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- Birgit Kriener, Tom Tetzlaff, Ad Aertsen, Markus Diesmann, Stefan Rotter
- Neural Computation
- 2008

The function of cortical networks depends on the collective interplay between neurons and neuronal populations, which is reflected in the correlation of signals that can be recorded at different levels. To correctly interpret these observations it is important to understand the origin of neuronal correlations. Here we study how cells in large recurrent… (More)

- Birgit Kriener, Moritz Helias, Ad Aertsen, Stefan Rotter
- Journal of Computational Neuroscience
- 2008

Can the topology of a recurrent spiking network be inferred from observed activity dynamics? Which statistical parameters of network connectivity can be extracted from firing rates, correlations and related measurable quantities? To approach these questions, we analyze distance dependent correlations of the activity in small-world networks of neurons with… (More)

- Frank Van Bussel, Birgit Kriener, Marc Timme
- Front. Comput. Neurosci.
- 2011

Networks of well-known dynamical units but unknown interaction topology arise across various fields of biology, including genetics, ecology, and neuroscience. The collective dynamics of such networks is often sensitive to the presence (or absence) of individual interactions, but there is usually no direct way to probe for their existence. Here we present an… (More)

- Ivan Raikov, Robert Cannon, +17 authors Botond Szatmary
- BMC Neuroscience
- 2011

The growing number of large-scale neuronal network models has created a need for standards and guidelines to ease model sharing and facilitate the replication of results across different simulators. To foster community efforts towards such standards, the International Neuroinformatics Coordinating Facility (INCF) has formed its Multiscale Modeling program,… (More)

- Thomas Heiberg, Birgit Kriener, Tom Tetzlaff, Alex Casti, Gaute T. Einevoll, Hans Ekkehard Plesser
- Journal of Computational Neuroscience
- 2013

Firing-rate models provide a practical tool for studying signal processing in the early visual system, permitting more thorough mathematical analysis than spike-based models. We show here that essential response properties of relay cells in the lateral geniculate nucleus (LGN) can be captured by surprisingly simple firing-rate models consisting of a… (More)

- Birgit Kriener, Moritz Helias, Stefan Rotter, Markus Diesmann, Gaute T. Einevoll
- BMC Neuroscience
- 2013

Pattern formation, i.e., the generation of an inhomogeneous spatial activity distribution in a dynamical system with translation invariant structure, is a well-studied phenomenon in neuronal network dynamics, specifically in neural field models. These are population models to describe the spatio-temporal dynamics of large groups of neurons in terms of… (More)

- Yann Le Franc, Andrew P Davison, +7 authors Erik De Schutter
- BMC Neuroscience
- 2012

The diversity of modeling approaches in computational neuroscience makes model sharing, retrieval, reuse and reproducibility difficult and even sometimes impossible. To address this problem, standardized languages have been developed by and for the community, such as NeuroML [1], PyNN [2] and NineML (http://software.incf.org/software/nineml). Although these… (More)

- Birgit Kriener, Håkon Enger, Tom Tetzlaff, Hans Ekkehard Plesser, Marc-Oliver Gewaltig, Gaute T. Einevoll
- Front. Comput. Neurosci.
- 2014

Random networks of integrate-and-fire neurons with strong current-based synapses can, unlike previously believed, assume stable states of sustained asynchronous and irregular firing, even without external random background or pacemaker neurons. We analyze the mechanisms underlying the emergence, lifetime and irregularity of such self-sustained activity… (More)

- Sharon M Crook, James A Bednar, +12 authors Sacha van Albada
- Network
- 2012

As computational neuroscience matures, many simulation environments are available that are useful for neuronal network modeling. However, methods for successfully documenting models for publication and for exchanging models and model components among these projects are still under development. Here we briefly review existing software and applications for… (More)

Synchrony prevalently emerges from the interactions of coupled dynamical units. For simple systems such as networks of phase oscillators, the asymptotic synchronization process is assumed to be equivalent to a Markov process that models standard diffusion or random walks on the same network topology. In this paper, we analytically derive the conditions for… (More)