A collaborative guide to Rapid Invisible Frequency Tagging (RIFT): Methods, insights, and recommendations

Publication date

2026

Authors

Arora, Kabir
Hustá, Cecília
Bouwkamp, Floortje
Seijdel, Noor
Bai, Songyun
Han, Qiu
Kenemans, LeonISNI 0000000390041596
van der Stigchel, S.ISNI 0000000396732697
Gayet, SuryaORCID 0000-0001-9728-1272ISNI 000000037261256X
Spaak, Eelke

Editors

Advisors

Supervisors

Document Type

Article
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License

cc_by

Abstract

Rapid Invisible Frequency Tagging (RIFT) is a recent advance in frequency tagging that exploits novel, high-frequency displays to modulate luminance at imperceptibly high frequencies. RIFT goes beyond low-frequency tagging by allowing researchers to track neural responses to rhythmic stimulation while avoiding perceptual confounds. RIFT is thus a promising method to address central questions in rhythmic cognition, including attention, multimodal integration, and the neural mechanisms underlying oscillatory coordination in perception. However, setting up a RIFT study involves several technical and conceptual considerations. In an effort to make RIFT more accessible, we provide a comprehensive guide for implementing RIFT in cognitive neuroscience. On the basis of the joint experiences and data-driven insights of multiple laboratories, we provide practical recommendations derived from empirical datasets to improve reproducibility, covering hardware requirements, stimulus design, analysis approaches, and interpretation of results. We hope that this guide helps readers to both identify the conceptual areas where RIFT offers promising insights and navigate the technical caveats that come with the approach.

Keywords

neural oscillations, RIFT, SSVEP, Neuroscience (miscellaneous), Medicine (miscellaneous), Radiology Nuclear Medicine and imaging, Clinical Neurology

Citation

Arora, K, Hustá, C, Bouwkamp, F, Seijdel, N, Bai, S, Han, Q, Kenemans, J L, Van der Stigchel, S, Gayet, S, Spaak, E, Chota, S & Drijvers, L 2026, 'A collaborative guide to Rapid Invisible Frequency Tagging (RIFT) : Methods, insights, and recommendations', Imaging Neuroscience, vol. 4, IMAG.a.1273. https://doi.org/10.1162/IMAG.a.1273