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Sparsely connected networks of spiking neurons (Brunel 2000)
Accession: 42020
The dynamics of networks of sparsely connected excitatory and inhibitory integrate-and-fire neurons are studied analytically (and with simulations). The analysis reveals a rich repertoire of states, including synchronous states in which neurons fire regularly; asynchronous states with stationary global activity and very irregular individual cell activity; and states in which the global activity oscillates but individual cells fire irregularly, typically at rates lower than the global oscillation frequency. See paper for more and details.
Reference: Brunel N (2000) Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons. J Comput Neurosci 8:183-208 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type:  Connectionist Network;
Brain Region(s)/Organism:  
Cell Type(s):   
Channel(s):   
Gap Junctions:  
Receptor(s):  
Gene(s):  
Transmitter(s):  
Simulation Environment:  NEST (formerly BLISS/SYNOD);
Model Concept(s):  Activity Patterns; Oscillations; Spatio-temporal Activity Patterns; Simplified Models;
Implementer(s):  Gewaltig, Marc-Oliver [marc-oliver.gewaltig@epfl.ch];
\
brunel
readme.txt
brunel.sli
                            
Readme.txt for an implementation of the model associated with the
paper:

Brunel N (2000) Dynamics of sparsely connected networks of excitatory
and inhibitory spiking neurons. J Comput Neurosci 8:183-208

The brunel.sli file was supplied by Marc-Oliver Gewaltig and runs
under NEST.  Please contact Marc-Oliver Gewaltig
marc-oliver.gewaltig at epfl.ch for more information.

20120105 IMPORTANT NOTE:
*** the brunel.sli file included here is incompatible with the most
recent version of NEST.  Please use the version in

examples/nest/brunel-2000.sli

in your local NEST installation. It is also suggested (and supported
by "Tom Tetzlaff" [t.tetzlaff at fz-juelich.de]) to control NEST from
python using PyNEST: see

http://nest-initiative.org/index.php/PyNEST

In

pynest/examples/brunel-delta-nest.py

you'll find a python script for the Brunel network example.


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