Erin C McKiernan

How open science helps researchers succeed

Open access, open data, open source and other open scholarship practices are growing in popularity and necessity. However, widespread adoption of these practices has not yet been achieved. One reason is that researchers are uncertain about how sharing their work will affect their careers. We review literature demonstrating that open research is associated with increases in citations, media attention, potential collaborators, job opportunities and funding opportunities. These findings are evidence that open research practices bring significant benefits to researchers relative to more traditional closed practices. DOI: http://dx.doi.org/10.7554/eLife.16800.001

Relating ion channel expression, bifurcation structure, and diverse firing patterns in a model of an identified motor neuron

Neurons show diverse firing patterns. Even neurons belonging to a single chemical or morphological class, or the same identified neuron, can display different types of electrical activity. For example, motor neuron MN5, which innervates a flight muscle of adult Drosophila, can show distinct firing patterns under the same recording conditions. We developed a two-dimensional biophysical model and show that a core complement of just two voltage-gated channels is sufficient to generate firing pattern diversity. We propose Shab and DmNav to be two candidate genes that could encode these core currents, and find that changes in Shab channel expression in the model can reproduce activity resembling the main firing patterns observed in MN5 recordings. We use bifurcation analysis to describe the different transitions between rest and spiking states that result from variations in Shab channel expression, exposing a connection between ion channel expression, bifurcation structure, and firing patterns in models of membrane potential dynamics.

Effects of manipulating slowpoke calcium-dependent potassium channel expression on rhythmic locomotor activity in Drosophila larvae.

Rhythmic motor behaviors are generated by networks of neurons. The sequence and timing of muscle contractions depends on both synaptic connections between neurons and the neurons’ intrinsic properties. In particular, motor neuron ion currents may contribute significantly to motor output. Large conductance Ca2+-dependent K+ (BK) currents play a role in action potential repolarization, interspike interval, repetitive and burst firing, burst termination and interburst interval in neurons. Mutations in slowpoke (slo) genes encoding BK channels result in motor disturbances. This study examined the effects of manipulating slo channel expression on rhythmic motor activity using Drosophila larva as a model system. Dual intracellular recordings from adjacent body wall muscles were made during spontaneous crawling-related activity in larvae expressing a slo mutation or a slo RNA interference construct. The incidence and duration of rhythmic activity in slo mutants were similar to wild-type control animals, while the timing of the motor pattern was altered. slo mutants showed decreased burst durations, cycle durations, and quiescence intervals, and increased duty cycles, relative to wild-type. Expressing slo RNAi in identified motor neurons phenocopied many of the effects observed in the mutant, including decreases in quiescence interval and cycle duration. Overall, these results show that altering slo expression in the whole larva, and specifically in motor neurons, changes the frequency of crawling activity. These results suggest an important role for motor neuron intrinsic properties in shaping the timing of motor output.

Mitigating effects of vaccination on influenza outbreaks given constraints in stockpile size and daily administration capacity

BackgroundInfluenza viruses are a major cause of morbidity and mortality worldwide. Vaccination remains a powerful tool for preventing or mitigating influenza outbreaks. Yet, vaccine supplies and daily administration capacities are limited, even in developed countries. Understanding how such constraints can alter the mitigating effects of vaccination is a crucial part of influenza preparedness plans. Mathematical models provide tools for government and medical officials to assess the impact of different vaccination strategies and plan accordingly. However, many existing models of vaccination employ several questionable assumptions, including a rate of vaccination proportional to the population at each point in time.MethodsWe present a SIR-like model that explicitly takes into account vaccine supply and the number of vaccines administered per day and places data-informed limits on these parameters. We refer to this as the non-proportional model of vaccination and compare it to the proportional scheme typically found in the literature.ResultsThe proportional and non-proportional models behave similarly for a few different vaccination scenarios. However, there are parameter regimes involving the vaccination campaign duration and daily supply limit for which the non-proportional model predicts smaller epidemics that peak later, but may last longer, than those of the proportional model. We also use the non-proportional model to predict the mitigating effects of variably timed vaccination campaigns for different levels of vaccination coverage, using specific constraints on daily administration capacity.ConclusionsThe non-proportional model of vaccination is a theoretical improvement that provides more accurate predictions of the mitigating effects of vaccination on influenza outbreaks than the proportional model. In addition, parameters such as vaccine supply and daily administration limit can be easily adjusted to simulate conditions in developed and developing nations with a wide variety of financial and medical resources. Finally, the model can be used by government and medical officials to create customized pandemic preparedness plans based on the supply and administration constraints of specific communities.

