Event-related potential P3 change in mild Parkinson's disease

Abstract BackgroundPatients with Parkinson’s disease (PD) can develop the cognitive adverse effect of impulse control disorders (ICDs) while undergoing a pharmacological treatment for motor control dysfunctions with a dopamine agonist (DA). Conventional clinical interviews or questionnaires can be biased and may not provide an accurate diagnosis in the early stage. A wearable electroencephalogram (EEG)-sensing headset paired with an examination procedure can be a potential user-friendly method to explore ICD-related biomarkers that can reflect brain activity abnormalities and detect its early signs and progression.MethodsA stereotypical Go/NoGo test that targets impulse inhibition was performed with 59 individuals, including heathy controls, patients with PD, and patients with PD diagnosed with ICD. A low-cost LEGO-like EEG headset was used to record concurrent EEG signals. The event-related potential (ERP) analytical framework was then used to explore ICD-related EEG abnormalities after DA treatment.ResultsOnly PD patients with ICD exhibited a tendency for N2 and P3 amplitude deterioration at the fronto-central regions (i.e., Fz, FCz, and Cz); in particular, the P3 counterpart reached statistical significance (p<0.05). Neither PD patients nor healthy controls (without DA) replicated such findings. Furthermore, N2 amplitude deterioration was found to be related to ICD severity at Fz (r=-0.28, p=0.04).ConclusionsA low-cost LEGO-like EEG headset successfully captured ERP neuromarkers for the objective assessment of ICD in PD patients undergoing DA treatment. The present objective neuro-evidence could provide complementary information to conventional clinical scales used to diagnose the ICD adverse effect.

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Review of prodromal symptoms in Parkinson's Disease detected by MRI, EEG And microbiome

10.31226/osf.io/yfnmw ◽

2019 ◽

Author(s):

Isabel Cristina Echeverri ◽

Maria de la Iglesia Vayá ◽

Jose Molina Mateo ◽

Francia Restrepo de Mejia ◽

Belarmino Segura Giraldo

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Magnetic Resonance ◽

Substantia Nigra ◽

Evidence Synthesis ◽

Magnetic Resonance Images ◽

Event Related Potential ◽

Motor Symptoms ◽

The Brain ◽

Early Parkinson’S Disease

Context: Parkinson’s disease (PD) is catalogued as a disorder that causes motor symptoms; the evidence of literature shows the PD starts with non-motor signs, which can be detected in prodromal phases. These previous phases can be analyzed and studied through magnetic resonance images (MRI), electroencephalography (EEG) and microbiome.Objective: To systematically review the areas of the brain and brain-gut axis which affect in early Parkinson’s disease that can possibly be visualized and analyzed by MRI, EEG and the microbiome.Evidence acquisition: Pubmed and Embase databases were used until July 30, 2018 as to search for early Parkinson’s disease at its earliest non-motor symptoms stage by using MRI, EEG, and microbiome. The search was performed according to the requirements of a systematic review. In order to identify reports, we evaluated them following the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) criteria. Evidence synthesis: MRI and EEG have provided the advances to find features for PD over the last decade. Those techniques identify motor symptoms on substantia nigra where the patient shows a dopamine deficiency. However, over recent years, researchers have found that PD has prodromal phases, that is, PD is not simply a neurodegenerative disorder characterized by the dysfunction of dopaminergic. Thus, high field MRI, event-related potential (ERP) and microbiota data shows a significant change on the brain cortex, white and grey matter, the extrapyramidal system, brain signals and the gut.Conclusion: The structural MRI is a useful technique in detecting the stages of motor symptoms on the substantia nigra in patients with PD. The use of magnetic resonance as an early detector requires a high magnetic field, as to identify the areas which diagnose that the patient could be in the premotor stages. On the other hand, EEG performed well in detecting PD features. Furthermore, microbiome sequencing might include the classification of bacterial families that could help to detect PD in its prodromal phase. Thus, the combination of all these techniques can support the possibility of diagnosing PD in its very early stages.

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