Robert J Butera

Georgia Institute of Technology, Atlanta, Georgia, United States

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Publications (87)176.36 Total impact

  • Yogi A. Patel · Robert J Butera
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    ABSTRACT: 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 non-monotonic block threshold relationship with increasing KES frequency. The distinct trends with frequency of the two components enable 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 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 and selective control of neural circuits underlying sensorimotor function. Copyright © 2014, Journal of Neurophysiology.
    Journal of Neurophysiology 04/2015; 113(10):jn.00529.2014. DOI:10.1152/jn.00529.2014 · 3.04 Impact Factor
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    Sharon E Norman · Robert J Butera
    BMC Neuroscience 07/2014; 15(Suppl 1):P195. DOI:10.1186/1471-2202-15-S1-P195 · 2.85 Impact Factor
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    ABSTRACT: 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.
    PLoS Computational Biology 05/2014; 10(5):e1003622. DOI:10.1371/journal.pcbi.1003622 · 4.83 Impact Factor
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    ABSTRACT: The injection of computer-simulated conductances through the dynamic clamp technique has allowed researchers to probe the intercellular and intracellular dynamics of cardiac and neuronal systems with great precision. By coupling computational models to biological systems, dynamic clamp has become a proven tool in electrophysiology with many applications, such as generating hybrid networks in neurons or simulating channelopathies in cardiomyocytes. While its applications are broad, the approach is straightforward: synthesizing traditional patch clamp, computational modeling, and closed-loop feedback control to simulate a cellular conductance. Here, we present two example applications: artificial blocking of the inward rectifier potassium current in a cardiomyocyte and coupling of a biological neuron to a virtual neuron through a virtual synapse. The design and implementation of the necessary software to administer these dynamic clamp experiments can be difficult. In this chapter, we provide an overview of designing and implementing a dynamic clamp experiment using the Real-Time eXperiment Interface (RTXI), an open-source software system tailored for real-time biological experiments. We present two ways to achieve this using RTXI's modular format, through the creation of a custom user-made module and through existing modules found in RTXI's online library.
    Methods in molecular biology (Clifton, N.J.) 01/2014; 1183:327-54. DOI:10.1007/978-1-4939-1096-0_21 · 1.29 Impact Factor
  • Robert Butera · Sharon Norman
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    ABSTRACT: DefinitionPhase response curves (PRCs) describe how an oscillator responds to input perturbations given at various times during the oscillator cycle. Phase resetting, and by extension PRCs, can be classified as weak or strong based on a geometric analysis of perturbations to the limit cycle (Glass and Winfree 1984). This geometric classification of PRCs is distinct from that based on the bifurcation structure of the state space (Rinzel and Ermentrout 1989).Detailed DescriptionIntroductionMany types of biological systems exhibit oscillations. In neuroscience, oscillations are evident at a variety of spatial and temporal scales, from the repetitive firing of action potentials (single neuron, milliseconds to seconds) to the circadian rhythms evident in the suprachiasmatic nucleus (thousands of neurons, one day).Computational modeling has evolved since the pioneering work of Hodgkin and Huxley, but for many neural systems, sufficient data may not exist to construct a detailed, conductance- ...
    Encyclopedia of Computational Neuroscience, 01/2014: pages 1-5; , ISBN: 978-1-4614-7320-6
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    ABSTRACT: 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. Bioelectromagnetics © 2013 Wiley Periodicals, Inc.
    Bioelectromagnetics 12/2013; 34(8). DOI:10.1002/bem.21810 · 1.86 Impact Factor
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    Sharon E Norman · Carmen C Canavier · Robert J Butera
    BMC Neuroscience 07/2013; 14(1). DOI:10.1186/1471-2202-14-S1-P50 · 2.85 Impact Factor
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    ABSTRACT: This article summarizes the discussions held during the first IEEE Life Sciences Grand Challenges Conference held on October 4-5, 2012 at the National Academy of Sciences in Washington DC, and the grand challenges identified by the conference participants. Despite tremendous efforts to develop the knowledge and ability that are essential in addressing biomedical and health problems using engineering methodologies, the optimization of this approach towards engineering the life sciences and healthcare remains a grand challenge. The conference was aimed at high-level discussions by participants representing various sectors, including academia, government, and industry. Grand challenges were identified by the conference participants in five areas, including engineering the brain and nervous system, engineering the cardiovascular system, engineering of cancer diagnostics, therapeutics, and prevention, translation of discoveries to clinical applications, and education and training. A number of these challenges are identified and summarized in this article.
    IEEE transactions on bio-medical engineering 02/2013; 60(3). DOI:10.1109/TBME.2013.2244886 · 2.23 Impact Factor
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    Natalia Toporikova · Robert J Butera
