Abstract
Steady-state visual evoked potentials (SSVEPs) are widely used in human neuroscience studies and applications such as brain-computer interface. Surprisingly, no previous study has systematically evaluated different reference methods for SSVEP analysis, despite that signal reference is crucial for proper assessment of neural activities. In the present study, using four datasets from our previous SSVEP studies (Chen et al., 2017a, 2017b, 2019) and three public datasets from other studies (Baker et al., 2021; Lygo et al., 2021; Vilidaite et al., 2018), we compared four reference methods: monopolar reference, common average reference, linked-mastoids reference, and Laplacian reference. The quality of the resulted SSVEP signals was compared in terms of both signal-to-noise ratios (SNRs) and reliability. The results showed that Laplacian reference, which uses signals at the electrode Oz after subtracting the average of nearby electrodes to reduce common noise, gave rise to the highest SNRs. Furthermore, the Laplacian reference resulted in SSVEP signals that were highly reliable across recording sessions or trials. These results suggest that Laplacian reference is optimal for SSVEP studies and applications. Laplacian reference is especially advantageous for SSVEP experiments where short preparation time is preferred, since it requires only data from a few occipital electrodes.