Large-Scale Network underpinnings of sustained gripping in Parkinson’s Disease

Poster Session D - Monday, April 15, 2024, 8:00 – 10:00 am EDT, Sheraton Hall ABC

Oliver Kohl¹ (oliver.kohl@psych.ox.ac.uk), Chetan Gohil¹, Nahid Zokaei¹, Mark Woolrich¹, Kia Nobre^1,2, Andrew Quinn^1,3; ¹University of Oxford, ²Yale University, ³University of Birmingham

Parkinson’s Disease (PD) is a neurodegenerative disorder affecting movement control. Previous magnetoencephalography (MEG) studies have demonstrated movement-related modulations of motor cortical activity to be attenuated in PD. While most research investigating oscillatory power during movements focused on motor cortical activations, their network context has been widely neglected. We hypothesise that investigating motor cortical oscillatory activation from a network perspective offers a more precise description of oscillatory processes underpinning movement, and may provide more sensitive markers of changes related to PD. We analysed MEG recordings of healthy controls (HC) and PD volunteers obtained during performance of a sustained-gripping task with two grip-force conditions. Following source reconstruction and parcellating of the data, we applied a Hidden Markov Model to obtain a dynamic, large-scale network description of the data, based on distinctive patterns of oscillatory activity. Spectral features and trial-averaged occurrence probabilities of the extracted networks were compared between the two groups. Two networks with increased motor cortical activation were identified, each characterised by unique spatial-temporal characteristics. The occurrence probabilities of these networks were associated with task-related beta power modulations and gripping strength. The dynamics of both networks did not differ between HCs and PD volunteers, but motor cortical beta power was decreased during occurrences of one of the two networks, characterised by high activations in motor cortical and posterior areas, in PD volunteers. Our results open new avenues for investigating oscillatory processes underlying movements and markers of PD by highlighting the importance of studying motor cortical oscillatory activation within its network context.

Topic Area: PERCEPTION & ACTION: Motor control