FV 11 Physical activity at youth is associated with the strength of connectivity in subcortical locomotor and motor networks: A resting-state fMRI study. (May 2022)

• Record Type: Journal Article
• Authors: Kögler, S.; Hiew, S.; Nguemeni, C.; Pham, M.; Volkmann, J.; Zeller, D.
• Is Part Of: Clinical neurophysiology. Volume 137(2022)
• Page Start: e7
• Publication Date: 2022-05
• Subjects: Neurophysiology -- Periodicals; Electroencephalography -- Periodicals; Electromyography -- Periodicals; Neurology -- Periodicals; 612.8
• DOI: 10.1016/j.clinph.2022.01.019
• Languages: English
• ISSNs: 1388-2457

Abstract

Abstract : Background: In the face of aging and neurological disease some people show better motor function than others despite similar structural preconditions of the nervous system, suggesting the existence of a reserve that enables them to compensate for damages. Previous work in stroke patients has identified connections between regions of the subcortical locomotor and motor networks that are strongly linked to better motor outcome. Objective: To identify associations between resting-state functional connectivity (rs-FC) between regions of the subcortical locomotor and motor networks, performance in a visuomotor adaptation task, and current as well as past physical activity. Methods: In this preliminary study, 11 neurologically healthy individuals (mean age: 43 [21-63]; 55% female) were included. High-resolution T1-weighted MRI was acquired to quantify brain atrophy, and resting-state functional connectivity (rsFC) of the motor network was assessed. A visuomotor adaptation task (VAT) was used as a measure of current adaptive performance. The main measure of adaptive performance were the rates of adaptation and deadaptation. This was measured as the rate of change in error between the start of the adaptation/deadaptation phase and the plateau. The plateau range was determined as the mean ± standard deviation of the last 32 trials. Plateaus were defined as the trial in which subsequent 5 trials fell within the plateau range. Additionally, subjects reported their current and past physical activity. Relationships between regional brain volumes, rsFC values, VAT measures, and reported physical activity were evaluated using Spearman's partial correlations with age as a covariate. Results: Physical activity between ages 14 and 21 was strongly correlated with connectivity between right premotor area (PMA) and left supplementary motor area (SMA) (r=0.89, p=0.001), right PMA and left M1 (r=0.85, p=0.004), left SMA and left PMA (r=0.85, p<0.001), and pedunculopontine nucleus (PPN) and right superior frontal gyrus (SFG) (r=0.85, p<0.001). The rate of deadaptation positively correlated with the volume of the right M1 and right SMA (r=0.70, p=0.023; r=0.69, p=0.027). Conclusion: The present pilot study indicates that physical activity at ages 14-21 may turn out to be an important determinant of individual motor network efficiency. Further steps of analysis will be done to investigate the link between locomotor adaptation rates and motor adaptive capacity. This may ultimately enable us to assess quantitative aspects of the individual motor reserve and to further understand its contribution to successful adaptation to ageing and disease.