Jason J. Kutch

Challenges and new approaches to proving the existence of muscle synergies of neural origin.

Muscle coordination studies repeatedly show low-dimensionality of muscle activations for a wide variety of motor tasks. The basis vectors of this low-dimensional subspace, termed muscle synergies, are hypothesized to reflect neurally-established functional muscle groupings that simplify body control. However, the muscle synergy hypothesis has been notoriously difficult to prove or falsify. We use cadaveric experiments and computational models to perform a crucial thought experiment and develop an alternative explanation of how muscle synergies could be observed without the nervous system having controlled muscles in groups. We first show that the biomechanics of the limb constrains musculotendon length changes to a low-dimensional subspace across all possible movement directions. We then show that a modest assumption—that each muscle is independently instructed to resist length change—leads to the result that electromyographic (EMG) synergies will arise without the need to conclude that they are a product of neural coupling among muscles. Finally, we show that there are dimensionality-reducing constraints in the isometric production of force in a variety of directions, but that these constraints are more easily controlled for, suggesting new experimental directions. These counter-examples to current thinking clearly show how experimenters could adequately control for the constraints described here when designing experiments to test for muscle synergies—but, to the best of our knowledge, this has not yet been done.

Computational Models for Neuromuscular Function

Computational models of the neuromuscular system hold the potential to allow us to reach a deeper understanding of neuromuscular function and clinical rehabilitation by complementing experimentation. By serving as a means to distill and explore specific hypotheses, computational models emerge from prior experimental data and motivate future experimental work. Here we review computational tools used to understand neuromuscular function including musculoskeletal modeling, machine learning, control theory, and statistical model analysis. We conclude that these tools, when used in combination, have the potential to further our understanding of neuromuscular function by serving as a rigorous means to test scientific hypotheses in ways that complement and leverage experimental data.

Muscle redundancy does not imply robustness to muscle dysfunction

It is well-known that muscle redundancy grants the CNS numerous options to perform a task. Does muscle redundancy, however, allow sufficient robustness to compensate for loss or dysfunction of even a single muscle? Are all muscles equally redundant? We combined experimental and computational approaches to establish the limits of motor robustness for static force production. In computer-controlled cadaveric index fingers, we find that only a small subset (<5%) of feasible forces is robust to loss of any one muscle. Importantly, the loss of certain muscles compromises force production significantly more than others. Further computational modeling of a multi-joint, multi-muscle leg demonstrates that this severe lack of robustness generalizes to whole limbs. These results provide a biomechanical basis to begin to explain why redundant motor systems can be vulnerable to even mild neuromuscular pathology.

Optimal control of HIV infection with a continuously-mutating viral population

There has been much discussion in recent years devoted to determining the optimal methodology for administering anti-viral medication therapies to fight HIV infection. There are many reasons to seek such an optimal therapy, including the minimization of drug toxicity and monetary cost. However, there is increasing recognition that exposure to many anti-HIV medications produces extremely rapid changes in the viral population in an infected individual, from drug-sensitive to drug-insensitive viral strains. This paper investigates the reasons underlying the development of drug-insensitive HIV strains, and then, using numerical optimal control techniques, demonstrates that optimal drug administration may be useful in increasing patient health by delaying the emergence of drug-resistant mutant viral strains.

Altered resting state neuromotor connectivity in men with chronic prostatitis/chronic pelvic pain syndrome: A MAPP: Research Network Neuroimaging Study.

