Abstract
Background.
Passive robot-generated arm movements in conjunction with
proprioceptive decision making and feedback modulate functional
connectivity (FC) in sensory motor networks and improve sensorimotor
adaptation in normal individuals. This proof-of-principle study
investigates whether these effects can be observed in stroke patients.
Methods.
A total of 10 chronic stroke patients with a range of stable motor and
sensory deficits (Fugl-Meyer Arm score [FMA] 0-65, Nottingham Sensory
Assessment [NSA] 10-40) underwent resting-state functional magnetic
resonance imaging before and after a single session of robot-controlled
proprioceptive training with feedback. Changes in FC were identified in
each patient using independent component analysis as well as a seed
region–based approach. FC changes were related to impairment and changes
in task performance were assessed.
Results. A single training
session improved average arm reaching accuracy in 6 and proprioception
in 8 patients. Two networks showing training-associated FC change were
identified. Network C1 was present in all patients and network C2 only
in patients with FM scores >7. Relatively larger C1 volume in the
ipsilesional hemisphere was associated with less impairment (r = 0.83 for NSA, r
= 0.73 for FMA). This association was driven by specific regions in the
contralesional hemisphere and their functional connections
(supramarginal gyrus with FM scores r = 0.82, S1 with NSA scores r = 0.70, and cerebellum with NSA score r = −0.82).
Conclusion.
A single session of robot-controlled proprioceptive training with
feedback improved movement accuracy and induced FC changes in sensory
motor networks of chronic stroke patients. FC changes are related to
functional impairment and comprise bilateral sensory and motor network
nodes.
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