Brain-computer interface (BCI) systems were developed so that people can control computers or machines through their brain activity without moving their limbs. The P300 speller is one of the BCI applications used most commonly, as is very simple and reliable and can achieve satisfactory performance. However, like other BCIs, the P300 speller still has room for improvements in terms of its practical use, for example, selecting the best compromise between spelling accuracy and information transfer rate (ITR; speed) so that the P300 speller can maintain high accuracy while increasing spelling speed. Therefore, seeking correlates of, and predicting, the P300 speller’s performance is necessary to understand and improve the technique. In this work, we investigated the correlations between rapid serial visual presentation (RSVP) task features and the P300 speller’s performance. Fifty-five subjects participated in the RSVP and conventional matrix P300 speller tasks and RSVP behavioral and electroencephalography (EEG) features were compared in the P300’s speller performance. We found that several of the RSVP’s event-related potential (ERP) and behavioral features were correlated with the P300 speller’s offline binary classification accuracy. Using these features, we propose a simple multi-feature performance predictor (
r
= 0.53,
p
= 0.0001) that outperforms any single feature performance predictor, including that of the conventional RSVP T1% predictor (
r
= 0.28,
p
= 0.06). This result demonstrates that selective multi-features can predict BCI performance better than a single feature alone.
Measuring neuronal activity of transcranial direct current stimulation (tDCS) is essential for investigating tDCS in stimuli or after stimuli effects. The aim of this study was to investigate the oscillatory changes from anodal tDCS using electrocorticography (ECoG) on beagles. We applied 2 mA anodal tDCS and monitored the ECoG signals (32 channels, 512 Hz sampling rate) for 15 minutes in three anesthetized beagles. Then, we compared the power changes before, during, and after tDCS in six different bands (delta, theta, alpha, beta, low-gamma, and mid-gamma bands). The significantly increasing oscillatory changes from the mid-frequency bands (theta, alpha, and beta bands) to the high-frequency bands (low-gamma and mid-gamma bands) were observed. The results suggest that anodal tDCS may modulate high-frequency bands in the focal area of the cortex, which is relevant to electroencephalogram (EEG) studies.
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