Periodic Reporting for period 1 - INcEPTION (Induction of NEuromuscular Plasticity for natural motor rehabilitaTION)
Periodo di rendicontazione: 2022-10-01 al 2025-03-31
Humans possess a remarkable ability to control multiple muscles in the upper extremities, enabling a wide range of complex movements. Given the large number of muscles involved in arm and shoulder motion, each with distinct anatomical and mechanical properties, movement control is believed to rely on the modulation of correlated activity between motoneuron pools. This coordination reduces the complexity of motor control, allowing for efficient movement execution.
In neuromuscular disorders, such as those affecting chronic stroke survivors or individuals recovering from breast cancer treatments, upper limb movement coordination is often impaired. These deficits may stem from the nervous system's reduced ability to restore the original connectivity between motoneuron pools. Therefore, understanding the neural mechanisms underlying coordinated muscle activity could provide valuable insights into the role of synaptic synchronization in movement generation.
Recent technological advancements have enabled significant progress in this field. Non-invasive multichannel surface electromyography combined with decomposition algorithms can now identify individual motor unit discharge patterns. This approach provides a direct and reliable measure of the correlated activity between motoneuron pools. Furthermore, emerging evidence demonstrates that non-invasive stimulation techniques, such as transcranial magnetic stimulation and sensory electrical stimulation, can effectively modulate excitatory and inhibitory synaptic inputs to motoneuron pools. These breakthroughs suggest new strategies for promoting plasticity in motoneuron connectivity, opening possibilities for improving neurorehabilitation protocols in individuals with motor disorders.
The INcEPTION has three interlinked research objectives (ROs). The RO1 seeks to reliably quantify the correlated activity between motoneuron pools during voluntary tasks involving the shoulder and arm across multiple degrees of freedom in healthy individuals. The RO2 aims to develop innovative methods for inducing reorganization of motoneuron connectivity in the main arm and shoulder muscles, using magnetic and electrical stimulation of cortical and sensory pathways. Finally, the RO3 aims to integrate findings from RO1 and RO2 into a novel framework for estimating and modulating neural activity patterns in the arm and shoulder muscles of individuals with upper limb disabilities.
In neuromuscular disorders, such as those affecting chronic stroke survivors or individuals recovering from breast cancer treatments, upper limb movement coordination is often impaired. These deficits may stem from the nervous system's reduced ability to restore the original connectivity between motoneuron pools. Therefore, understanding the neural mechanisms underlying coordinated muscle activity could provide valuable insights into the role of synaptic synchronization in movement generation.
Recent technological advancements have enabled significant progress in this field. Non-invasive multichannel surface electromyography combined with decomposition algorithms can now identify individual motor unit discharge patterns. This approach provides a direct and reliable measure of the correlated activity between motoneuron pools. Furthermore, emerging evidence demonstrates that non-invasive stimulation techniques, such as transcranial magnetic stimulation and sensory electrical stimulation, can effectively modulate excitatory and inhibitory synaptic inputs to motoneuron pools. These breakthroughs suggest new strategies for promoting plasticity in motoneuron connectivity, opening possibilities for improving neurorehabilitation protocols in individuals with motor disorders.
The INcEPTION has three interlinked research objectives (ROs). The RO1 seeks to reliably quantify the correlated activity between motoneuron pools during voluntary tasks involving the shoulder and arm across multiple degrees of freedom in healthy individuals. The RO2 aims to develop innovative methods for inducing reorganization of motoneuron connectivity in the main arm and shoulder muscles, using magnetic and electrical stimulation of cortical and sensory pathways. Finally, the RO3 aims to integrate findings from RO1 and RO2 into a novel framework for estimating and modulating neural activity patterns in the arm and shoulder muscles of individuals with upper limb disabilities.
A systematic review addressing gaps in motor unit research has been conducted, with results presented at international conferences (Motoneuron Meeting 2024, SfN 2024) and under review for publication.
Several studies investigated neural correlations between motoneurons during diverse tasks, resulting in publications and over ten abstracts at prominent conferences, including ISEK 2024 and ICNR 2024:
1. Effect of changes in muscle length: HDsEMG from leg muscles showed that increased muscle length reduces common synaptic oscillations.
2. Motor learning: HDsEMG from leg and hand muscles revealed reduced physiological tremor band oscillations during force-matching task learning.
3. Synergistic and non-synergistic hand tasks: Recordings from hand muscles indicated reduced tremor band oscillations during synergistic tasks compared to non-synergistic ones.
4. Neural modules across repetitive tasks: linear and non-linear methods were implemented to estimate motor unit connectivity during repetitive isometric tasks. A novel network-information framework was applied to motor unit data.
A novel protocol was developed for assessing motoneuron connectivity in shoulder muscles. Using a robotic arm and a six-degrees-of-freedom load cell, isometric forces across multi-directional tasks were recorded. HDsEMG data from deltoid and pectoralis muscles were collected, ensuring precise electrode placement and reproducibility through motion capture. Data decomposition is ongoing, with a methodological paper in preparation.
A new decomposition approach for HDsEMG recordings has been developed, capable of identifying motor unit action potentials under various conditions. Preliminary results are promising, and data collected from multiple muscles is being used to refine the algorithm. Moreover, a matheuristic method for automated motor unit spike train cleaning has been tested and presented at IEEE EMBC 2024, with manuscripts under preparation.
