Because the Ultimate community considers itself to be progressive, despite its largely Caucasian makeup, one topic of exploration was the political landscape of the Ultimate community. A second unique aspect of ultimate is the system for enforcing rules used by the players on the field, known as the spirit of the game. This system replaces referees and creates an ethical dynamic both during play and within the community that is not found in other sports. The last major topic of study here is the self-perception of the players as athletes. Because Ultimate continues to maintain a reputation as an alternative sport, athletes may perceive themselves differently than in more established sports.
When asked if Ultimate players perceived the Ultimate community as accepting of athletes who are people of color (POC) or members of the lesbian, gay, bisexual, or transgender community (LGBT), the community reported being accepting of all minorities. However, acceptance of POC athletes was rated significantly lower than the acceptance of LGBT athletes. When asked about comradery, the respondents rated comradery higher within the Ultimate community than in other sports. When asked how impartial players were in Ultimate compared to other sports, players with more experience tended to report perceiving themselves as more impartial. All demographics reported being more impartial in Ultimate than in other athletics. When asked about the seriousness of Ultimate, those who had not played another sport considered Ultimate to be more serious than those who had played another sport. In addition, players with more years of Ultimate experience also considered it to be more serious than those with fewer years of experience. Overall, additional studies on Ultimate culture are needed in order to obtain more viewpoints, as there is a lack of research in this field for comparison.
Voltage gated ion channels play a major role in determining a neuron's firing behavior, resulting in the specific processing of synaptic input patterns. Drosophila and other invertebrates provide valuable model systems for investigating ion channel kinetics and their impact on firing properties. Despite the increasing importance of Drosophila as a model system, few computational models of its ion channel kinetics have been developed. In this study, experimentally observed biophysical properties of voltage gated ion channels from the fruitfly Drosophila melanogaster are used to develop a minimal, conductance based neuron model. We investigate the impact of the densities of these channels on the excitability of the model neuron. Changing the channel densities reproduces different in situ observed firing patterns and induces a switch from integrator to resonator properties. Further, we analyze the preference to input frequency and how it depends on the channel densities and the resulting bifurcation type the system undergoes. An extension to a three dimensional model demonstrates that the inactivation kinetics of the sodium channels play an important role, allowing for firing patterns with a delayed first spike and subsequent high frequency firing as often observed in invertebrates, without altering the kinetics of the delayed rectifier current.
Our eyes move continuously. Even when we attempt to fix our gaze, we produce “fixational” eye movements including microsaccades, drift and tremor. The potential role of microsaccades versus drifts in the control of eye position has been debated for decades and remains in question today. Here we set out to determine the corrective functions of microsaccades and drifts on gaze-position errors due to blinks in non-human primates (Macaca mulatta) and humans. Our results show that blinks contribute to the instability of gaze during fixation, and that microsaccades, but not drifts, correct fixation errors introduced by blinks. These findings provide new insights about eye position control during fixation, and indicate a more general role of microsaccades in fixation correction than thought previously.
Computational models are increasingly important for studying complex neurophysiological systems. As scientific tools, it is essential that such models can be reproduced and critically evaluated by a range of scientists. However, published models are currently implemented using a diverse set of modeling approaches, simulation tools, and computer languages making them inaccessible and difficult to reproduce. Models also typically contain concepts that are tightly linked to domain-specific simulators, or depend on knowledge that is described exclusively in text-based documentation. To address these issues we have developed a compact, hierarchical, XML-based language called LEMS (Low Entropy Model Specification), that can define the structure and dynamics of a wide range of biological models in a fully machine readable format.
We describe how LEMS underpins the latest version of NeuroML and show that this framework can define models of ion channels, synapses, neurons and networks. Unit handling, often a source of error when reusing models, is built into the core of the language by specifying physical quantities in models in terms of the base dimensions. We show how LEMS, together with the open source Java and Python based libraries we have developed, facilitates the generation of scripts for multiple neuronal simulators and provides a route for simulator free code generation. We establish that LEMS can be used to define models from systems biology and map them to neuroscience-domain specific simulators, enabling models to be shared between these traditionally separate disciplines. LEMS and NeuroML 2 provide a new, comprehensive framework for defining computational models of neuronal and other biological systems in a machine readable format, making them more reproducible and increasing the transparency and accessibility of their underlying structure and properties.