Visual tagging frequency influences SSVEP and early ERP responses during detection and working memory
Abstract Steady-state visual evoked potentials (SSVEPs) are widely used to track selective attention by tagging different visual objects at distinct flicker frequencies. However, whether the choice of tagging frequency itself influences neural and cognitive measures beyond the SSVEP response remains unclear. Here, 27 participants performed detection and 1-back working memory tasks while a central target and peripheral distractors flickered at either 8.6–12 Hz, with the location of each frequency counterbalanced across participants. The working memory task produced slower responses, more errors, and greater perceived difficulty than detection. Tagging frequency strongly influenced neural responses, with 8.6 Hz eliciting higher SSVEP signal-to-noise ratios than 12 Hz regardless of stimulus location. Nevertheless, stronger SSVEP responses for centrally attended stimuli were associated with fewer working memory errors, while SSVEPs for attended and distractor stimuli were negatively correlated. In addition, the working memory task produced a larger P1-N1 peak-to-peak difference, and tagging frequency modulated the amplitude of early ERP responses. Together, these findings indicate that tagging frequency can influence SSVEP and early ERP measures and should be treated as an active design factor in frequency-tagging studies.
Authors
- David Bruce Grayden (ORCID: https://orcid.org/0000-0002-5497-7234)
- Ayla Barutchu (ORCID: https://orcid.org/0000-0002-8744-3458)
- Olivia L. Carter (ORCID: https://orcid.org/0000-0001-7708-6154)
- Mohit Naresh Shivdasani (ORCID: https://orcid.org/0000-0002-0692-4971)
- Robert Hester (ORCID: https://orcid.org/0000-0003-0982-8026)
- Jihan Yang
Institutions
- Deakin University (AU)
- The University of Melbourne (AU)
- Florey Institute of Neuroscience and Mental Health (AU)
- UNSW Sydney (AU)
Publication Details
- Journal
- Scientific Reports
- Published
- 2026-10-31
- DOI
- https://doi.org/10.1038/s41598-026-76566-x
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 0.00