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000205104 1001_ $$0P:(DE-HGF)0$$aHahne, Jan$$b0$$eCorresponding author
000205104 245__ $$aA unified framework for spiking and gap-junction interactions in distributed neuronal network simulations
000205104 260__ $$aLausanne$$bFrontiers Research Foundation$$c2015
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000205104 520__ $$aContemporary simulators for networks of point and few-compartment model neurons come with a plethora of ready-to-use neuron and synapse models and support complex network topologies. Recent technological advancements have broadened the spectrum of application further to the efficient simulation of brain-scale networks on supercomputers. In distributed network simulations the amount of spike data that accrues per millisecond and process is typically low, such that a common optimization strategy is to communicate spikes at relatively long intervals, where the upper limit is given by the shortest synaptic transmission delay in the network. This approach is well-suited for simulations that employ only chemical synapses but it has so far impeded the incorporation of gap-junction models, which require instantaneous neuronal interactions. Here, we present a numerical algorithm based on a waveform-relaxation technique which allows for network simulations with gap junctions in a way that is compatible with the delayed communication strategy. Using a reference implementation in the NEST simulator, we demonstrate that the algorithm and the required data structures can be smoothly integrated with existing code such that they complement the infrastructure for spiking connections. We show that the unified framework for gap-junction and spiking interactions achieves high performance and delivers high accuracy.
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000205104 536__ $$0G:(EU-Grant)604102$$aHBP - The Human Brain Project (604102)$$c604102$$fFP7-ICT-2013-FET-F$$x2
000205104 536__ $$0G:(DE-Juel1)HGF-SMHB-2014-2018$$aMSNN - Theory of multi-scale neuronal networks (HGF-SMHB-2014-2018)$$cHGF-SMHB-2014-2018$$fMSNN$$x3
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000205104 536__ $$0G:(DE-Juel1)hwu12_20141101$$aScalable solvers for linear systems and time-dependent problems (hwu12_20141101)$$chwu12_20141101$$fScalable solvers for linear systems and time-dependent problems$$x6
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000205104 7001_ $$0P:(DE-Juel1)144806$$aHelias, Moritz$$b1
000205104 7001_ $$0P:(DE-Juel1)151364$$aKunkel, Susanne$$b2
000205104 7001_ $$0P:(DE-HGF)0$$aIgarashi, Jun$$b3
000205104 7001_ $$0P:(DE-HGF)0$$aBolten, Matthias$$b4
000205104 7001_ $$0P:(DE-HGF)0$$aFrommer, Andreas$$b5
000205104 7001_ $$0P:(DE-Juel1)144174$$aDiesmann, Markus$$b6
000205104 773__ $$0PERI:(DE-600)2452964-3$$a10.3389/fninf.2015.00022$$n22$$p00022$$tFrontiers in computational neuroscience$$v9$$x1662-5188$$y2015
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