E-lectures within an integrated multimedia course design

Course design should be student-centred in that courses are designed for students. But the consequences of that imperative differ from course to course and from student to student. This paper describes two courses that take student-centredness seriously. It also contextualises the way in which these courses are presented. Since students have different cognitive and affective styles and different social and personal backgrounds and approaches, a variety of presentational approaches are outlined which are integrated in each course. The courses are presented traditionally in lectures, practical workshops, and tutorials, but also in a textbook, downloadable PowerPoint slides, and, innovatively, as QuickTime movies in which the PowerPoint is integrated with a voiceover from the lecture. Online quizzes and surveys are also provided so that students can receive feedback on their progress and on communal views. None of this is possible without accommodating presentation vehicles. These are also described

E-lectures within an integrated multimedia course design

Course design should be student-centred in that courses are designed for students. But the consequences of that imperative differ from course to course and from student to student. This paper describes two courses that take student-centredness seriously. It also contextualises the way in which these courses are presented. Since students have different cognitive and affective styles and different social and personal backgrounds and approaches, a variety of presentational approaches are outlined which are integrated in each course. The courses are presented traditionally in lectures, practical workshops, and tutorials, but also in a textbook, downloadable PowerPoint slides, and, innovatively, as QuickTime movies in which the PowerPoint is integrated with a voiceover from the lecture. Online quizzes and surveys are also provided so that students can receive feedback on their progress and on communal views. None of this is possible without accommodating presentation vehicles. These are also described

Deploying and Optimizing Embodied Simulations of Large-Scale Spiking Neural Networks on HPC Infrastructure

Simulating the brain-body-environment trinity in closed loop is an attractive proposal to investigate how perception, motor activity and interactions with the environment shape brain activity, and vice versa. The relevance of this embodied approach, however, hinges entirely on the modeled complexity of the various simulated phenomena. In this article, we introduce a software framework that is capable of simulating large-scale, biologically realistic networks of spiking neurons embodied in a biomechanically accurate musculoskeletal system that interacts with a physically realistic virtual environment. We deploy this framework on the high performance computing resources of the EBRAINS research infrastructure and we investigate the scaling performance by distributing computation across an increasing number of interconnected compute nodes. Our architecture is based on requested compute nodes as well as persistent virtual machines; this provides a high-performance simulation environment that is accessible to multi-domain users without expert knowledge, with a view to enable users to instantiate and control simulations at custom scale via a web-based graphical user interface. Our simulation environment, entirely open source, is based on the Neurorobotics Platform developed in the context of the Human Brain Project, and the NEST simulator. We characterize the capabilities of our parallelized architecture for large-scale embodied brain simulations through two benchmark experiments, by investigating the effects of scaling compute resources on performance defined in terms of experiment runtime, brain instantiation and simulation time. The first benchmark is based on a large-scale balanced network, while the second one is a multi-region embodied brain simulation consisting of more than a million neurons and a billion synapses. Both benchmarks clearly show how scaling compute resources improves the aforementioned performance metrics in a near-linear fashion. The second benchmark in particular is indicative of both the potential and limitations of a highly distributed simulation in terms of a trade-off between computation speed and resource cost. Our simulation architecture is being prepared to be accessible for everyone as an EBRAINS service, thereby offering a community-wide tool with a unique workflow that should provide momentum to the investigation of closed-loop embodiment within the computational neuroscience community.journal articl

Brain simulation as a cloud service: The Virtual Brain on EBRAINS

The Virtual Brain (TVB) is now available as open-source services on the cloud research platform EBRAINS (ebrains.eu). It offers software for constructing, simulating and analysing brain network models including the TVB simulator; magnetic resonance imaging (MRI) processing pipelines to extract structural and functional brain networks; combined simulation of large-scale brain networks with small-scale spiking networks; automatic conversion of user-specified model equations into fast simulation code; simulation-ready brain models of patients and healthy volunteers; Bayesian parameter optimization in epilepsy patient models; data and software for mouse brain simulation; and extensive educational material. TVB cloud services facilitate reproducible online collaboration and discovery of data assets, models, and software embedded in scalable and secure workflows, a precondition for research on large cohort data sets, better generalizability, and clinical translation

