DeepLabCut increases markerless tracking efficiency in X-ray video analysis of rodent locomotion.

Despite the prevalence of rat models to study human disease and injury, existing methods for quantifying behavior through skeletal movements are problematic owing to skin movement inaccuracies associated with optical video analysis, or require invasive implanted markers or time-consuming manual rotoscoping for X-ray video approaches. We examined the use of a machine learning tool, DeepLabCut, to perform automated, markerless tracking in bi-planar X-ray videos of locomoting rats. Models were trained on 590 pairs of video frames to identify 19 unique skeletal landmarks of the pelvic limb. Accuracy, precision and time savings were assessed. Machine-identified landmarks deviated from manually labeled counterparts by 2.4±0.2 mm (n=1710 landmarks). DeepLabCut decreased analysis time by over three orders of magnitude (1627×) compared with manual labeling. Distribution of these models may enable the processing of a large volume of accurate X-ray kinematics locomotion data in a fraction of the time without requiring surgically implanted markers.

Hard real-time closed-loop electrophysiology with the Real-Time eXperiment Interface (RTXI).

The ability to experimentally perturb biological systems has traditionally been limited to static pre-programmed or operator-controlled protocols. In contrast, real-time control allows dynamic probing of biological systems with perturbations that are computed on-the-fly during experimentation. Real-time control applications for biological research are available; however, these systems are costly and often restrict the flexibility and customization of experimental protocols. The Real-Time eXperiment Interface (RTXI) is an open source software platform for achieving hard real-time data acquisition and closed-loop control in biological experiments while retaining the flexibility needed for experimental settings. RTXI has enabled users to implement complex custom closed-loop protocols in single cell, cell network, animal, and human electrophysiology studies. RTXI is also used as a free and open source, customizable electrophysiology platform in open-loop studies requiring online data acquisition, processing, and visualization. RTXI is easy to install, can be used with an extensive range of external experimentation and data acquisition hardware, and includes standard modules for implementing common electrophysiology protocols.

Stochastic slowly adapting ionic currents may provide a decorrelation mechanism for neural oscillators by causing wander in the intrinsic period.

Oscillatory neurons integrate their synaptic inputs in fundamentally different ways than normally quiescent neurons. We show that the oscillation period of invertebrate endogenous pacemaker neurons wanders, producing random fluctuations in the interspike intervals (ISI) on a time scale of seconds to minutes, which decorrelates pairs of neurons in hybrid circuits constructed using the dynamic clamp. The autocorrelation of the ISI sequence remained high for many ISIs, but the autocorrelation of the ΔISI series had on average a single nonzero value, which was negative at a lag of one interval. We reproduced these results using a simple integrate and fire (IF) model with a stochastic population of channels carrying an adaptation current with a stochastic component that was integrated with a slow time scale, suggesting that a similar population of channels underlies the observed wander in the period. Using autoregressive integrated moving average (ARIMA) models, we found that a single integrator and a single moving average with a negative coefficient could simulate both the experimental data and the IF model. Feeding white noise into an integrator with a slow time constant is sufficient to produce the autocorrelation structure of the ISI series. Moreover, the moving average clearly accounted for the autocorrelation structure of the ΔISI series and is biophysically implemented in the IF model using slow stochastic adaptation. The observed autocorrelation structure may be a neural signature of slow stochastic adaptation, and wander generated in this manner may be a general mechanism for limiting episodes of synchronized activity in the nervous system.

Differential fiber-specific block of nerve conduction in mammalian peripheral nerves using kilohertz electrical stimulation.

Kilohertz electrical stimulation (KES) has been shown to induce repeatable and reversible nerve conduction block in animal models. In this study, we characterized the ability of KES stimuli to selectively block specific components of stimulated nerve activity using in vivo preparations of the rat sciatic and vagus nerves. KES stimuli in the frequency range of 5-70 kHz and amplitudes of 0.1-3.0 mA were applied. Compound action potentials were evoked using either electrical or sensory stimulation, and block of components was assessed through direct nerve recordings and muscle force measurements. Distinct observable components of the compound action potential had unique conduction block thresholds as a function of frequency of KES. The fast component, which includes motor activity, had a monotonically increasing block threshold as a function of the KES frequency. The slow component, which includes sensory activity, showed a nonmonotonic block threshold relationship with increasing KES frequency. The distinct trends with frequency of the two components enabled selective block of one component with an appropriate choice of frequency and amplitude. These trends in threshold of the two components were similar when studying electrical stimulation and responses of the sciatic nerve, electrical stimulation and responses of the vagus nerve, and sensorimotor stimulation and responses of the sciatic nerve. This differential blocking effect of KES on specific fibers can extend the applications of KES conduction block to selective block and stimulation of neural signals for neuromodulation as well as selective control of neural circuits underlying sensorimotor function.

