‘Not to escape the world but to join it’: responding to climate change with imagination not fantasy

The work of climate scientists, demonstrating human-driven climate change, has not provoked the widespread and far-reaching changes to human behaviour necessary to avert potentially catastrophic environmental trajectories. This work has not yet sufficiently been able to engage the individual and collective imagination. Drawing on Samuel Taylor Coleridge (1772–1834) and Iris Murdoch (1919–1999), we can distinguish two modes under which the human imagination can operate: in Murdoch's terms, these are ‘imagination’ and ‘fantasy’. To relate imaginatively is to be willing to allow one's internal image of the world to be changed by what one encounters, while an outlook characterized by fantasy relates to the world as one would wish it were, rather than how it actually is. Fantasy, therefore, operates not only among those who deny climate change, but also among those who entertain the promise of a technological solution too optimistically. An imaginative outlook, by contrast, evaluates actions and patterns of behaviour in terms of their relation to a wider whole. This is necessary for providing the degree of agency required to step out of a cycle of ever accelerating production, which is explored in terms of an analogy to a discussion of revenge and forgiveness from Hannah Arendt (1906–1975). Ultimately, the need to engage the imagination is an opportunity as well as a challenge. To live imaginatively is fulfilling, and that is precisely what the challenges of climate change require

Reproducible Software Appliances for Experimentation

International audienceExperiment reproducibility is a milestone of the scientific method. Reproducibility of experiments in computer science would bring several advantages such as code re-usability and technology transfer. The reproducibility problem in computer science has been solved partially, addressing particular class of applications or single machine setups. In this paper we present our approach oriented to setup complex environments for experimentation, environments that require a lot of configuration and the installation of several software packages. The main objective of our approach is to enable the exact and independent reconstruction of a given software environment and the reuse of code. We present a simple and small software appliance generator that helps an experimenter to construct a specific software stack that can be deployed on different available testbeds

A Commitment to Open Source in Neuroscience

Modern neuroscience increasingly relies on custom-developed software, but much of this is not being made available to the wider community. A group of researchers are pledging to make code they produce for data analysis and modeling open source, and are actively encouraging their colleagues to follow suit

Fish under exercise

Improved knowledge on the swimming physiology of fish and its application to fisheries science and aquaculture (i.e., farming a fitter fish) is currently needed in the face of global environmental changes, high fishing pressures, increased aquaculture production as well as increased concern on fish well-being. Here, we review existing data on teleost fish that indicate that sustained exercise at optimal speeds enhances muscle growth and has consequences for flesh quality. Potential added benefits of sustained exercise may be delay of ovarian development and stimulation of immune status. Exercise could represent a natural, noninvasive, and economical approach to improve growth, flesh quality as well as welfare of aquacultured fish: a FitFish for a healthy consumer. All these issues are important for setting directions for policy decisions and future studies in this area. For this purpose, the FitFish workshop on the Swimming Physiology of Fish (http://www.ub.edu/fitfish2010) was organized to bring together a multidisciplinary group of scientists using exercise models, industrial partners, and policy makers. Sixteen international experts from Europe, North America, and Japan were invited to present their work and view on migration of fishes in their natural environment, beneficial effects of exercise, and applications for sustainable aquaculture. Eighty-eight participants from 19 different countries contributed through a poster session and round table discussion. Eight papers from invited speakers at the workshop have been contributed to this special issue on The Swimming Physiology of Fish

libNeuroML and PyLEMS: using Python to combine procedural and declarative modeling approaches in computational neuroscience.

NeuroML is an XML-based model description language, which provides a powerful common data format for defining and exchanging models of neurons and neuronal networks. In the latest version of NeuroML, the structure and behavior of ion channel, synapse, cell, and network model descriptions are based on underlying definitions provided in LEMS, a domain-independent language for expressing hierarchical mathematical models of physical entities. While declarative approaches for describing models have led to greater exchange of model elements among software tools in computational neuroscience, a frequent criticism of XML-based languages is that they are difficult to work with directly. Here we describe two Application Programming Interfaces (APIs) written in Python (http://www.python.org), which simplify the process of developing and modifying models expressed in NeuroML and LEMS. The libNeuroML API provides a Python object model with a direct mapping to all NeuroML concepts defined by the NeuroML Schema, which facilitates reading and writing the XML equivalents. In addition, it offers a memory-efficient, array-based internal representation, which is useful for handling large-scale connectomics data. The libNeuroML API also includes support for performing common operations that are required when working with NeuroML documents. Access to the LEMS data model is provided by the PyLEMS API, which provides a Python implementation of the LEMS language, including the ability to simulate most models expressed in LEMS. Together, libNeuroML and PyLEMS provide a comprehensive solution for interacting with NeuroML models in a Python environment

INCF/OCNS Software Working Group

Neuroscience cannot exist without its ecosystem of community-developed software tools that many of us rely heavily upon. The newly established Software Working Group, a community working group shared by the International Neuroinformatics Coordinating Facility (INCF) and the Organization for Computational Neurosciences (OCNS), aims to undertake activities that focus on these software tools. Members of the working group will find and discuss relevant software tools, learn and teach how to use them, test and review them, and report bugs to inform tool developers of issues when required. The working group will also strive to learn how these tools work to get involved in their development and maintenance. The aim is to ensure that the tools that our community depends on continue to be maintained by actively engaged community members, and to bring end users into close collaboration with tool developers. Since the working group includes many tool developers, it also serves as a platform to exchange design and development ideas, and will assist in improving interoperability between related tools. Another related goal of the working group is to help members define, improve, and teach transferable skills in the area of modern research software development, particularly in but not limited to, computational neuroscience. The working group is designed to be flexible, instead of being linked to a particular goal. This approach allows the group to pursue timely projects that its members value and are interested in working on. The current goals of the working group are: - To set up and maintain a living document of the current best practices in research software development to serve as a reference for the research community, especially tool developers - To host regular “developer sessions” where developer teams of various tools discuss their development pipelines (or workflows)—to disseminate various development practices, and help potential contributors get started. The activities of the working group can be followed on its website at https://ocns.github.io/SoftwareWG

A Comprehensive Workflow for General-Purpose Neural Modeling with Highly Configurable Neuromorphic Hardware Systems

In this paper we present a methodological framework that meets novel requirements emerging from upcoming types of accelerated and highly configurable neuromorphic hardware systems. We describe in detail a device with 45 million programmable and dynamic synapses that is currently under development, and we sketch the conceptual challenges that arise from taking this platform into operation. More specifically, we aim at the establishment of this neuromorphic system as a flexible and neuroscientifically valuable modeling tool that can be used by non-hardware-experts. We consider various functional aspects to be crucial for this purpose, and we introduce a consistent workflow with detailed descriptions of all involved modules that implement the suggested steps: The integration of the hardware interface into the simulator-independent model description language PyNN; a fully automated translation between the PyNN domain and appropriate hardware configurations; an executable specification of the future neuromorphic system that can be seamlessly integrated into this biology-to-hardware mapping process as a test bench for all software layers and possible hardware design modifications; an evaluation scheme that deploys models from a dedicated benchmark library, compares the results generated by virtual or prototype hardware devices with reference software simulations and analyzes the differences. The integration of these components into one hardware-software workflow provides an ecosystem for ongoing preparative studies that support the hardware design process and represents the basis for the maturity of the model-to-hardware mapping software. The functionality and flexibility of the latter is proven with a variety of experimental results