Neuromodulation impact on nonlinear firing behavior of a reduced model motoneuron with the active dendrite

Neuromodulatory inputs from brainstem systems modulate the normal function of spinal motoneurons by altering the activation properties of persistent inward currents (PICs) in their dendrites. However, the effect of the PIC on firing outputs also depends on its location in the dendritic tree. To investigate the interaction between PIC neuromodulation and PIC location dependence, we used a two-compartment model that was biologically realistic in that it retains directional and frequency-dependent electrical coupling between the soma and the dendrites, as seen in multi-compartment models based on full anatomical reconstructions of motoneurons. Our two-compartment approach allowed us to systematically vary the coupling parameters between the soma and the dendrite to accurately reproduce the effect of location of the dendritic PIC on the generation of nonlinear (hysteretic) motoneuron firing patterns. Our results show that as a single parameter value for PIC activation was either increased or decreased by 20% from its default value, the solution space of the coupling parameter values for nonlinear firing outputs was drastically reduced by approximately 80%. As a result, the model tended to fire only in a linear mode at the majority of dendritic PIC sites. The same results were obtained when all parameters for the PIC activation simultaneously changed only by approximately ±10%. Our results suggest the democratization effect of neuromodulation: the neuromodulation by the brainstem systems may play a role in switching the motoneurons with PICs at different dendritic locations to a similar mode of firing by reducing the effect of the dendritic location of PICs on the firing behavior

Linking Motoneuron PIC Location to Motor Function in Closed-Loop Motor Unit System Including Afferent Feedback: A Computational Investigation

The goal of this study is to investigate how the activation location of persistent inward current (PIC) over motoneuron dendrites is linked to motor output in the closed-loop motor unit. Here, a physiologically realistic model of a motor unit including afferent inputs from muscle spindles was comprehensively analyzed under intracellular stimulation at the soma and synaptic inputs over the dendrites during isometric contractions over a full physiological range of muscle lengths. The motor output of the motor unit model was operationally assessed by evaluating the rate of force development, the degree of force potentiation and the capability of self-sustaining force production. Simulations of the model motor unit demonstrated a tendency for a faster rate of force development, a greater degree of force potentiation, and greater capacity for self-sustaining force production under both somatic and dendritic stimulation of the motoneuron as the PIC channels were positioned farther from the soma along the path of motoneuron dendrites. Interestingly, these effects of PIC activation location on force generation significantly differed among different states of muscle length. The rate of force development and the degree of force potentiation were systematically modulated by the variation of PIC channel location for shorter-than-optimal muscles but not for optimal and longer-than-optimal muscles. Similarly, the warm-up behavior of the motor unit depended on the interplay between PIC channel location and muscle length variation. These results suggest that the location of PIC activation over motoneuron dendrites may be distinctively reflected in the motor performance during shortening muscle contractions. Copyright © 2020 Kim.1

Effective Stimulation Type and Waveform for Force Control of the Motor Unit System: Implications for Intraspinal Microstimulation

The input-output properties of spinal motoneurons and muscle fibers comprising motor units are highly non-linear. The goal of this study was to investigate the stimulation type (continuous versus discrete) and waveform (linear versus non-linear) controlling force production at the motor unit level under intraspinal microstimulation. We constructed a physiological model of the motor unit with computer software enabling virtual experiments on single motor units under a wide range of input conditions, including intracellular and synaptic stimulation of the motoneuron and variation in the muscle length under neuromodulatory inputs originating from the brainstem. Continuous current intensity and impulse current frequency waveforms were inversely estimated such that the motor unit could linearly develop and relax the muscle force within a broad range of contraction speeds and levels during isometric contraction at various muscle lengths. Under both continuous and discrete stimulation, the stimulation waveform non-linearity increased with increasing speed and level of force production and with decreasing muscle length. Only discrete stimulation could control force relaxation at all muscle lengths. In contrast, continuous stimulation could not control force relaxation at high contraction levels in shorter-than-optimal muscles due to persistent inward current saturation on the motoneuron dendrites. These results indicate that non-linear adjustment of the stimulation waveform is more effective in regard to varying the force profile and muscle length and that the discrete stimulation protocol is a more robust approach for designing stimulation patterns aimed at neural interfaces for precise movement control under pathological conditions.1

