides a detailed topographical view of abnormal brain activity in MS patients, especially localized to occipital areas. Interestingly, poor cognitive performance was related to high resting-state alpha1 power indicating that changes in oscillatory activity might be of value as an objective measure of disease burden in MS patients.

Early patterns of functional brain development associated with autism spectrum disorder in tuberous sclerosis complex

“…The integrity of long-range structural connections is reflected in measurements of functional network properties, with oscillations in the alpha range found to be particularly reflective of changes in white matter structure [Jann et al, 2012;Picci, Gotts, & Scherf, 2016;Teipel et al, 2009;Valdés-Hernández et al, 2010]. Conversely, disorders of white matter are associated with disruptions in alpha oscillations, with decreased PAF demonstrated in vascular dementia [Moretti et al, 2004], multiple sclerosis [Leocani et al, 2000;Tewarie et al, 2014;Van der Meer et al, 2013], and white (but not gray) matter tumors [Gloor, Kalabay, & Giard, 1968;Goldensohn, 1979]. Decreased PAF and reduced APC may therefore indicate delayed or atypical maturation of white matter during the infancy period, which is consistent with the disrupted interhemispheric white matter connections that have been identified later in TSC [Baumer et al, 2017;Im et al, 2016;Krishnan et al, 2010;Peters et al, 2012].…”

Early patterns of functional brain development associated with autism spectrum disorder in tuberous sclerosis complex

“…The integrity of long range structural connections is reflected in measurements of functional network properties, with oscillations in the alpha range found to be particularly reflective of changes in white matter structure (Jann et al, 2012;Picci, Gotts, & Scherf, 2016;Teipel et al, 2009;Valdés-Hernández et al, 2010). Conversely, disorders of white matter are associated with disruptions in alpha oscillations, with decreased PAF demonstrated in vascular dementia (Moretti et al, 2004), multiple sclerosis (Leocani et al, 2000;Tewarie et al, 2014;Van der Meer et al, 2013), and white (but not gray) matter tumors (Gloor, Kalabay, & Giard, 1968;Goldensohn, 1979). Decreased PAF and reduced APC may therefore indicate delayed or atypical maturation of white matter during the infancy period, which is consistent with the disrupted interhemispheric white matter connections that have been identified later in TSC (Baumer et al, 2017;Im et al, 2015;Krishnan et al, 2010;Peters et al, 2012).…”

Test-retest reliability of resting-state magnetoencephalography power in sensor and source space

“…Supporting this idea, several spectral measures derived from MEG and EEG recordings in resting, such as absolute or relative power of each frequency band, have been applied to brain rhythm analysis and have been shown to reflect changes related to normal and pathological states. These findings reported disturbed oscillatory activity in developmental disorders, such as autism [Cornew et al, 2013], in psychiatric disorders, such as schizophrenia [Fehr et al, 2001], and neurodegenerative diseases, such as Multiple Sclerosis [Van Der Meer et al, 2013] or Alzheimer's disease [Fern andez et al, 2006] and Mild Cognitive Impairment [Garc es et al, 2013]. Additionally, drug-related changes versus placebo have been assessed in MEG pharmacological studies (e.g., the case of methylphenidate treatment in children with Attention Deficit Hyperactivity Disorder [Wienbruch et al, 2005]).…”