Dataset Information

Beta-band motor unit coherence and nonlinear surface EMG features of the first dorsal interosseous muscle vary with force.

ABSTRACT: Motor unit firing times are weakly coupled across a range of frequencies during voluntary contractions. Coherent activity within the beta-band (15-35 Hz) has been linked to oscillatory cortical processes, providing evidence of functional connectivity between the motoneuron pool and motor cortex. The aim of this study was to investigate whether beta-band motor unit coherence is altered with increasing abduction force in the first dorsal interosseous muscle. Coherence between motor unit firing times, extracted from decomposed surface electromyography (EMG) signals, was investigated in 17 subjects at 10, 20, 30, and 40% of maximum voluntary contraction. Corresponding changes in nonlinear surface EMG features (specifically sample entropy and determinism, which are sensitive to motor unit synchronization) were also examined. A reduction in beta-band and alpha-band coherence was observed as force increased [F(3, 151)?=?32, P < 0.001 and F(3, 151)?=?27, P < 0.001, respectively], accompanied by corresponding changes in nonlinear surface EMG features. A significant relationship between the nonlinear features and motor unit coherence was also detected (r?=?-0.43?±?0.1 and r?=?0.45?±?0.1 for sample entropy and determinism, respectively; both P < 0.001). The reduction in beta-band coherence suggests a change in the relative contribution of correlated and uncorrelated presynaptic inputs to the motoneuron pool, and/or a decrease in the responsiveness of the motoneuron pool to synchronous inputs at higher forces. The study highlights the importance of considering muscle activation when investigating changes in motor unit coherence or nonlinear EMG features and examines other factors that can influence coherence estimation.NEW & NOTEWORTHY Intramuscular alpha- and beta-band coherence decreased as muscle contraction force increased. Beta-band coherence was higher in groups of high-threshold motor units than in simultaneously active lower threshold units. Alterations in motor unit coherence with increases or decreases in force and with the onset of fatigue were accompanied by corresponding changes in surface electromyography sample entropy and determinism. Mixed-model analysis indicated mean firing rate and number of motor units also influenced the coherence estimate.

SUBMITTER: McManus L

PROVIDER: S-EPMC6766730 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Beta-band motor unit coherence and nonlinear surface EMG features of the first dorsal interosseous muscle vary with force.

McManus Lara L Flood Matthew W MW Lowery Madeleine M MM

Journal of neurophysiology 20190731 3

Motor unit firing times are weakly coupled across a range of frequencies during voluntary contractions. Coherent activity within the beta-band (15-35 Hz) has been linked to oscillatory cortical processes, providing evidence of functional connectivity between the motoneuron pool and motor cortex. The aim of this study was to investigate whether beta-band motor unit coherence is altered with increasing abduction force in the first dorsal interosseous muscle. Coherence between motor unit firing tim ...[more]

PMID: 31365308

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Project description:ObjectiveWe sought to determine lesion sites and spatial lesion patterns in spontaneous anterior interosseous nerve syndrome (AINS) with high-resolution magnetic resonance neurography (MRN).MethodsIn 20 patients with AINS and 20 age- and sex-matched controls, MRN of median nerve fascicles was performed at 3T with large longitudinal anatomical coverage (upper arm/elbow/forearm): 135 contiguous axial slices (T2-weighted: echo time/repetition time 52/7,020 ms, time of acquisition: 15 minutes 48 seconds, in-plane resolution: 0.25 × 0.25 mm). Lesion classification was performed by visual inspection and by quantitative analysis of normalized T2 signal after segmentation of median nerve voxels.ResultsIn all patients and no controls, T2 lesions of individual fascicles were observed within upper arm median nerve trunk and strictly followed a somatotopic/internal topography: affected were those motor fascicles that will form the anterior interosseous nerve further distally while other fascicles were spared. Predominant lesion focus was at a mean distance of 14.6 ± 5.4 cm proximal to the humeroradial joint. Discriminative power of quantitative T2 signal analysis and of qualitative lesion rating was high, with 100% sensitivity and 100% specificity (p < 0.0001). Fascicular T2 lesion patterns were rated as multifocal (n = 17), monofocal (n = 2), or indeterminate (n = 1) by 2 independent observers with strong agreement (kappa = 0.83).ConclusionIt has been difficult to prove the existence of fascicular/partial nerve lesions in spontaneous neuropathies using clinical and electrophysiologic findings. With MRN, fascicular lesions with strict somatotopic organization were observed in upper arm median nerve trunks of patients with AINS. Our data strongly support that AINS in the majority of cases is not a surgically treatable entrapment neuropathy but a multifocal mononeuropathy selectively involving, within the main trunk of the median nerve, the motor fascicles that continue distally to form the anterior interosseous nerve.

Project description:Neuromuscular physiology is a vibrant research field that has recently seen exciting advances. Previous publications have focused on thorough analyses of particular aspects of neuromuscular physiology, yet an integration of the various novel findings into a single, comprehensive model is missing. In this article, we provide a unified description of a comprehensive mathematical model of surface electromyographic (EMG) measurements and the corresponding force signal in skeletal muscles, both consolidating and extending the results of previous studies regarding various components of the neuromuscular system. The model comprises motor unit (MU) pool organization, recruitment and rate coding, intracellular action potential generation and the resulting EMG measurements, as well as the generated muscular force during voluntary isometric contractions. Mathematically, it consists of a large number of linear PDEs, ODEs, and various stochastic nonlinear relationships, some of which are solved analytically, others numerically. A parameterization of the electrical and mechanical components of the model is proposed that ensures a physiologically meaningful EMG-force relation in the simulated signals, in particular taking the continuous, size-dependent distribution of MU parameters into account. Moreover, a novel nonlinear transformation of the common drive model input is proposed, which ensures that the model force output equals the desired target force. On a physiological level, this corresponds to adjusting the rate coding model to the force generating capabilities of the simulated muscle, while from a control theoretic point of view, this step is equivalent to an exact linearizing transformation of the controlled neuromuscular system. Finally, an alternative analytical formulation of the EMG model is proposed, which renders the physiological meaning of the model more clear and facilitates a mathematical proof that muscle fibers in this model at no point in time represent a net current source or sink. A consistent description of a complete physiological model as presented here, including thorough justification of model component choices, will facilitate the use of these advanced models in future research. Results of a numerical simulation highlight the model's capability to reproduce many physiological effects observed in experimental measurements, and to produce realistic synthetic data that are useful for the validation of signal processing algorithms.

Dataset Information

Beta-band motor unit coherence and nonlinear surface EMG features of the first dorsal interosseous muscle vary with force.

Publications

Beta-band motor unit coherence and nonlinear surface EMG features of the first dorsal interosseous muscle vary with force.

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