EEG band power predicts single-trial reaction time in a hand motor task

The power of oscillatory brain sources can provide valuable information about trial-to-trial fluctuations considering the behavioural performance of subjects. Extracting such sources from electroencephalogram (EEG) recordings, however, proves to be difficult for most applications as the signal-to-noise ratio (SNR) in EEG typically is low. In an offline study with EEG data from three healthy subjects, we investigated the use of a recently introduced data-driven spatial filtering method called Source Power Comodulation (SPoC) [1]. Based on the trial-to-trial performance metric of a hand motor task, SPoC derives individually optimized linear spatial filters. They are optimized such that the resulting oscillatory signal component comodulates in band power with the performance metric at an increased SNR. Based on short intervals [-800; 0] ms prior to the go cue of ≈ 200 trials, we were able to identify individual oscillatory components. Their alpha band power comodulates with the reaction time (RT) during an isometric force control task of the hand. Using these components, it is possible to reach an average correlation of 0.19, with the best feature explaining up to 17% of the RT variation between single trials.