Slow noise in the period of a biological oscillator underlies gradual trends and abrupt transitions in phasic relationships in hybrid neural networks.

In order to study the ability of coupled neural oscillators to synchronize in the presence of intrinsic as opposed to synaptic noise, we constructed hybrid circuits consisting of one biological and one computational model neuron with reciprocal synaptic inhibition using the dynamic clamp. Uncoupled, both neurons fired periodic trains of action potentials. Most coupled circuits exhibited qualitative changes between one-to-one phase-locking with fairly constant phasic relationships and phase slipping with a constant progression in the phasic relationships across cycles. The phase resetting curve (PRC) and intrinsic periods were measured for both neurons, and used to construct a map of the firing intervals for both the coupled and externally forced (PRC measurement) conditions. For the coupled network, a stable fixed point of the map predicted phase locking, and its absence produced phase slipping. Repetitive application of the map was used to calibrate different noise models to simultaneously fit the noise level in the measurement of the PRC and the dynamics of the hybrid circuit experiments. Only a noise model that added history-dependent variability to the intrinsic period could fit both data sets with the same parameter values, as well as capture bifurcations in the fixed points of the map that cause switching between slipping and locking. We conclude that the biological neurons in our study have slowly-fluctuating stochastic dynamics that confer history dependence on the period. Theoretical results to date on the behavior of ensembles of noisy biological oscillators may require re-evaluation to account for transitions induced by slow noise dynamics.

Electrical polarization of titanium surfaces for the enhancement of osteoblast differentiation.

Electrical stimulation has been used clinically to promote bone regeneration in cases of fractures with delayed union or nonunion, with several in vitro and in vivo reports suggesting its beneficial effects on bone formation. However, the use of electrical stimulation of titanium (Ti) implants to enhance osseointegration is less understood, in part because of the few in vitro models that attempt to represent the in vivo environment. In this article, the design of a new in vitro system that allows direct electrical stimulation of osteoblasts through their Ti substrates without the flow of exogenous currents through the media is presented, and the effect of applied electrical polarization on osteoblast differentiation and local factor production was evaluated. A custom-made polycarbonate tissue culture plate was designed to allow electrical connections directly underneath Ti disks placed inside the wells, which were supplied with electrical polarization ranging from 100 to 500 mV to stimulate MG63 osteoblasts. Our results show that electrical polarization applied directly through Ti substrates on which the cells are growing in the absence of applied electrical currents may increase osteoblast differentiation and local factor production in a voltage-dependent manner.

Contentious problems in bioscience and biotechnology: a pilot study of an approach to ethics education.

This manuscript describes a pilot study in ethics education employing a problem-based learning approach to the study of novel, complex, ethically fraught, unavoidably public, and unavoidably divisive policy problems, called "fractious problems," in bioscience and biotechnology. Diverse graduate and professional students from four US institutions and disciplines spanning science, engineering, humanities, social science, law, and medicine analyzed fractious problems employing "navigational skills" tailored to the distinctive features of these problems. The students presented their results to policymakers, stakeholders, experts, and members of the public. This approach may provide a model for educating future bioscientists and bioengineers so that they can meaningfully contribute to the social understanding and resolution of challenging policy problems generated by their work.

Two types of independent bursting mechanisms in inspiratory neurons: an integrative model.

