22 citations · 27 across the 3 of their papers we have counts for
3 papers
math.NA2021
Using ODE waveform-relaxation methods to efficiently include gap junctions in distributed neural network simulations
Matthias Bolten, Jan Hahne
Waveform-relaxation methods divide systems of differential equations into subsystems and therefore allow for parallelization across the system. Here we present an application for O…
q-bio.NC2020★ 5 cited
Event-based update of synapses in voltage-based learning rules
Jonas Stapmanns, Jan Hahne, Moritz Helias +3
Due to the point-like nature of neuronal spiking, efficient neural network simulators often employ event-based simulation schemes for synapses. Yet many types of synaptic plasticit…
q-bio.NC2016★ 22 cited
Integration of continuous-time dynamics in a spiking neural network simulator
Jan Hahne, David Dahmen, Jannis Schuecker +4
Contemporary modeling approaches to the dynamics of neural networks consider two main classes of models: biologically grounded spiking neurons and functionally inspired rate-based…