Search

link to homepage

Institute of Neuroscience and Medicine
(leer)

Navigation and service


Emulation of dynamical systems by recurrent neural networks

  • Properties of learnable dynamical systems
  • Network capacity
  • Role of single-neuron dynamics and cortical network connectivity

An essential prerequisite for any living being's survival is its ability to predict its environment and to adjust its behaviour according to the outcome of this prediction. From a physicist's point of view, our world constitutes a set of dynamical systems. It has been hypothesized that the mammalian neocortex has evolved towards a flexible dynamical substrate in order to emulate external dynamical systems, similar to a spring emulating the motion of a pendulum. Once a particular dynamical system is learned, trajectories for any (new) initial condition can be predicted. Recent studies have demonstrated that simple recurrent neural networks can indeed be trained to emulate a large number of dynamical systems. Current research in our group is focusing on the properties of the dynamical systems which can be emulated by a given neural network, the network capacity and the role of realistic single-neuron dynamics and cortical network connectivity.

Related publications:

Maass W., Joshi P., Sontag E.D. (2007), Computational aspects of feedback in neural circuits PLOS Comp Biol 3(1):1-20

Legenstein R., Maass W. (2007), Edge of chaos and prediction of computational performance for neural circuit models, Neural Networks 20(3):323-334

Hausler S., Maass, W. (2006), A Statistical Analysis of Information-Processing Properties of Lamina-Specific Cortical Microcircuit Models, Cerebral Cortex 17:149-162

Jaeger H., Haas H. (2004), Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication Science 304(5667):78-80


Servicemeu

Homepage

Logo

 

 

 

YOUR OPINION MATTERS!

 

Dear visitor,

To make our website suit your needs even more and to give it a more appealing design, we would like you to answer a few short questions.

Answering these questions will take approx. 10 min.

Start now Close window

Thank you for your support!

 

In case you have already taken part in our survey or in case you have no time to take part now, you can simply close the window by clicking "close".

If you have any questions on the survey, please do not hesitate to contact: webumfrage@fz-juelich.de.

 

Your Team at Forschungszentrum Jülich

 

Note: Forschungszentrum Jülich works with the market research institute SKOPOS to anonymously conduct and analyze the survey. SKOPOS complies with the statutory requirements on data protection as well as with the regulations of ADM (Arbeitskreis Deutscher Markt- und Sozialforschungsinstitute e.V.) and ESOMAR (Europäische Gesellschaft für Meinungs- und Marketingforschung). Your data will not be forwarded to third parties.