Dynamic Field Theory: Conceptual Foundations and Applications in the Cognitive and Developmental Sciences

This page contains material for the DFT tutorial at the Cognitive Science conference in Berlin, 2013. Here you will find an abstract and the lecture material of the tutorial.

Objectives and scope

Dynamical Systems thinking has been influential in the way psychologists, cognitive scientists, and neuroscientists think about sensori-motor behavior and its development. The initial emphasis on motor behavior was expanded when the concept of dynamic activation fields provided access to embodied cognition.

Dynamical Field Theory (DFT) offers a framework for thinking about representation-in-the-moment that is firmly grounded in both Dynamical Systems thinking and neurophysiology. Dynamic Neural Fields are formalizations of how neural populations represent the continuous dimensions that characterize perceptual features, movements, and cognitive decisions. Neural fields evolve dynamically under the influence of inputs as well as strong neuronal interaction, generating elementary forms of cognition through dynamical instabilities. The concepts of DFT establish links between brain and behavior, helping to define experimental paradigms in which behavioral signatures of specific neural mechanisms can be observed. These paradigms can be modeled with Dynamic Neural Fields, deriving testable predictions and providing quantitative accounts of behavior.

One obstacle for researchers wishing to use DFT has been that the mathematical and technical skills required to make these concepts operational are not part of the standard repertoire of cognitive scientists. The goal of this tutorial is, therefore, to provide the training and tools to overcome this obstacle.

We will provide a systematic introduction to the central concepts of DFT and their grounding in both Dynamical Systems concepts and neurophysiology. We will discuss the concrete mathematical implementation of these concepts in Dynamic Neural Field models, giving all needed background and providing participants with some hands-on experience using interactive simulators in MATLAB. We will review robotic implementations to make the ideas concrete. Finally, we will take participants through a number of selected, exemplary case studies in which the concepts and associated models have been used to ask questions about elementary forms of embodied cognition and their development.

Target audience

No specific prior knowledge of the mathematics of dynamical systems models or neural networks is required as the mathematical and conceptual foundations will be provided during the tutorial. An interest in formal approaches to cognition is an advantage.

Computer use

Participants who bring laptops with Matlab installed (student version is sufficient) will be able to follow demonstrations by actively working with the simulator during the lectures.

Online resources

Publications, lecture material, and interactive simulators can be found on other pages of this website and on the website of the Delta center of the University of Iowa.

Yearly summer school

Institut für Neuroinformatik (INI)
Ruhr-Universit├Ąt Bochum, Germany
Next event:
August 25-30, 2014

Apply now!
Application deadline is June 15, 2014.

Contact

For general enquiries, please contact Prof. Dr. Gregor Schöner

To apply for the DFT summer school, please follow the instructions for application.