Neuronal Dynamics for Embodied Cognition 2020

Our annual summer school gives students an in-depth look at dynamic field theory over the course of a single week. The summer school covers everything from the basics of dynamic field theory up to our latest research projects. 

This virtual edition of our summer school will consist of two parts: A live-lecture series and a hands-on workshop.

The lecture series will be held as a video conference and provides a step-by-step introduction to Dynamic Field Theory. It is open to everyone; you only have to register with your email address. Lectures will take place from August 31 to September 4 between 3:00 and 6:00 pm (UTC +2).

The two-and-a-half-day project workshop gives students the opportunity to put the newly acquired skills to use in a concrete hands-on modeling project. Students solve the task in our open-source simulation environment under the guidance of a personal tutor. The one-on-one tutoring limits the number of participants who can take part in the workshop. To apply, please fill out the online application form, which asks for a cover letter and a CV as well as some other information that we use to prepare projects for you. We encourage workshop applications by small groups of participants, maybe two or three colleagues who will work together locally on the same project and may share a tutor. All participants of such a group should apply separately and list their potential group partners in the application form. The workshop will take place September 3-5. Personal tutoring via video conference will be available on each workshop day at flexible hours.

Participation in any part of the school is free of charge.

Who is this summer school for?

The summer school is aimed at students at the advanced undergraduate or graduate level, postdocs and faculty members in the areas of embodied cognition, cognitive science, developmental science, cognitive neuroscience, developmental robotics, autonomous robotics, cognitive robotics, and anyone who wants to learn about dynamic field theory.

Structure of the school

The school is led by Prof. Gregor Schöner, who lectures on the basic concepts of DFT in the live lecture series. Workshop sessions provide hands-on training working with dynamic field models in COSIVINA and CEDAR, our interactive simulation environments. Students learn to create a dynamic field model from the ground up and learn how to apply the concepts of DFT to their home domain of interest.


For the hands-on work, the exercises and projects, we use numeric simulators. COSIVINA is a simulator for dynamic field theory that is based on Matlab and supports quick assembly of DFT models, for instance to account for human behavioral data.

Models based on larger field architectures can be implemented in the C++ based simulator CEDAR, which features a graphical user interface in which core elements of DFT can be assembled without in-depth programming knowledge.  For more advanced projects in CEDAR, basic knowledge of C++ is required.

Topics covered

Some of the topics that the summer school covers include:

  • Neural dynamics and basic attractor states
  • Dynamic fields
  • Introduction to COSIVINA and CEDAR
  • Links to neurophysiology and embodiment
  • Multi-dimensional fields and multi-layer dynamics
  • Spatial transformations and objects in a scene
  • Developmental dynamics and preferential looking
  • Sequence learning and higher level cognition


See separate tab, one for the school, one for the workshop. 


03:00PM (UTC+2) · 03:30PM (UTC+2): Welcome (Mathis Richter)

03:30PM (UTC+2) · 04:30PM (UTC+2): Introduction (Gregor Schöner)

04:30PM (UTC+2) · 06:00PM (UTC+2): DFT Core Lecture (Gregor Schöner)


10:00AM (UTC+2) · 03:00PM (UTC+2): Free exercise work (optional)

03:00PM (UTC+2) · 03:15PM (UTC+2): DFT Exercise Feedback (Mathis Richter)

03:15PM (UTC+2) · 04:00PM (UTC+2): CEDAR Tutorial, Preparation of Exercise (Mathis Richter)

04:00PM (UTC+2) · 05:00PM (UTC+2): DFT Models (Gregor Schöner)

05:00PM (UTC+2) · 06:00PM (UTC+2): Embodied Neural Dynamics (Gregor Schöner)


10:00AM (UTC+2) · 03:00PM (UTC+2): Free exercise work (optional)

03:00PM (UTC+2) · 03:30PM (UTC+2): CEDAR Exercise Feedback (Mathis Richter)

03:30PM (UTC+2) · 04:30PM (UTC+2): Higher Dimensional Neural Fields (Gregor Schöner)

04:30PM (UTC+2) · 05:30PM (UTC+2): Sequence Generation (Gregor Schöner)

05:30PM (UTC+2) · 06:00PM (UTC+2): Workshop Project Overview


03:00PM (UTC+2) · 03:45PM (UTC+2): Case study 1: Scene Representation (Raul Grieben)

03:45PM (UTC+2) · 04:30PM (UTC+2): Case study 2: Relational Concepts (Mathis Richter)

04:30PM (UTC+2) · 05:00PM (UTC+2): Guest lecture: Quentin Houbre, Tampere Univ. Finland: Developmental Robotics with DFT: From Sensorimotor Contingencies to Autonomous Goals Discovery

