RESUMO
Aging is typically associated with substantial declines in motor functioning as well as robust changes in the functional organization of brain networks. Previous research has investigated the link between these 2 age-varying factors but examinations were predominantly limited to the functional organization within motor-related brain networks. Little is known about the relationship between age-related behavioral impairments and changes in functional organization at the whole brain (i.e., multiple network) level. This knowledge gap is surprising given that the decreased segregation of brain networks (i.e., increased internetwork connectivity) can be considered a hallmark of the aging process. Accordingly, we investigated the association between declines in motor performance across the adult lifespan (20-75 years) and age-related modulations of functional connectivity within and between resting state networks. Results indicated that stronger internetwork resting state connectivity observed as a function of age was significantly related to worse motor performance. Moreover, performance had a significantly stronger association with the strength of internetwork as compared with intranetwork connectivity, including connectivity within motor networks. These findings suggest that age-related declines in motor performance may be attributed to a breakdown in the functional organization of large-scale brain networks rather than simply age-related connectivity changes within motor-related networks.
Assuntos
Envelhecimento/fisiologia , Envelhecimento/psicologia , Encéfalo/fisiologia , Desempenho Psicomotor/fisiologia , Adulto , Idoso , Mapeamento Encefálico , Feminino , Humanos , Imageamento por Ressonância Magnética , Masculino , Pessoa de Meia-Idade , Vias Neurais/fisiologia , Adulto JovemRESUMO
Recent research on traumatic brain injury (TBI) has shown that impairments in cognitive and executive control functions are accompanied by a disrupted neural connectivity characterized by white matter damage. We constructed binary and weighted brain structural networks in 21 patients with chronic TBI and 17 healthy young adults utilizing diffusion tensor tractography and calculated topological properties of the networks using a graph theoretical method. Executive function was assessed with the local global task and the trail making task, requiring inhibition, updating, and switching. The results revealed that TBI patients were less successful than controls on the executive tasks, as shown by the higher reaction times, higher switch costs, and lower accuracy rates. Moreover, both TBI patients and controls exhibited a small world topology in their white matter networks. More importantly, the TBI patients demonstrated increased shortest path length and decreased global efficiency of the structural network. These findings suggest that TBI patients have a weaker globally integrated structural brain network, resulting in a limited capacity to integrate information across brain regions. Furthermore, we showed that the white matter networks of both groups contained highly connected hub regions that were predominately located in the parietal cortex, frontal cortex, and basal ganglia. Finally, we showed significant correlations between switching performance and network property metrics within the TBI group. Specifically, lower scores on the switching tasks corresponded to a lower global efficiency. We conclude that analyzing the structural brain network connectivity provides new insights into understanding cognitive control changes following brain injury.