Macroscale Gradient-Informed Neural Oscillation Topography in Parkinson's Disease
Poster No:
155
Submission Type:
Abstract Submission
Authors:
Hao Ding1, Bange Manuel2, Hannah Küehe3, Jenny Blech3, Muthuraman Muthuraman2
Institutions:
1Universitätsklinikum würzburg, würzburg, würzburg, 2Universität Augsburg, Augsburg, Augsburg, 3Universitätsmedizin Mainz, Mainz, Mainz
First Author:
Co-Author(s):
Introduction:
Parkinson's disease (PD) is a complex neurological disorder characterized by aberrant beta and symptom specific gamma oscillations linked to motor and cognitive deficits. The roles of these oscillations and their specific topographic brain areas during resting and active states remain underexplored, underscoring the need to identify reliable spatial biomarkers and neural oscillatory target regions for therapeutic options.
Methods:
We investigated 35 patients with PD and 35 age- and sex-matched healthy controls using 256-channel high-density electroencephalography during both resting-state and a simple motor task, where participants held both hands outstretched in front of their body. Individual T1-weighted MRI scans were acquired for source reconstruction. Functional connectivity was quantified using the imaginary component of the complex Pearson correlation coefficient, and functional gradients were computed using normalized angle and diffusion embedding. Directional information flow was estimated using deep learning-based Granger causality. Significant topographic differences between PD and controls were assessed using a surface linear model, and its validation was assessed through classification accuracy and prediction of clinical ratings. Enrichment analysis explored the neurobiological mechanisms associated with the identified differential representations.
Results:
Beta-band gradients exhibited significant differences in the motor and prefrontal cortices during resting and motor states (P<0.05), with prefrontal alterations correlating with disease duration. Gamma-band gradients showed elevated activity in the temporal lobe during rest and hypoactivity in the somatosensory cortex during motor tasks (P<0.05). These clusters classified PD patients with 90% accuracy and precisely predicted clinical severity (P<0.05). Community-based analysis highlighted somatomotor network deficits during resting state and ventral network impairments during tasks. Enrichment analysis revealed disruptions in dopaminergic synapse, calcium signalling, and neurotransmitter transport pathways, correlating with PD-specific conditions such as Parkinsonian disorders, Lewy body disease, and sleep disturbances (P<0.05).
Conclusions:
Our findings reveal crucial spatial neural oscillatory targets in PD, offering potential biomarkers for monitoring and treatment. Frequency-specific changes in beta and gamma bands, particularly in motor, prefrontal, temporal, and somatosensory cortices, could guide adaptive deep brain stimulation (aDBS). These insights, especially when refined through techniques like electrocorticography, provide specific targets for advancing aDBS and neuromodulation therapies in PD. By connecting these patterns to clinical severity and molecular mechanisms, our study lays the foundation for more precise and effective PD treatments.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Novel Imaging Acquisition Methods:
EEG
Physiology, Metabolism and Neurotransmission:
Neurophysiology of Imaging Signals 2
Keywords:
DISORDERS
Electroencephaolography (EEG)
1|2Indicates the priority used for review
Abstract Information
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Guerra, A., Colella, D., Giangrosso, M., Cannavacciuolo, A., Paparella, G., Fabbrini, G., ... & Bologna, M. (2022). Driving motor cortex oscillations modulates bradykinesia in Parkinson’s disease. Brain, 145(1), 224-236.