The network of coupled neurons in the pre-Bötzinger complex (pBC) of the medulla generates a bursting rhythm, which underlies the inspiratory phase of respiration. In some of these neurons, bursting persists even when synaptic coupling in the network is blocked and respiratory rhythmic discharge stops. Bursting in inspiratory neurons has been extensively studied, and two classes of bursting neurons have been identified, with bursting mechanism depends on either persistent sodium current or changes in intracellular Ca(2+), respectively. Motivated by experimental evidence from these intrinsically bursting neurons, we present a two-compartment mathematical model of an isolated pBC neuron with two independent bursting mechanisms. Bursting in the somatic compartment is modeled via inactivation of a persistent sodium current, whereas bursting in the dendritic compartment relies on Ca(2+) oscillations, which are determined by the neuromodulatory tone. The model explains a number of conflicting experimental results and is able to generate a robust bursting rhythm, over a large range of parameters, with a frequency adjusted by neuromodulators.

Synaptic and intrinsic determinants of the phase resetting curve for weak coupling.

A phase resetting curve (PRC) keeps track of the extent to which a perturbation at a given phase advances or delays the next spike, and can be used to predict phase locking in networks of oscillators. The PRC can be estimated by convolving the waveform of the perturbation with the infinitesimal PRC (iPRC) under the assumption of weak coupling. The iPRC is often defined with respect to an infinitesimal current as z(i)(ϕ), where ϕ is phase, but can also be defined with respect to an infinitesimal conductance change as z(g)(ϕ). In this paper, we first show that the two approaches are equivalent. Coupling waveforms corresponding to synapses with different time courses sample z(g)(ϕ) in predictably different ways. We show that for oscillators with Type I excitability, an anomalous region in z(g)(ϕ) with opposite sign to that seen otherwise is often observed during an action potential. If the duration of the synaptic perturbation is such that it effectively samples this region, PRCs with both advances and delays can be observed despite Type I excitability. We also show that changing the duration of a perturbation so that it preferentially samples regions of stable or unstable slopes in z(g)(ϕ) can stabilize or destabilize synchrony in a network with the corresponding dynamics.

Effects of heterogeneity in synaptic conductance between weakly coupled identical neurons.

A significant degree of heterogeneity in synaptic conductance is present in neuron to neuron connections. We study the dynamics of weakly coupled pairs of neurons with heterogeneities in synaptic conductance using Wang-Buzsaki and Hodgkin-Huxley model neurons which have Types I and II excitability, respectively. This type of heterogeneity breaks a symmetry in the bifurcation diagrams of equilibrium phase difference versus the synaptic rate constant when compared to the identical case. For weakly coupled neurons coupled with identical values of synaptic conductance a phase locked solution exists for all values of the synaptic rate constant, α. In particular, in-phase and anti-phase solutions are guaranteed to exist for all α. Heterogeneity in synaptic conductance results in regions where no phase locked solution exists and the general loss of the ubiquitous in-phase and anti-phase solutions of the identically coupled case. We explain these results through examination of interaction functions using the weak coupling approximation and an in-depth analysis of the underlying multiple cusp bifurcation structure of the systems of coupled neurons.

Conflicting effects of excitatory synaptic and electric coupling on the dynamics of square-wave bursters.

Using two-cell and 50-cell networks of square-wave bursters, we studied how excitatory coupling of individual neurons affects the bursting output of the network. Our results show that the effects of synaptic excitation vs. electrical coupling are distinct. Increasing excitatory synaptic coupling generally increases burst duration. Electrical coupling also increases burst duration for low to moderate values, but at sufficiently strong values promotes a switch to highly synchronous bursts where further increases in electrical or synaptic coupling have a minimal effect on burst duration. These effects are largely mediated by spike synchrony, which is determined by the stability of the in-phase spiking solution during the burst. Even when both coupling mechanisms are strong, one form (in-phase or anti-phase) of spike synchrony will determine the burst dynamics, resulting in a sharp boundary in the space of the coupling parameters. This boundary exists in both two cell and network simulations. We use these results to interpret the effects of gap-junction blockers on the neuronal circuitry that underlies respiration.

Mechanism, dynamics, and biological existence of multistability in a large class of bursting neurons.

Multistability, the coexistence of multiple attractors in a dynamical system, is explored in bursting nerve cells. A modeling study is performed to show that a large class of bursting systems, as defined by a shared topology when represented as dynamical systems, is inherently suited to support multistability. We derive the bifurcation structure and parametric trends leading to multistability in these systems. Evidence for the existence of multirhythmic behavior in neurons of the aquatic mollusc Aplysia californica that is consistent with our proposed mechanism is presented. Although these experimental results are preliminary, they indicate that single neurons may be capable of dynamically storing information for longer time scales than typically attributed to nonsynaptic mechanisms.