Imagining the “open” university: Sharing scholarship to improve research and education

Open scholarship, such as the sharing of articles, code, data, and educational resources, has the potential to improve university research and education as well as increase the impact universities can have beyond their own walls. To support this perspective, I present evidence from case studies, published literature, and personal experiences as a practicing open scholar. I describe some of the challenges inherent to practicing open scholarship and some of the tensions created by incompatibilities between institutional policies and personal practice. To address this, I propose several concrete actions universities could take to support open scholarship and outline ways in which such initiatives could benefit the public as well as institutions. Importantly, I do not think most of these actions would require new funding but rather a redistribution of existing funds and a rewriting of internal policies to better align with university missions of knowledge dissemination and societal impact.

From spinal cord to hippocampus: links between bifurcation structure, ion channel expression, and firing patterns in a variety of neuron types

Neurons throughout the brain show remarkable diversity in their firing patterns, ranging from the generation of single action potentials to repetitive firing characterized by distinct latencies, firing frequencies, and spike shapes in response to current injection [3-5]. We present a minimal electrodiffusion-based model of membrane potential dynamics [1,2] to explore the diversity of firing patterns in a variety of neuron types, including spinal motor neurons and hippocampal granule cells. The minimal model includes voltage-gated sodium and potassium currents as well as a non-voltage-gated leak current. Our results demonstrate that small changes in the relative expression of potassium to sodium channels produce membranes with different underlying bifurcation structures. These bifurcation structures determine the way in which neurons transition from rest to spiking and, consequently, the types of firing patterns that can be observed. In addition, altering the activation kinetics of potassium channels produces additional changes in bifurcation structure, most notably, variations in the sequence of bifurcations that occur as the neuron moves from rest to spiking and back to rest again. Thus, we present not only a general biophysical model that can be used to explore firing pattern diversity in many different types of neurons, but demonstrate the links between bifurcation structure, relative ion channel expression, and firing patterns.

Biophysical modeling of excitability and membrane integration at the single cell and network levels

Ion channels facilitate the diffusion of specific ions across neuronal membranes. If large enough, this movement of charge creates currents that may change the membrane potential. Biophysical models of membrane potential assume the trans-membrane currents flow within an “equivalent electrical circuit” in which ion channels are represented by resistors arranged in parallel. The functions representing the trans-membrane currents mediated by channels are typically written using Ohm’s law. It is possible to describe channel-mediated currents by taking diffusion into consideration [1], but such formulations are not widely used in the literature. Here we present a model of membrane potential in which channel gating and current density are derived from first principles of thermodynamics, assuming that currents are produced by electrodiffusion. These models display properties that cannot be observed in conductance-based models, such as rectification of membrane currents. Guidelines for parameter estimation, and specific rules to adjust the model against experimental data, are presented along with examples of parameter regimes that yield representations of specific electrophysiological signatures with a biophysically sound baseline. Bifurcation analysis is used to describe transitions between qualitatively different behaviors of the model and link them to functionally relevant properties observable in neurons of different types. Network extensions are constructed using realistic synaptic input and local field potential oscillations to illustrate how networks may display potentially different responses to afferent input depending on the intrinsic properties of the participating neurons. The electrodiffusion formulation presented here constitutes a theoretical improvement over conductance-based models that may advance our current understanding of dynamical behavior in single cells and networks.

