Zobrazeno 1 - 10
of 138
pro vyhledávání: '"Schwalger, Tilo"'
We propose a novel multi-scale modeling framework for infectious disease spreading, borrowing ideas and modeling tools from the so-called Refractory Density (RD) approach. We introduce a microscopic model that describes the probability of infection f
Externí odkaz:
http://arxiv.org/abs/2407.02396
Publikováno v:
PLoS Comput Biol 18(12): e1010809 (2022)
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 pattern is hippocampal replay, which is critical for memory consolidation
Externí odkaz:
http://arxiv.org/abs/2204.01675
Autor:
Schwalger, Tilo
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 input noise lends itself to modeling biophysical noise processes, the phe
Externí odkaz:
http://arxiv.org/abs/2109.07416
Population equations for infinitely large networks of spiking neurons have a long tradition in theoretical neuroscience. In this work, we analyze a recent generalization of these equations to populations of finite size, which takes the form of a nonl
Externí odkaz:
http://arxiv.org/abs/2106.14721
Autor:
Schieferstein, Natalie1,2 (AUTHOR) natalie.schieferstein@freenet.de, Schwalger, Tilo2,3 (AUTHOR), Lindner, Benjamin2,4 (AUTHOR), Kempter, Richard1,2,5 (AUTHOR) natalie.schieferstein@freenet.de
Publikováno v:
PLoS Computational Biology. 2/20/2024, Vol. 20 Issue 2, p1-50. 50p.
Publikováno v:
Phys. Rev. E 102, 022407 (2020)
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 capture spike synchronization effects of stochastic spiking neurons such as
Externí odkaz:
http://arxiv.org/abs/2003.06038
Autor:
Schwalger, Tilo, Chizhov, Anton V.
The dominant modeling framework for understanding cortical computations are heuristic firing rate models. Despite their success, these models fall short to capture spike synchronization effects, to link to biophysical parameters and to describe finit
Externí odkaz:
http://arxiv.org/abs/1909.10007
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, we extend a recent theory for mesoscopic population dynamics with st
Externí odkaz:
http://arxiv.org/abs/1812.09414
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 dynamics over multiple timescales. We analyze how the dynamical properti
Externí odkaz:
http://arxiv.org/abs/1812.06925
Publikováno v:
PLoS Comput. Biol., 13(4):e1005507, 2017
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 single neurons is unclear. Here we derive an equation for several int
Externí odkaz:
http://arxiv.org/abs/1611.00294