Journal
DEVELOPMENTAL COGNITIVE NEUROSCIENCE
Volume 54, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.dcn.2022.101066
Keywords
Steady-state visual evoked potential (ssVEP); Frequency tagging; Frequency domain; Time-frequency domain; MATLAB; FreqTag
Categories
Funding
- National Science Foundation, US [1728133]
- National Institute of Human Health and Child Development, US [R21HD102715-01]
- Direct For Social, Behav & Economic Scie
- Division Of Behavioral and Cognitive Sci [1728133] Funding Source: National Science Foundation
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ssVEP frequency tagging is a method increasingly used in electrophysiological studies of visual attention and perception, suitable for studying various populations. Specific signal processing methods are necessary for leveraging the strength of this method.
Steady-state visual evoked potential (ssVEP) frequency tagging is an increasingly used method in electrophysiological studies of visual attention and perception. Frequency tagging is suitable for studies examining a wide range of populations, including infants and children. Frequency tagging involves the presentation of different elements of a visual array at different temporal rates, thus using stimulus timing to tag the brain response to a given element by means of a unique time signature. Leveraging the strength of the ssVEP frequency tagging method to isolate brain responses to concurrently presented and spatially overlapping visual objects requires specific signal processing methods. Here, we introduce the FreqTag suite of functions, an open source MATLAB toolbox. The purpose of the FreqTag toolbox is three-fold. First, it will equip users with a set of transparent and reproducible analytical tools for the analysis of ssVEP data. Second, the toolbox is designed to illustrate fundamental features of frequency domain and time-frequency domain approaches. Finally, decision criteria for the application of different functions and analyses are described. To promote reproducibility, raw algorithms are provided in a modular fashion, without additional hidden functions or transformations. This approach is intended to facilitate a fundamental understanding of the transformations and algorithmic steps in FreqTag, and to allow users to visualize and test each step in the toolbox.
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