The logos are courtesy of Amanda Pasquali (thanks, Amanda !)

Introduction

The GEneral NEural SImulation System, GENESIS for short, started as an advanced software application for biologically accurate neuronal modeling in the late eighties. Today it continues to be used for neuronal simulations but it has also been applied to various domains outside computational neuroscience. However, with a history of over 30 years the software architecture has become obsolete resulting in many deficiencies such as duplicate code, no automated regression testing Further extension of the source code proves to be extremely difficult. One of the core problems responsible for this situation, is that GENESIS is a monolithic software system, implementing many different user-visible functions.

The Neurospaces project is a development center for software components of computational neuroscience simulators. Some of the advantages of developing independent software components are:

• It simplifies the individual components and encourages other developers to get involved.
• It allows for separate testing of the components. More than 1500 use case tests have been defined for the individual software components. Of course there are also many integration tests. The regression tester output can be found here.
• Interfacing to an individual component is more simple than interfacing to a do-all monolithic system. As an example the compartmental solver developed for the Neurospaces project, Heccer, can be directly connected to Matlab.
• Integrating different components, gives different flavors of the same simulator, and enhances the user experienced consistency when constructing, exploring and running multi-scale models.
• A component based software system avoids vendor-lockin. Its life-cycle is more smooth than that of a monolithic system, because software components can be upgraded one at a time.

The Neurospaces project delivers many software components that have first been developed in isolation, then possibly been integrated into a single simulator. The core of the important components was finished several years ago.

Software components that have been developed, include:

• The Genesis Script Language Interface: a scripting component that reads Genesis 2 scripts and feeds them to the Neurospaces model container.
• GShell: an interactive front-end that integrates with other software components.
• Heccer: a fast compartmental solver, a backend.
• Neurospaces Model Container: provides a solver independent internal and external storage format for models.
• The Exchange Module: provides the model-container with interfaces to XML based model descriptions such as NeuroML.
• Discrete Event System (DES): consists of a discrete event distributor and queuer. This is used for abstract modeling of an action potential traveling inside an axon as a 'discrete event'. This component is optimized for networks of realistic neuronal models that have Hodgkin-Huxley channels and / or a neuronal morphology.
• SSP: a flexible scheduler written in Perl, to run simulations with the Neurospaces model container and Heccer.
• The Neurospaces Studio: some tools for graphical browsing and command line usage.
• The Geometry Library is a general purpose geometry library, with some essential geometrical operators, not commonly found in other geometrical libraries. The Reconstruct Interface uses the Geometry Library to support the conversion of contours exported by the Reconstruct software to the Neurospaces declarative NDF format.
• The Neurospaces Project Browser for browsing projects and inspecting simulation results.
• The Developer Package contains the Neurospaces installer and developer tools that have emerged from developing Neurospaces software components.
• The Configurator package contains configuration utilities for the other tools. It is not needed for the other tools to work properly. Rather, it allows to set up model database and simulation servers in a convenient way.
• The Neurospaces Workflow Automation Engine helps automating complicated system shell tasks during the development of a software project. Typical examples of workflow automation are shell commands with arguments and options that are hard to remember, to compile source code on a build server, to convert documentation to a web page, to flash a binary image such as the Linux kernel to a small or embedded device, or start the execution of command sequences in synchrony on different virtual machines.

Publications:

