Functional connectivity of brain associated with passive range of motion exercise: Proprioceptive input promoting motor activation?

被引:13
|
作者
Nasrallah, Fatima A. [1 ,6 ]
Mohamed, Abdalla Z. [1 ]
Campbell, Megan E. J. [1 ]
Yap, Hong Kai [2 ,3 ]
Yeow, Chen-Hua [4 ]
Lim, Jeong Hoon [5 ]
机构
[1] Univ Queensland, Queensland Brain Inst, Brisbane, Qld 4072, Australia
[2] Singapore Inst Neurotechnol, Singapore, Singapore
[3] Adv Robot Ctr, Singapore, Singapore
[4] Natl Univ Singapore, Dept Biomed Engn, Singapore 117583, Singapore
[5] Natl Univ Singapore, Yong Loo Lin Sch Med, Dept Med, Singapore 119228, Singapore
[6] Natl Univ Singapore, Clin Imaging Res Ctr, Singapore, Singapore
关键词
Functional magnetic resonance imaging; Soft actuators; Soft wearable robotics; Tactile stimulation; Proprioceptive stimulation; BAYESIAN MODEL SELECTION; 10 SIMPLE RULES; AREA; ROBUST; OPTIMIZATION; REGISTRATION; ORGANIZATION; UNCERTAINTY; MOVEMENT; ACCURATE;
D O I
10.1016/j.neuroimage.2019.116023
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Soft robotics have come to the forefront of devices available for rehabilitation following stroke; however, objective evaluation of the specific brain changes following rehabilitation with these devices is lacking. In this study, we utilized functional Magnetic Resonance Imaging (fMRI) and dynamic causal modeling (DCM) to characterize the activation of brain areas with a MRI compatible glove actuator compared to the conventional manual therapy. Thirteen healthy volunteers engaged in a motor-visual fMRI task under four different conditions namely active movement, manual passive movement, passive movement using a glove actuator, and crude tactile stimulation. Brain activity following each task clearly identified the somatosensory motor area (SMA) as a major hub orchestrating activity between the primary motor (M1) and sensory (S1) cortex. During the glove-induced passive movement, activity in the motor-somatosensory areas was reduced, but there were significant increases in motor cortical activity compared to manual passive movement. We estimated the modulatory signaling from within a defined sensorimotor network (SMA, M1, and S1), through DCM and highlighted a dual-gating of sensorimotor inputs to the SMA. Proprioceptive signaling from S1 to the SMA reflected positive coupling for the manually assisted condition, while M1 activity was positively coupled to the SMA during the glove condition. Importantly, both the S1 and M1 were shown to influence each other's connections with the SMA, with inhibitory nonlinear modulation by the M1 on the S1-SMA connection, and similarly S1 gated the M1-SMA connection. The work is one of the first to have applied effective connectivity to examine sensorimotor activity ensued by manual or robotic passive range of motion exercise, crude tactile stimulation, and voluntary movements to provide a basis for the mechanism by which soft actuators can alter brain activity.
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页数:10
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