 We also compared with a supervised method - Convolutional Neural Network (CNN)  . Results: For session-by-session alignment, using G-W resulted in  alignment accuracy of 70 \pm 4 \% (weighted mean \pm standard error) , whereas using CNN resulted in classification accuracy of 58%DIFDELCMD < \pm %%% 5 \% across five subjects.
<meaning-changed>  We also compared with a supervised method - Convolutional Neural Network (CNN)  . Results: For session-by-session alignment, using G-W resulted in  alignment accuracy of 70 \pm 4 \% (weighted mean \pm standard error) , whereas using CNN resulted in classification accuracy of 58%DIFDELCMD < \pm %%% 5 \% across five subjects.
 We also compared with a supervised method - Convolutional Neural Network (CNN) . Results: In a sample of six subjects, G-W resulted in alignment accuracy of 70 \pm 4 \% (weighted mean \pm standard error) , whereas using CNN resulted in classification accuracy of 58%DIFDELCMD < \pm %%% 5 \% across five subjects.