Changes in brain functional network connectivity after stroke

Wei Li, Yapeng Li, Wenzhen Zhu, Xi Chen, Wei Li, Yapeng Li, Wenzhen Zhu, Xi Chen

Abstract

Studies have shown that functional network connection models can be used to study brain network changes in patients with schizophrenia. In this study, we inferred that these models could also be used to explore functional network connectivity changes in stroke patients. We used independent component analysis to find the motor areas of stroke patients, which is a novel way to determine these areas. In this study, we collected functional magnetic resonance imaging datasets from healthy controls and right-handed stroke patients following their first ever stroke. Using independent component analysis, six spatially independent components highly correlated to the experimental paradigm were extracted. Then, the functional network connectivity of both patients and controls was established to observe the differences between them. The results showed that there were 11 connections in the model in the stroke patients, while there were only four connections in the healthy controls. Further analysis found that some damaged connections may be compensated for by new indirect connections or circuits produced after stroke. These connections may have a direct correlation with the degree of stroke rehabilitation. Our findings suggest that functional network connectivity in stroke patients is more complex than that in hea-lthy controls, and that there is a compensation loop in the functional network following stroke. This implies that functional network reorganization plays a very important role in the process of rehabilitation after stroke.

Keywords: NSFC grant; brain injury; brain network; functional magnetic resonance imaging; functional network connectivity; independent component analysis; motor areas; nerve regeneration; neural plasticity; neural regeneration; stroke.

Conflict of interest statement

Conflicts of interest: None declared.

Figures

Figure 1
Figure 1
Six independent components highly correlated to the experimental paradigm were chosen. A–F represent the selection components obtained by the group independent component analysis, and the regions comprising each component are shown in Table 3. Component A mainly includes frontal lobe, medial frontal gyrus, and superior frontal gyrus. Component B includes frontal lobe and temporal lobe. Component C includes paracentral lobule, culmen, and cerebellum anterior lobe. Component D includes superior frontal gyrus, occipital lobe and inferior frontal gyrus. Component E includes the covarying regions in limbic lobe and anterior cingulate cortex. Component F includes parietal lobe and precuneus. The color illustrated the activation level. In this study, the components, which were highly correlated to the paradigm of experiments, took priority over other components. Because the purpose of this study was related to motor function, components that had no apparent relationship to motor execution were excluded.
Figure 2
Figure 2
Functional network connectivity model for the healthy controls. Components A–F represent the independent component analysis components that were selected for establishing the functional network (the regions comprising each component are shown in Table 3). The links indicate that there was a correlation between the two components, and the direction of the arrow describes the lag relationship between the two linked components. For example, C→F means that component C precedes component F according to the group lag average.
Figure 3
Figure 3
Functional network connectivity model for the stroke patients. Components A–F represent the independent component analysis components that were selected for establishing the functional network (the regions comprising each component are shown in Table 3). The links indicate that there was a correlation between the two components, and the direction of the arrow describeds the lag relationship between the two linked components. For example, C→F means that component C preceded component F according to the group lag average.
Figure 4
Figure 4
Illustration of lesion location in red for each patient. A–F indicate the six stroke patients in the experiment. The red circled area in the figure is the position of the lesion.
Figure 5
Figure 5
The movement paradigm of the subjects in the magnetic field. The task occurred in 20-second (20 s) blocks of movements alternated with 20 s intervals as rest periods: Rest – Movements (Left) – Rest – Movements (Right) – Rest – Movements (Left) – Rest – Movements (Right) – Rest – Movements (Left) – Rest – Movements (Right) – Rest.

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