Reduced Effective Connectivity in the Motor Cortex in Parkinson’s Disease

Abstract

Fast rhythms excess is a hallmark of Parkinson’s Disease (PD). To implement innovative, non-pharmacological, neurostimulation interventions to restore cortical-cortical interactions, we need to understand the neurophysiological mechanisms underlying these phenomena. Here, we investigated effective connectivity on source-level resting-state electroencephalography (EEG) signals in 15 PD participants and 10 healthy controls. First, we fitted multivariate auto-regressive models to the EEG source waveforms. Second, we estimated causal connections using Granger Causality, which provide information on connections’ strength and directionality. Lastly, we sought significant differences connectivity patterns between the two populations characterizing the network graph features—i.e., global efficiency and node strength. Causal brain networks in PD show overall poorer and weaker connections compared to controls quantified as a reduction of global efficiency. Motor areas appear almost isolated, with a strongly impoverished information flow particularly from parietal and occipital cortices. This striking isolation of motor areas may reflect an impaired sensory-motor integration in PD. The identification of defective nodes/edges in PD network may be a biomarker of disease and a potential target for future interventional trials.

Increased Effective Connectivity of the Left Parietal Lobe During Walking Tasks in Parkinson’s Disease

“…Individuals with Parkinson's disease (PD) experience gait disorders that result in an increased risk of falling and a substantially decreased life quality [1]. Early gait disorders are characterized by 40 reduced gait speed and stride length and increased 41 gait variability [2, 3], suggesting that changes in walk-emission tomography (PET) findings [14][15][16]. However, a major limitation of these studies is that the participants could not walk on a pathway in a realistic environment.…”

“…Prior studies have reported EC patterns in PD based on electroencephalogram (EEG), functional magnetic resonance imaging (fMRI), and positron emission tomography (PET) findings [ 14–16 ]. However, a major limitation of these studies is that the participants could not walk on a pathway in a realistic environment.…”

Neural Networks and Connectivity among Brain Regions

“…On the other hand, the use of EEG data is receiving increasing attention in the current literature due to the simplicity of the experimental setup and its capacity to detect rapid temporal changes in neural activity. Three papers in this Special Issue infer connectivity from EEG ( [8][9][10]). The first two papers use Granger connectivity (bivariate in Tarasi et al [9] and multivariate in Formaggio et al [8]).…”

“…Three papers in this Special Issue infer connectivity from EEG ( [8][9][10]). The first two papers use Granger connectivity (bivariate in Tarasi et al [9] and multivariate in Formaggio et al [8]). In contrast, the last paper (Taberna et al [10]) uses a different approach based on band-limited power envelope correlations.…”

“…The paper by Formaggio et al [8] is also based on source activity reconstruction from resting-state EEG data and on the estimation of Granger connectivity networks. The aim is to discover differences in connectivity patterns between subjects with Parkinson's disease (PD) and healthy controls.…”