When Tagging Frequency Matters to Attention: Effects on SSVEPs, ERPs, and Cognitive Processing

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The study examined whether the choice of visual flicker tagging frequency affects neural and cognitive measures of selective attention, using SSVEPs and ERPs during detection and 1-back working memory tasks in 27 participants. Central targets and peripheral distractors flickered at either 8.6 Hz or 12 Hz, and the authors found that while the working memory task involved slower responses, more errors, and higher perceived difficulty than detection, tagging frequency strongly influenced neural responses, with 8.6 Hz producing higher SSVEP signal-to-noise ratios than 12 Hz regardless of stimulus location. They also reported that stronger SSVEPs for centrally attended stimuli were linked to fewer working memory errors and larger early visual ERP responses, and that tagging frequency changed the timing and amplitude of early ERP effects, with the paper noting these effects as a methodological non-neutrality rather than a focus on a clinical mechanism. This paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

Selective attention enables the prioritization of task-relevant information while managing distractors, and steady-state visual evoked potentials (SSVEPs) are widely used to track this process by tagging different visual objects at distinct flicker frequencies. However, whether the choice of tagging frequency itself influences other neural and cognitive measures 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 Hz or 12 Hz. The working memory task produced slower responses, more errors, and greater perceived difficulty than detection. Tagging frequency strongly shaped 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 and larger early visual ERP responses, 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 altered the timing and amplitude of early ERP effects. Together, these findings show that tagging frequency is not a neutral methodological parameter, but one that shapes both neural indices of attention and their relationship to cognitive performance.
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Abstract Selective attention enables the prioritization of task-relevant information while managing distractors, and steady-state visual evoked potentials (SSVEPs) are widely used to track this process by tagging different visual objects at distinct flicker frequencies. However, whether the choice of tagging frequency itself influences other neural and cognitive measures 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 Hz or 12 Hz. The working memory task produced slower responses, more errors, and greater perceived difficulty than detection. Tagging frequency strongly shaped 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 and larger early visual ERP responses, 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 altered the timing and amplitude of early ERP effects. Together, these findings show that tagging frequency is not a neutral methodological parameter, but one that shapes both neural indices of attention and their relationship to cognitive performance. Competing Interest Statement The authors have declared no competing interest. Footnotes Note: Data collection was conducted while A.B. was affiliated with Florey Institute of Neuroscience and Mental Health, Melbourne, Australia.

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