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Confounds in the Data-Comments on "Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features".
IEEE Transactions on Pattern Analysis and Machine Intelligence ( IF 20.8 ) Pub Date : 2022-11-07 , DOI: 10.1109/tpami.2021.3121268
Hamad Ahmed 1 , Ronnie B. Wilbur 2 , Hari M. Bharadwaj 3 , Jeffrey Mark Siskind 1
Affiliation  

Neuroimaging experiments in general, and EEG experiments in particular, must take care to avoid confounds. A recent TPAMI paper uses data that suffers from a serious previously reported confound. We demonstrate that their new model and analysis methods do not remedy this confound, and therefore that their claims of high accuracy and neuroscience relevance are invalid.

中文翻译:

在关于“通过神经活动和视觉特征的多模式学习解码大脑表征”的数据评论中混淆。

一般的神经影像学实验,尤其是脑电图实验,必须注意避免混淆。最近的一篇 TPAMI 论文使用的数据遭受了先前报告的严重混淆。我们证明他们的新模型和分析方法不能弥补这种混淆,因此他们声称的高精度和神经科学相关性是无效的。
更新日期:2021-10-19
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