scholarly journals Event-Related Potentials Elicited by Face and Face Pareidolia in Parkinson’s Disease

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Gulsum Akdeniz ◽  
Gonul Vural ◽  
Sadiye Gumusyayla ◽  
Hesna Bektas ◽  
Orhan Deniz
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Visual Processing ◽  
Visual Recognition ◽  
Early Stage ◽  
Event Related Potentials ◽  
Control Group ◽  
Expression Recognition ◽  
Emotional Facial Expressions ◽  
Related Potentials

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.

scholarly journals Identification of an early-stage Parkinson’s disease neuromarker using event-related potentials, brain network analytics and machine-learning

PLoS ONE ◽  
2022 ◽  
Vol 17 (1) ◽  
pp. e0261947
Author(s):  
Sharon Hassin-Baer ◽  
Oren S. Cohen ◽  
Simon Israeli-Korn ◽  
Gilad Yahalom ◽  
Sandra Benizri ◽  
...  
Keyword(s):  
Machine Learning ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Early Stage ◽  
Event Related Potentials ◽  
Brain Network ◽  
Cognitive Tasks ◽  
Network Analytics ◽  
Related Potentials ◽  
Advanced Analysis

Objective The 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. Background Currently, 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. Methods Nineteen 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. Results The 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). Conclusions This 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.

scholarly journals Early-stage visual processing abnormalities in high-functioning autism spectrum disorder (ASD)

2010 ◽  
Vol 1 (2) ◽  
Author(s):  
Joshua Baruth ◽  
Manuel Casanova ◽  
Lonnie Sears ◽  
Estate Sokhadze
Keyword(s):  
Autism Spectrum Disorder ◽  
Visual Processing ◽  
Auditory Processing ◽  
Physiological Stress ◽  
Early Stage ◽  
Event Related Potentials ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Control Group ◽  
Related Potentials

AbstractIt has been reported that individuals with autism spectrum disorder (ASD) have abnormal responses to the sensory environment. For these individuals sensory overload can impair functioning, raise physiological stress, and adversely affect social interaction. Early-stage (i.e. within 200 ms of stimulus onset) auditory processing abnormalities have been widely examined in ASD using event-related potentials (ERP), while ERP studies investigating early-stage visual processing in ASD are less frequent. We wanted to test the hypothesis of early-stage visual processing abnormalities in ASD by investigating ERPs elicited in a visual oddball task using illusory figures. Our results indicate that individuals with ASD have abnormally large cortical responses to task irrelevant stimuli over both parieto-occipital and frontal regions-of-interest (ROI) during early stages of visual processing compared to the control group. Furthermore, ASD patients showed signs of an overall disruption in stimulus discrimination, and had a significantly higher rate of motor response errors.

Habituation of event-related potentials in patients with Parkinson's disease

2000 ◽  
Vol 68 (5) ◽  
pp. 741-747 ◽  
Author(s):  
Chunhui Jiang ◽  
Yumiko Kaseda ◽  
Rumi Kumagai ◽  
Yoko Nakano ◽  
Shigenobu Nakamura
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Event Related Potentials ◽  
Related Potentials

scholarly journals A Neurophysiological Study of Semantic Processing in Parkinson’s Disease

2016 ◽  
Vol 23 (1) ◽  
pp. 78-89 ◽  
Author(s):  
Anthony J. Angwin ◽  
Nadeeka N.W. Dissanayaka ◽  
Alison Moorcroft ◽  
Katie L. McMahon ◽  
Peter A. Silburn ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Semantic Processing ◽  
Time Course ◽  
Event Related Potentials ◽  
Mean Amplitude ◽  
Repetition Effects ◽  
Related Potentials ◽  
The Mean ◽  
Written Word

