Biology subjects

Simpetru, R. C.

Publications and source records attributed to Simpetru, R. C..

3 recordsLinked to original sources

bioRxiv2026

Physiological and pathological motor unit phenotypes coexist within single motor pools after cervical SCI

Individuals with chronic cervical spinal cord injury (SCI) retain voluntary motor unit (MU) activation below the level of the lesion despite profound impairments in muscle relaxation, yet the MU-level mechanisms underlying this dissociation remain unclear. Here, we investigated MU recruitment and derecruitment dynamics using high-density surface EMG (HD-sEMG) and intramuscular EMG (iEMG), in functionally paralyzed muscles across open- and closed-loop tasks in four participants with chronic cervical SCI. Building on prior work that distinguished task-modulated from non-modulated MUs, we combined closed-loop MU feedback with targeted intramuscular implants to determine whether tonic units remain accessible to voluntary control and whether distinct firing phenotypes coexist within individual motor pools. Participants voluntarily recruited MUs and modulated discharge rates (45.2%), but a significant fraction (54.8%) of active MUs could not be derecruited during attempted relaxation. Quantitative analysis of 409 MUs revealed that derecruitment impairment spans a graded continuum rather than the binary distinction between modulated and non-modulated units reported previously. Three phenotypes, controllable (45.2%), modulated-tonic (42.8%), and tonic (12%), partition this spectrum based on derecruitment timing, discharge regularity, and firing persistence and coexist within the same motor pools, including within single muscle compartments sampled intramuscularly. Kaplan-Meier survival analysis confirmed graded derecruitment dynamics: controllable units ceased firing within 500 ms of rest onset, whereas most tonic units persisted throughout the observation window (log-rank{chi} 2= 164.10, P < 0.001). Tonic units displayed highly regular discharge consistent with intrinsic motoneuron excitation via persistent inward currents (PIC). Phenotypes were consistent across recording modalities and task contexts, and phenotype effects on derecruitment metrics exceeded movement-type effects by an order of magnitude. These findings identify impaired MU derecruitment as a core feature of spastic paralysis, driven by maladaptive motoneuron and spinal network properties that preserved descending drive cannot fully counteract. A proof-of-concept spike-train-level temporal filter selectively suppressed tonic firing while preserving voluntary modulation (>94% correlation retained), demonstrating a physiologically grounded strategy for improving neural interfacing after SCI.

neuroscience↗

bioRxiv2026

MyoGen: Unified Biophysical Modeling of Human Neuromotor Activity and Resulting Signals

Understanding human motor control requires integrating cortical and spinal cord activity, muscle mechanics, and electrophysiology, levels that are often studied separately. We present MyoGen, an open-source framework that unifies spinal circuitry, proprioceptive feedback, musculotendon dynamics, cortical activity, and multimodal electromyography (EMG) generation in a single, interoperable platform. Spinal motor neurons and the resulting motor unit (MU) action potentials represent the only neural cells that can be accessed at scale in humans. We used human MU ensembles to validate our model across a wide range of experimental conditions. Using data-driven optimization, we found that MyoGen produces MU population activity that closely matches experimental discharge-rate distributions and discharge variability across human muscles. Moreover, it generates decomposable surface and intramuscular EMG, reproduces beta-band modulation of descending drive and its nonlinear transformation into force, and implements complete sensorimotor loops. Dimensionality reduction of simulated agonist-antagonist EMG reveals low-dimensional control manifolds consistent with experimental recordings from both healthy and spinal cord injured individuals. MyoGen provides physiologically grounded, ground-truth data and integrates seamlessly with analysis pipelines, enabling systematic investigation of motor control principles, validation of signal-processing algorithms, and exploration of sensorimotor interactions that are experimentally inaccessible.

neuroscience↗

bioRxiv2025

Voluntary Dissociation of Motor Unit Activity in the Vastii Muscles

The CNS coordinates movement through consistent activation patterns across muscles and motor units, suggesting the presence of a relatively fixed and high-dimensional number of neural constraints on voluntary actions. In the human quadriceps, the vastus medialis (VM) and vastus lateralis (VL) control the knee extensor torque and are considered a synergistic pair largely activated by shared neural inputs. However, some evidence suggests that these muscles, or even subregions within them, can be controlled independently. In this study, we investigated whether humans can dissociate neural input to VM and VL during isometric contractions. Ten participants received real-time feedback from multiple intramuscular EMG electrodes that targeted different regions of the VM and VL while attempting to activate each muscle or sub-regions selectively. We found that nine out of ten subjects were able to clearly separate VM and VL activity based on the intramuscular EMG feedback. However, motor unit decomposition from the intramuscular EMGs revealed that selective recruitment of a unique set of motor units was possible only within the proximal region of VM. In contrast, VL and distal VM showed highly correlated activation, indicating tight functional coupling. Correlation analyses confirmed that the proximal VM exhibited distinct activation profiles compared with both distal VM and VL, supporting the existence of compartmentalized control within VM. These findings demonstrate that it is possible to dissociate the activation of motor units within this synergistic muscle group during low-force isometric contractions.

neuroscience↗