Brain network activity associated with altered motor control in individuals with chronic pain is not well understood. Chronic Prostatitis/Chronic Pelvic Pain Syndrome (CP/CPPS) is a debilitating condition in which previous studies have revealed altered resting pelvic floor muscle activity in men with CP/CPPS compared to healthy controls. We hypothesized that the brain networks controlling pelvic floor muscles would also show altered resting state function in men with CP/CPPS. Here we describe the results of the first test of this hypothesis focusing on the motor cortical regions, termed pelvic-motor, that can directly activate pelvic floor muscles. A group of men with CP/CPPS (N = 28), as well as group of age-matched healthy male controls (N = 27), had resting state functional magnetic resonance imaging scans as part of the Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) Research Network study. Brain maps of the functional connectivity of pelvic-motor were compared between groups. A significant group difference was observed in the functional connectivity between pelvic-motor and the right posterior insula. The effect size of this group difference was among the largest effect sizes in functional connectivity between all pairs of 165 anatomically-defined subregions of the brain. Interestingly, many of the atlas region pairs with large effect sizes also involved other subregions of the insular cortices. We conclude that functional connectivity between motor cortex and the posterior insula may be among the most important markers of altered brain function in men with CP/CPPS, and may represent changes in the integration of viscerosensory and motor processing.

Cortical Activation Associated with Muscle Synergies of the Human Male Pelvic Floor

Human pelvic floor muscles have been shown to operate synergistically with a wide variety of muscles, which has been suggested to be an important contributor to continence and pelvic stability during functional tasks. However, the neural mechanism of pelvic floor muscle synergies remains unknown. Here, we test the hypothesis that activation in motor cortical regions associated with pelvic floor activation are part of the neural substrate for such synergies. We first use electromyographic recordings to extend previous findings and demonstrate that pelvic floor muscles activate synergistically during voluntary activation of gluteal muscles, but not during voluntary activation of finger muscles. We then show, using functional magnetic resonance imaging (fMRI), that a region of the medial wall of the precentral gyrus consistently activates during both voluntary pelvic floor muscle activation and voluntary gluteal activation, but not during voluntary finger activation. We finally confirm, using transcranial magnetic stimulation, that the fMRI-identified medial wall region is likely to generate pelvic floor muscle activation. Thus, muscle synergies of the human male pelvic floor appear to involve activation of motor cortical areas associated with pelvic floor control.

Unique Microstructural Changes in the Brain Associated with Urological Chronic Pelvic Pain Syndrome (UCPPS) Revealed by Diffusion Tensor MRI, Super-Resolution Track Density Imaging, and Statistical Parameter Mapping: A MAPP Network Neuroimaging Study

Studies have suggested chronic pain syndromes are associated with neural reorganization in specific regions associated with perception, processing, and integration of pain. Urological chronic pelvic pain syndrome (UCPPS) represents a collection of pain syndromes characterized by pelvic pain, namely Chronic Prostatitis/Chronic Pelvic Pain Syndrome (CP/CPPS) and Interstitial Cystitis/Painful Bladder Syndrome (IC/PBS), that are both poorly understood in their pathophysiology, and treated ineffectively. We hypothesized patients with UCPPS may have microstructural differences in the brain compared with healthy control subjects (HCs), as well as patients with irritable bowel syndrome (IBS), a common gastrointestinal pain disorder. In the current study we performed population-based voxel-wise DTI and super-resolution track density imaging (TDI) in a large, two-center sample of phenotyped patients from the multicenter cohort with UCPPS (N = 45), IBS (N = 39), and HCs (N = 56) as part of the MAPP Research Network. Compared with HCs, UCPPS patients had lower fractional anisotropy (FA), lower generalized anisotropy (GA), lower track density, and higher mean diffusivity (MD) in brain regions commonly associated with perception and integration of pain information. Results also showed significant differences in specific anatomical regions in UCPPS patients when compared with IBS patients, consistent with microstructural alterations specific to UCPPS. While IBS patients showed clear sex related differences in FA, MD, GA, and track density consistent with previous reports, few such differences were observed in UCPPS patients. Heat maps illustrating the correlation between specific regions of interest and various pain and urinary symptom scores showed clustering of significant associations along the cortico-basal ganglia-thalamic-cortical loop associated with pain integration, modulation, and perception. Together, results suggest patients with UCPPS have extensive microstructural differences within the brain, many specific to syndrome UCPPS versus IBS, that appear to be localized to regions associated with perception and integration of sensory information and pain modulation, and seem to be a consequence of longstanding pain.

