Eye movement especially vertical oculomotor impairment as an aid to assess Parkinson’s disease

Zhang, JianYuan; Zhang, Bin; Ren, Qingguo; Zhong, Qing; Li, Ye; Liu, GuoTao; Ma, Xinyan; Zhao, Chuanzhi

doi:10.1007/s10072-020-04796-6

Cited by 18 publications

(26 citation statements)

References 19 publications

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“…Indeed, our findings are very much in line with those previously reported in the scientific literature on oculomotor anomalies specific to PD. Our finding of an increased rate of saccadic intrusions during fixation confirms previous reports (Tsitsi et al, 2021;Otero et al, 2013;Altiparnak et al, 2006;Zhang et al, 2021). With regards to measures of gaze stability, to our knowledge, only one study reported BCEA and horizontal/vertical gaze SD measures in PD patients and found no significant differences with healthy controls (Tsitsi et al, 2021).…”

Section: Discussionsupporting

confidence: 91%

“…Pro-saccades have been more extensively studied in PD than measures of fixation instability. Findings regarding saccade latency have been mixed to date, with several studies finding either no differences between PD patients and controls (Gitchel et al, 2012;Blekher et al, 2009, Perkins et al, 2021Nagai et al, 2020), shorter latencies in PD (Zhou et al, 2021) and longer latencies in PD (Zhang et al, 2021;Wu et al 2020;Waldthaler et al, 2019). It's unclear why this discrepancy across studies exists, but it may have to do with the type of eye-tracking technology used; the majority of the studies cited above that found either no difference or shorter latencies in PD used infrared eye-trackers from manufacturers such as Eyelink and Tobii, whereas the majority of studies cited above finding increased latencies used devices from other manufacturers such as Micromedical Technologies and Interacoustics, and EyeBrain.…”

Section: Discussionmentioning

confidence: 99%

“…In AD, oculomotor signatures of disease severity have been identified via correlations between specific eye movement characteristics and the Mini-Mental State Examination (MMSE) (Crawford et al, 2005;Noiret et al, 2018;Simó-Servat et al, 2019;Yang et al, 2013). Similarly, in PD, several oculomotor metrics have been shown to correlate with the Unified Parkinson's Disease Rating Scale (UPDRS) or some of its subscales (Antoniades et al, 2015;Lu et al, 2019;Waldthaler et al, 2019;Zhang et al, 2021), whereas in MS similar relationships have been observed between such metrics and the Expanded Disability Status Scale (EDSS) or the Symbol Digit Modalities Test (SDMT) (Gajamange et al, 2019;Nygaard et al, 2015;Kolbe et al, 2014;Sheehy et al, 2020;Polet et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

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A novel tablet-based software for the acquisition and analysis of gaze and eye movement parameters: a preliminary validation study in Parkinson’s disease

Villers-Sidani

Voss

Guitton

et al. 2023

Preprint

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The idea that eye movements can reflect certain aspects of brain function and inform on the presence of neurodegeneration is not a new one. Indeed, a growing body of research has shown that several neurodegenerative disorders, such as Alzheimer's and Parkinson's Disease, present characteristic eye movement anomalies and that specific gaze and eye movement parameters correlate with disease severity. The use of detailed eye movement recordings in research and clinical settings, however, has been limited due to the expensive nature and limited scalability of the required equipment. Here we test a novel technology that can track and measure eye movement parameters using the embedded camera of a mobile tablet. We show that using this technology can replicate several well-known findings regarding oculomotor anomalies in Parkinson's disease, and furthermore show that several parameters significantly correlate with disease severity as assessed with the MDS-UPDRS motor subscale. This tablet-based tool has the potential to accelerate eye movement research via affordable and scalable eye-tracking and aid with the identification of disease status and monitoring of disease progression in clinical settings.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A novel tablet-based software for the acquisition and analysis of gaze and eye movement parameters: a preliminary validation study in Parkinson’s disease

Villers-Sidani

Voss

Guitton

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Zhang et al [ 37 ] investigated 49 Parkinson’s patients, including 35 early-stage (Hoehn and Yahr: 1–2 staging) and 14 advanced PD subjects (Hoehn and Yahr scale: 3 to 5 staging) and 23 healthy subjects. In addition to clinically significant PD symptoms, video-oculography was used to measure EM features such as eye fixation stability, horizontal and vertical reflexive saccade (RS), and horizontal and vertical smooth-pursuit movements.…”

