Steady-state visually evoked potentials: focus on essential paradigms and future perspectives.

By François-Benoît Vialatte, Monique Maurice, Justin H. G. Dauwels, Andrzej S. Cichocki. Progress in neurobiology, 2010

1,055 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/27e95e2fd8cd693af572aff4a669da107dd664a4

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In Cellular and Molecular Neuroscience

In Cognitive Neuroscience

Citations in the corpus

A High-Speed Brain Speller using steady-State Visual evoked potentials (2014, background): “47 For example, a 4-target system can be realized using two frequencies ( e.g. , 10Hz and 15Hz) and two phases ( e.g. , 0 and 180 degrees).”
A Comparison Study of Canonical Correlation Analysis Based Methods for Detecting Steady-State Visual Evoked Potentials (2015, methodology): “Various target identification methods have been developed for detecting SSVEPs in BCIs [2 – 4].”
High-speed spelling with a noninvasive brain–computer interface (2015, background): “Recently, the BCI speller using steady-state VEPs (SSVEPs) has attracted increasing attention due to its high communication rate and little user training (4, 10, 11).”
A Benchmark Dataset for SSVEP-Based Brain–Computer Interfaces (2017, neutral): “Recently, steady-state visual evoked potentials (SSVEPs) have been widely used in visual BCIs due to advantages of high information transfer rate (ITR) and little user training [8], [9].”
Filter bank canonical correlation analysis for implementing a high-speed SSVEP-based brain–computer interface (2015, background): “The steady-state visual evoked potential (SSVEP)-based brain – computer interface (BCI) has attracted more and more attention in the ﬁ eld of BCI due to its advantages such as high information transfer rate (ITR) and little user training (Wang et al 2008, Vialatte et al 2010).”
A comprehensive review of EEG-based brain–computer interface paradigms (2019, background): “As opposed to transient VEP which is used to measure the travel time of a visual stimulus from the eye to the occipital cortex [117], SSVEP depicts a stable characteristic of the spectral content of EEG signals.”
Rhythmic visual stimulation as a window into early brain development: A systematic review (2023, background): “By presenting stimuli at different rhythmic stimulation frequencies, it is possible to induce resonant rhythmic brain responses and to assess these responses in the electroencephalogram (EEG) (Vialatte et al., 2010).”
GLOBAL ACADEMIC TRENDS OF METABOLIC AND ELECTRICAL BIOMEDICAL TOOLS IN MARKETING (2024, unknown): “SST furnishes immediate insight into neural oscillations and functional connectivity in response to stimuli through the utilisation of high-density electroencephalography (EEG) recordings (Vialatte et al., 2010).”