Abstract. We propose an event-driven framework dedicated to the design and the simulation of networks of spiking neurons. It consists of an abstract model of spiking neurons and an efficient event-driven simulation engine so as to achieve good performance

Anevent-drivenframeworkforthesimulationof

networksofspikingneurons

OlivierRochel,DominiqueMartinez

LORIA-Campusscienti queB.P.239

F-54506Vand uvre-les-NancyCedex

E-mail:{rochel,dmartine}@loria.fr

Abstract.Weproposeanevent-drivenframeworkdedicatedtothe

designandthesimulationofnetworksofspikingneurons.Itconsists

ofanabstractmodelofspikingneuronsandane cientevent-driven

simulationenginesoastoachievegoodperformanceinthesimulation

phasewhilemaintainingahighlevelof exibilityandprogrammability

inthemodellingphase.Ourmodelofneuronsencompassesalargeclass

ofspikingneuronsrangingfromusualleakyintegrate-and- reneuronsto

moreabstractneurons,e.g.de nedascomplex nitestatemachines.As

aresult,theproposedframeworkallowsthesimulationoflargenetworks

thatcanbecomposedofuniqueordi erenttypesofneurons.

1Introduction

Inanevent-drivensimulation,thesimulatedtime(oftencalledvirtualtime)isadvancedbycomputingthestateofthesystemateventoccurenceinstantsonly,whereasinatime-drivensimulationitisadvancedusingarbitrarytimesteps[2].Mappingsuchanevent-drivenschemetoapulsedcoupledneuralnetworkisstraightforward:thepulses(orspikes)areinstantaneous,canoccuratanytime,andthereforecanbeseenasthe“events”thatdeterminetheevolutionofthesystem.Inthecontextofaspikingneuralnetworksimulation,abasicevent-drivensimulationenginethusfollowsthisscheme:

1.Findthenexteventtobeprocessed,thatis,thenextneuronthatshould re(orreceive)aspike.

2.Updatethestateoftheneuronconcernedbythisevent

3.Schedulepossibleeventsinducedbythatchange

4.Ifsomeeventsarepending,returntothe rststep.Otherwise,thesim-ulationends.