26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)

High Performance Computing (HPC) Resources for Parallel Simulations and Data Analysis: NSG and HPAC

Need free, easy access to HPC resources to run widely used neural simulators or connectome analysis tools? Interested in new, free HPC tools developed by the HBP, including hardware, simulation and analytics software?The Neuroscience Gateway (NSG) project and the High Performance Analytics and Computing (HPAC) of the Human Brain Project will host a joint satellite workshop at the Society for Neuroscience (SfN) 2017 annual meeting in Washington D.C. Workshop presenters are neuroscientists who are involved in computational neuroscience research and education as well as developers of tools (such as NEST, NEURON) used in computational neuroscience

High Performance Computing (HPC) Resources for Parallel Simulations and Data Analysis: NSG and HPAC

Need free, easy access to HPC resources to run widely used neural simulators or connectome analysis tools? Interested in new, free HPC tools developed by the HBP, including hardware, simulation and analytics software?The Neuroscience Gateway (NSG) project and the High Performance Analytics and Computing (HPAC) of the Human Brain Project will host a joint satellite workshop at the Society for Neuroscience (SfN) 2018 annual meeting in San Diego California. Workshop presenters are neuroscientists who are involved in computational neuroscience research and education as well as developers of tools (such as NEST, NEURON) used in computational neuroscience

High Performance Computing (HPC) Resources for Parallel Simulations and Data Analysis: NSG and HPAC

Need free, easy access to HPC resources to run widely used neural simulators or connectome analysis tools? Interested in new, free HPC tools developed by the HBP, including hardware, simulation and analytics software?The Neuroscience Gateway (NSG) project and the High Performance Analytics and Computing (HPAC) of the Human Brain Project will host a joint satellite workshop at the Society for Neuroscience (SfN) 2018 annual meeting in San Diego California. Workshop presenters are neuroscientists who are involved in computational neuroscience research and education as well as developers of tools (such as NEST, NEURON) used in computational neuroscience

Neuroscience Gateway – An Overview

The Neuroscience Gateway (NSG http://www.nsgportal.org), a NSF funded project, catalyzes computational neuroscience research by lowering or eliminating the <br>administrative and technical barriers that can make it difficult for <br>neuroscience researchers to access supercomputer resources for large <br>scale simulations and brain image data processing. It provides free and <br>open access to supercomputers using time acquired via the peer reviewed allocation process managed by the Extreme Science and Engineering Discovery Environment (XSEDE). <br><br>It has about 400 registered users. Total core hours used, per-user rate of usage, and the number of users have all been growing at a rapid rate. Given current annual usage and the rate at which it has risen over the past 4 years, we expect NSG users to need about 10,000,000 core hours in 2017. <br><br>NSG is enabling participation by the wider neuroscience community in <br>research that would otherwise involve too great a computational burden, <br>such as large scale and detailed models of cells and networks, parameter <br>optimization, brain image processing, connectome pipelines etc., <br>resulting in over 50 publications and posters to date. <br><br>Many neuroscientists who are developing new network modeling tools, data <br>driven parameter optimization pipelines (such as the BluePyOpt from the <br>Human Brain Project) etc. are using the NSG to disseminate their results <br>to the neuroscience community. <br><br>NSG's scope has been expanded to offer programmatic access to <br>supercomputing resources in addition to access via the web portal. <br>Developing and operating the NSG has given us a unique opportunity to <br>understand and analyze how a very diverse range of neuroscientists are <br>using an environment like the NSG, and examine their growing need for <br>supercomputer power, as well as associated issues and needs for <br>collaboration, data sharing/management and various forms of computing

Simulation of networks of spiking neurons: A review of tools and strategies

We review different aspects of the simulation of spiking neural networks. We start by reviewing the different types of simulation strategies and algorithms that are currently implemented. We next review the precision of those simulation strategies, in particular in cases where plasticity depends on the exact timing of the spikes. We overview different simulators and simulation environments presently available (restricted to those freely available, open source and documented). For each simulation tool, its advantages and pitfalls are reviewed, with an aim to allow the reader to identify which simulator is appropriate for a given task. Finally, we provide a series of benchmark simulations of different types of networks of spiking neurons, including Hodgkin-Huxley type, integrate-and-fire models, interacting with current-based or conductance-based synapses, using clock-driven or event-driven integration strategies. The same set of models are implemented on the different simulators, and the codes are made available. The ultimate goal of this review is to provide a resource to facilitate identifying the appropriate integration strategy and simulation tool to use for a give

J Comput Neurosci DOI 10.1007/s10827-007-0038-6 TOPICAL REVIEW ON TECHNIQUES Simulation of networks of spiking neurons: A review of tools and strategies

Abstract We review different aspects of the simulation of spiking neural networks. We start by reviewing the different types of simulation strategies and algorithms that are currently implemented. We next review the precision of those simulation strategies, in particular in cases where plasticity depends on the exact timing of Action Editor: Barry J. Richmon

Nine Best Practices for Research Software Registries and Repositories: A Concise Guide

Scientific software registries and repositories serve various roles in their respective disciplines. These resources improve software discoverability and research transparency, provide information for software citations, and foster preservation of computational methods that might otherwise be lost over time, thereby supporting research reproducibility and replicability. However, developing these resources takes effort, and few guidelines are available to help prospective creators of registries and repositories. To address this need, we present a set of nine best practices that can help managers define the scope, practices, and rules that govern individual registries and repositories. These best practices were distilled from the experiences of the creators of existing resources, convened by a Task Force of the FORCE11 Software Citation Implementation Working Group during the years 2019-2020. We believe that putting in place specific policies such as those presented here will help scientific software registries and repositories better serve their users and their disciplines