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. 2021 Jul 13;15:659410. doi: 10.3389/fnhum.2021.659410

Table 6.

Relation detection results of the multi-modal model using the recurrent EEG decoding component.

Randomly initialized GloVe BERT
Model P R F1 (std) P R F1 (std) P R F1 (std)
Baseline 0.404 0.525 0.452 (0.04) 0.501 0.609 0.539 (0.05) 0.522 0.788 0.623 (0.05)
+ noise 0.420 0.424 0.408 (0.07) 0.577 0.497 0.532 (0.03) 0.675 0.585 0.625 (0.03)
+ ET 0.421 0.404 0.402 (0.06) 0.547 0.476 0.506 (0.04) 0.661 0.631 0.644 (0.03)
+ EEG full 0.345 0.343 0.334 (0.05) 0.511 0.387 0.432 (0.09) 0.652 0.690 0.668* (0.10)
+ EEG θ 0.430 0.421 0.414 (0.07) 0.582 0.508 0.539 (0.07) 0.646 0.736 0.684* (0.08)
+ EEG α 0.368 0.373 0.358 (0.12) 0.582 0.515 0.542 (0.06) 0.652 0.715 0.679* (0.07)
+ EEG β 0.349 0.340 0.329 (0.09) 0.581 0.497 0.532 (0.10) 0.674 0.726 0.696+ (0.06)
+ EEG γ 0.410 0.399 0.397 (0.05) 0.554 0.488 0.514 (0.09) 0.666. 0.715 0.686* (0.07)
+θ+α+β+γ 0.370 0.376 0.363 (0.09) 0.554 0.488 0.514 (0.09) 0.675 0.646 0.659 (0.04)

We report precision (P), recall (R), F1-score and the standard deviation (std) between five runs. The best results per column are marked in bold. Significance is indicated on the F1-score with asterisks:

*

denotes p < 0.05 (uncorrected), + denotes p < 0.003 (Bonferroni corrected p-value).