Steady-state visual evoked potential and its applications in studying visual selective attention

Abstract

Steady-state visual evoked potentials (SSVEP), an evoked brain potential, possesses the same frequency as periodic visual stimuli evoking potentials. It is extensively utilized in Brain-Computer Interface and human cognitive research. Moreover, the amplitude of SSVEP is sensitive to resources allocation of visual selective attention, and therefore can always serve as a corresponding electrophysiological indicator. In comparison with event-related potentials (ERPs) presented by P300 and N2pc, SSVEP index can be flexibly applied to a variety of paradigms and avoid errors caused by the brain lateralization as different items can be present in the center or in the same region of the view. Furthermore, SSVEP can reflect attention variation because of its continuity and sensibility to attention fluctuation. Besides, ERPs and SSVEP may reflect diverse attentive stages, and certain evidence suggests the attentive stage that SSVEP reflects is earlier compared with ERPs. Specifically, SSVEP may reflect the regulation that brain regions in charge of advanced cognitive function act on the visual cortex or the earlier stage of visual attention. Nevertheless, ERPs might reveal a later stage accomplished by brain regions responsible for higher-order cognitive processes such as the parietal lobe. In the study of visual selective attention, the frequency tagging is primarily employed to induce SSVEP. Visual stimuli are presented periodically at various frequencies to evoke SSVEP so that the stimuli are frequency tagged. We are able to figure out the allocation of attentive resources in those conditions by means of comparing SSVEP amplitude that the same stimulus evokes in a wide range of conditions. The frequency tagging is particularly appropriate to visual selective attention, especially feature-based and space-based attention. Benefiting from its accurate and sensitive reflection of attentive spatial distribution, SSVEP-based frequency tagging is widely adopted in space-based attention and directly proves the attention focus is shape-flexible and dividable but not always a solid circle. On the other hand, researchers developed the random dot kinematograms (RDK) paradigm for feature-based attention, which prolongs instantaneous feature-based attention process so that SSVEP can detect it. With RDK paradigm, researchers find strong evidence that feature-based attention does exist and has a global attentive activation. However, the other kind of visual selective attention, object-based attention, cannot be explored by frequency tagging because periodic flicker will be a highlighted feature so that participants will consider it as an object recognition marker and further destroy the integrity of the object. In the future, researchers can attempt to add emotion, reward and punishment, and working memory representations as research variables, or to build connections between feature-based attention and spatial-based attention in the process of using SSVEP to explore visual selective attention. In addition, the results of BCI algorithms for SSVEP have a potential for being a new visual selective attention index.