Bharadwaj et al. (2023) present a comments paper evaluating the classification accuracy of several state-of-the-art methods using EEG data averaged over random class samples. According to the results, some of the methods achieve above-chance accuracy, while the method proposed in (Palazzo et al. 2020), that is the target of their analysis, does not. In this rebuttal, we address these claims and explain why they are not grounded in the cognitive neuroscience literature, and why the evaluation procedure is ineffective and unfair.

Rebuttal to 'Comments on 'Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features' '

Palazzo S.;Spampinato C.;Kavasidis I.;Giordano D.;
2024-01-01

Abstract

Bharadwaj et al. (2023) present a comments paper evaluating the classification accuracy of several state-of-the-art methods using EEG data averaged over random class samples. According to the results, some of the methods achieve above-chance accuracy, while the method proposed in (Palazzo et al. 2020), that is the target of their analysis, does not. In this rebuttal, we address these claims and explain why they are not grounded in the cognitive neuroscience literature, and why the evaluation procedure is ineffective and unfair.
2024
brain-computer interface
EEG
human vision
neuroimaging
neuroscience
Object classification
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/651089
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