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    ABSTRACT: Neuromodulators, such as amines and neuropeptides, alter the activity of neurons and neuronal networks. In this work, we investigate how neuromodulators, which activate G(q)-protein second messenger systems, can modulate the bursting frequency of neurons in a critical portion of the respiratory neural network, the pre-Bötzinger complex (preBötC). These neurons are a vital part of the ponto-medullary neuronal network, which generates a stable respiratory rhythm whose frequency is regulated by neuromodulator release from the nearby Raphe nucleus. Using a simulated 50-cell network of excitatory preBötC neurons with a heterogeneous distribution of persistent sodium conductance and Ca(2+), we determined conditions for frequency modulation in such a network by simulating interaction between Raphe and preBötC nuclei. We found that the positive feedback between the Raphe excitability and preBötC activity induces frequency modulation in the preBötC neurons. In addition, the frequency of the respiratory rhythm can be regulated via phasic release of excitatory neuromodulators from the Raphe nucleus. We predict that the application of a G(q) antagonist will eliminate this frequency modulation by the Raphe and keep the network frequency constant and low. In contrast, application of a G(q) agonist will result in a high frequency for all levels of Raphe stimulation. Our modeling results also suggest that high [K(+)] requirement in respiratory brain slice experiments may serve as a compensatory mechanism for low neuromodulatory tone.
    Respiratory Physiology & Neurobiology 11/2012; 185(3). DOI:10.1016/j.resp.2012.11.013 · 1.97 Impact Factor
  • Jonathan Newman · Robert J Butera
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    ABSTRACT: Multirhythmicity, the coexistence of multiple oscillatory attractors in a dynamic system, is explored in a type of bursting nerve cell. It is shown that in the multirhythmic parameter regime, spike addition during the active phase of bursting causes alternating concentric regions of contraction and expansion in the vector field of the slow variables. This produces concentric, isolated annuluses in state space, therefore, multirhythmicity. Evidence for the existance of multirthmic behaviour 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 temporal information for longer time scales than typically attributed to non-synaptic mechanisms.
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    Sharon E Norman · Carmen C Canavier · Robert J Butera
    BMC Neuroscience 07/2012; 13(1). DOI:10.1186/1471-2202-13-S1-P174 · 2.85 Impact Factor
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    BMC Neuroscience 07/2012; 13(1). DOI:10.1186/1471-2202-13-S1-P173 · 2.85 Impact Factor
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    Natalia Toporikova · Robert J Butera
    BMC Neuroscience 07/2012; 13(1). DOI:10.1186/1471-2202-13-S1-P175 · 2.85 Impact Factor
  • Roberta M Berry · Jason Borenstein · Robert J Butera
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    ABSTRACT: 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.
    Science and Engineering Ethics 03/2012; 19(2). DOI:10.1007/s11948-012-9359-6 · 1.52 Impact Factor
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    Laveeta Joseph · Robert J Butera
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    ABSTRACT: Conduction block using high-frequency alternating current (HFAC) stimulation has been shown to reversibly block conduction through various nerves. However, unlike simulations and experiments on myelinated fibers, prior experimental work in our lab on the sea-slug, Aplysia, found a nonmonotonic relationship between frequency and blocking thresholds in the unmyelinated fibers. To resolve this discrepancy, we investigated the effect of HFAC waveforms on the compound action potential of the sciatic nerve of frogs. Maximal stimulation of the nerve produces a compound action potential consisting of the A-fiber and C-fiber components corresponding to the myelinated and unmyelinated fibers' response. In our study, HFAC waveforms were found to induce reversible block in the A-fibers and C-fibers for frequencies in the range of 5-50 kHz and for amplitudes from 0.1-1 mA. Although the A-fibers demonstrated the monotonically increasing threshold behavior observed in published literature, the C-fibers displayed a nonmonotonic relationship, analogous to that observed in the unmyelinated fibers of Aplysia. This differential blocking behavior observed in myelinated and unmyelinated fibers during application of HFAC waveforms has diverse implications for the fields of selective stimulation and pain management.
    IEEE transactions on neural systems and rehabilitation engineering: a publication of the IEEE Engineering in Medicine and Biology Society 08/2011; 19(5):550-7. DOI:10.1109/TNSRE.2011.2163082 · 2.82 Impact Factor
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    Natalia Toporikova · Robert Butera
    BMC Neuroscience 07/2011; 12(1). DOI:10.1186/1471-2202-12-S1-P25 · 2.85 Impact Factor
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    Natalia Toporikova · Robert J Butera
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    ABSTRACT: 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.
    Journal of Computational Neuroscience 06/2011; 30(3):515-28. DOI:10.1007/s10827-010-0274-z · 2.09 Impact Factor
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    ABSTRACT: 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.
    Journal of Computational Neuroscience 05/2011; 31(3):701-11. DOI:10.1007/s10827-011-0340-1 · 2.09 Impact Factor
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    Patrick J Bradley · Kurt Wiesenfeld · Robert J Butera
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    ABSTRACT: 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.
    Journal of Computational Neuroscience 04/2011; 30(2):455-69. DOI:10.1007/s10827-010-0270-3 · 2.09 Impact Factor
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    Srisairam Achuthan · Robert J Butera · Carmen C Canavier
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    ABSTRACT: 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.
    Journal of Computational Neuroscience 04/2011; 30(2):373-90. DOI:10.1007/s10827-010-0264-1 · 2.09 Impact Factor

Publication Stats

2k Citations
176.36 Total Impact Points

Institutions

  • 1999–2014
    • Georgia Institute of Technology
      • • Department of Biomedical Engineering
      • • School of Electrical & Computer Engineering
      • • Laboratory for Neuroengineering
      Atlanta, Georgia, United States
  • 2007–2011
    • Emory University
      Atlanta, Georgia, United States
  • 2008
    • Columbia University
      New York, New York, United States
  • 1995–1999
    • Rice University
      • Department of Electrical and Computer Engineering
      Houston, Texas, United States
  • 1998
    • The National Institute of Diabetes and Digestive and Kidney Diseases
      베서스다, Maryland, United States