Brain Connectivity Associated with Muscle Synergies in Humans.

The human brain is believed to simplify the control of the large number of muscles in the body by flexibly combining muscle coordination patterns, termed muscle synergies. However, the neural connectivity allowing the human brain to access and coordinate muscle synergies to accomplish functional tasks remains unknown. Here, we use a surprising pair of synergists in humans, the flexor hallucis longus (FHL, a toe flexor) and the anal sphincter, as a model that we show to be well suited in elucidating the neural connectivity underlying muscle synergy control. First, using electromyographic recordings, we demonstrate that voluntary FHL contraction is associated with synergistic anal sphincter contraction, but voluntary anal sphincter contraction occurs without FHL contraction. Second, using fMRI, we show that two important medial wall motor cortical regions emerge in relation to these tasks: one located more posteriorly that preferentially activates during voluntary FHL contraction and one located more anteriorly that activates during both voluntary FHL contraction as well as voluntary anal sphincter contraction. Third, using transcranial magnetic stimulation, we demonstrate that the anterior region is more likely to generate anal sphincter contraction than FHL contraction. Finally, using a repository resting-state fMRI dataset, we demonstrate that the anterior and posterior motor cortical regions have significantly different functional connectivity with distinct and distant brain regions. We conclude that specific motor cortical regions in humans provide access to different muscle synergies, which may allow distinct brain networks to coordinate muscle synergies during functional tasks. SIGNIFICANCE STATEMENT How the human nervous system coordinates activity in a large number of muscles is a fundamental question. The brain and spinal cord are believed to simplify the control of muscles by grouping them into functional units called muscle synergies. Motor cortex is involved in activating muscle synergies; however, the motor cortical connections that regulate muscle synergy activation are unknown. Here, we studied pelvic floor muscle synergies to elucidate these connections in humans. Our experiments confirmed that distinct motor cortical regions activate different muscle synergies. These regions have different connectivity to distinct brain networks. Our results are an important step forward in understanding the cortical control of human muscles synergies, and may also have important clinical implications for understanding movement dysfunction.

A Novel Synthesis of Computational Approaches Enables Optimization of Grasp Quality of Tendon-Driven Hands

We propose a complete methodology to find the full set of feasible grasp wrenches and the corresponding wrench-direction-independent grasp quality for a tendon-driven hand with arbitrary design parameters. Monte Carlo simulations on two representative designs combined with multiple linear regression identified the parameters with the greatest potential to increase this grasp metric. This synthesis of computational approaches now enables the systematic design, evaluation, and optimization of tendon-driven hands.

Extraction of Individual Muscle Mechanical Action From Endpoint Force

Most motor tasks require the simultaneous coordination of multiple muscles. That coordination is poorly understood in part because there is no noninvasive means of isolating a single muscles contribution to the resultant endpoint force. The contribution of a single motor unit to isometric tasks can, however, be characterized using the spike-triggered averaging (STA) technique, applied to a single motor units spike train. We propose that a technique analogous to STA, which we call electromyogram (EMG)-weighted averaging (EWA), can be applied to surface EMGs to extract muscle mechanical action from the natural endpoint force fluctuations generated during steady isometric contraction. We demonstrate this technique on simultaneous recordings of fingertip force and surface EMG from the first dorsal interosseous (FDI) and extensor indicis (EI) of humans. The EWA direction was approximately the same across a wide range of fingertip force directions, and the average EWA direction was consistent with mechanical action direction of these muscles estimated from cadaveric and imaging data: the EWA directions were 193 +/- 2 degrees for the FDI and 71 +/- 5 degrees for the EI (95% confidence). EWA transient behavior also appears to capture temporal characteristics of muscle force fluctuations with peak force time and general waveform shape similar to that of the associated spike-triggered averages from single motor units. The EWA may provide a means of empirically characterizing the complex transformation between muscle force and endpoint force without the need for invasive electrode recordings or complex anatomical measurements of musculoskeletal geometry.