Dataset Information

Event-Related Potentials Elicited by Face and Face Pareidolia in Parkinson's Disease.

ABSTRACT: Background:Parkinson's disease is associated with impaired ability to recognize emotional facial expressions. In addition to a visual processing disorder, a visual recognition disorder may be involved in these patients. Pareidolia is a type of complex visual illusion that permits the interpretation of a vague stimulus as something known to the observer. Parkinson's patients experience pareidolic illusions. N170 and N250 waveforms are two event-related potentials (ERPs) involved in emotional facial expression recognition. Objective:In this study, we investigated how Parkinson's patients process face and face-pareidolia stimuli at the neural level using N170, vertex positive potential (VPP), and N250 components of event-related potentials. Methods:To examine the response of face and face-pareidolia processing in Parkinson's patients, we measured the N170, VPP, and N250 components of the event-related brain potentials in a group of 21 participants with Parkinson's disease and 26 control participants. Results:We found that the latencies of N170 and VPP responses to both face and face-pareidolia stimuli were increased along with their amplitudes, and the amplitude of N250 responses decreased in Parkinson's patients compared to the control group. In both control and Parkinson's patients, face stimuli generated greater ERP amplitude and shorter latency in responses than did face-pareidolia stimuli. Conclusion:The results of our study showed that ERPs associated with face and also face-pareidolia stimuli processing are changed in early-stage neurophysiological activity in the temporoparietal cortex of Parkinson's patients.

SUBMITTER: Akdeniz G

PROVIDER: S-EPMC7150676 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Event-Related Potentials Elicited by Face and Face Pareidolia in Parkinson's Disease.

Akdeniz Gulsum G Vural Gonul G Gumusyayla Sadiye S Bektas Hesna H Deniz Orhan O

Parkinson's disease 20200331

<h4>Background</h4>Parkinson's disease is associated with impaired ability to recognize emotional facial expressions. In addition to a visual processing disorder, a visual recognition disorder may be involved in these patients. Pareidolia is a type of complex visual illusion that permits the interpretation of a vague stimulus as something known to the observer. Parkinson's patients experience pareidolic illusions. N170 and N250 waveforms are two event-related potentials (ERPs) involved in emotio ...[more]

PMID: 32318259

Similar Datasets

Project description:In Parkinson's disease (PD) patients, visual misperceptions are a major problem within the non-motor symptoms. Pareidolia, i.e., the tendency to perceive a specific, meaningful image in an ambiguous visual pattern, is a phenomenon that occurs also in healthy subjects. Literature suggests that the perception of face pareidolia may be increased in patients with neurodegenerative diseases. We aimed to examine, within the same experiment, face perception and the production of face pareidolia in PD patients and healthy controls (HC). Thirty participants (15 PD patients and 15 HC) were presented with 47 naturalistic photographs in which faces were embedded or not. The likelihood to perceive the embedded faces was modified by manipulating their transparency. Participants were asked to decide for each photograph whether a face was embedded or not. We found that PD patients were significantly less likely to recognize embedded faces than controls. However, PD patients also perceived faces significantly more often in locations where none were actually present than controls. Linear regression analyses showed that gender, age, hallucinations, and Multiple-Choice Vocabulary Intelligence Test (MWT) score were significant predictors of face pareidolia production in PD patients. Montreal Cognitive Assessment (MoCA) was a significant predictor for pareidolia production in PD patients in trials in which a face was embedded in another region [F (1, 13) = 24.4, p = <0.001]. We conclude that our new embedded faces paradigm is a useful tool to distinguish face perception performance between HC and PD patients. Furthermore, we speculate that our results observed in PD patients rely on disturbed interactions between the Dorsal (DAN) and Ventral Attention Networks (VAN). In photographs in which a face is present, the VAN may detect this as a behaviourally relevant stimulus. However, due to the deficient communication with the DAN in PD patients, the DAN would not direct attention to the correct location, identifying a face at a location where actually none is present.

Project description:ObjectiveThe purpose of this study is to explore the possibility of developing a biomarker that can discriminate early-stage Parkinson's disease from healthy brain function using electroencephalography (EEG) event-related potentials (ERPs) in combination with Brain Network Analytics (BNA) technology and machine learning (ML) algorithms.BackgroundCurrently, diagnosis of PD depends mainly on motor signs and symptoms. However, there is need for biomarkers that detect PD at an earlier stage to allow intervention and monitoring of potential disease-modifying therapies. Cognitive impairment may appear before motor symptoms, and it tends to worsen with disease progression. While ERPs obtained during cognitive tasks performance represent processing stages of cognitive brain functions, they have not yet been established as sensitive or specific markers for early-stage PD.MethodsNineteen PD patients (disease duration of ≤2 years) and 30 healthy controls (HC) underwent EEG recording while performing visual Go/No-Go and auditory Oddball cognitive tasks. ERPs were analyzed by the BNA technology, and a ML algorithm identified a combination of features that distinguish early PD from HC. We used a logistic regression classifier with a 10-fold cross-validation.ResultsThe ML algorithm identified a neuromarker comprising 15 BNA features that discriminated early PD patients from HC. The area-under-the-curve of the receiver-operating characteristic curve was 0.79. Sensitivity and specificity were 0.74 and 0.73, respectively. The five most important features could be classified into three cognitive functions: early sensory processing (P50 amplitude, N100 latency), filtering of information (P200 amplitude and topographic similarity), and response-locked activity (P-200 topographic similarity preceding the motor response in the visual Go/No-Go task).ConclusionsThis pilot study found that BNA can identify patients with early PD using an advanced analysis of ERPs. These results need to be validated in a larger PD patient sample and assessed for people with premotor phase of PD.

Dataset Information

Event-Related Potentials Elicited by Face and Face Pareidolia in Parkinson's Disease.

Publications

Event-Related Potentials Elicited by Face and Face Pareidolia in Parkinson's Disease.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets