1 citations · 1 across the 2 of their papers we have counts for
4 papers
Mapping Input Noise to Escape Noise in Integrate-and-fire neurons: A Level-Crossing Approach
Tilo Schwalger
Noise in spiking neurons is commonly modeled by a noisy input current or by generating output spikes stochastically with a voltage-dependent hazard rate ("escape noise"). While inp…
Mind the Last Spike -- Firing Rate Models for Mesoscopic Populations of Spiking Neurons
Tilo Schwalger, Anton V. Chizhov
The dominant modeling framework for understanding cortical computations are heuristic firing rate models. Despite their success, these models fall short to capture spike synchroniz…
Mesoscopic population equations for spiking neural networks with synaptic short-term plasticity
Valentin Schmutz, Wulfram Gerstner, Tilo Schwalger
Coarse-graining microscopic models of biological neural networks to obtain mesoscopic models of neural activities is an essential step towards multi-scale models of the brain. Here…
How single neuron properties shape chaotic dynamics and signal transmission in random neural networks
Samuel P. Muscinelli, Wulfram Gerstner, Tilo Schwalger
While most models of randomly connected networks assume nodes with simple dynamics, nodes in realistic highly connected networks, such as neurons in the brain, exhibit intrinsic dy…