NEMOS: A Java-Based Tool for Neural Models Simulations
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1
Universidade de Sao Paulo, Brazil
There has been a great interest recently in the construction of large-scale computer simulations of anatomically detailed neuronal network models of brain areas [1]. The main feature of these simulations is that they put more emphasis on anatomical detail rather than on single-cell model realism. In particular, they use simplified spiking neuron models such as integrate-and-fire or Izhikevich model instead of Hodgkin-Huxley type models. The usefulness of this strategy for the simulation of large-scale networks is that they offer a good compromise between computational cost and single-cell spiking behavior.
There are many software tools designed for the simulation of both single neuron and network models with varying levels of detail [2]. In this work, we present the Neural Models Simulator (NEMOS), which is a Java-based environment for the simulation of large-scale spiking neural network models. NEMOS was developed to have a simple and intuitive interface so that the user may simulate neurons and networks with little or no computer programming skills. Nevertheless, NEMOS provides the user with an application program interface (API), which can be used to design new models of neurons, synapses and networks and extend existing ones.
In order to make the running task of time-dependent models (neurons, synapses and inputs) easy, the system has a kernel that controls all of them in a synchronous way. NEMOS has many spiking neuron models already built in and available to be used, such as integrate-and-fire, FitzHugh-Nagumo, Izhikevich, etc. Synapses are modeled using variations of the alpha function. The software allows users to create several objects of the same type with their parameters following a given probability distribution, which facilitates the construction of large-scale networks. The objects are capable to handle events, so that it is possible to simulate responses to external actions while a simulation advances.
To test NEMOS, we built a large-scale model of the olfactory bulb with mitral and granule cells modeled by the Izhikevich model. The results show that the software can simulate a model with thousands of cells in an acceptable time.
Acknowledgments: ACR is supported by a research grant from CNPq.
References
1. Izhikevich, E. M. and Edelman, G. M., Large-scale model of mammalian thalamocortical systems. PNAS, 105:3593-3598, 2008.
2. Brette R. et al., Simulation of networks of spiking neurons: a review of tools and strategies. J. Comput. Neurosci., 23:349-398, 2007.
Conference:
Neuroinformatics 2009, Pilsen, Czechia, 6 Sep - 8 Sep, 2009.
Presentation Type:
Oral Presentation
Topic:
Large scale modeling
Citation:
Figueira
L and
Roque
A
(2019). NEMOS: A Java-Based Tool for Neural Models Simulations.
Front. Neuroinform.
Conference Abstract:
Neuroinformatics 2009.
doi: 10.3389/conf.neuro.11.2009.08.041
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Received:
22 May 2009;
Published Online:
09 May 2019.
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Correspondence:
Lucas Figueira, Universidade de Sao Paulo, Sao Paolo, Brazil, lucasbf@gmail.com