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Neurophysiological Biomarkers of Cortical Plasticity Induced by Neuromodulation

Periodic Reporting for period 1 - NeuroN (Neurophysiological Biomarkers of Cortical Plasticity Induced by Neuromodulation)

Reporting period: 2015-10-01 to 2017-08-31

The aim of the project NeuroN is to investigate the neurophysiological correlates of changes in excitability of the cortical and spinal pathways involved into ankle dorsiflexion in healthy individuals as well as in acute stroke patients. Stroke is one the major causes of death and serious long-term disability nowadays. Approximately 1.1 million people in Europe suffered a stroke each year, and ischemic stroke accounts for almost 80% of the cases. Also, as the population is constantly ageing, the incidence of stroke is expected to increase. When it is not fatal, stroke consequences can be devastating and can impact substantially the quality of life. Hemiparesis, lack of coordination, spasticity, communication and cognitive disorders are among the most common motor impairments. Among others, stroke survivors may exhibit a reduced walking performance due to a decreased range of motion of the ankle joint resulting in the so-called drop foot. Recovery of walking for post-stroke patients is mostly based on physical therapy activities which involve direct therapists’ observations and manipulation of the lower limbs (bottom-up approach). Although proven to be successful, this type of training induces high cost for the healthcare systems. Hence, many studies have tried to seek for alternative type of training by focusing on motor learning and plasticity as the key to induce a lasting brain reorganization. Brain-computer interfaces, which have been developed to control rehabilitation robots or electrical stimulation of muscles, have proven to be effective only when the artificial activation of somatosensory afferents reaches the sensory cortex during the negative phase of the movement-related cortical potential usually detected up to 1 s before the actual movement execution (or the attempted one). Such a closed-loop BCI system has proven to increase cortical excitability and thus to activate and reorganize the motor cortex areas. In NeuroN we explored the effectiveness of BCI training on acute stroke patients and we investigated the changes occurring in the cortical and spinal pathways and how the same are modified after the training. The outcomes of the research were impressive as we have highlighted how new pathways emerge as an alternative to pyramidal pathways. We suggest that these new pathways are of reticulospinal origin with oscillations around 13 Hz and that they are suppressed following the BCI training as a proof of the effectiveness of the platform in reorganizing brain areas.
Since the beginning, the focus of the work has been to implement and test the framework of the novel brain-computer interface (BCI) platform. This part of the project was performed while at the Institute of Neurorehabilitation Systems (NRS, Göttingen, Germany). The platform consisted of a desktop computer, the EEG recording system and of a sensorised pedal device for facilitating the recovery of ankle function of an ankle foot orthosis. These devices were controlled via software and allowed the recording of EEG signals during actual and imagined movements. Movement-related cortical potentials (MRCPs) were then extracted (MRCPs). They consist in a low-frequency negative shift (0.05- 3 Hz) in the EEG signals occurring 2 s ahead a voluntary movement. The MRCP thus, reflect the cortical processes involved in movement planning and movement preparation. The novel added value to the platform resides in the addition of a system for recording high-density EMG signals (HD-EMG). All the elements in the platform were synchronized and the final system was tested on a cohort of 30 acute stroke patients recruited at the Neurorehabilitation unit of the Brøndelsev Hospital during the secondment period at Aalborg University (AAU, Aalborg, Demark). Patients were divided into two groups (one BCI and one SHAM), in a blind way to the patient, the physicians and the therapists and they underwent a 12 sessions training, during which the EEG was recorded while patients performed an ankle dorsiflexion using the sensorised pedal. The intention of movement was detected from EEG signals and electrical stimulation was delivered at motor threshold to the tibial nerve at the time of occurrence of the negative peak of the MRCP. Patients within the SHAM group underwent the same training, but in this case the stimulation they received was at sensory level. The platform was further improved, by adding the system for Transcranial Magnetic Stimulation to be used before and after the training of the very first and the very last sessions to assess the changes in the motor potentials evoked by the magnetic field. On the first and twelfth session, HD-EMG was also recorded, before and after the BCI training to assess the changes in corticospinal pathways and motor neuron response to training. Some features were extracted from the HD-EMG and the coherence between motor neuron discharge timings was computed. In fact, coherence function provides information about the oscillations generated by the nervous system and is commonly used to quantify the strength and the frequency of common synaptic inputs to the motor neuron pool as well as to trace the neuronal reorganizations functionally relevant for motor recovery. The results show that at baseline, acute stroke survivors exhibit a coherence peak around 13 Hz, which cannot be identified in the coherence spectrum computed in a cohort of healthy age-matched individuals. This result outlines how the motor system reorganizes shortly after a stroke and how the therapies for the recovery of movement should be tailored to allow for a more functional and rapid recovery.
The outcome of the NeuroN project has a huge impact within different disciplines. The added value to the scientific knowledge is substantial. For the first time we have shown how in the period after the occurrence of stroke, new motor pathways emerge as an alternative to those who are impaired. This was possible thanks to the recording of HD-EMG signals which, in turn, allowed to decode the activities of more than 1000 motor neurons. Also, the social and economic impact of the project is very high since with this new shared knowledge, clinicians can define new therapies for the functional recovery of walking of stroke survivors with an overall improvement in patients’ quality of life.
Detailed view of the BCI platform used