Towards increased data transmission rate for a three-class metabolic brain-computer interface based on transcranial Doppler ultrasound

► We investigated the future viability of a three-class ultrasound-based BCI. ► We differentiated three mental states offline based on changes in blood flow. ► We determined the time window that maximized data transmission rate. ► Data transmission rate peaked when mental task length was 20 s. ► Classification accuracies exceeded 70% using time-domain features and LDA.