Impaired activation of the prefrontal executive network during working memory processing in multiple sclerosis

Abstract

In multiple sclerosis (MS), working memory (WM) impairment occurs soon after disease onset and significantly affects the patient’s quality of life. Functional imaging research in MS aims to investigate the neurophysiological underpinnings of WM impairment. In this context, we utilized a data-driven technique, the time delay embedded- hidden Markov model (TDE-HMM), to extract spectrally defined functional networks in magnetoencephalographic (MEG) data acquired during a WM visual-verbal n-back task. We observed that two networks show an altered activation in RR-MS patients. First, the activation of an early theta prefrontal network linked to stimulus encoding and attentional control significantly decreased in RR-MS compared to HC. This diminished activation correlated with reduced accuracy in task performance in the MS group, suggesting an impaired encoding and learning process. Secondly, a frontoparietal network characterized by beta coupling is activated between 300 and 600 ms after stimulus onset; this resembles the characteristic event-related P300, a cognitive marker extensively explored in EEG studies. The activation of this network is amplified in patients treated with benzodiazepine, in line with the well-known benzodiazepine-induced beta enhancement. Altogether, the TDE-HMM technique extracted task-relevant functional networks showing disease-specific and treatment- related alterations, revealing potential new markers to assess and track WM impairment in MS.HighlightsWe decomposed the brain dynamics underlying a WM n-back task in data-driven, spectrally defined whole-brain networks in both healthy controls and people with relapsing-remitting-MS (pwMS).PwMS showed a significantly decreased activation of an early theta prefrontal network linked to stimulus encoding and attentional control.The weaker activation of this prefrontal theta network is correlated with worse task performance.A beta frontoparietal network with a P300-like temporal evolution was significantly modulated by the use of benzodiazepines.The model distinguished disease-induced and treatment-induced dynamic network alterations.

Neurophysiological avenues to better conceptualizing adaptive cognition

“…These states have a spatial profile, can be characterized by specific frequency content, and (in the case of M/EEG) allow us to analyze the dynamics at millisecond resolution, i.e., these brain states have lifetimes in the order of 50-100 ms. These methods have been used to characterize the effect of normal brain functioning, benzodiazepines 32 , or working memory in health 33 and disease 34 . Given that these models capture fast transient brain dynamics and can capture the stability of specific brain networks, they are excellent candidates for distinguishing people on the persistence vs flexibility axis.…”