ArticleFrontiers in neuroinformatics2018
Decoding Steady-State Visual Evoked Potentials From Electrocorticography.
Article in Frontiers in neuroinformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Multisensory flicker modulates widespread brain networks and reduces interictal epileptiform discharges.Nature communications · 2024Trial
- Signal acquisition of brain-computer interfaces: A medical-engineering crossover perspective review.Fundamental research · 2025Review
- A Methodology for Enhancing SSVEP Features Using Adaptive Filtering Based on the Spatial Distribution of EEG Signals.Micromachines · 2023Article
- Brain-computer interface paradigms and neural coding.Frontiers in neuroscience · 2023Review
- Practical real-time MEG-based neural interfacing with optically pumped magnetometers.BMC biology · 2021Article
- An Open Dataset for Wearable SSVEP-Based Brain-Computer Interfaces.Sensors (Basel, Switzerland) · 2021Article
- High-gamma oscillations precede visual steady-state responses: A human electrocorticography study.Human brain mapping · 2020Article
- Fast periodic visual stimulation to highlight the relationship between human intracerebral recordings and scalp electroencephalography.Human brain mapping · 2020Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We report on a unique electrocorticography (ECoG) experiment in which Steady-State Visual Evoked Potentials (SSVEPs) to frequency- and phase-tagged stimuli were recorded from a large subdural grid covering the entire right occipital cortex of a human subject. The paradigm is popular in EEG-based Brain Computer Interfacing where selectable targets are encoded by different frequency- and/or phase-tagged stimuli. We compare the performance of two state-of-the-art SSVEP decoders on both ECoG- and scalp-recorded EEG signals, and show that ECoG-based decoding is more accurate for very short stimulation lengths (i.e., less than 1 s). Furthermore, whereas the accuracy of scalp-EEG decoding benefits from a multi-electrode approach, to address interfering EEG responses and noise, ECoG decoding enjoys only a marginal improvement as even a single electrode, placed over the posterior part of the primary visual cortex, seems to suffice. This study shows, for the first time, that EEG-based SSVEP decoders can in principle be applied to ECoG, and can be expected to yield faster decoding speeds using less electrodes.
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Registered trials
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