Before revision:  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 5 \% across five subjects.
After revision:  We compared these approaches with three supervised methods: multi-class Support Vector Machine (SVM), 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 5 \% across five subjects.