• Allan D. Coop, George N. Reeke Jr.: The Composite Neuron: A Realistic One-Compartment Purkinje Cell Model Suitable for Large-Scale Neuronal Network Simulations. Journal of Computational Neuroscience 10(2): 173-186 (2001)
  explains the capabilities of the Dash compartmental solver.
• George N. Reeke Jr., Allan D. Coop: Estimating the Temporal Interval Entropy of Neuronal Discharge. Neural Computation 16(5): 941-970 (2004))
• H. Cornelis and E. De Schutter, Neurospaces: Separating modeling and simulation, Neurocomputing 52-54: 227-231 (2003)
  http://www.tnb.ua.ac.be/publications/pub065/Cornelis_NeuComp_03.pdf
  Explains the Neurospaces design goals.
• H. Cornelis and E. De Schutter, Neurospaces parameter handling, Neurocomputing 58-60: 1079-1084 (2004)
  http://www.tnb.ua.ac.be/publications/pub081/CornelisNC04.pdf
  Explains algorithms that allow (1) to access models in an intuitive way, and (2) to optimize the memory use of Neurospaces. The latter is actually a preparation of partitioning algorithms for large models, see below.
• H. Cornelis, Examining Neuronal models with Neurospaces studio (poster presentation at Wam-bamm 2006).
• H. Cornelis and E. De Schutter, Neurospaces: towards automated model partitioning for parallel computers (Neurocomputing Volume 70, Issues 10-12, June 2007, Pages 2117-2121, http://www.sciencedirect.com/science/article/B6V10-4MC12J2-6/2/809ad2a06d0761296cff8133b96272b5).
  Explains a partitioning algorithm to enable transparant parallelization of large heterogeneous simulations.
• Hugo Cornelis, Huo Lu, Angelica Esquivel and James M. Bower, Modeling a single dendritic compartment using Neurospaces and GENESIS-3 (poster presentation, CNS 2007).
  Reports about a multi-scale computational neuroscience project, using tools of the Neurospaces project.
• Hugo Cornelis, Huo Lu, Julia S. Georgi and James M. Bower, Comparative computational study of cerebellar Purkinje cell form and function (poster presentation, Society for Neuroscience Meeting, November 2007).
  Reports about a project that compares the passive electrical properties of Purkinje cells of 5 different species. In total 120,000 simulations were run in about four weeks of time. The Neurospaces project browser was crucial to run and manage the simulations, analyze the results, and visualize color-coded representations of the morphologies.
• Hugo Cornelis, Michael Edwards, Allan D. Coop, James M. Bower: The CBI Architecture for Computational Simulation of Realistic Neurons and Circuits in the GENESIS 3 Software Federation (poster presentation, Computational Neuroscience Meeting, July 2008).
  Establishes the relationships between the CBI architecture, the GENESIS 3 neuronal simulator, and the Neurospaces project.
• Hugo Cornelis, Allan D. Coop, James M. Bower: The Neurospaces Project Browser in the GENESIS 3 Software Federation: Design and Targets (poster presentation, Computational Neuroscience Meeting, July 2008).
  Documents the capabilities of the Neurospaces project browser, the interfaces, the file distribution mechanisms.
• James M. Bower, Hugo Cornelis, Rachael Wilcox: Comparative Evolutionary Computational Analysis of Cerebellar Purkinje Cell Structure and Function (poster presentation, Computational Neuroscience Meeting, July 2009).
• Allan D. Coop, Hugo Cornelis, Armando Rodriguez, James M. Bower: Using GENESIS 3 for single neuron modeling (poster presentation, Computational Neuroscience Meeting, July 2009).
  Documents the capabilities of the GENESIS 3 simulation and documentation systems.
• Allan D. Coop, Hugo Cornelis, Fidel Santamaria: Dendritic excitability modulates dendritic information processing in a Purkinje cell model Frontiers in Computational Neuroscience, 30 March 2010 https://www.frontiersin.org/articles/10.3389/fncom.2010.00006/full
  A paper that uses the GENESIS 3 simulation system to conveniently run thousands of research simulations with the project browser.
• Hugo Cornelis, Armando L. Rodriguez, Allan D. Coop, James M. Bower: Python as a Federation Tool for GENESIS 3.0 (January 20, 2012).
  Documents the use of the Python programming language to establish the CBI as a open and federated software architecture. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0029018
• Hugo Cornelis, Allan D. Coop, James M. Bower: A Federated Design for a Neurobiological Simulation Engine: The CBI Federated Software Architecture (January 5, 2012). https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0028956
  Documents the philosophical underpinnings, the design and the architecture of a Neurospaces based simulator.