Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Correct block-design experiments mitigate temporal correlation bias in
  EEG classification   It is argued in [1] that [2] was able to classify EEG responses to visual
stimuli solely because of the temporal correlation that exists in all EEG data
and the use of a block design. We here show that the main claim in [1] is
drastically overstated and their other analyses are seriously flawed by wrong
methodological choices. To validate our counter-claims, we evaluate the
performance of state-of-the-art methods on the dataset in [2] reaching about
50% classification accuracy over 40 classes, lower than in [2], but still
significant. We then investigate the influence of EEG temporal correlation on
classification accuracy by testing the same models in two additional
experimental settings: one that replicates [1]'s rapid-design experiment, and
another one that examines the data between blocks while subjects are shown a
blank screen. In both cases, classification accuracy is at or near chance, in
contrast to what [1] reports, indicating a negligible contribution of temporal
correlation to classification accuracy. We, instead, are able to replicate the
results in [1] only when intentionally contaminating our data by inducing a
temporal correlation. This suggests that what Li et al. [1] demonstrate is that
their data are strongly contaminated by temporal correlation and low
signal-to-noise ratio. We argue that the reason why Li et al. [1] observe such
high correlation in EEG data is their unconventional experimental design and
settings that violate the basic cognitive neuroscience design recommendations,
first and foremost the one of limiting the experiments' duration, as instead
done in [2]. Our analyses in this paper refute the claims of the "perils and
pitfalls of block-design" in [1]. Finally, we conclude the paper by examining a
number of other oversimplistic statements, inconsistencies, misinterpretation
of machine learning concepts, speculations and misleading claims in [1].

20
The categories of this paper are: acc-phys
18
The categories of this paper are: econ
29
The categories of this paper are: funct-an
3
The categories of this paper are: physics
8
The categories of this paper are: hep-ex
7
The categories of this paper are: hep-th
26
The categories of this paper are: bayes-an
37
The categories of this paper are: supr-con
5
The categories of this paper are: gr-qc
15
The categories of this paper are: nucl-ex
32
The categories of this paper are: atom-ph
28
The categories of this paper are: alg-geom
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The categories of this paper are: comp-gas
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The categories of this paper are: mtrl-th
9
The categories of this paper are: nlin
24
The categories of this paper are: dg-ga