CA1 pyramidal cells have diverse biophysical properties, affected by development, experience, and aging

Neuron types (e.g., pyramidal cells) within one area of the brain are often considered homogeneous, despite variability in their biophysical properties. Here we review literature demonstrating variability in the electrical activity of CA1 hippocampal pyramidal cells (PCs), including responses to somatic current injection, synaptic stimulation, and spontaneous network-related activity. In addition, we describe how responses of CA1 PCs vary with development, experience, and aging, and some of the underlying ionic currents responsible. Finally, we suggest directions that may be the most impactful in expanding this knowledge, including the use of text and data mining to systematically study cellular heterogeneity in more depth; dynamical systems theory to understand and potentially classify neuron firing patterns; and mathematical modeling to study the interaction between cellular properties and network output. Our goals are to provide a synthesis of the literature for experimentalists studying CA1 PCs, to give theorists an idea of the rich diversity of behaviors models may need to reproduce to accurately represent these cells, and to provide suggestions for future research.

The role of the large-conductance calcium-dependent potassium channel, BK/Slowpoke, in shaping motor neuron firing during rhythmic activity

Rhythmic muscle contractions underlie a number of crucial motor behaviors, such as respiration and locomotion. The timing of contractions is determined by the intrinsic activity and synaptic interactions of neurons within what are called central pattern generating (CPG) networks [1,2]. In many systems, motor neurons (MNs) are not part of the classically-defined CPG. However, research suggests that ionic currents in MNs may shape the timing of the final motor output [3,4]. A lot of work has focused particularly on the role of potassium currents in shaping responsiveness and firing of MNs [3,5]. Large-conductance calcium-dependent potassium (BK) currents, encoded by members of the Slowpoke (Slo) gene family, can contribute to action potential repolarization, regulation of firing frequency and interspike interval, repetitive firing, and burst termination [6]. Mutations of Slo genes also lead to a variety of motor disturbances [6]. We developed a biophysical model of bursting activity in MNs to explore the circumstances under which a BK/Slo current expressed in MNs can shape the timing of motor output underlying locomotion. We identify mechanisms by which the BK/Slo current changes the bursting output of MNs, and describe the different behaviors that are observed for varying membrane densities of the underlying channel. We also present preliminary data consisting of electrophysiological recordings from larval Drosophila showing that the changes in motor output predicted by the model are indeed observed when genetic manipulations of Slo channel density (RNA interference constructs) are targeted to MNs [7]. Our results not only further understanding of the specific role of BK/Slo channels in MNs, but contribute more generally to the growing knowledge on the role intrinsic MN properties play in shaping rhythmic motor output.

Differential contribution of A-type potassium currents in shaping neuronal responses to synaptic input

Neurons receive input from thousands of excitatory and inhibitory synapses, but they are not merely passive receivers and transmitters of information. The intrinsic properties of neurons, and more specifically the collection of ion channels expressed, influence a cells excitability and integration processes. The role of different voltage-dependent transient (A-type) and persistent (delayed rectifier) potassium currents in shaping the activity of neurons in response to synaptic input is not well understood. We developed a biophysical model incorporating realistic synaptic input [1] to investigate the specific roles played by distinct A-type potassium channels encoded by different genes, namely Shaker/Kv1 and Shal/Kv4. We find that these two channel types, which are functionally distinguished by their inactivation properties, exert different control mechanisms on the transitions between rest and repetitive spiking in neurons. Bifurcation analysis is used to characterize the influence of each channel and the overall behavior of the membrane as a function of the relative presence of the two A-type channels. We found that the influence of each channel type depends on the resting potential of the neuron, suggesting that modulation and/or network states may shift their relative contribution. For example, at a particular membrane potential, Shal/Kv4 channels are more likely to mediate delays to first spike in response to excitatory input. Overall, this work increases our understanding of the interaction between intrinsic properties and synaptic input in creating neuronal response profiles. Further, we provide a link between relative gene expression and bifurcation structures in dynamical systems modeling neuronal membranes.