Core Competencies for Undergraduates in Bioengineering and Biomedical Engineering: Findings, Consequences, and Recommendations.

This paper provides a synopsis of discussions related to biomedical engineering core curricula that occurred at the Fourth BME Education Summit held at Case Western Reserve University in Cleveland, Ohio in May 2019. This summit was organized by the Council of Chairs of Bioengineering and Biomedical Engineering, and participants included over 300 faculty members from 100+ accredited undergraduate programs. This discussion focused on six key questions: QI: Is there a core curriculum, and if so, what are its components? QII: How does our purported core curriculum prepare students for careers, particularly in industry? QIII: How does design distinguish BME/BIOE graduates from other engineers? QIV: What is the state of engineering analysis and systems-level modeling in BME/BIOE curricula? QV: What is the role of data science in BME/BIOE undergraduate education? QVI: What core experimental skills are required for BME/BIOE undergrads? s. Indeed, BME/BIOI core curricula exists and has matured to emphasize interdisciplinary topics such as physiology, instrumentation, mechanics, computer programming, and mathematical modeling. Departments demonstrate their own identities by highlighting discipline-specific sub-specialties. In addition to technical competence, Industry partners most highly value our students' capacity for problem solving and communication. As such, BME/BIOE curricula includes open-ended projects that address unmet patient and clinician needs as primary methods to prepare graduates for careers in industry. Culminating senior design experiences distinguish BME/BIOE graduates through their development of client-centered engineering solutions to healthcare problems. Finally, the overall BME/BIOE curriculum is not stagnant-it is clear that data science will become an ever-important element of our students' training and that new methods to enhance student engagement will be of pedagogical importance as we embark on the next decade.

Computational model of TASK channels and PKC-pathway dependent serotonergic modulatory effects in respiratory-related neurons.

Hypoglossal motoneurons (HMs) receive serotonergic innervations from medullary raphe neurons and produce rhythmic discharge patterns closely associated with respiratory rhythm generated in the pre-Bötzinger complex (pBC). HM activity is subject to modulation by numerous factors including serotonin (5-HT), TRH, norepinephrine (NE), substance P (SP), pH, multiple protein kinases and phosphatases. In this present work, we introduce a computational HM model that facilitates the investigation of how neuromodulatory factors such as 5-HT and pH, can affect HM activities.

Challenges associated with nerve conduction block using kilohertz electrical stimulation.

Neuromodulation therapies, which electrically stimulate parts of the nervous system, have traditionally attempted to activate neurons or axons to restore function or alleviate disease symptoms. In stark contrast to this approach is inhibiting neural activity to relieve disease symptoms and/or restore homeostasis. One potential approach is kilohertz electrical stimulation (KES) of peripheral nerves-which enables a rapid, reversible, and localized block of conduction. This review highlights the existing scientific and clinical utility of KES and discusses the technical and physiological challenges that must be addressed for successful translation of KES nerve conduction block therapies.

Kilohertz Electrical Stimulation Nerve Conduction Block: Effects of Electrode Material.

Kilohertz electrical stimulation (KES) has enabled a novel new paradigm for spinal cord and peripheral nerve stimulation to treat a variety of neurological diseases. KES can excite or inhibit nerve activity and is used in many clinical devices today. However, the impact of different electrode materials on the efficacy of KES is unknown. We investigated the effect of different electrode materials and their respective charge injection mechanisms on KES nerve block thresholds using 20- and 40-kHz current-controlled sinusoidal KES waveforms. We evaluated the nerve block threshold and the power requirements for achieving an effective KES nerve block. In addition, we evaluated potential effects on the onset duration and recovery of normal conduction after delivery of KES. We found that thresholds and the onset and recovery of KES nerve block are not a function of the electrode material. In contrast, the power dissipation varies among electrode materials and is a function of the materials' properties at high frequencies. We conclude that materials with a proven track record of chronic stability, both for the tissue and electrode, are suitable for developing KES nerve block therapies.

Serotonergic enhancement of a 4-AP-sensitive current mediates the synaptic depression phase of spike timing-dependent neuromodulation.

