Biology subjects

Heckman, C. J.

Publications and source records attributed to Heckman, C. J..

7 recordsLinked to original sources

bioRxiv2024

Voluntary co-contraction of ankle muscles alters motor unit discharge characteristics and reduces estimates of persistent inward currents

Motoneuronal persistent inward currents (PICs) are both facilitated by neuromodulatory inputs and highly sensitive to local inhibitory circuits (e.g., Ia reciprocal inhibition). Methods aimed to increase group Ia reciprocal inhibition from the antagonistic muscle have been successful in decreasing PICs, and the diffuse actions of neuromodulators released during activation of remote muscles have increased PICs. However, it remains unknown how motoneurons function in the presence of simultaneous excitatory and inhibitory commands. To probe this topic, we investigated motor unit (MU) discharge patterns and estimated PICs during voluntary co-contraction of ankle muscles, which simultaneously demands the contraction of agonist-antagonist pairs. Twenty young adults randomly performed triangular ramps (10s up and down) of both co-contraction (simultaneous dorsiflexion and plantarflexion) and isometric dorsiflexion to a peak of 30% of their maximum muscle activity from a maximal voluntary contraction. Motor unit spike trains were decomposed from high-density surface electromyography recorded over the tibialis anterior (TA) using blind source separation algorithms. Voluntary co-contraction altered motor unit discharge rate characteristics, decreasing estimates of PICs by 20% (4.47 pulses per second (pps) vs 5.57 pps during isometric dorsiflexion). These findings suggest that, during voluntary co-contraction, the inhibitory input from the antagonist muscle overcomes the additional excitatory and neuromodulatory drive that may occur due to the co-contraction of the antagonist muscle, which constrains PIC behavior. KEY POINTSVoluntary co-contraction is a unique motor behavior that concurrently provides increases in excitatory and inhibitory inputs to motoneurons. During co-contraction of agonist-antagonist pairs, agonist motor unit discharge characteristics are altered, consistent with reductions in persistent inward current magnitude. Reciprocal inhibition from the antagonist likely becomes proportional to the increase in neural drive to the agonist, dampening the magnitude of persistent inward currents.

physiology↗

bioRxiv2023

GABA Increases Sensory Transmission In Monkeys

Sensory input flow is central to voluntary movements. For almost a century, GABA was believed to modulate this flow by inhibiting sensory axons in the spinal cord to sculpt neural inputs into skilled motor output. Instead, here we show that GABA can also facilitate sensory transmission in monkeys and consequently increase spinal and cortical neural responses to sensory inputs challenging our understanding of generation and perception of movement.

neuroscience↗

bioRxiv2022

Supercomputers and Reverse Engineering of Motoneuron Firing Patterns

In this study, we develop new reverse engineering (RE) techniques to identify the organization of the synaptic inputs generating firing patterns of populations of neurons. We tested these techniques in silico to allow rigorous evaluation of their effectiveness, using remarkably extensive parameter searches enabled by massively-parallel computation on supercomputers. We chose spinal motoneurons as our target neural system, since motoneurons process all motor commands and have well established input-output properties. One set of simulated motoneurons was driven by 300,000+ simulated combinations of excitatory, inhibitory, and neuromodulatory inputs. Our goal was to determine if these firing patterns had sufficient information to allow RE identification of the input combinations. Like other neural systems, the motoneuron input-output system is likely non-unique. This non-uniqueness could potentially limit this RE approach, as many input combinations can produce similar outputs. However, our simulations revealed that firing patterns contained sufficient information to sharply restrict the solution space. Thus, our RE approach successfully generated estimates of the actual simulated patterns of excitation, inhibition, and neuromodulation, with variances accounted for ranging from 75% to 90%. It was striking that nonlinearities induced in firing patterns by the neuromodulation inputs did not impede RE, but instead generated distinctive features in firing patterns that aided RE. These simulations demonstrate the potential of this form of RE analysis. It is likely that the ever-increasing capacity of supercomputers will allow increasingly accurate RE of neuron inputs from their firing patterns from many neural systems.

