EEG-Derived Functional Connectivity Patterns Associated with Mild Cognitive Impairment in Parkinson’s Disease

Objective: To evaluate EEG-derived functional connectivity (FC) patterns associated with mild cognitive impairment (MCI) in Parkinson’s disease (PD). METHODS: A sample of 15 patients without cognitive impairment (PD-WCI), 15 with MCI (PD-MCI), and 26 healthy subjects were studied. The EEG was performed in the waking functional state with eyes closed, for the functional analysis it was used the synchronization likelihood (SL) and graph theory (GT). RESULTS: PD-MCI patients showed decreased FC in frequencies alpha, in posterior regions, and delta with a generalized distribution. Patients, compared to the healthy people, presented a decrease in segregation (lower clustering coefficient in alpha p = 0.003 in PD-MCI patients) and increased integration (shorter mean path length in delta (p = 0.004) and theta (p = 0.002) in PD-MCI patients). There were no significant differences in the network topology between the parkinsonian groups. In PD-MCI patients, executive dysfunction correlated positively with global connectivity in beta (r = 0.47) and negatively with the mean path length at beta (r = −0.45); alterations in working memory were negatively correlated with the mean path length at beta r = −0.45. CONCLUSIONS: PD patients present alterations in the FC in all frequencies, those with MCI show less connectivity in the alpha and delta frequencies. The neural networks of the patients show a random topology, with a similar organization between patients with and without MCI. In PD-MCI patients, alterations in executive function and working memory are related to beta integration

SARS-CoV-2 Infection and Risk Management in Multiple Sclerosis

The novel coronavirus can cause a severe respiratory disease with impact on the central nervous system, as has been reported by several medical health services. In the COVID-19 pandemic caused by the SARS-CoV-2 neurotrophic virus, neurologists have focused their attention on the early identification of suggestive manifestations of the neurological impact of the disease. In this context, they are exploring related chronic disease and the possibility of achieving a more effective understanding of symptoms derived from COVID-19 infection and those derived from the course of preexisting neurological disease. The present review summarizes evidence from the infection with SARS-CoV-2 and the management of the risks of multiple sclerosis and how it is related to the risks of general comorbidities associated with COVID-19. In addition, we reviewed other factors characteristic of MS, such as relapses, and the maximum tolerated dose of treatment medications from clinical and experimental evidence