Address for Correspondence: (2008)
Wolfgang Maass, Thomas Natschläger, Henry Markram, Wolfgang Maass, Thomas Natschlaeger, ...
A key challenge for neural modeling is to explain how a continuous stream of multi-modal input from a rapidly changing environment can be processed by stereotypical recurrent circuits of...
Extracting Knowledge and Computable Models from Data- Needs, Expectations, and Experience (2008)
Thomas Natschläger, Felix Kossak, Mario Drobics
Abstract In modern industrial manufacturing, a great amount of data is gathered to monitor and analyze a given production process. Intelligent analysis of such data helps to reveal as much...
Address for Correspondence: (2008)
Wolfgang Maass, Thomas Natschläger, Henry Markram, Wolfgang Maass, Thomas Natschlaeger, ...
A key challenge for neural modeling is to explain how a continuous stream of multi-modal input from a rapidly changing environment can be processed by stereotypical recurrent circuits of...
Thomas Natschläger, Nils Bertschinger, Robert Legenstein
In this paper we analyze the relationship between the computational capabilities of randomly connected networks of threshold gates in the timeseries domain and their dynamical properties. In...
Chapter 9 Computer Models and Analysis Tools for Neural (2008)
Thomas Natschläger, Henry Markram, Wolfgang Maass
Abstract: This chapter surveys web resources regarding computer models and analysis tools for neural microcircuits. In particular it describes the features of a new website (www.lsm.tugraz.at) that...
Romain Brette, Michelle Rudolph, Ted Carnevale, Michael Hines, David Beeman, James M. Bower, ...
Abstract We review different aspects of the simulation of spiking neural networks. We start by reviewing the different types of simulation strategies and algorithms that are currently implemented. We...
Thomas Natschläger, Wolfgang Maass, Eduardo D. Sontag, Anthony Zador
Experimental data show that biological synapses behave quite differently from the symbolic synapses in common artificial neural network models. Biological synapses are dynamic, i.e., their “weight...
Wolfgang Maass, Thomas Natschläger, Henry Markram
A key challenge for neural modeling is to explain how a continuous stream of multi-modal input from a rapidly changing environment can be processed by stereotypical recurrent circuits of...
Wolfgang Maass, Thomas Natschläger, Henry Markram
A key challenge for neural modeling is to explain how a continuous stream of multi-modal input from a rapidly changing environment can be processed by stereotypical recurrent circuits of...
Fading memory and kernel properties of generic cortical microcircuit models (2005)
Maass, Wolfgang, Natschläger, Thomas, Markram, Henry
It is quite difficult to construct circuits of spiking neurons that can carry out complex computational tasks. On the other hand even randomly connected circuits of spiking neurons can in principle...
Dynamics of information and emergent computation in generic neural microcircuit models (2005)
Thomas Natschläger, Wolfgang Maass
We employ an efficient method using Bayesian and linear classifiers for analyzing the dynamics of information in high-dimensional states of generic cortical microcircuit models. It is shown that such...
Dynamics of information and emergent computation in generic neural microcircuit models (2004)
Natschläger, Thomas, Maass, Wolfgang
We employ an efficient method using Bayesian and linear classifiers for analyzing the dynamics of information in high-dimensional states of generic cortical microcircuit models. It is shown that such...
Information dynamics and emergent computation in recurrent circuits of spiking neurons (2004)
Thomas Natschläger, Wolfgang Maass
We employ an efficient method using Bayesian and linear classifiers for analyzing the dynamics of information in high-dimensional states of generic cortical microcircuit models. It is shown that such...
On the computational power of circuits of spiking neurons (2003)
Wolfgang Maass, Thomas Natschläger, Henry Markram
It is quite difficult to construct circuits of spiking neurons that can carry out complex computational tasks. On the other hand even randomly connected circuits of spiking neurons can in principle...
Information Dynamics and Emergent Computation in Recurrent Circuits of Spiking Neurons (2003)
Thomas Natschläger, Thomas Natschl Ager, Wolfgang Maass
We employ an efficient method using Bayesian and linear classifiers for analyzing the dynamics of information in high-dimensional states of generic cortical microcircuit models. It is shown that such...
Thomas Natschläger, Thomas Natschlaeger, Henry Markram, Henry Markram, Wolfgang Maass, Wolfgang Maass, ...
this article show that on the basis of this new paradigm one can now train a stereotypical recurrent network of integrate-and-fire neurons to carry out basically any real-time computation on spike...
Finding the Key to a Synapse (2001)
Thomas Natschläger, Wolfgang Maass
Experimental data have shown that synapses are heterogeneous: different synapses respond with different sequences of amplitudes of postsynaptic responses to the same spike train. Neither the role of...
Processing of Time Series by Neural Circuits with Biologically Realistic Synaptic Dynamics (2000)
Thomas Natschläger, Wolfgang Maass, E. Sontag, A. Zador
Experimental data show that biological synapses behave quite differently from the symbolic synapses in common artificial neural network models.
Exact VC-Dimension of Boolean Monomials (1996)
Thomas Natschläger, Michael Schmitt
We show that the Vapnik-Chervonenkis dimension of Boolean monomials over n variables is at most n for all n 2. It follows that the VC-dimension is determined exactly and is, except for n = 1, equal...
PCSIM: A Parallel Simulation Environment for Neural Circuits Fully Integrated with Python
Pecevski, Dejan, Natschläger, Thomas, Schuch, Klaus
The Parallel Circuit SIMulator (PCSIM) is a software package for simulation of neural circuits. It is primarily designed for distributed simulation of large scale networks of spiking point neurons....