Cortical neurodynamics changes mediate the efficacy of a personalized neuromodulation against multiple sclerosis fatigue

Abstract

The people with multiple sclerosis (MS) often report that fatigue restricts their life. Nowadays, pharmacological treatments are poorly effective accompanied by relevant side effects. A 5-day transcranial direct current stimulation (tDCS) targeting the somatosensory representation of the whole body (S1) delivered through an electrode personalized based on the brain MRI was efficacious against MS fatigue (FaReMuS treatment). This proof of principle study tested whether possible changes of the functional organization of the primary sensorimotor network induced by FaReMuS partly explained the effected fatigue amelioration. We measured the brain activity at rest through electroencephalography equipped with a Functional Source Separation algorithm and we assessed the neurodynamics state of the primary somatosensory (S1) and motor (M1) cortices via the Fractal Dimension and their functional connectivity via the Mutual Information. The dynamics of the neuronal electric activity, more distorted in S1 than M1 before treatment, as well as the network connectivity, altered maximally between left and right M1 homologs, reverted to normal after FaReMuS. The intervention-related changes explained 48% of variance of fatigue reduction in the regression model. A personalized neuromodulation tuned in on specific anatomo-functional features of the impaired regions can be effective against fatigue.

The Potential Role of Neurophysiology in the Management of Multiple Sclerosis-Related Fatigue

“…They used a tailored procedure with personalized electrodes based on the patients' brain MRI located in place through an MRI-guided neuronavigation system. In a more recent study of this group, the importance of the individual baseline neural networks activity has been outlined as a further parameter for individualized treatment (110). The results of their studies support the efficacy of personalized tDCS approaches.…”

“…The group of Tecchio et al focused on a personalized anodal tDCS approach targeting the whole-body primary somatosensory areas (S1) bilaterally, following the evidence of S1 reduced excitability and M1 hyperexcitability in PwMS with fatigue (109)(110)(111)(112). They used a tailored procedure with personalized electrodes based on the patients' brain MRI located in place through an MRI-guided neuronavigation system.…”

Haemodynamic activity characterization of resting state networks by fractal analysis and thalamocortical morphofunctional integrity in chronic migraine

“…In addition, recent evidence has demonstrated that in many cases brain signals considered as belonging to a frequency-defined class of brain rhythms do not represent sustained oscillations, but rather brief bouts of activity that are repeated intermittently (i.e., non-rhythmic) [15,16]. Recognition that physiological time series contain "hidden information" that might be captured by non-linear methods such as fractal analysis, may provide crucial and so far overlooked physiological information in healthy and pathological conditions [17][18][19][20]. However, while this type of nonlinear approaches is no longer an issue in the domain of EEG, there are just few applications on the analysis of micro [21] and macro [22,23] structural neuroimaging data.…”

Characterisation of Haemodynamic Activity in Resting State Networks by Fractal Analysis

“…30,31 Recognition that physiological time series contain "hidden information" that might be captured by nonlinear methods such as fractal analysis (FA), may provide crucial and so far overlooked physiological information in healthy and pathological conditions. [32][33][34][35][36][37][38][39] We have shown that FD can be used to dissociate RSNs from EEG data 9 but, to our knowledge, no study has used FD in functional magnetic resonance imaging (fMRI)-derived RSNs. To fill this gap, we used a data-driven approach based on hierarchical clustering to differentiate RSNs based on their functional roles.…”