A novel experimental protocol to investigate corticospinal transmission to spinal motoneurons of hand muscles during repeated transcranial magnetic stimulation (rTMS) has been validated. Results showed that specific rTMS frequencies and intensities are linearly transmitted to spinal motoneurons. Preliminary findings were shared at SfN 2024 and ICNR 2024.
Several studies investigated neural correlations between motoneurons during diverse tasks, resulting in publications and over ten abstracts at prominent conferences, including ISEK 2024 and ICNR 2024:
1. Effect of changes in muscle length: HDsEMG from leg muscles showed that increased muscle length reduces common synaptic oscillations.
2. Motor learning: HDsEMG from leg and hand muscles revealed reduced physiological tremor band oscillations during force-matching task learning.
3. Synergistic and non-synergistic hand tasks: Recordings from hand muscles indicated reduced tremor band oscillations during synergistic tasks compared to non-synergistic ones.
4. Neural modules across repetitive tasks: linear and non-linear methods were implemented to estimate motor unit connectivity during repetitive isometric tasks. A novel network-information framework was applied to motor unit data.
A novel protocol was developed for assessing motoneuron connectivity in shoulder muscles. Using a robotic arm and a six-degrees-of-freedom load cell, isometric forces across multi-directional tasks were recorded. HDsEMG data from deltoid and pectoralis muscles were collected, ensuring precise electrode placement and reproducibility through motion capture. Data decomposition is ongoing, with a methodological paper in preparation.
A new decomposition approach for HDsEMG recordings has been developed, capable of identifying motor unit action potentials under various conditions. Preliminary results are promising, and data collected from multiple muscles is being used to refine the algorithm. Moreover, a matheuristic method for automated motor unit spike train cleaning has been tested and presented at IEEE EMBC 2024, with manuscripts under preparation.
A novel experimental protocol to investigate corticospinal transmission to spinal motoneurons of hand muscles during repeated transcranial magnetic stimulation (rTMS) has been validated. Results showed that specific rTMS frequencies and intensities are linearly transmitted to spinal motoneurons. Preliminary findings were shared at SfN 2024 and ICNR 2024.
Cabral et al., eNeuro 2024: This study significantly advanced motor control research by demonstrating that learning a new force-matching task is mediated by reductions in specific frequency bands of common oscillations reaching the motor neuron pool. Simulations revealed that spinal interneurons likely phase-cancel these oscillations from cortical inputs, providing a mechanistic explanation for the observed data. These findings illuminate how the central nervous system adapts neural correlations during motor learning, offering new insights into the neural basis of skill acquisition.
Dos Santos et al.; SfN 2024: This groundbreaking study was the first to directly investigate corticospinal transmission to spinal motor neurons during repeated transcranial magnetic stimulation (rTMS). It identified specific rTMS frequencies and intensities that are linearly transmitted to motor neuron pools and showed that rTMS over the primary motor cortex can modify neural correlations between spinal motoneurons. These findings have significant implications for using rTMS to induce targeted neural connectivity changes, potentially aiding neuromuscular rehabilitation in individuals with motor disabilities.
Zanotti et al.; EMBC 2024, 2024: A novel approach for resolving superpositions of action potentials was developed, treating the problem as a binary decision (an action potential is either present or not). This innovative method overcomes computational challenges associated with binary formulations, achieving greater speed and accuracy compared to existing techniques. The approach represents a breakthrough in signal processing and will serve as a foundation for several tasks in the project, potentially shifting the field toward more precise binary methods.
Zanotti and Negro; IEEE MetroXRAINE 2024: A general method for automatic cleaning of motor unit spike trains was introduced, eliminating the need for manual intervention by experts and reducing errors. Unlike traditional methods that rely on statistical properties, this approach incorporates physiological constraints for greater accuracy. Although validated on simulated data, real-world testing is underway using a comprehensive dataset. This innovation promises to enhance data reliability and drive progress across multiple project objectives.
Dos Santos et al.; SfN 2024: This groundbreaking study was the first to directly investigate corticospinal transmission to spinal motor neurons during repeated transcranial magnetic stimulation (rTMS). It identified specific rTMS frequencies and intensities that are linearly transmitted to motor neuron pools and showed that rTMS over the primary motor cortex can modify neural correlations between spinal motoneurons. These findings have significant implications for using rTMS to induce targeted neural connectivity changes, potentially aiding neuromuscular rehabilitation in individuals with motor disabilities.
Zanotti et al.; EMBC 2024, 2024: A novel approach for resolving superpositions of action potentials was developed, treating the problem as a binary decision (an action potential is either present or not). This innovative method overcomes computational challenges associated with binary formulations, achieving greater speed and accuracy compared to existing techniques. The approach represents a breakthrough in signal processing and will serve as a foundation for several tasks in the project, potentially shifting the field toward more precise binary methods.
Zanotti and Negro; IEEE MetroXRAINE 2024: A general method for automatic cleaning of motor unit spike trains was introduced, eliminating the need for manual intervention by experts and reducing errors. Unlike traditional methods that rely on statistical properties, this approach incorporates physiological constraints for greater accuracy. Although validated on simulated data, real-world testing is underway using a comprehensive dataset. This innovation promises to enhance data reliability and drive progress across multiple project objectives.