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Clinical implication of high-density EEG sleep recordings in Parkinson’s disease

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The diagnosis of Parkinson's disease (PD) is made relatively late in the pathological process, when already most of the dopaminergic synapses have died. The evidence showed that, at the time… Click to show full abstract

The diagnosis of Parkinson's disease (PD) is made relatively late in the pathological process, when already most of the dopaminergic synapses have died. The evidence showed that, at the time of the clinical diagnosis, which can be done only after motor symptoms' appearance, the pathogenetic process is too advanced for a potential neuroprotective agent to be efficacious. Thus, the identification of early markers of neurodegeneration would be essential in the fight again the disease. A growing body of literature reported that non-motor symptoms, including sleep disorders, are commonly the earliest manifestation of the disease (i.e. prodromal stage). Furthermore, evidence claimed that these disturbances may have an impact on the progression of the disease itself, possibly altering its phenotype and leading to the emergence of levodopa-induced dyskinesia (LID), a typical treatment-related complication. The early recognition of subjects at risk of developing PD would offer the opportunity to evaluate the efficacy of possible neuroprotective agents. Additionally, the early identification of sleep alterations, which could possibly be considered an indicator of aberrant brain plasticity and thus be helpful in predicting the emergence of LID, if confirmed, would offer a platform for testing possible sleep targeted therapies able to protect the patients from the development of this treatment-induced condition. In this review, new techniques for the study of sleep will be addressed, in order to investigate their possible role as diagnostic and prognostic tools in the evaluation of patients suffering from PD.

Keywords: high density; clinical implication; disease; parkinson disease; implication high

Journal Title: Journal of Neuroscience Methods
Year Published: 2020

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