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Connectivity in the neural control of muscles in stroke patients.

Periodic Reporting for period 1 - NeuralCon (Connectivity in the neural control of muscles in stroke patients.)

Reporting period: 2016-10-01 to 2018-09-30

The project NeuralCon aims to overcome the existing limitations in the estimation of the coupling between muscles and provide new insights on the control of multiple muscles in healthy individuals and stroke patients. This innovative research will be based on information extracted by advanced decomposition algorithms from the concurrent neural activity of multiple muscles. Stroke is one of the most important causes of disability worldwide. After a stroke, the motor deficits of upper and lower limbs may be substantial. In recent years, the hypothesis that the coordination of multiple muscles is wired at the neural level in a synergistic way has received strong experimental evidence. In case of ischemic stroke, the synergistic patterns are highly impaired and result in abnormal co-activation patterns that are functionally limiting since they decrease the capacity to activate the muscles independently. The degree of abnormal muscle co-contraction and spasticity may restrict the efficiency of rehabilitation training. In experimental conditions, it is possible to measure the degree of synergy between muscles from the recorded electromyographic (EMG) signals. However, recent literature has shown some important limitations of the approaches based on standard surface EMG signals. Recently, surface EMG electrodes may be combined in 2D arrays covering a relatively large portion of the investigated muscle(s). High-density sEMG signals can provide important information on the characteristics of different motor units, both at the peripheral and central levels and allow overcoming the classically used techniques based on amplitude characteristics of the signal to infer the neural activation of the muscles. In fact, more advanced methods that are capable of identifying the discharge times of individual motor units are now available for HD sEMG signals. Starting from this information, it is possible to extract variables that are related to the actual synaptic input received by the motor neurons. For these reasons, the project Neuralcon addressed the characterization of the neural coupling using innovative approaches applied to pre-processed high-density EMG signals and the spike trains identified from multiple muscles during voluntary contractions. The final aim was the identification of advanced biomarkers for assessing and monitoring motor dysfunction during the rehabilitation of stroke individuals. The results of the project showed that the analysis of the high-density EMG recordings during voluntary isometric contractions in the upper and lower limbs of stroke individuals can provide important information on the synergistic control of multiple muscle groups during the rehabilitation process. It was demonstrated that markers of neural activity (spinal motor neuron) can describe the fatigability and the spasticity in these patients and provide new clinical markers of motor impairment. During the project, we committed designing innovative algorithms for the improvement of motor unit identification, tracking, and alpha motor neuron spike train processing in order to make the clinical translation of these tools a reality in the near future.
From the beginning of the project, we focused on the development of the framework for the recording and analysis of multiple muscle groups during isometric contractions in stroke individuals. For this purpose, two devices for the recording of the upper and lower limb muscles were developed. The device for the upper limb consists of a flexible system made of aluminum to record flexion and extension forces of the wrist and finger muscles on both arms. The device included two force cells and the arm support was modified in order to avoid the direct contact between the EMG electrodes and the metal parts of the recording system. Similarly, a system for the recording of the lower limb forces (dorsi and plantaflexion of the ankle) was designed. The device provides the possibility to record ankle forces at different angles (neural position +- 30 degrees) and accommodate patients with different levels of plasticity. Both systems were combined with a two channels force amplifier and a 256 channels high-density EMG amplifier. Three surface EMG matrices of 64 electrodes were used for both the upper (two matrices on the flexors and one on the extensors muscles on the forearm) and the lower (soleus, medial gastrocnemius and tibialis anterior muscles) limb. A feedback of the extension/flexion force of the hand fingers or dorsi/plantaflexion force of the ankle was programmed in MATLAB and showed to the subject in real-time. In order to understand the limitations of the experimental framework and quantify possible effects of fatigue in stroke individuals, we performed a large set of protocols on a group of healthy and young individuals. Briefly, the experiments investigated the behavior of populations of motor units in a broad range of muscles, forces, and tasks. This provided a baseline for comparison with the stroke recordings. The main findings of this set of experiments showed for the first time that the neural activity of populations of motor units can be extracted in a variety of conditions and tracked across levels, sessions or after training interventions. Additionally, the combination of these innovative decomposition tools and the correlation analysis of populations of motor units spike trains showed the clear neural signature of motor control. For example, during a short session of force-matching training, we demonstrated that the control-to-neural noise ratio was improved after the repetition of the task. During the second year of the project, in acute stroke patients, we were able to track neural changes in five patients in three sessions (T0 admittance, T15 days after admittance in the clinic and T45) during the rehabilitation period. We are currently finishing the data collections in the stroke individuals. The results of the project have been disseminated in different forms. Until now, the signals recorded on the volunteers and the computational tools developed during the project have been included in several journal publications and five additional publications are in the final preparation phase. The results of the project have been presented in five international conferences and have been delivered in form of seminars in different laboratories worldwide. Finally, the project was presented in two events organized by the host institution for the general public.
The results of the project Neuralcon have a large impact and have been exploited in different fields: clinical neuro-rehabilitation, prosthesis control, adapted physical activity, signal processing, and computational neuroscience. We showed that the combination of advanced signal processing and robust statistical techniques with high-density EMG recordings can provide reliable neural-markers of simultaneous muscle control in healthy individuals and motor impairment in stroke patients. This innovative framework provided the possibility to decode the neural code of movements in these individuals and characterize the rehabilitation training in patients. The social and economic impact of the project is substantial since the advanced tools that have been designed for the evaluation of natural and pathological muscle co-contractions have been and will be used for clinical rehabilitation and functional physical activity.