Decoding self-automated and motivated finger movements using novel single-frequency filtering method – An EEG study

Abstract

Electroencephalography (EEG) provides the temporal resolution required to map the neural activations for studying motor movements and control. This study aims to compare the power amplitude of electrodes covering the central and frontal regions of a 32-channel scalp EEG. The activations from a standard index finger-tapping and a game paradigm are analyzed. Twenty-five right-handed and five left-handed healthy subjects (range = 18–30 years; mean = 24.25 years; SD = 3.96 years) participated in this study. A novel single-frequency filter (SFF) bank was applied to identify the peak amplitude from the power spectral density plots. The results show that the gaming paradigm yields lower or comparable power amplitudes than the standard finger tapping. We observed that the right-hand finger tapping by the left-handed subjects shows lower between-subject dispersion in amplitude. Nonparametric Spearman correlation showed no association between game scores and power amplitude for the right-handed participants. However, for left-handers, both positive and negative associations were observed. This study demonstrates the efficacy of SFF for extracting power amplitudes with a better signal-to-noise ratio, which has implications in BCI and motor rehabilitation applications. The findings support the role of game paradigms for motor movement research and in understanding bilateral hemispheric activations in cognitive tasks.