neuroscience↗

bioRxiv2022

Antagonist tendon vibration dampens estimates of persistent inward currents in motor units of the human lower limb

We can readily measure motoneuron discharge patterns in humans due to the one-to-one spike relation between motoneuron and muscle fiber action potentials, which allows us to make inferences about motor commands. Persistent inward currents (PICs), which provide gain control of motoneuronal output, are facilitated by monoaminergic input from the brainstem. This monoaminergic input is greatly diffuse, but resulting PICs are highly sensitive to inhibitory inputs. Antagonist muscle stretch, and thus Ia input from the antagonist decreases PIC magnitudes in the decerebrate cat. In the present study, we explored whether estimates of PICs are altered with vibratory input to antagonist muscles in humans. MUs of the tibialis anterior (TA), soleus (SOL), and medial gastrocnemius (MG) were discriminated using high-density surface electromyography and convolutive blind source separation. We estimated PICs using the paired MU analysis technique, which quantifies discharge rate hysteresis ({Delta}F) by comparing the discharge rate of a lower-threshold MU at the onset and offset of a higher-threshold MU. Participants performed isometric plantarflexion and dorsiflexion contractions to a peak of 30% of maximal voluntary contraction, with 10 s ascending and descending phases. In half of the trials, we applied vibration to the antagonist tendon and found that {Delta}F in agonist MUs decreased in the presence of vibration. These findings suggest that inhibition from the antagonist muscle, most likely Ia reciprocal inhibition, can reduce discharge rate hysteresis. This provides insights about non-invasive methods potentially capable of dampening PICs in hyperexcitable motoneurons, which are manifest in some neurological impairments. KEY POINTSO_LIPersistent inward currents in motoneurons amplify synaptic inputs and thus have a major impact on motor unit firing patterns. C_LIO_LIWe show that sustained vibration to the antagonist tendon reduces estimates of persistent inward currents ({Delta}F) of the contracting muscle in both the plantarflexors and dorsiflexors. C_LIO_LIThese findings provide evidence for the important role of sensory input in the control of persistent inward currents in the human. C_LIO_LIReciprocal inhibition may help refine neuromodulatory commands to tailor motor unit activation to diverse movement patterns and specific tasks, and loss of inhibition may exacerbate symptoms of neurological impairment. C_LI

physiology↗

bioRxiv2021

Algorithmic Parameter Estimation and Uncertainty Quantification for Hodgkin-Huxley Neuron Models

Experimental data-based parameter search for Hodgkin-Huxley-style (HH) neuron models is a major challenge for neuroscientists and neuroengineers. Current search strategies are often computationally expensive, are slow to converge, have difficulty handling nonlinearities or multimodalities in the objective function, or require good initial parameter guesses. Most important, many existing approaches lack quantification of uncertainties in parameter estimates even though such uncertainties are of immense biological significance. We propose a novel method for parameter inference and uncertainty quantification in a Bayesian framework using the Markov chain Monte Carlo (MCMC) approach. This approach incorporates prior knowledge about model parameters (as probability distributions) and aims to map the prior to a posterior distribution of parameters informed by both the model and the data. Furthermore, using the adaptive parallel tempering strategy for MCMC, we tackle the highly nonlinear, noisy, and multimodal loss function, which depends on the HH neuron model. We tested the robustness of our approach using the voltage trace data generated from a 9-parameter HH model using five levels of injected currents (0.0, 0.1, 0.2, 0.3, and 0.4 nA). Each test consisted of running the ground truth with its respective currents to estimate the model parameters. To simulate the condition for fitting a frequency-current (F-I) curve, we also introduced an aggregate objective that runs MCMC against all five levels simultaneously. We found that MCMC was able to produce many solutions with acceptable loss values (e.g., for 0.0 nA, 889 solutions were within 0.5% of the best solution and 1,595 solutions within 1% of the best solution). Thus, an adaptive parallel tempering MCMC search provides a "landscape" of the possible parameter sets with acceptable loss values in a tractable manner. Our approach is able to obtain an intelligently sampled global view of the solution distributions within a search range in a single computation. Additionally, the advantage of uncertainty quantification allows for exploration of further solution spaces, which can serve to better inform future experiments.

