In recent years, applications of the network science to electrophysiological data have increased as electrophysiological techniques are not only relatively low cost, largely available on the territory and non-invasive, but also potential tools for large population screening. One of the emergent methods for the study of functional connectivity in electrophysiological recordings is graph theory: it allows to describe the brain through a mathematic model, the graph, and provides a simple representation of a complex system. As Alzheimer’s and Parkinson’s disease are associated with synaptic disruptions and changes in the strength of functional connectivity, they can be well described by functional connectivity analysis computed via graph theory. The aim of the present review is to provide an overview of the most recent applications of the graph theory to electrophysiological data in the two by far most frequent neurodegenerative disorders, Alzheimer’s and Parkinson’s diseases.

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Objective: A large part of the cerebral cortex is dedicated to the processing of visual stimuli and there is still much to understand about such processing modalities and hierarchies. The main aim of the present study is to investigate the differences between Directional (DS) and non-Directional (n-DS) visual stimuli processing by time-frequency analysis of brain EEG activity during a visuo-motor task. EEG data were divided into 4 Regions of Interest (ROIs) (Frontal, Central, Parietal, Occipital). Approach: The analysis of the visual stimuli processing was based on the combination of electroencephalographic recordings and Time-frequency analysis. Event Related Spectral Perturbations (ERSPs) were computed with spectrum analysis that allow to obtain the average time course of relative changes induced by the stimulus presentation in spontaneous EEG amplitude spectrum. Main results: Visual stimuli processing enhanced the same pattern of spectral modulation in all investigated ROIs with differences in amplitudes and timing. Additionally, statistically significant differences in Occipital ROI between the DS and n-DS visual stimuli processing in theta, alpha and beta bands were found. Significance: These evidences suggest that ERSPs could be a useful tool to investigate the encoding of visual information in different brain regions. Because of their simplicity and their capability in the representation of brain activity, the ERSPs might be used as biomarkers of functional recovery for example in the rehabilitation of visual dysfunction and motor impairment following a stroke, as well as diagnostic tool of anomalies in brain functions in neurological diseases tailored to personalized treatments in clinical environment.

Different visual stimuli can capture and shift attention into different directions. Few studies have explored differences in brain response due to directional (DS) and non-directional visual stimuli (nDS). To explore the latter, event-related potentials (ERP) and contingent negative variation (CNV) during a visuomotor task were evaluated in 19 adults. To examine the relation between task performance and ERPs, the participants were divided into faster (F) and slower (S) groups based on their reaction times (RTs). Moreover, to reveal ERP modulation within the same subject, each recording from the single participants was subdivided into F and S trials based on the specific RT. ERP latencies were analysed between conditions ((DS, nDS); (F, S subjects); (F, S trials)). Correlation was analysed between CNV and RTs. Our results reveal that the ERPs’ late components are modulated differently by DS and nDS conditions in terms of amplitude and location. Differences in ERP amplitude, location and latency, were also found according to subjects’ performance, i.e., between F and S subjects and trials. In addition, results show that the CNV slope is modulated by the directionality of the stimulus and contributes to motor performance. A better understanding of brain dynamics through ERPs could be useful to explain brain states in healthy subjects and to support diagnoses and personalized rehabilitation in patients with neurological diseases.

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