AbstractObjectives: Cognitive-linguistic impairments in Parkinson’s disease (PD) have been well documented; however, few studies have explored the neurophysiological underpinnings of semantic deficits in PD. This study investigated semantic function in PD using event-related potentials. Methods: Eighteen people with PD and 18 healthy controls performed a semantic judgement task on written word pairs that were either congruent or incongruent. Results: The mean amplitude of the N400 for new incongruent word pairs was similar for both groups, however the onset latency was delayed in the PD group. Further analysis of the data revealed that both groups demonstrated attenuation of the N400 for repeated incongruent trials, as well as attenuation of the P600 component for repeated congruent trials. Conclusions: The presence of N400 congruity and N400 repetition effects in the PD group suggests that semantic processing is generally intact, but with a slower time course as evidenced by the delayed N400. Additional research will be required to determine whether N400 and P600 repetition effects are sensitive to further cognitive decline in PD. (JINS, 2017, 23, 78–89)

Working Memory and Facial Expression Recognition in Patients with Parkinson’s Disease

2014 ◽  
Vol 20 (5) ◽  
pp. 496-505 ◽  
Author(s):  
Laura Alonso-Recio ◽  
Pilar Martín-Plasencia ◽  
Ángela Loeches-Alonso ◽  
Juan M. Serrano-Rodríguez
Keyword(s):  
Parkinson’S Disease ◽  
Working Memory ◽  
Parkinson's Disease ◽  
Facial Expression ◽  
Facial Expression Recognition ◽  
Spatial Location ◽  
Expression Recognition ◽  
Emotional Facial Expression ◽  
Emotional Facial Expressions ◽  
Spatial Locations

AbstractFacial expression recognition impairment has been reported in Parkinson’s disease. While some authors have referred to specific emotional disabilities, others view them as secondary to executive deficits frequently described in the disease, such as working memory. The present study aims to analyze the relationship between working memory and facial expression recognition abilities in Parkinson’s disease. We observed 50 patients with Parkinson’s disease and 49 healthy controls by means of an n-back procedure with four types of stimuli: emotional facial expressions, gender, spatial locations, and non-sense syllables. Other executive and visuospatial neuropsychological tests were also administered. Results showed that Parkinson’s disease patients with high levels of disability performed worse than healthy individuals on the emotional facial expression and spatial location tasks. Moreover, spatial location task performance was correlated with executive neuropsychological scores, but emotional facial expression was not. Thus, working memory seems to be altered in Parkinson’s disease, particularly in tasks that involve the appreciation of spatial relationships in stimuli. Additionally, non-executive, facial emotional recognition difficulty seems to be present and related to disease progression. (JINS, 2014, 20, 1–10)

scholarly journals Topographic Mapping of P300 and Frontal Cognitive Function in Parkinson’s Disease

2000 ◽  
Vol 12 (3) ◽  
pp. 143-148 ◽  
Author(s):  
Mutsumi Iijima ◽  
Mikio Osawa ◽  
Makoto Iwata ◽  
Akiko Miyazaki ◽  
Hideaki Tei
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Frontal Lobe ◽  
Event Related Potentials ◽  
Wisconsin Card Sorting Test ◽  
P300 Amplitude ◽  
Oddball Paradigm ◽  
P300 Latency ◽  
Card Sorting ◽  
Related Potentials

The purpose of this study was to evaluate the relationship between P300 that is one of the event-related potentials and frontal cognitive functions in Parkinson’s disease (PD) without clinically apparent dementia.Subjects were 20 PD cases 48 to 79 years of age, all of whom were within normal limits on the Mini-Mental State examination, and 55 age-matched healthy adults.P300 was elicited with an auditory oddball paradigm and recorded at 15 sites on the scalp. Cognitive functioning of the frontal lobe was evaluated using the New Modified Wisconsin Card Sorting Test (WCST) and the Letter Pick-Out Test (LPOT) which reflects selective attention and semantic categorization.P300 latency was delayed in 30.0% of P300 demonstrated abnormal distribution in 20.0%. the WCST and the LPOT were abnormal in 15.0%, P300 latency significantly correlated with number of subcategories achieved on the WCST. P300 amplitude correlated with scores on the LPOT. These results suggest that cognitive dysfunction which linked partly to the frontal lobe might begin in PD even without clinically apparent dementia.

