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Network connectivity of motor control in the ageing brain

Older individuals typically display stronger regional brain activity than younger subjects during motor performance. However, knowledge regarding age-related changes of motor network interactions between brain regions remains scarce. We here investigated the impact of ageing on the interaction of co...

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Detalles Bibliográficos
Autores principales: Michely, J., Volz, L.J., Hoffstaedter, F., Tittgemeyer, M., Eickhoff, S.B., Fink, G.R., Grefkes, C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5852391/
https://www.ncbi.nlm.nih.gov/pubmed/29552486
http://dx.doi.org/10.1016/j.nicl.2018.02.001
Descripción
Sumario:Older individuals typically display stronger regional brain activity than younger subjects during motor performance. However, knowledge regarding age-related changes of motor network interactions between brain regions remains scarce. We here investigated the impact of ageing on the interaction of cortical areas during movement selection and initiation using dynamic causal modelling (DCM). We found that age-related psychomotor slowing was accompanied by increases in both regional activity and effective connectivity, especially for ‘core’ motor coupling targeting primary motor cortex (M1). Interestingly, younger participants within the older group showed strongest connectivity targeting M1, which steadily decreased with advancing age. Conversely, prefrontal influences on the motor system increased with advancing age, and were inversely correlated with reduced parietal influences and core motor coupling. Interestingly, higher net coupling within the prefrontal-premotor-M1 axis predicted faster psychomotor speed in ageing. Hence, as opposed to a uniform age-related decline, our findings are compatible with the idea of different age-related compensatory mechanisms, with an important role of the prefrontal cortex compensating for reduced coupling within the core motor network.