Section: Eye Movements and Neurodegenerative Diseasesmentioning

confidence: 99%

Machine Learning and Eye Movements Give Insights into Neurodegenerative Disease Mechanisms

Przybyszewski

Śledzianowski

Chudzik

et al. 2023

Sensors

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Humans are a vision-dominated species; what we perceive depends on where we look. Therefore, eye movements (EMs) are essential to our interactions with the environment, and experimental findings show EMs are affected in neurodegenerative disorders (ND). This could be a reason for some cognitive and movement disorders in ND. Therefore, we aim to establish whether changes in EM-evoked responses can tell us about the progression of ND, such as Alzheimer’s (AD) and Parkinson’s diseases (PD), in different stages. In the present review, we have analyzed the results of psychological, neurological, and EM (saccades, antisaccades, pursuit) tests to predict disease progression with machine learning (ML) methods. Thanks to ML algorithms, from the high-dimensional parameter space, we were able to find significant EM changes related to ND symptoms that gave us insights into ND mechanisms. The predictive algorithms described use various approaches, including granular computing, Naive Bayes, Decision Trees/Tables, logistic regression, C-/Linear SVC, KNC, and Random Forest. We demonstrated that EM is a robust biomarker for assessing symptom progression in PD and AD. There are navigation problems in 3D space in both diseases. Consequently, we investigated EM experiments in the virtual space and how they may help find neurodegeneration-related brain changes, e.g., related to place or/and orientation problems. In conclusion, EM parameters with clinical symptoms are powerful precision instruments that, in addition to their potential for predictions of ND progression with the help of ML, could be used to indicate the different preclinical stages of both diseases.

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“…Zhang et al [37] investigated 49 Parkinson's patients, including 35 early-stage (Hoehn and Yahr: 1 -2 staging) and 14 advanced PD subjects (Hoehn and Yahr scale: 3 to 5 staging), and 23 healthy subjects. In addition, to clinically significant PD symptoms, video-oculography was used to measure EM such as eye fixation stability, horizontal and vertical reflexive saccade (RS), and horizontal and vertical smooth pursuit movements.…”

Section: Em In Pd -Multimodal Approachmentioning

confidence: 99%

Machine Learning and Eye Movements Give Insights into Neurodegenerative Disease Mechanisms

Przybyszewski¹,

Śledzianowski²,

Chudzik³

et al. 2022

Preprint

View full text Add to dashboard Cite

Humans are a vision-dominated species, and what we see depends on where we look. Therefore, eye movements (EM) are essential to our interactions with the environment, and experimental findings show EM is affected in neurodegenerative disorders (ND). It could be a reason for some cognitive and movement disorders in ND. Therefore, we aim to determine if changes in EM-evoked responses can tell us about ND, such as Alzheimer’s (AD) and Parkinson’s Disease (PD) progression in different stages. In the present review, we have analyzed the results of neurological, psychological, and EM (saccades, antisaccades, pursuit) tests to predict disease progression with Machine Learning (ML) methods. Described predictive algorithms are using various approaches, including Granular Computing, Naive Bayes, Decision Trees/Tables, Logistic Regression, C-/LinearSVC, KNC, and Random Forest. We demonstrated that EM is a robust biomarker for assessing symptom progression in PD and AD. There are also navigation problems in 3D space in both diseases. Consequently, we investigated EM experiments in the virtual space and how they may help find neurodegeneration-related brain changes. In conclusion: EM parameters with clinical symptoms are powerful precision instruments that, in addition to predictions of ND progression with the help of ML, could be used to indicate the different preclinical stages of both diseases.

show abstract

Eye movement especially vertical oculomotor impairment as an aid to assess Parkinson’s disease

Cited by 18 publications

References 19 publications

A novel tablet-based software for the acquisition and analysis of gaze and eye movement parameters: a preliminary validation study in Parkinson’s disease

A novel tablet-based software for the acquisition and analysis of gaze and eye movement parameters: a preliminary validation study in Parkinson’s disease

Machine Learning and Eye Movements Give Insights into Neurodegenerative Disease Mechanisms

Machine Learning and Eye Movements Give Insights into Neurodegenerative Disease Mechanisms

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