Variability of Muscle Synergies in Hand Grasps: Analysis of Intra- and Inter-Session Data

Background. Muscle synergy analysis is an approach to understand the neurophysiological mechanisms behind the hypothesized ability of the Central Nervous System (CNS) to reduce the dimensionality of muscle control. The muscle synergy approach is also used to evaluate motor recovery and the evolution of the patients’ motor performance both in single-session and longitudinal studies. Synergy-based assessments are subject to various sources of variability: natural trial-by-trial variability of performed movements, intrinsic characteristics of subjects that change over time (e.g., recovery, adaptation, exercise, etc.), as well as experimental factors such as different electrode positioning. These sources of variability need to be quantified in order to resolve challenges for the application of muscle synergies in clinical environments. The objective of this study is to analyze the stability and similarity of extracted muscle synergies under the effect of factors that may induce variability, including inter- and intra-session variability within subjects and inter-subject variability differentiation. The analysis was performed using the comprehensive, publicly available hand grasp NinaPro Database, featuring surface electromyography (EMG) measures from two EMG electrode bracelets. Methods. Intra-session, inter-session, and inter-subject synergy stability was analyzed using the following measures: variance accounted for (VAF) and number of synergies (NoS) as measures of reconstruction stability quality and cosine similarity for comparison of spatial composition of extracted synergies. Moreover, an approach based on virtual electrode repositioning was applied to shed light on the influence of electrode position on inter-session synergy similarity. Results. Inter-session synergy similarity was significantly lower with respect to intra-session similarity, both considering coefficient of variation of VAF (approximately 0.2–15% for inter vs. approximately 0.1% to 2.5% for intra, depending on NoS) and coefficient of variation of NoS (approximately 6.5–14.5% for inter vs. approximately 3–3.5% for intra, depending on VAF) as well as synergy similarity (approximately 74–77% for inter vs. approximately 88–94% for intra, depending on the selected VAF). Virtual electrode repositioning revealed that a slightly different electrode position can lower similarity of synergies from the same session and can increase similarity between sessions. Finally, the similarity of inter-subject synergies has no significant difference from the similarity of inter-session synergies (both on average approximately 84–90% depending on selected VAF). Conclusion. Synergy similarity was lower in inter-session conditions with respect to intra-session. This finding should be considered when interpreting results from multi-session assessments. Lastly, electrode positioning might play an important role in the lower similarity of synergies over different sessions.

Quantitative rt-PCR analysis of uncoupling protein isoforms in mouse brain cortex: methodological optimization and comparison of expression with brown adipose tissue and skeletal muscle

Sylvain Eric Lengacher, Pierre Magistretti, Luc Pellerin

Uncoupling proteins (UCPs) present in the inner mitochondrial membrane are involved in uncoupling respiration from ATP synthesis. Five UCP isoforms have been identified but information about their presence and level of expression in the central nervous system remains incomplete. To determine the nature and proportion of UCP isoform mRNAs present in brain cortex, we developed and optimized a specific quantitative reverse-transcription polymerase chain reaction procedure. Optimal range of RNA concentrations to be used in the reverse-transcriptase reaction was determined. Primer design and concentration were optimized for each target gene while polymerase chain reaction efficiency was assessed for a range of reverse-transcriptase dilutions. Genomic contribution to the quantitative signal was evaluated for each isoform and minimized. Three reference genes were tested for normalization, and beta-actin was found to be the most stable among tissues. Results indicate that brain cortex contains significant amounts of all UCP mRNAs, with UCP5 and UCP4 being the most abundant, as opposed to brown adipose tissue and skeletal muscle, which predominantly express UCP1 and UCP3, respectively. These data provide a first quantitative assessment of UCP mRNA expression in mouse brain, showing the presence of all five isoforms with distinct proportions, thus suggesting specific roles in the central nervous system.

2004

Spatiotemporal stimulation strategies in neuroprostheses to improve locomotion after spinal cord injury