Event-related potentials reveal memory deficits in Parkinson's disease

1999 ◽  
Vol 8 (2) ◽  
pp. 165-172 ◽  
Author(s):  
Hisao Tachibana ◽  
Yasushi Miyata ◽  
Masanaka Takeda ◽  
Minoru Sugita ◽  
Tsunetaka Okita
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Event Related Potentials ◽  
Memory Deficits ◽  
Related Potentials

scholarly journals Compared with Monocyte to High-Density Lipoprotein Ratio (MHR) and Neutrophil to Lymphocyte Ratio (NLR),Neutrophil to High-Density Lipoprotein Ratio (NHR) is more Valuable in the Inflammatory Process of Parkinson's Disease

2021 ◽  
Author(s):  
Qingli Fan ◽  
Zhu Liu ◽  
Shizheng Wu ◽  
Yancheng Lei
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
High Density Lipoprotein ◽  
Early Stage ◽  
Density Lipoprotein ◽  
High Density ◽  
Neutrophil To Lymphocyte Ratio ◽  
Control Group ◽  
Course Of Disease ◽  
Lymphocyte Ratio

Abstract Background: Inflammatory response plays an important role in the pathologic process and prognosis of Parkinson's disease (PD).We investigated the relationship between the neutrophil to high-density lipoprotein ratio (NHR),neutrophil to lymphocyte ratio (NLR),and monocyte to high-density lipoprotein ratio (MHR) on the prediction of PD and its course and severity.Methods: Patients with Parkinson's disease were selected (n=101) and divided into three groups according to the onset cycle:<6 years (n=64),6-10 years (n=23) and > 10 years(n=14).And according to Hoehn and Yahr classification: 1~2.5 is the early stage (n=55);Grades 3~5 are divided into two groups (n=46).In addition, healthy subjects (n=97) matched with the above pd patients in the same period were selected as the control group.In this way, the influence of NHR, NLR, MHR and other indicators on corresponding groups is evaluated.Results: Neutrophils, NHR and NLR in PD group were significantly higher than those in control group. nevertheless, lymphocyte, total cholesterol, low density lipoprotein and hemoglobin were significantly lower than those in the control group. Multi-factor logistic regression analysis indicated that NHR (odds ratio (OR)=1.456,95%CI:1.007~2.104,P=0.046) and NLR(OR=1.663,95%CI:1.101~2.513,P=0.016) were risk factors for Parkinson's disease, while MHR had no significant correlation with Parkinson's disease. The AUC(area under the ROC curve) of PD predicted by NHR and NLR were 0.648(95%CI:0.572~0.724,P=0.0003) and 0.718 (95%CI:0.646~0.790,P<0.0001),respectively, and the critical values for optimal diagnosis were3.104×109/mmol and 1.939×109/mmol. Spearman analysis showed that NHR was significantly negatively correlated with the course of disease.Conclusions: In summary, NHR not only has strong predictive value for PD disease, but also is closely related to the course of disease. NHR levels may be better predictors of long-term clinical outcomes in PD patients than MHR and NLR.

scholarly journals The Use of Event-Related Potentials and Machine Learning to Improve Diagnostic Testing and Prediction of Disease Progression in Parkinson’s Disease

2021 ◽  
Author(s):  
Robin Vlieger ◽  
Elena Daskalaki ◽  
Deborah Apthorp ◽  
Christian J Lueck ◽  
Hanna Suominen
Keyword(s):  
Machine Learning ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Disease Progression ◽  
Objective Assessment ◽  
Diagnostic Testing ◽  
Event Related Potentials ◽  
Disease Status ◽  
Related Potentials ◽  
Machine Learning Models

Current tests of disease status in Parkinson’s disease suffer from high variability, limiting their ability to determine disease severity and prognosis. Event-related potentials, in conjunction with machine learning, may provide a more objective assessment. In this study, we will use event-related potentials to develop machine learning models, aiming to provide an objective way to assess disease status and predict disease progression in Parkinson’s disease.

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