Mrachacz-Kersting N, Jiang N, Stevenson AJ, Niazi IK, Kostic V, Pavlovic A, Radovanovic S, Djuric-Jovicic M, Agosta F, Dremstrup K, Farina D. Efficient neuroplasticity induction in chronic stroke patients by an associative brain-computer interface. J Neurophysiol 115: 1410 -1421, 2016. First published December 30, 2015 doi:10.1152/jn.00918.2015 have the potential to improve functionality in chronic stoke patients when applied over a large number of sessions. Here we evaluated the effect and the underlying mechanisms of three BCI training sessions in a double-blind sham-controlled design. The applied BCI is based on Hebbian principles of associativity that hypothesize that neural assemblies activated in a correlated manner will strengthen synaptic connections. Twenty-two chronic stroke patients were divided into two training groups. Movement-related cortical potentials (MRCPs) were detected by electroencephalography during repetitions of foot dorsiflexion. Detection triggered a single electrical stimulation of the common peroneal nerve timed so that the resulting afferent volley arrived at the peak negative phase of the MRCP (BCI associative group) or randomly (BCI nonassociative group). Fugl-Meyer motor assessment (FM), 10-m walking speed, foot and hand tapping frequency, diffusion tensor imaging (DTI) data, and the excitability of the corticospinal tract to the target muscle [tibialis anterior (TA)] were quantified. The TA motor evoked potential (MEP) increased significantly after the BCI associative intervention, but not for the BCI nonassociative group. FM scores (0.8 Ϯ 0.46 point difference, P ϭ 0.01), foot (but not finger) tapping frequency, and 10-m walking speed improved significantly for the BCI associative group, indicating clinically relevant improvements. Corticospinal tract integrity on DTI did not correlate with clinical or physiological changes. For the BCI as applied here, the precise coupling between the brain command and the afferent signal was imperative for the behavioral, clinical, and neurophysiological changes reported. This association may become the driving principle for the design of BCI rehabilitation in the future. Indeed, no available BCIs can match this degree of functional improvement with such a short intervention.

Detection of movement intention from neural signals combined with assistive technologies may be used for effective neurofeedback in rehabilitation. In order to promote plasticity, a causal relation between intended actions (detected for example from the EEG) and the corresponding feedback should be established. This requires reliable detection of motor intentions. In this study, we propose a method to detect movements from EEG with limited latency. In a self-paced asynchronous BCI paradigm, the initial negative phase of the movement-related cortical potentials (MRCPs), extracted from multi-channel scalp EEG was used to detect motor execution/imagination in healthy subjects and stroke patients. For MRCP detection, it was demonstrated that a new optimized spatial filtering technique led to better accuracy than a large Laplacian spatial filter and common spatial pattern. With the optimized spatial filter, the true positive rate (TPR) for detection of movement execution in healthy subjects (n = 15) was 82.5 ± 7.8%, with latency of -66.6 ± 121 ms. Although TPR decreased with motor imagination in healthy subject (n = 10, 64.5 ± 5.33%) and with attempted movements in stroke patients (n = 5, 55.01 ± 12.01%), the results are promising for the application of this approach to provide patient-driven real-time neurofeedback.

This paper proposes the development and experimental tests of a self-paced asynchronous brain-computer interfacing (BCI) system that detects movement related cortical potentials (MRCPs) produced during motor imagination of ankle dorsiflexion and triggers peripheral electrical stimulations timed with the occurrence of MRCPs to induce corticospinal plasticity. MRCPs were detected online from EEG signals in eight healthy subjects with a true positive rate (TPR) of 67.15 ± 7.87% and false positive rate (FPR) of 22.05 ±9.07%. The excitability of the cortical projection to the target muscle (tibialis anterior) was assessed before and after the intervention through motor evoked potentials (MEP) using transcranial magnetic stimulation (TMS). The peak of the evoked potential significantly (P=0.02) increased after the BCI intervention by 53 ± 43% (relative to preintervention measure), although the spinal excitability (tested by stretch reflexes) did not change. These results demonstrate for the first time that it is possible to alter the corticospinal projections to the tibialis anterior muscle by using an asynchronous BCI system based on online motor imagination that triggered peripheral stimulation. This type of repetitive proprioceptive feedback training based on self-generated brain signal decoding may be a requirement for purposeful skill acquisition in intact humans and in the rehabilitation of persons with brain damage.

Based on EEG data recorded from 11 subjects with eyes open and the left mastoid (M) reference, three data sets were generated by re-referencing to the conventional linked mastoids (L), average (A) and the new 'infinity' (I) reference provided by the reference electrode standardization technique (REST, Yao 2001 Physiol. Meas. 22 693-711). The EEG power in the alpha frequency band with the four different references was calculated and compared with respect to the total energy and spatial amplitude weight centre (AWC) coordinates, to compare the effects of different references on power mapping in the frequency domain. Compared with the I reference, the AWCs of the EEG with the M reference show significant shifts to the right, frontal and superficial positions, the L reference significant shifts to frontal and superficial positions, and the A reference shifts the AWC significantly to a deeper position. Furthermore, the power maps of the M and L references have larger total power than the I reference, while that of the A reference has the smallest total power. These results confirm that different choices of reference electrodes result in systematic changes in the distribution of EEG frequency power, and in order to reduce the effect of such systematic shifts on the explanation of EEG mappings, a common reference is necessary for EEG research. We recommend the I reference for objective use in cross-laboratory studies and clinical practices, as it is far from all the other electrodes and can act as a neutral reference.

The results indicate that it is possible to detect movement intentions with limited latencies, and extract and classify different levels of force and speed, which may be combined with assistive technologies for patient-driven neurorehabilitation.