activity
20132024
most citedTowards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size

170 citations · 356 across the 12 of their papers we have counts for

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9 papers · 1 filter

q-bio.NC2024★ 2 cited

How random connectivity shapes the fluctuating dynamics of finite-size neural populations

Nils E. Greven, Jonas Ranft, Tilo Schwalger

Mesoscopic models of finite-size neuronal populations are crucial to understand the dynamics of neural networks in the brain, especially their fluctuations and response to stimuli.…

q-bio.NC2022★ 17 cited

Mesoscopic description of hippocampal replay and metastability in spiking neural networks with short-term plasticity

Bastian Pietras, Valentin Schmutz, Tilo Schwalger

Bottom-up models of functionally relevant patterns of neural activity provide an explicit link between neuronal dynamics and computation. A prime example of functional activity pat…

q-bio.NC2021

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…

q-bio.NC2020★ 20 cited

Low-dimensional firing-rate dynamics for populations of renewal-type spiking neurons

Bastian Pietras, Noé Gallice, Tilo Schwalger

The macroscopic dynamics of large populations of neurons can be mathematically analyzed using low-dimensional firing-rate or neural-mass models. However, these models fail to captu…

q-bio.NC2019

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…

q-bio.NC2018★ 1 cited

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…

q-bio.NC2016★ 170 cited

Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size

Tilo Schwalger, Moritz Deger, Wulfram Gerstner

Neural population equations such as neural mass or field models are widely used to study brain activity on a large scale. However, the relation of these models to the properties of…

q-bio.NC2013★ 40 cited

Fluctuations and information filtering in coupled populations of spiking neurons with adaptation

Moritz Deger, Tilo Schwalger, Richard Naud +1

Finite-sized populations of spiking elements are fundamental to brain function, but also used in many areas of physics. Here we present a theory of the dynamics of finite-sized pop…

q-bio.NC2013★ 53 cited

Patterns of interval correlations in neural oscillators with adaptation

Tilo Schwalger, Benjamin Lindner

Neural firing is often subject to negative feedback by adaptation currents. These currents can induce strong correlations among the time intervals between spikes. Here we study ana…