Networks of spiking neurons: a review of tools and strategies (Brette et al. 2007)

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This package provides a series of codes that simulate networks of spiking neurons (excitatory and inhibitory, integrate-and-fire or Hodgkin-Huxley type, current-based or conductance-based synapses; some of them are event-based). The same networks are implemented in different simulators (NEURON, GENESIS, NEST, NCS, CSIM, XPP, SPLIT, MVAspike; there is also a couple of implementations in SciLab and C++). The codes included in this package are benchmark simulations; see the associated review paper (Brette et al. 2007). The main goal is to provide a series of benchmark simulations of networks of spiking neurons, and demonstrate how these are implemented in the different simulators overviewed in the paper. See also details in the enclosed file Appendix2.pdf, which describes these different benchmarks. Some of these benchmarks were based on the Vogels-Abbott model (Vogels TP and Abbott LF 2005).
1 . Vogels TP, Abbott LF (2005) Signal propagation and logic gating in networks of integrate-and-fire neurons. J Neurosci 25:10786-95 [PubMed]
2 . Brette R, Rudolph M, Carnevale T, Hines M, Beeman D, Bower JM, Diesmann M, Morrison A, Goodman PH, Harris FC, Zirpe M, Natschläger T, Pecevski D, Ermentrout B, Djurfeldt M, Lansner A, Rochel O, Vieville T, Muller E, Davison AP, El Boustani S, Destexhe A (2007) Simulation of networks of spiking neurons: a review of tools and strategies. J Comput Neurosci 23:349-98 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s): Abstract integrate-and-fire leaky neuron;
Gap Junctions:
Simulation Environment: NEURON; GENESIS; NEST; C or C++ program; XPP; CSIM; NCS; SPLIT; MVASpike; SciLab; Brian; PyNN; Python;
Model Concept(s): Activity Patterns; Methods;
Implementer(s): Carnevale, Ted [Ted.Carnevale at]; Hines, Michael [Michael.Hines at]; Davison, Andrew [Andrew.Davison at]; Destexhe, Alain [Destexhe at]; Ermentrout, Bard []; Brette R; Bower, James; Beeman, Dave; Diesmann M; Morrison A ; Goodman PH; Harris Jr, FC; Zirpe M ; Natschlager T ; Pecevski D ; Djurfeldt M; Lansner, Anders [ala at]; Rochel O ; Vieville T ; Muller E ; El Boustani, Sami [elboustani at]; Rudolph M ;
Section 18.7.3 of the BoG (Utility Functions for Synapses) describes and
gives a listing for the synapse_info function.

Usage:   synapse_info path_to_synchan
Example: synapse_info /network/cell[5]/apical1/Ex_channel

This is used to return a list of synaptic connections to the channel, their
sources, weights, and delays.  It uses some of the built-in GENESIS commands:

getsyncount [presynaptic-element] [postsynaptic-element]
getsynindex <presynptic-element> <postpostsynaptic-element> [-number n]
getsynsrc <postsynaptic-element> <index>
getsyndest  <presynptic-element> <n> [-index] //n is the no of spike message


function synapse_info(path)
   str path,src
   int i
   float weight,delay
   floatformat %.3g
   for(i=0;i<{getsyncount {path}};i=i+1)
   src={getsynsrc {path} {i}}
   weight={getfield {path} synapse[{i}].weight}
   delay={getfield {path} synapse[{i}].delay }
   echo synapse[{i}] :\
        src = {src} weight ={weight} delay ={delay}

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