Deploying and Optimizing Embodied Simulations of Large-Scale Spiking Neural Networks on HPC Infrastructure

Simulating the brain-body-environment trinity in closed loop is an attractive proposal to investigate how perception, motor activity and interactions with the environment shape brain activity, and vice versa. The relevance of this embodied approach, however, hinges entirely on the modeled complexity of the various simulated phenomena. In this article, we introduce a software framework that is capable of simulating large-scale, biologically realistic networks of spiking neurons embodied in a biomechanically accurate musculoskeletal system that interacts with a physically realistic virtual environment. We deploy this framework on the high performance computing resources of the EBRAINS research infrastructure and we investigate the scaling performance by distributing computation across an increasing number of interconnected compute nodes. Our architecture is based on requested compute nodes as well as persistent virtual machines; this provides a high-performance simulation environment that is accessible to multi-domain users without expert knowledge, with a view to enable users to instantiate and control simulations at custom scale via a web-based graphical user interface. Our simulation environment, entirely open source, is based on the Neurorobotics Platform developed in the context of the Human Brain Project, and the NEST simulator. We characterize the capabilities of our parallelized architecture for large-scale embodied brain simulations through two benchmark experiments, by investigating the effects of scaling compute resources on performance defined in terms of experiment runtime, brain instantiation and simulation time. The first benchmark is based on a large-scale balanced network, while the second one is a multi-region embodied brain simulation consisting of more than a million neurons and a billion synapses. Both benchmarks clearly show how scaling compute resources improves the aforementioned performance metrics in a near-linear fashion. The second benchmark in particular is indicative of both the potential and limitations of a highly distributed simulation in terms of a trade-off between computation speed and resource cost. Our simulation architecture is being prepared to be accessible for everyone as an EBRAINS service, thereby offering a community-wide tool with a unique workflow that should provide momentum to the investigation of closed-loop embodiment within the computational neuroscience community

Fenix: Distributed e-Infrastructure Services for EBRAINS

The Human Brain Project (HBP) (https://humanbrainproject.eu/) is a large-scale flagship project funded by the European Commission with the goal of establishing a research infrastructure for brain science. This research infrastructure is currently being realised and will be called EBRAINS (https://ebrains.eu/). The wide ranging EBRAINS services for the brain research communities require diverse access, processing and storage capabilities. As a result, it will strongly rely on e-infrastructure services. The HBP led to the creation of Fenix (https://fenix-ri.eu/), a collaboration of five European supercomputing centres, who are providing a set of federated e-infrastructure services to EBRAINS. The Fenix architecture has been designed to uniquely address the need for a wide spectrum of services, from high performance computing (HPC) to on-demand cloud technologies to identity and access federation, for facilitating ease of access and usage of distributed e-infrastructure resources. In this article we describe the underlying concepts for an audience of computational science end-users and developers of domain-specific applications, workflows and platforms services. To exemplify the use of Fenix, we will discuss selected use cases demonstrating how brain researchers can use the offered infrastructure services and describe how access to these resources can be obtained

Anion doping as a probe of cooperativity in the molecular spin-crossover compound [FeL2][BF4]2 (L = 2,6-di{pyrazol-1-yl}pyridine)

The complex dications in the cooperative spin-crossover compound [FeL2][BF4]2 (2,6-di(pyrazol-1-yl)pyridine) pack through p–p interactions into a 2-D layered structure (a terpyridine embrace motif)..

Archival Data Repository Services to Enable HPC and Cloud Workflows in a Federated Research e-Infrastructure

Five European supercomputing centres, namely BSC (Spain), CEA (France), CINECA (Italy), CSCS (Switzerland), and JSC (Germany), agreed to align their high-end computing and storage services to facilitate the creation of the Fenix Research Infrastructure. In addition to the traditional extreme-scale computing and data services, Fenix provides a set of Cloud-type services as well as services needed for federation. In this paper, we describe the architecture of the Fenix infrastructure and how it can be used for representative workflows from the Human Brain Project (HBP). The concept of the Active Data Repository (ACD) is chosen to highlight demarcation between HPC and Cloud access models