Brain oscillations reflect pattern formation of cell assemblies’ activity, which is often disturbed in neurological and psychiatric diseases like depression, schizophrenia and stroke. In the neurobiological analysis and treatment of these conditions, transcranial electric currents applied to the brain proved beneficial. However, the direct effects of these currents on brain oscillations have remained an enigma because of the inability to record them simultaneously. Here we report a novel strategy that resolves this problem. We describe accurate reconstructed localization of dipolar sources and changes of brain oscillatory activity associated with motor actions in primary cortical brain regions undergoing transcranial electric stimulation. This new method allows for the first time direct measurement of the effects of non-invasive electrical brain stimulation on brain oscillatory activity and behavior.

Objective: Transcranial direct current stimulation (tDCS) improves motor learning and can affect emotional processing and attention. However, it is unclear whether learned electroencephalography (EEG)-based brain-machine interface (BMI) control during tDCS is feasible, how application of transcranial electric currents during BMI control would interfere with feature-extraction of physiological brain signals and how it affects brain control performance. Here we tested this combination and evaluated stimulation-dependent artifacts across different EEG frequencies and stability of motor imagery-based BMI control.Approach: Ten healthy volunteers were invited to two BMI-sessions, each comprising two 60-trial blocks. During the trials, learned desynchronization of mu-rhythms (8–15 Hz) associated with motor imagery (MI) recorded over C4 was translated into online cursor movements on a computer screen. During block 2, either sham (session A) or anodal tDCS (session B) was applied at 1 mA with the stimulation electrode placed 1 cm anterior of C4.Main results: tDCS was associated with a significant signal power increase in the lower frequencies most evident in the signal spectrum of the EEG channel closest to the stimulation electrode. Stimulation-dependent signal power increase exhibited a decay of 12 dB per decade, leaving frequencies above 9 Hz unaffected. Analysis of BMI control performance did not indicate a difference between blocks and tDCS conditions.Conclusion: Application of tDCS during learned EEG-based self-regulation of brain oscillations above 9 Hz is feasible and safe, and might improve applicability of BMI systems.

BackgroundAbnormal upper arm-forearm muscle synergies after stroke are poorly understood. We investigated whether upper arm function primes paralyzed forearm muscles in chronic stroke patients after Brain-Machine Interface (BMI)-based rehabilitation. Shaping upper arm-forearm muscle synergies may support individualized motor rehabilitation strategies.MethodsThirty-two chronic stroke patients with no active finger extensions were randomly assigned to experimental or sham groups and underwent daily BMI training followed by physiotherapy during four weeks. BMI sessions included desynchronization of ipsilesional brain activity and a robotic orthosis to move the paretic limb (experimental group, n = 16). In the sham group (n = 16) orthosis movements were random. Motor function was evaluated with electromyography (EMG) of forearm extensors, and upper arm and hand Fugl-Meyer assessment (FMA) scores. Patients performed distinct upper arm (e.g., shoulder flexion) and hand movements (finger extensions). Forearm EMG activity significantly higher during upper arm movements as compared to finger extensions was considered facilitation of forearm EMG activity. Intraclass correlation coefficient (ICC) was used to test inter-session reliability of facilitation of forearm EMG activity.ResultsFacilitation of forearm EMG activity ICC ranges from 0.52 to 0.83, indicating fair to high reliability before intervention in both limbs. Facilitation of forearm muscles is higher in the paretic as compared to the healthy limb (p<0.001). Upper arm FMA scores predict facilitation of forearm muscles after intervention in both groups (significant correlations ranged from R = 0.752, p = 0.002 to R = 0.779, p = 0.001), but only in the experimental group upper arm FMA scores predict changes in facilitation of forearm muscles after intervention (R = 0.709, p = 0.002; R = 0.827, p<0.001).ConclusionsResidual upper arm motor function primes recruitment of paralyzed forearm muscles in chronic stroke patients and predicts changes in their recruitment after BMI training. This study suggests that changes in upper arm-forearm synergies contribute to stroke motor recovery, and provides candidacy guidelines for similar BMI-based clinical practice.

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