Jérôme Gandar

Spinal cord injury (SCI) disrupts communication within central nervous system and lead to range of neurological disorders including paralysis. Current rehabilitation strategies to restore locomotion are poorly effective in people with severe SCI. Epidural electrical stimulation (EES) showed promising results in animal models and humans to improve recovery. However, EES protocols have remained empirical, which has limited the efficacy of this paradigm. In this thesis, I report my contribution to the development of EES related software and hardware that were driven by the under- standing of the mechanisms underlying EES. These neurotechnologies showed a remarkable efficacy to reestablish locomotion in animal models of leg paralysis. EES protocols have primarily been delivered with continuous stimulations applied over the middle of the spinal cord, independently of current limb positions. However the natural activity of the spinal cord does not correspond to this limited monotone modulation. In the first part of this thesis, we developed spatiotemporal stimulation protocols that seek to reproduce the natural activity of the spinal cord during walking. Using computational models, we identified optimal electrode locations that target individual posterior roots. These simulations steered the design of spatially selective spinal implants. Control software triggered stimulation trains in real-time to engage extensor and flexor synergies according to limb positions. This spatiotemporal neuro- modulation therapy enhanced locomotor performances in rats with severe SCI. However, these spatiotemporal neuromodulation protocols were controlled via an external computer. The animal had no control over the occurrence of the stimulation. To remedy this limitation, we designed a brain-spine interface. We linked motor states decoded from leg motor cortex activity to spinal cord stimulation protocols to elicited the intended movements. We implemented this brain-spine interface in a nonhuman primate models of transient unilateral leg paralysis. All the animals immediately regained movements of the paralyzed leg. There is often a mechanical mismatch between current stiff implants and the soft neural tissues of the host. The third part of this thesis is dedicated to the design and fabrication of soft neural implants that present the same elasticity as the dura mater. These implants maintain the ability to deliver electrochemical stimulation while being stretched. Such interfaces can be applied to multiple neuroprosthetic applications, including the restoration of locomotion in paralyzed rats. In the last part of this thesis, I addressed the current limitations of spinal implant specificity. We found that EES activates the large afferent fibers within the dorsal rots and developed novel implants that take advantage of the known trajectories of the dorsal roots to increase the specificity of EES. First, we built a precise anatomical computational model of the lumbosacral roots. We then ran simulations that identi- fied multipolar electrode configurations capable of steering the current specifcally. These results drove the fabrication of soft neural implants that we inserted chronically in rat models of severe SCI. Experiments showed that multipolar EES increases the specificity of the stimulation compared to conventional protocols. All the concepts developed and validated in my thesis are already applied or are steering applications in humans with SCI.

EPFL2019

Enhancing our understanding of human fine manipulation skills and advancing robot dexterity in grasping

Kunpeng Yao

From surgery to watchmaking, fine-manipulation skills highly rely on the dexterity afforded by both hands. Coordination is key to human dexterity. Specifically, humans need not only to govern the abundant intrinsic degrees of freedom (DOFs) to allocate controls of task-demanded variables, but also to adapt postures in response to extrinsic task conditions. In spite of the recent advances in robotics research, human dexterity remains unattainable for robots, especially in terms of flexibility and adaptability. Therefore, it is necessary to gain insights into human fine-manipulation skills, to advance the dexterity of robots in similar tasks. This thesis deepens our understanding of human dexterity by investigating the human coordination in fine-manipulation skills taken from watchmaking craftsmanship.The first part of this thesis investigates both intrinsic and extrinsic coordination of upper-limbs in a non-symmetrical and non-rhythmic bimanual fine-manipulation task. We conduct a comparative study in the assembly of a spring on the watch face. Analysis of motion kinematics reveals that professional subjects mitigate the task challenge by actively modifying task conditions. Moreover, we offer a novel perspective to understand the skill acquisition in humans. We hypothesize that the evolution of coordination during skill improvement is driven by the changes in the structure of the optimal criterion of the central nervous system. We employ a bi-level optimization framework to infer the structure of this optimal criterion.The second part investigates how roles and control variables are distributed across hands and fingers. We compare task performance of human subjects under two experimental conditions when dismounting a screw from a watch face. When the watch face needed positioning, the role distribution of both hands was strongly influenced by hand dominance; when the watch face was stationary, a variety of hand pose combinations emerged. We propose a taxonomy of bimanual hand pose combinations and develop a graphical matrix-based representation approach to afford analysis of experimental observations. Our analysis suggests that the control of independent task demands is distributed across either hands or functional groups of fingers.In the third part, we take inspiration from human coordination principle to advance the dexterity of a robotic hand by exploiting its redundant DOFs. We propose a human-like algorithm to enable a robotic hand to grasp objects using arbitrary surface regions, no longer restricted to regular grasp types, such as pinch or power grasp. We present an iterative process to empower the robotic hand to grasp multiple objects in sequence. Moreover, we formulate a strategy to facilitate the exploitation of redundant DOFs for multitask planning. Our approaches have been validated both in simulation and on a real robotic hand.In summary, this thesis not only offers a deeper understanding of human dexterity by revealing both the intrinsic and extrinsic coordination of upper-limbs and the role distribution across hands in bimanual fine-manipulation tasks, but also proposes algorithms that enable multi-fingered robotic hands to achieve human-like dexterous grasping of a single or even multiple objects using arbitrary surface regions. This thesis offers the prospect of developing algorithms for robotic dexterous grasping and manipulation, and also inspires the design of novel robotic hands and manipulators.