The mechanism underlying spike timing-dependent neuromodulation (STDN) was investigated in the opisthobranch mollusc Tritonia diomedea. The serotonergic dorsal swim interneurons (DSIs) dynamically modulated the synaptic output of ventral swim interneuron B (VSI); immediately after DSI stimulation, there was a potentiation of VSI synaptic strength followed by a longer-lasting synaptic depression. The potentiation phase of STDN was unaffected by spike broadening produced by the potassium channel blocker 4-aminopyridine (4-AP). In contrast, the depression phase was eliminated by 4-AP. Bath-applied serotonin (5-HT) decreased VSI spike duration and increased the magnitude of the A-current (IA), a voltage-dependent, transient, outward current. 4-AP preferentially blocked IA and prevented the spike narrowing caused by 5-HT, uncovering the full extent of 5-HT-induced synaptic potentiation. A consistent correlation was observed between IA and spike duration, but the correlation between synaptic strength and spike duration differed between preparations. Conductance-based simulations showed that the magnitude of A-current conductance could affect spike duration and gave an estimation of the change needed to produce spike narrowing. An artificial IA introduced into the VSI in the presence of 4-AP by means of the dynamic-clamp technique restored spike duration and gave a further approximation of the magnitude of modulation needed for spike narrowing. Together, these results suggest a mechanism for STDN: the DSIs release 5-HT, which causes a spike duration-independent enhancement of synaptic strength and a longer-lasting enhancement of IA that narrows the VSI spike and hence decreases VSI synaptic strength. Thus, STDN arises from the dynamics of independent intracellular signaling events.

Kilohertz Electrical Stimulation Nerve Conduction Block: Effects of Electrode Surface Area.

Kilohertz electrical stimulation (KES) induces repeatable and reversible conduction block of nerve activity and is a potential therapeutic option for various diseases and disorders resulting from pathological or undesired neurological activity. However, successful translation of KES nerve block to clinical applications is stymied by many unknowns, such as the relevance of the onset response, acceptable levels of waveform contamination, and optimal electrode characteristics. We investigated the role of electrode geometric surface area on the KES nerve block threshold using 20- and 40-kHz current-controlled sinusoidal KES. Electrodes were electrochemically characterized and used to characterize typical KES waveforms and electrode charge characteristics. KES nerve block amplitudes, onset duration, and recovery of normal conduction after delivery of the KES were evaluated along with power requirements for effective KES nerve block. Results from this investigation demonstrate that increasing electrode geometric surface area provides for a more power-efficient KES nerve block. Reductions in block threshold by increased electrode surface area were found to be KES-frequency-dependent, with block thresholds and average power consumption reduced by greater than two times with 20-kHz KES waveforms and greater than three times for 40-kHz KES waveforms.

Corrigendum: Kilohertz frequency nerve block enhances anti-inflammatory effects of vagus nerve stimulation.

This corrects the article DOI: 10.1038/srep39810.

Kilohertz frequency nerve block enhances anti-inflammatory effects of vagus nerve stimulation.

Efferent activation of the cervical vagus nerve (cVN) dampens systemic inflammatory processes, potentially modulating a wide-range of inflammatory pathological conditions. In contrast, afferent cVN activation amplifies systemic inflammatory processes, leading to activation of the hypothalamic-pituitary-adrenal (HPA) axis, the sympathetic nervous system through the greater splanchnic nerve (GSN), and elevation of pro-inflammatory cytokines. Ideally, to clinically implement anti-inflammatory therapy via cervical vagus nerve stimulation (cVNS) one should selectively activate the efferent pathway. Unfortunately, current implementations, in animal and clinical investigations, activate both afferent and efferent pathways. We paired cVNS with kilohertz electrical stimulation (KES) nerve block to preferentially activate efferent pathways while blocking afferent pathways. Selective efferent cVNS enhanced the anti-inflammatory effects of cVNS. Our results demonstrate that: (i) afferent, but not efferent, cVNS synchronously activates the GSN in a dose-dependent manner; (ii) efferent cVNS enabled by complete afferent KES nerve block enhances the anti-inflammatory benefits of cVNS; and (iii) incomplete afferent KES nerve block exacerbates systemic inflammation. Overall, these data demonstrate the utility of paired efferent cVNS and afferent KES nerve block for achieving selective efferent cVNS, specifically as it relates to neuromodulation of systemic inflammation.