Resting-State Functional Networks Correlate with Motor Performance in a Complex Visuomotor Task
An EEG Microstate Pilot Study on Healthy Individuals
Joaquin Penalver-Andres (University of Bern)
Karin A. Buetler (University of Bern)
Thomas Koenig (University of Bern)
R. M. Müri (University of Bern)
Laura Marchal (TU Delft - Human-Robot Interaction, University of Bern)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
Developing motor and cognitive skills is needed to achieve expert (motor) performance or functional recovery from a neurological condition, e.g., after stroke. While extensive practice plays an essential role in the acquisition of good motor performance, it is still unknown whether certain person-specific traits may predetermine the rate of motor learning. In particular, learners’ functional brain organisation might play an important role in appropriately performing motor tasks. In this paper, we aimed to study how two critical cognitive brain networks—the Attention Network (AN) and the Default Mode Network (DMN)—affect the posterior motor performance in a complex visuomotor task: virtual surfing. We hypothesised that the preactivation of the AN would affect how participants divert their attention towards external stimuli, resulting in robust motor performance. Conversely, the excessive involvement of the DMN—linked to internally diverted attention and mind-wandering—would be detrimental for posterior motor performance. We extracted seven widely accepted microstates—representing participants mind states at rest—out of the Electroencephalography (EEG) resting-state recordings of 36 healthy volunteers, prior to execution of the virtual surfing task. By correlating neural biomarkers (microstates) and motor behavioural metrics, we confirmed that the preactivation of the posterior DMN was correlated with poor posterior performance in the motor task. However, we only found a non-significant association between AN preactivation and the posterior motor performance. In this EEG study, we propose the preactivation of the posterior DMN—imaged using EEG microstates—as a neural trait related to poor posterior motor performance. Our findings suggest that the role of the executive control system is to preserve an homeostasis between the AN and the DMN. Therefore, neurofeedback-based downregulation of DMN preactivation could help optimise motor training.
help_outline