Biology subjects

Consul, N.

Publications and source records attributed to Consul, N..

2 recordsLinked to original sources

bioRxiv2025

Personalized mapping of inhibitory spinal circuits via neural decoding of high-density electromyography and in silico modelling

Studying human motoneuron activity through electromyography (EMG) can yield insights into the operation of fundamental spinal cord microcircuits. Traditional surface and needle electromyography (EMG) methodologies have limited capacity to shed light on the diversity of motor unit (MU) control strategies that may be unique to each individual. Here, we employed high-density surface EMG (HDsEMG) to sample multiple MUs per subject to investigate the dynamics of inhibitory spinal microcircuits in both upper and lower limb control. We characterised the net inhibition as a function of individual MU firing rates, revealing subject-specific relationships. In silico modelling replicated these experimental characteristics and suggested that properties of the inhibitory currents rather than motoneuron size are responsible for net functional inhibition. Our results show that HDsEMG can highlight distinct control strategies across circuits and motor pools, revealing subject-specific properties of inhibitory spinal microcircuits. TEASERHigh-density surface EMG electrodes can reveal the functional properties of inhibitory spinal circuits

neuroscience↗

bioRxiv2017

Inferring intracellular signal transduction circuitry from molecular perturbation experiments

The development of network inference methodologies that accurately predict connectivity in dysregulated pathways may enable the rational selection of patient therapies. Accurately inferring an intracellular network from data remains a very challenging problem in molecular systems biology. Living cells integrate extremely robust circuits that exhibit significant heterogeneity, but still respond to external stimuli in predictable ways. This phenomenon allows us to introduce a network inference methodology that integrates measurements of protein activation from perturbation experiments. The methodology relies on logic-based networks to provide a predictive approximation of the transfer of signals in a network. The approach presented was validated in silico with a set of test networks and applied to investigate the epidermal growth factor receptor signaling of a breast epithelial cell line, MFC10A. In our analysis, we predict the potential signaling circuitry most likely responsible for the experimental readouts of several proteins in the mitogen activated protein kinase and phosphatidylinositol-3 kinase pathways. The approach can also be used to identify additional necessary perturbation experiments to distinguish between a set of possible candidate networks.

systems biology↗