This title appears in the Scientific Report :
2013
Simulating neuronal networks - basics and applications
Simulating neuronal networks - basics and applications
The field of computational neuroscience has received a substantial boost during the last two decades. Based on experimental findings, scientists investigate the properties of neural networks both by analytical and numerical approaches. Simulations play a major role in this field and recent advances...
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Personal Name(s): | Schmidt, Maximilian (Corresponding author) |
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van Albada, Sacha / Bakker, Rembrandt / Diesmann, Markus | |
Contributing Institute: |
Computational and Systems Neuroscience; IAS-6 Computational and Systems Neuroscience; INM-6 |
Imprint: |
2013
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Conference: | Jülich-Torino Workshop on Computational Neurosciences, Turin (Italy), 2013-10-04 - 2013-10-04 |
Document Type: |
Talk (non-conference) |
Research Program: |
Brain-Scale Simulations Helmholtz Alliance on Systems Biology Brain-inspired multiscale computation in neuromorphic hybrid systems Signalling Pathways and Mechanisms in the Nervous System |
Publikationsportal JuSER |
The field of computational neuroscience has received a substantial boost during the
last two decades. Based on experimental findings, scientists investigate the properties
of neural networks both by analytical and numerical approaches. Simulations play a
major role in this field and recent advances in simulation technology make it possible
to simulate networks of more than 109 neurons. The basis of neuronal simulations is
the reduction of biological neurons and synapses to one to few differential equations
mimicking the behavior in diverse situations. The talk will introduce basic concepts of
neuronal simulations and some of the most common models used to emulate neurons
and synapses.
A multitude of software tools with different focuses and strengths is being used for
neuronal simulations. One of the most popular tools is NEST [1], which specializes
in the simulation of small to large networks of point neurons, negecting the spatial
structure of the cells. I will introduce the tool and show some basic examples.
As a complex application of NEST, I will introduce our project about a multi-area
model, which is designed to capture the dynamical properties of the vision-related
cortical areas of a macaque monkey. |