Di Scala G, Dupuy M, Guillaud E, Doat E, Barse E, Dillhareguy B, Jean F A M, Audiffren M, Cazalets J R, Chanraud S
a Institut de Neurosciences Cognitives et Intégratives d'Aquitaine (INCIA), Université de Bordeaux, CNRS-UMR 5287 , Bordeaux , France.
b École Pratique des Hautes Études (EPHE), PSL Research University , Paris , France.
Exp Aging Res. 2019 Jan-Feb;45(1):41-56. doi: 10.1080/0361073X.2018.1560108. Epub 2019 Jan 11.
Background/Study context: Posture and gait are complex sensorimotor functions affected by age. These difficulties are particularly apparent when performing cognitively demanding tasks. Characterizing the functional organization of brain networks involved in these associations remains a challenge because of the incompatibility of brain imagery techniques with gross body movements. The present study aimed at testing whether resting-state functional connectivity of sensorimotor networks is associated with posture and gait performance recorded offline, in young and older adults.
Young (n = 12, mean = 24.1 y/o) and older (n = 14, mean = 65.6 y/o) healthy adults were tested for stability of their posture and gait. Four hours later, anatomical and functional brain imaging data were collected with Magnetic Resonance Imaging (MRI). Bilateral precentral and postcentral gyri were used as seeds in a graph theory analysis focused on global and local efficiency. The possible association between these data and posture and gait performance was examined.
Both samples presented similar sensorimotor graphs, but with different global and local efficiencies (small world properties). The association between the networks' graph measures and posture and gait performance also differed across groups: local efficiency was correlated with gait stability in challenging conditions in older adults, but not in young adults.
This exploratory study suggests that combining analyses of functional networks and offline body movement may provide important information about motor function. In older adults, the association between graph properties of the sensorimotor network and gait performance in challenging conditions may be indicative of compensatory processes. Prospective studies involving more subjects with a larger age range are warranted.
背景/研究背景:姿势和步态是受年龄影响的复杂感觉运动功能。在执行需要认知能力的任务时,这些困难尤为明显。由于脑成像技术与全身运动不兼容,表征参与这些关联的脑网络的功能组织仍然是一个挑战。本研究旨在测试感觉运动网络的静息态功能连接是否与年轻人和老年人离线记录的姿势和步态表现相关。
对年轻(n = 12,平均年龄 = 24.1岁)和年长(n = 14,平均年龄 = 65.6岁)的健康成年人进行姿势和步态稳定性测试。四小时后,通过磁共振成像(MRI)收集解剖学和功能性脑成像数据。在专注于全局和局部效率的图论分析中,将双侧中央前回和中央后回用作种子点。检查这些数据与姿势和步态表现之间的可能关联。
两个样本呈现出相似的感觉运动图,但全局和局部效率(小世界特性)不同。网络的图测量与姿势和步态表现之间的关联在不同组中也有所不同:局部效率与年长成年人在具有挑战性的条件下的步态稳定性相关,但与年轻成年人无关。
这项探索性研究表明,将功能网络分析与离线身体运动相结合可能会提供有关运动功能的重要信息。在年长成年人中,感觉运动网络的图特性与具有挑战性条件下的步态表现之间的关联可能表明存在代偿过程。有必要开展涉及更多受试者且年龄范围更广的前瞻性研究。