Abstract
Brain oscillations, e.g. measured by electro- or magnetoencephalography (EEG/MEG), are causally linked to brain functions that are fundamental for perception, cognition and learning. Recent advances in neurotechnology provide means to non-invasively target these oscillations using amplitude-modulated transcranial alternating current stimulation (AM-tACS). However, online adaptation of stimulation parameters to ongoing brain oscillations remains an unsolved problem due to stimulation artifacts that impede such adaptation, particularly at target frequencies. Here, we introduce a real-time compatible artifact rejection algorithm (Stimulation Artifact Source Separation, SASS) that overcomes this limitation. SASS is a spatial filter (linear projection) removing EEG signal components that are maximally different in the presence versus absence of stimulation. This enables the reliable removal of stimulation-specific signal components, while leaving physiological signal components unaffected. For validation of SASS, we evoked brain activity with known phase and amplitude using 10 Hz visual flickers. 64-channel EEG was recorded during and in absence of 10 Hz AM-tACS targeting the visual cortex. Phase differences between AM-tACS and the visual stimuli were randomized, so that steady-state visually evoked potentials (SSVEPs) were phase-locked to the visual stimuli but not to the AM-tACS signal. For validation, inter-trial phase-locking value (PLV) and mean amplitude of single-trial EEG signals recorded during and in absence of AM-tACS were compared. When no artifact rejection method was applied, AM-tACS stimulation artifacts impeded reconstruction of SSVEP amplitude and phase. Using SASS, PLV and mean amplitudes of single-trial EEG signals recorded during and in absence of AM-tACS were comparable. These results indicate that SASS can be used to establish adaptive (closed-loop) AM-tACS, a potentially powerful tool to target various brain functions and to investigate how AM-tACS interacts with electric brain oscillations.
Highlights
– Stimulation Artifact Source Separation (SASS), a real-time-compatible signal decomposition algorithm for separating electric brain activity and stimulation signal artifacts related to amplitude-modulated transcranial alternating current stimulation (AM-tACS), is introduced.
– Employing SASS, phase and amplitude of steady state visually evoked potentials (SSVEPs) were reliably recovered from electroencephalography (EEG) recordings
– SASS paves the way for online adaptation of stimulation parameters to ongoing brain oscillatory activity