Speech Enhancement for Virtual Meetings on Cellular Networks

We study speech enhancement using deep learning (DL) for virtual meetings on cellular devices, where transmitted speech has background noise and transmission loss that affects speech quality. Since the Deep Noise Suppression (DNS) Challenge dataset does not contain practical disturbance, we collect a transmitted DNS (t-DNS) dataset using Zoom Meetings over T-Mobile network. We select two baseline models: Demucs and FullSubNet. The Demucs is an end-to-end model that takes time-domain inputs and outputs time-domain denoised speech, and the FullSubNet takes time-frequency-domain inputs and outputs the energy ratio of the target speech in the inputs. The goal of this project is to enhance the speech transmitted over the cellular networks using deep learning models

Recombinant phage coated 1D Al2O3 nanostructures for controlling the adhesion and proliferation of endothelial cells

A novel synthesis of a nanostructured cell adhesive surface is investigated for future stent developments. One-dimensional (1D) Al2O3 nanostructures were prepared by chemical vapor deposition of a single source precursor. Afterwards, recombinant filamentous bacteriophages which display a short binding motif with a cell adhesive peptide (RGD) on p3 and p8 proteins were immobilized on these 1D Al2O3 nanostructures by a simple dip-coating process to study the cellular response of human endothelial EA hy.926. While the cell density decreased on as-deposited 1D Al2O3 nanostructures, we observed enhanced cell proliferation and cell-cell interaction on recombinant phage overcoated 1D Al2O3 nanostructures. The recombinant phage overcoating also supports an isotropic cell spreading rather than elongated cell morphology as we observed on as-deposited Al2O3 1D nanostructures

Asymmetry in Signal Propagation between the Soma and Dendrites Plays a Key Role in Determining Dendritic Excitability in Motoneurons

It is widely recognized that propagation of electrophysiological signals between the soma and dendrites of neurons differs depending on direction, i.e. it is asymmetric. How this asymmetry influences the activation of voltage-gated dendritic channels, and consequent neuronal behavior, remains unclear. Based on the analysis of asymmetry in several types of motoneurons, we extended our previous methodology for reducing a fully reconstructed motoneuron model to a two-compartment representation that preserved asymmetric signal propagation. The reduced models accurately replicated the dendritic excitability and the dynamics of the anatomical model involving a persistent inward current (PIC) dispersed over the dendrites. The relationship between asymmetric signal propagation and dendritic excitability was investigated using the reduced models while varying the asymmetry in signal propagation between the soma and the dendrite with PIC density constant. We found that increases in signal attenuation from soma to dendrites increased the activation threshold of a PIC (hypo-excitability), whereas increases in signal attenuation from dendrites to soma decreased the activation threshold of a PIC (hyper-excitability). These effects were so strong that reversing the asymmetry in the soma-to-dendrite vs. dendrite-to-soma attenuation, reversed the correlation between PIC threshold and distance of this current source from the soma. We propose the tight relation of the asymmetric signal propagation to the input resistance in the dendrites as a mechanism underlying the influence of the asymmetric signal propagation on the dendritic excitability. All these results emphasize the importance of maintaining the physiological asymmetry in dendritic signaling not only for normal function of the cells but also for biophysically realistic simulations of dendritic excitability. © 2014 Kim et al.1

Observation of orientation-dependent photovoltaic behaviors in aligned organic nanowires

We fabricated organic nanowire (NW) solar cells based on aligned NWs of n-channel organic semiconductor, N,N???-bis(2-phenylethyl)-perylene-3,4:9, 10-tetracarboxylic diimide via a filtration-and-transfer alignment method. It is well known that most efficient charge transport typically takes place along the long axis of organic NWs. However, there is no systematic study on the correlation between the orientation of NWs in the active layer and the power conversion efficiency (PCE) of solar cells. Our results demonstrate the effects of alignment direction of NWs on the PCE of organic solar cells with single-crystalline NWs.open0