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ISSN 2225-4676 (Electronic)

2022, Number 1

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Rev Cubana Neurol Neurocir 2022; 12 (1)

Electroencephalogram-Derived Functional Connectivity in Parkinson´s Disease without Dementia

Berrillo BS, Morales CLM, Pedroso II, Peláez SAA, Sánchez CA, Alfonso AM

Language: Spanish
References: 36
Page: 1-20
PDF size: 467.68 Kb.


ABSTRACT

Introduction: Parkinson's disease is a common neurodegenerative disease characterized by a set of motor and non-motor symptoms that affect the lives of patients.
Objective: To assess resting-state electroencephalogram-derived functional connectivity and network topological properties in patients with Parkinson's disease without dementia.
Methods: Cross-sectional study of cases and controls in 26 patients diagnosed with Parkinson's disease without dementia and 26 healthy subjects. The electroencephalogram was obtained while awake. Functional connectivity was calculated based on the spatial synchronization matrix between the electrodes. For the quantification of graph theory, the parameters clustering coefficient, mean path length, local and global efficiency were evaluated.
Results: Patients with Parkinson's disease showed increased synchronization for beta frequency and decreased synchronization for alpha, theta, and delta frequencies compared to healthy subjects (permutation test p<0.05). In the topological properties of the network, the local efficiency and beta, theta, and delta mean path length, as well as the alpha, beta, theta, and delta clustering coefficient were lower in Parkinson's disease patients compared to healthy subjects (test independent samples p<0.05).
Conclusions: Alterations in functional connectivity and patterns described in graph theory for all frequency bands of the electroencephalogram in patients with Parkinson's disease without dementia show a de-structuring of the functional network towards a more random one, therefore, it is thought that from very early stages of the disease, there are already alterations in functional brain networks.


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