Generating Visual Flickers for Eliciting Robust Steady-State Visual Evoked Potentials at Flexible Frequencies Using Monitor Refresh Rate

• Published in: PloS one Vol. 9; no. 6; p. e99235
• Main Authors: Nakanishi, Masaki, Wang, Yijun, Wang, Yu-Te, Mitsukura, Yasue, Jung, Tzyy-Ping
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 11.06.2014; Public Library of Science (PLoS)
• Subjects: Approximation; Biology and Life Sciences; Brain; Brain-Computer Interfaces; Cellular telephones; Comparative analysis; Computer applications; Electroencephalography; Engineering; Engineering and Technology; Evoked potentials; Evoked Potentials, Visual; Flicker Fusion; Human-computer interface; Humans; Implants; Information transfer; Latency; Mathematical analysis; Nervous system; Neurosciences; Scalp; Steady state; User training; Visual evoked potentials; La Jolla California; United States > US; California
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0099235

In the study of steady-state visual evoked potentials (SSVEPs), it remains a challenge to present visual flickers at flexible frequencies using monitor refresh rate. For example, in an SSVEP-based brain-computer interface (BCI), it is difficult to present a large number of visual flickers simultaneously on a monitor. This study aims to explore whether or how a newly proposed frequency approximation approach changes signal characteristics of SSVEPs. At 10 Hz and 12 Hz, the SSVEPs elicited using two refresh rates (75 Hz and 120 Hz) were measured separately to represent the approximation and constant-period approaches. This study compared amplitude, signal-to-noise ratio (SNR), phase, latency, scalp distribution, and frequency detection accuracy of SSVEPs elicited using the two approaches. To further prove the efficacy of the approximation approach, this study implemented an eight-target BCI using frequencies from 8-15 Hz. The SSVEPs elicited by the two approaches were found comparable with regard to all parameters except amplitude and SNR of SSVEPs at 12 Hz. The BCI obtained an averaged information transfer rate (ITR) of 95.0 bits/min across 10 subjects with a maximum ITR of 120 bits/min on two subjects, the highest ITR reported in the SSVEP-based BCIs. This study clearly showed that the frequency approximation approach can elicit robust SSVEPs at flexible frequencies using monitor refresh rate and thereby can largely facilitate various SSVEP-related studies in neural engineering and visual neuroscience.