Stimulation artifact source separation (SASS) for assessing electric brain oscillations during transcranial alternating current stimulation (tACS)

• Published in: NeuroImage (Orlando, Fla.) Fla.), 2021-03, Vol.228, p.117571-117571, Article 117571
• Main Authors: Haslacher, David, Nasr, Khaled, Robinson, Stephen E., Braun, Christoph, Soekadar, Surjo R.
• Format: Article
• Language: English
• Subjects: Adult; Algorithms; Brain - physiology; Brain oscillations; Cognition; Decomposition; EEG; Eigenvalues; Electrodes; Electroencephalography; Electroencephalography (EEG); Evoked Potentials, Visual - physiology; Female; Humans; Magnetoencephalography; Male; Noise; Oscillations; Physiology; Signal processing; Signal Processing, Computer-Assisted; Single-trial; Stimulation artifact; Transcranial alternating current stimulation (tACS); Transcranial Direct Current Stimulation - methods; Visual cortex; Visual stimuli; Young Adult
• ISSN: 1053-8119; 1095-9572
• DOI: 10.1016/j.neuroimage.2020.117571

•Stimulation Artifact Source Separation (SASS) is introduced, 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)•Employing SASS, phase and amplitude of single-trial steady state visual evoked potentials (SSVEPs) were reliably recovered from electroencephalography (EEG) recordings at the frequency targeted with AM-tACS•SASS enables assessment of single-trial oscillatory brain activity at the target frequency during stimulation and paves the way for online adaptation of stimulation parameters to ongoing brain oscillations 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 frequency-tuned 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 the target frequency. 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 across 7 healthy human volunteers. 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, distributions of single-trial amplitude and phase of EEG signals recorded during and in absence of AM-tACS were compared for each participant. When no artifact rejection method was applied, AM-tACS stimulation artifacts impeded assessment of single-trial SSVEP amplitude and phase. Using SASS, amplitude and phase of single trials recorde