Abstract #1569

Dynamic Causal Modelling identifies abnormal effective connectivity between supratentorial cortex and cerebellum in Multiple Sclerosis.

Gökçe Korkmaz^1,2, Roberta Maria Lorenzi¹, Adnan Alahmadi^2,3, Francesca Ravera^1,2, Rebecca Samson², Egidio D’Angelo^1,4, Fulvia Palesi¹, Ahmed Toosy^2,5, and Claudia A.M. Gandini Wheeler-Kingshott^1,2,4

¹Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy, ²NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom, ³Department of Diagnostic Radiology, College of Applied medical sciences, King Abdulaziz University, Jeddah, Saudi Arabia, ⁴Digital Neuroscience Centre, IRCCS Mondino Foundation, Pavia, Italy, ⁵NMR Research Unit, Department of Brain Repair and Rehabilitation, Queen Square MS Centre, UCL Institute of Neurology, University College London, London, United Kingdom

Synopsis

Keywords: fMRI Analysis, Functional Connectivity, fMRI (task based), Cerebellum, Dynamic Causal Modelling, Effective Connectivity, EDSS

Motivation: Multi-modal approaches are crucial for understanding how pathological conditions affect brain network connectivity and alter the BOLD signal.

Goal(s): Characterise the causal architecture of brain regions activated during a visuomotor task and see how the applied grip force modulates brain connectivity in Multiple Sclerosis (MS).

Approach: Dynamic Causal Modelling (DCM) was used to estimate the effective connectivity of a six-regions brain network in 9 healthy and 15 MS participants.

Results: Both, MS and healthy volunteers presented the same effective connectivity architecture, however grip-force modulation of BOLD signal and cortical-cerebellar recruitment was altered in MS.

Impact: Investigating how MS affects the cortical and cerebellar involvement during a visuomotor task provides better understanding of excitatory/inhibitory mechanisms and unravel the disease impact on brain networks. DCM can lead to more mechanistic insights into MS progression and therapeutic targets.

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