Biology subjects

Gronlund, C.

Publications and source records attributed to Gronlund, C..

3 recordsLinked to original sources

bioRxiv2023

Combining high-density electromyography and ultrafast ultrasound to assess individual motor unit properties in vivo

This study aims to compare two methods for the identification of anatomical and mechanical motor unit (MU) properties through the integration of high-density surface electromyography (HDsEMG) and ultrafast ultrasound (UUS). The two approaches rely on a combined analysis of the firing pattern of active MUs, identified from HDsEMG, and tissue velocity sequences of the muscle cross-section, obtained from UUS. The first method is the spike-triggered averaging (STA) of the tissue velocity sequence based on the occurrences of MU firings. The second is a method based on spatio-temporal independent component analysis (STICA) enhanced with the information of single MU firings. We compared the capability of these two approaches to identify the regions where single MU fibers are located within the muscle cross-section (MU displacement area) in vivo. HDsEMG signals and UUS images were detected simultaneously from biceps brachii in ten participants (6 males and 4 females) during low-level isometric elbow flexions. Experimental signals were processed by implementing both STA and STICA approaches. The medio-lateral distance between the estimated MU displacement areas and the centroid of the MU action potential distributions was used to compare the two methods. We found that STICA and STA are able to detect MU displacement areas. However, STICA provides more precise estimations to the detriment of higher computational complexity.

bioengineering↗

bioRxiv2023

Spatially repeatable components from ultrafast ultrasound are associated with motor unit activity in human isometric contractions

ObjectiveUltrafast ultrasound imaging has been used to measure intramuscular mechanical dynamics associated with single motor unit (MU) activations. Detecting MU activity from ultrasound sequences requires decomposing a displacement velocity field into components consisting of spatial maps and temporal displacement signals. These components can be associated with putative MU activity or spurious movements (noise). The differentiation between putative MUs and noise has been accomplished by comparing the temporal displacement signals with MU firings obtained from needle EMG. Here, we examined whether the repeatability of the spatial maps over brief time intervals can serve as a criterion for distinguishing putative MUs from noise in low-force isometric contractions. ApproachIn five healthy subjects, ultrafast ultrasound images and high-density surface EMG (HDsEMG) were recorded simultaneously from biceps brachii. MUs identified through HDsEMG decomposition were used as a reference to assess the outcomes of the ultrasound-based decomposition. For each contraction, displacement velocity sequences from the same eight-second ultrasound recording were separated into consecutive two-second epochs and decomposed. The Jaccard Similarity Coefficient (JSC) was employed to evaluate the repeatability of components spatial maps across epochs. Finally, the association between the ultrasound components and the MUs decomposed from HDsEMG was assessed. Main resultsAll the MU-matched components had JSC > 0.38, indicating they were repeatable and accounted for about one-third of the HDsEMG-detected MUs (1.8 {+/-} 1.6 matches over 4.9 {+/-} 1.8 MUs). The repeatable components (with JSC over the empirical threshold of 0.38) represented 14% of the total components (6.5 {+/-} 3.3 components). These findings align with our hypothesis that intra-sequence repeatability can differentiate putative MUs from spurious components and can be used for data reduction. SignificanceThe results of our study provide the foundation for developing stand-alone methods to identify MU in ultrafast ultrasound sequences and represent a step forward towards real-time imaging of active MU territories. These methods are relevant for studying muscle neuromechanics and designing novel neural interfaces.

bioengineering↗

bioRxiv2022

Optimization and comparison of two methods for spike train estimation in an unfused tetanic contraction of low threshold motor units

BackgroundHuman movement is generated by activating motor units (MUs), i.e., the smallest structures that can be voluntarily controlled. Recent findings have shown imaging of voluntarily activated MUs using ultrafast ultrasound based on displacement velocity images and a decomposition algorithm. Given this, estimates of trains of twitches (unfused tetanic signals) evoked by the neural discharges (spikes) of spinal motor neurons are provided. Based on these signals, a band-pass filter method (BPM) has been used to estimate its spike train. In addition, an improved spike estimation method consisting of a continuous Haar wavelet transform method (HWM) has been suggested. However, the parameters of the two methods have not been optimized, and their performance has not been compared rigorously. MethodHWM and BPM were optimized using simulations. Their performance was evaluated based on simulations and two experimental datasets with 21 unfused tetanic contractions considering their rate of agreement, spike offset, and spike offset variability with respect to the simulated or experimental spikes. ResultsA range of parameter sets that resulted in the highest possible agreement with simulated spikes was provided. Both methods highly agreed with simulated and experimental spikes, but HWM was a better spike estimation method than BPM because it had a higher agreement, less bias, and less variation (p < 0.001). ConclusionsThe optimized HWM will be an important contributor to further developing the identification and analysis of MUs using imaging, providing indirect access to the neural drive of the spinal cord to the muscle by the unfused tetanic signals.

bioengineering↗