Lecturer: Daniel Sabinasz, Raul Grieben, Gregor Schöner
Fields: Cognitive Science, Neural modeling
Content
YOU WILL NEED TO BRING YOUR OWN COMPUTER FOR THIS COURSE!
Dynamic Field Theory (DFT) provides a mathematical framework in which the emergence of cognition from its sensorimotor grounding can be understood. The activation dynamics of neural populations are organized as strongly recurrent neural networks that stabilize neural representations. Instabilities generate state transitions from which sequences of mental and motor acts emerge.
The tutorial will introduce the core concepts of DFT, while providing hands-on exercises and projects that make use of these concepts to build models of grounded cognition. We will discuss how DFT relates to other approaches to cognition.
Literature
- Schöner, G.: Dynamical Systems Approaches to Cognition. In: Sun, R (ed.): The Cambridge Handbook of Computational Psychology. 2nd Edition. Cambridge University Press (in press).
- (We will make a pre-print available).
- See dynamicfieldtheory.org for more resources
Lecturer
Daniel Sabinasz is a Doctoral Student at the Institute for Neural Computation (INI) at the Ruhr-University Bochum focussed on using DFT to account for higher cognition. His training is in computer science and cognitive science.
Raul Grieben is a Doctoral Student at the INI focussed on a neural dynamic account for visual search. His training is in applied computer science.
Gregor Schöner holds the chair for Theory of Cognitive Systems at the INI. His broad interdisciplinary profile touches movement science, visual psychophysics, cognitive science, neuroscience, and cognitive robotics. .He has held academic positions in the US, France, and Germany, has been funded through German, French, European, and US funding agencies, and has published over 270 scientific articles.
Affiliation: Ruhr-University Bochum
Homepage: https://www.ini.rub.de/