Graph Theory on Brain Cortical Sources in Parkinson’s Disease: The Analysis of ‘Small World’ Organization from EEG

Abstract

Parkinson’s disease (PD) is the second most common neurodegenerative disease in the elderly population. Similarly to other neurodegenerative diseases, the early diagnosis of PD is quite difficult. The current pilot study aimed to explore the differences in brain connectivity between PD and NOrmal eLDerly (Nold) subjects to evaluate whether connectivity analysis may speed up and support early diagnosis. A total of 26 resting state EEGs were analyzed from 13 PD patients and 13 age-matched Nold subjects, applying to cortical reconstructions the graph theory analyses, a mathematical representation of brain architecture. Results showed that PD patients presented a more ordered structure at slow-frequency EEG rhythms (lower value of SW) than Nold subjects, particularly in the theta band, whereas in the high-frequency alpha, PD patients presented more random organization (higher SW) than Nold subjects. The current results suggest that PD could globally modulate the cortical connectivity of the brain, modifying the functional network organization and resulting in motor and non-motor signs. Future studies could validate whether such an approach, based on a low-cost and non-invasive technique, could be useful for early diagnosis, for the follow-up of PD progression, as well as for evaluating pharmacological and neurorehabilitation treatments.

Scale-Free Functional Brain Networks Exhibit Increased Connectivity, Are More Integrated and Less Segregated in Patients with Parkinson’s Disease following Dopaminergic Treatment

“…It is of note that DT did not exclusively heighten or dampen the small-world properties of the network. Similar inconsistencies of small-worldliness were seen in Vecchio et al [48], where the small-world index (ratio of normalized clustering coefficient and normalized path length) was higher in PD in the alpha 2 but lower in the theta EEG band. Such complex interactions suggest that we should study the influence of DT in the small-world architecture of cortical networks even further.…”

Prognostic Role of Hemispherical Functional Connectivity in Stroke: A Study via Graph Theory Versus Coherence of Electroencephalography Rhythms

“…Functional connectivity of brain networks has been described by using different parameters, among them are coherence and graph theory. 6,9,10 These mathematical approaches have already been used to characterize impairment and recovery after stroke, frequently via magnetic resonance imaging, functional magnetic resonance imaging 11 and rarely via electroencephalography (EEG). 5,[12][13][14] However, because of its high temporal resolution and increasingly wide use in neurological diseases, EEG could be crucial for the study of stroke.…”

The effect of deep brain stimulation on cortico-subcortical networks in Parkinson’s disease patients with freezing of gait: Exhaustive exploration of a basic model

“…Synchronicity is arguably not the most straightforward measure for assessing whether the graph network is closer to the PD state or not. There are also small-worldness [28], global efficiency, calculation of minimum spanning trees, and other approaches [29]. However, when taken alone, these measures typically lead to inconsistent results across the literature [29, 30] or are inefficient in the case of signed [31] or directed graphs.…”