MIIND (Multiple Interacting Instantiations of Neural Dynamics) - bridging neural dynamics and cognitive modelling

Abstract

Event Abstract Back to Event MIIND (Multiple Interacting Instantiations of Neural Dynamics) - bridging neural dynamics and cognitive modelling Marc De Kamps1* and Frank Van Der Velde2 1 University of Leeds, United Kingdom 2 University of Leiden, Netherlands MIIND is a C++ framework with a PYTHON interface which facilitates modelling in cognitive neuroscience. In MIIND one can create networks in terms of spatial configurations. The node of such networks can be endowed with algorithms that evolve the state of the nodes. In this way network processes can be modelled in a very generic way. In principle any coupled system of equations which can be represented by a sparse irregular network can be modelled. Users can provide their own algorithms in a transparent way. MIIND also has some predefined algorithms: Wilson-Cowan dynamics and population density techniques for leaky-integrate-and-fire (LIF) neurons. Wilson-Cowan dynamics is widely used in models of high level cognition. Population density techniques describe large populations of spiking neurons in terms of a density function which captures the characteristics of the population in a way that is often more efficient than a straightforward simulation of the population. Networks of such equations are closely linked to coupled systems of Fokker-Planck equations. Since MIIND can create complex spatial structures and provides algorithms for modelling neural dynamics, it is suitable for modelling high level cognition. One example of its application is modelling object-based attention in vision in terms of interacting hierarchical neural networks, the so-called neural blackboard architecture. Another application is the investigation of the behaviour of the dynamics of cortical circuits. MIIND does not provide simulations of spiking neurons, such as NEST, NEURON, GENESIS or MOOSE, although it could encapsulate algorithms which drive such simulations. MIIND does not provide a monolithic interface, but offers modelling support at various levels. Modellers may decide, for example, to use only the representation of sparse networks, or to use the simulation loop for other than neural processes. Developers can easily borrow parts of MIIND while disregarding the parts that are not of interest. MIIND also comes with a library that can implement filter operations between layers of nodes. In this way it is easy to implement large filter bank structures, which are used in biologically inspired models of object recognition, such as HMAX and successors. This opens the possibility to model biological vision on the one hand, and to apply the principles to biologically inspired artificial vision on the other hand. MIIND uses ROOT for visualisation and data management. ROOT is a powerful Open Source package, developed by CERN. It relies on the GNU Scientific Library (GSL) for scientific computing. MIIND is still in its infancy. Important future challenges are: the development of parallelisation of the simulation loop, extending the visualisation capabilities and the development of population density techniques which go beyond LIF neurons. Conference: Neuroinformatics 2008, Stockholm, Sweden, 7 Sep - 9 Sep, 2008. Presentation Type: Poster Presentation Topic: Large Scale Modeling Citation: De Kamps M and Van Der Velde F (2008). MIIND (Multiple Interacting Instantiations of Neural Dynamics) - bridging neural dynamics and cognitive modelling. Front. Neuroinform. Conference Abstract: Neuroinformatics 2008. doi: 10.3389/conf.neuro.11.2008.01.090 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 28 Jul 2008; Published Online: 28 Jul 2008. * Correspondence: Marc De Kamps, University of Leeds, Leeds, United Kingdom, dekamps@comp.leeds.ac.uk Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Marc De Kamps Frank Van Der Velde Google Marc De Kamps Frank Van Der Velde Google Scholar Marc De Kamps Frank Van Der Velde PubMed Marc De Kamps Frank Van Der Velde Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.