KInNeSS: A Modular Framework for Computational Neuroscience
- 10 August 2008
- journal article
- Published by Springer Science and Business Media LLC in Neuroinformatics
- Vol. 6 (4), 291-309
- https://doi.org/10.1007/s12021-008-9021-2
Abstract
Making use of very detailed neurophysiological, anatomical, and behavioral data to build biologically-realistic computational models of animal behavior is often a difficult task. Until recently, many software packages have tried to resolve this mismatched granularity with different approaches. This paper presents KInNeSS, the KDE Integrated NeuroSimulation Software environment, as an alternative solution to bridge the gap between data and model behavior. This open source neural simulation software package provides an expandable framework incorporating features such as ease of use, scalability, an XML based schema, and multiple levels of granularity within a modern object oriented programming design. KInNeSS is best suited to simulate networks of hundreds to thousands of branched multi-compartmental neurons with biophysical properties such as membrane potential, voltage-gated and ligand-gated channels, the presence of gap junctions or ionic diffusion, neuromodulation channel gating, the mechanism for habituative or depressive synapses, axonal delays, and synaptic plasticity. KInNeSS outputs include compartment membrane voltage, spikes, local-field potentials, and current source densities, as well as visualization of the behavior of a simulated agent. An explanation of the modeling philosophy and plug-in development is also presented. Further development of KInNeSS is ongoing with the ultimate goal of creating a modular framework that will help researchers across different disciplines to effectively collaborate using a modern neural simulation platform.Keywords
This publication has 37 references indexed in Scilit:
- Simulation of networks of spiking neurons: A review of tools and strategiesJournal of Computational Neuroscience, 2007
- How much can we trust neural simulation strategies?Neurocomputing, 2007
- NEST (NEural Simulation Tool)Scholarpedia, 2007
- Nonlinear Interaction between Shunting and Adaptation Controls a Switch between Integration and Coincidence Detection in Pyramidal NeuronsJournal of Neuroscience, 2006
- A model of STDP based on spatially and temporally local information: Derivation and combination with gated decayNeural Networks, 2005
- A biophysical implementation of a bidirectional graph search algorithm to solve multiple goal navigation tasksConnection Science, 2005
- Which Model to Use for Cortical Spiking Neurons?IEEE Transactions on Neural Networks, 2004
- Simple model of spiking neuronsIEEE Transactions on Neural Networks, 2003
- Synaptic Modification by Correlated Activity: Hebb's Postulate RevisitedAnnual Review of Neuroscience, 2001
- Regulation of Synaptic Efficacy by Coincidence of Postsynaptic APs and EPSPsScience, 1997