This title appears in the Scientific Report :
2015
Please use the identifier:
http://hdl.handle.net/2128/9157 in citations.
Spectral properties of excitable systems subject to colored noise
Spectral properties of excitable systems subject to colored noise
Many phenomena in nature are described by excitable systems driven by colored noise. Studying the response properties of these systems comes along with considerable difficulties, due to the non-vanishing correlation time of the noise. For systems with noise fast compared to their intrinsic time scal...
Saved in:
Personal Name(s): | Schücker, Jannis (Corresponding Author) |
---|---|
Helias, Moritz / Diesmann, Markus | |
Contributing Institute: |
Computational and Systems Neuroscience; IAS-6 Computational and Systems Neuroscience; INM-6 |
Published in: | 2015 |
Imprint: |
2015
|
Conference: | DPG Frühjahrstagung der Sektion Kondensierte Materie, Berlin (Germany), 2015-03-15 - 2015-03-20 |
Document Type: |
Poster |
Research Program: |
Supercomputing and Modelling for the Human Brain Theory of multi-scale neuronal networks Brain-inspired multiscale computation in neuromorphic hybrid systems The Human Brain Project Theory, modelling and simulation |
Link: |
OpenAccess |
Publikationsportal JuSER |
Many phenomena in nature are described by excitable systems driven by colored noise. Studying the response properties of these systems comes along with considerable difficulties, due to the non-vanishing correlation time of the noise. For systems with noise fast compared to their intrinsic time scale, we here present a general method of reduction to a lower dimensional effective system, respecting the details of the noise in the boundary conditions. Static boundary conditions were derived earlier by a perturbative treatment of the arising boundary layer problem [1,2]. Here we extend this scheme to the dynamic case [3]. We apply the formalism to the leaky integrate-and-fire neuron model, revealing an analytical expression for the transfer function valid up to moderate frequencies. This enables the assessment of the stability of networks of these excitable units. |