Additional file 1: of Exploiting the heightened phase synchrony in patients with neuromuscular disease for the establishment of efficient motor imagery BCIs

Figure S1. Topographical representation of the statistically significant functional couplings (shown in Fig. 4). In the emerging graphs, the edge-width reflects the strength of the coupling and the node-size the number of edges incident to that node. The shown results correspond to Group-level analysis and reflect higher connectivity in the NMD patients. Figure S2. The classification performance in the state discrimination task (“left” vs “right”), when band-specific power-spectral density estimates are employed. Figure S3. The classification performance in the state discrimination task (“left” vs “right”), when the Common Spatial Pattern algorithm is employed in the 8–30 Hz frequency band as described by Fabien Lotte [1]. (ZIP 819 kb)

补充图S1：图4中展示的具有统计学显著性的功能连接（functional couplings）的脑区拓扑可视化结果。在该网络图中，边宽代表连接强度，节点尺寸则对应于该节点所关联的边的总数。本次展示的结果基于组水平分析，反映出NMD患者的脑连接水平更高。
补充图S2：当采用频段特异性功率谱密度估计方法时，状态判别任务（“左侧”与“右侧”）中的分类性能结果。
补充图S3：当按照Fabien Lotte[1]所述方法，在8–30 Hz频段下使用公共空间模式（Common Spatial Pattern, CSP）算法时，状态判别任务（“左侧”与“右侧”）中的分类性能结果。（压缩包大小：819 KB）