neuroscience↗

bioRxiv2020

Time course of alterations in adult spinal motoneuron properties in the SOD1(G93A) mouse model of ALS

Although ALS is an adult-onset neurodegenerative disease, motoneuron electrical properties are already altered during embryonic development. Motoneurons must therefore exhibit a remarkable capacity for homeostatic regulation to maintain a normal motor output for most of the life of the patient. In the present paper, we demonstrate how maintaining homeostasis could come at a very high cost. We studied the excitability of spinal motoneurons from young adult SOD1(G93A) mice to end-stage. Initially homeostasis is highly successful in maintaining their overall excitability. This initial success, however, is achieved by pushing some cells far above the normal range of passive and active conductances. As the disease progresses, both passive and active conductances shrink below normal values in the surviving cells. This shrinkage may thus promote survival, implying the previously large values contribute to degeneration. These results support the hypothesis that motoneuronal homeostasis may be "hyper-vigilant" in ALS and a source of accumulating stress. Significance StatementDuring ALS, motoneurons exhibit a remarkable ability to maintain a normal motor output despite continuous alterations of their electrophysiological properties, up to the point when overt symptoms become apparent. We show that this homeostatic process can sometimes push motoneurons beyond the normal range, which may be causing long-lasting harm.

neuroscience↗

bioRxiv2019

Sensitivity of the paired motor unit analysis for estimation of motoneuron excitability to commonly used constraints and filters

The nervous system has a tremendous ability to modify motoneuron excitability according to task demands through neuromodulatory synaptic input to motoneurons. Neuromodulatory inputs adjust the response of the motoneuron to excitatory and inhibitory ionotropic input and can facilitate the induction of persistent inward currents (PICs). PICs amplify and prolong the motoneuron response to synaptic inputs, and PIC impairment may play a major role in motor deficits observed in pathological conditions. Noninvasive estimation of the magnitude of neuromodulatory input and persistent inward currents in human motoneurons is achieved through a paired motor unit analysis ({Delta}F) that quantifies hysteresis in the firing rates at motor unit recruitment and derecruitment. While the {Delta}F technique is commonly used for estimating motoneuron excitability, computational parameters used for the technique vary across studies. In the present study, we assessed the sensitivity of the {Delta}F technique to several criteria commonly used in selecting motor unit pairs for analysis, as well as to methods used for smoothing the instantaneous motor unit firing rates. Using HD-sEMG and motor unit decomposition we obtained 5,409 motor unit pairs from the triceps brachii of ten healthy individuals during submaximal triangle contractions. The mean (SD) {Delta}F was 4.9 (1.08) pps, consistent with previous work using intramuscular recordings. There was an exponential plateau relationship between {Delta}F and the recruitment time difference between the motor unit pairs, with the plateau occurring at approximately 1 s. There was an exponential decay relationship between {Delta}F and the derecruitment time difference between the motor unit pairs, with the decay stabilizing at approximately 1.5 s. We found that reducing or removing the minimum threshold for the correlation of the rate-rate slope for the two units did not affect {Delta}F values or variance. Additionally, we found that removing motor unit pairs in which the control unit was saturated had no significant effect on {Delta}F. Smoothing filter selection had no substantial effect on {Delta}F values and {Delta}F variance; however, the length and type of smoothing filter affected the minimum recruitment and derecruitment time differences. Our results facilitate interpretation of findings from studies that implement the {Delta}F approach but use different computational parameters.

neuroscience↗