05:00PM (UTC+2) · 05:30PM (UTC+2): Guest lecture: Sebastian Schneegans, Dep. Psychology, Cambridge University: Drift in Neural Population Activity Causes Working Memory to Deteriorate Over Time

05:30PM (UTC+2) · 06:00PM (UTC+2): Discussion


03:00PM (UTC+2) · 03:45PM (UTC+2): Case study 3: Conceptual Combination (Daniel Sabinasz)

03:45PM (UTC+2) · 04:30PM (UTC+2): Case study 4: Intentional Systems (Jan Tekülve)

04:30PM (UTC+2) · 05:30PM (UTC+2): Guest lecture: Yulia Sandamirskya, Intel Labs: DFT and Neuromorphic Computing

05:30PM (UTC+2) · 06:00PM (UTC+2): General Discussion


03:00PM (UTC+2) · 04:30PM (UTC+2): Workshop Project Presentations (Participants)


10:00AM (UTC+2) · 11:00AM (UTC+2): Workshop Introduction

11:00AM (UTC+2) · 03:00PM (UTC+2): Workshop Tutoring


10:00AM (UTC+2) · 10:30AM (UTC+2): Visual Search Project Feedback

10:30AM (UTC+2) · 03:00PM (UTC+2): Workshop Tutoring


10:00AM (UTC+2) · 03:00PM (UTC+2): Workshop Tutoring (limited)

04:30PM (UTC+2) · 05:00PM (UTC+2): Discussion and Feedback

Welcome and introduction

Lecture slides Welcome
Video Introduction
Lecture slides Introduction

Introduction into the theme of the DFT school

DFT core lectures

Lectures and exercises about the foundations of dynamic field theory

Video DFT core lecture
Lecture slides DFT core lecture
Video DFT models
Lecture slides DFT models

Lecture about DFT models that account for behavior by establishing an interface between experimental conditions/experimental measures and inputs to models/measures on models

Exercises Exercise 1

An exercise sheet on the dynamics of neural nodes.

Exercises Exercise 2

An exercise sheet on the different dynamic regimes of a one-dimensional dynamic neural field.

CEDAR tutorial and exercise

Exercises CEDAR tutorial and exercise

This sheet covers most of the steps Mathis showed in the CEDAR tutorial, enabling you to copy the steps in your own time. At the end of the document is an additional exercise that the CEDAR tutorial does not cover and you can explore on your own.

Video CEDAR tutorial
Video CEDAR exercise
Configuration files CEDAR architecture files

This ZIP file contains the architecture files for CEDAR that are the solutions for the CEDAR tutorial and exercise. Included is also an architecture file, where the architecture works with sensory input from a video file. The video file is also included. Unzip the ZIP archive and open the JSON files inside the CEDAR graphical user interface (through the "File -> Open File" dialog.

Document CEDAR FAQ

This document covers some use cases you might encounter while working with cedar. It is  not necessary for the cedar exercise, but it might come in handy, if you want to start your own project in cedar. Feel free to contribute to this FAQ by mailing question suggestions to

Modeling projects

Video Project Overview

Unfortunately, the first few minutes are missing as we started the recording too late.

We will not keep this video on Youtube after the end of the summer school.

Exercises Cedar Project: Visual Search

This is the main cedar project. All other cedar projects start from here.

Configuration files Solution: Visual Search

Solution to the Cedar Project: Visual Search

Exercises Cedar Project: Spatial Language

A possible extension of the Visual Search project.

Exercises Cedar Project: Reaching

A possible extension of the Visual Search project.

Exercises Cedar Project: Generation of Sequences

A possible extension of the Visual Search project.

Exercises Cosivina Project: Simon Effect

This is the main Cosivina project. Many extensions are possible within Cosivina

Configuration files Cedar Template File

This file is the basis for all cedar projects

Configuration files Cedar Template File for Mac

This file does not contain the robotic simulator and might work better for Mac. It is not possible to do the reaching project with this file.

Document Spatial Language Project Background Material

This paper "Autonomous Neural Dynamics to Test Hypotheses in a Model of Spatial Language" by Richter, Lins, Schneegans, Sandamirskaya and Schöner from 2014 serves as additional background material for the Spatial Language project

Advanced DFT lectures

on higher dimensional fields and sequence generation 

Video Higher dimensions
Lecture slides Higher dimensions

Binding, coordinate transforms, and DFT architectures 

Video Sequential processing
Lecture slides Sequential processing

Final discussion

Lecture slides DFT and other theoretical perspectives

Brief notes on how DFT relates to distributed representations and VSA