Increased Subthalamic Nucleus Deep Brain Stimulation Amplitude Impairs Inhibitory Control of Eye Movements in Parkinson's Disease

Munoz, Miranda J.; Goelz, Lisa C.; Pal, Gian; Karl, Jessica A.; Metman, Leo Verhagen; Sani, Sepehr; Rosenow, Joshua M.; Ciolino, Jody D.; Kurani, Ajay S.; Corcos, Daniel M.; David, Fabian J.

doi:10.1111/ner.13476

Cited by 10 publications

(8 citation statements)

References 52 publications

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“…TEED is expected to be lower with 60 Hz than with 130 Hz stimulation when stimulation amplitude is kept constant. As a recent study showed that changing DBS amplitude influences antisaccade performance ( Munoz et al, 2021 ), we cannot exclude that any performance differences may be related to TEED differences (see also Methods section for further elaboration on this issue).…”

Section: Discussionmentioning

confidence: 99%

High (130 Hz)- and mid (60 Hz)-frequency deep brain stimulation in the subthalamic nucleus differentially modulate response inhibition: A preliminary combined EEG and eye tracking study

Waldthaler

Sperlich

König

et al. 2023

NeuroImage: Clinical

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Section: Discussionmentioning

confidence: 99%

High (130 Hz)- and mid (60 Hz)-frequency deep brain stimulation in the subthalamic nucleus differentially modulate response inhibition: A preliminary combined EEG and eye tracking study

Waldthaler

Sperlich

König

et al. 2023

NeuroImage: Clinical

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“…Munoz et al [ 28 ] studied whether bilateral deep stimulation of the basal ganglia–subthalamic nucleus (STN DBS) may affect the control of inhibition of eye movement in PD. They investigated the effect of DBS amplitude on inhibitory power during an antisaccade procedure on 10 PD patients after their DBS surgery.…”

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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“…Munoz et al [28] studied whether bilateral deep stimulation of the basal gangliasubthalamic nucleus (STN DBS) may affect the control of inhibition of eye movement in PD. They investigated the effect of the DBS amplitude on inhibitory power during an antisaccade procedure on 10 PD patients after their DBS surgery.…”

Section: Em In Pd -Saccades and Antisaccadesmentioning

confidence: 99%

Machine Learning and Eye Movements Give Insights into Neurodegenerative Disease Mechanisms

Przybyszewski¹,

Śledzianowski²,

Chudzik³

et al. 2022

Preprint

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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

Increased Subthalamic Nucleus Deep Brain Stimulation Amplitude Impairs Inhibitory Control of Eye Movements in Parkinson's Disease

Cited by 10 publications

References 52 publications

High (130 Hz)- and mid (60 Hz)-frequency deep brain stimulation in the subthalamic nucleus differentially modulate response inhibition: A preliminary combined EEG and eye tracking study

High (130 Hz)- and mid (60 Hz)-frequency deep brain stimulation in the subthalamic nucleus differentially modulate response inhibition: A preliminary combined EEG and eye tracking study

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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