biology

Gregor Schöner

Gregor Schöner is a biology topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Gregor Schöner rather than just read about it. In short: Gregor Schöner (born 1958 in Sindelfingen) is a German computational neuroscientist. He is a professor of the theory of cognitive systems at the Ruhr University Bochum and the director of the Institute for Neuroinformatics.

Key takeaways

Gregor Schöner belongs to biology; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Gregor Schöner to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Gregor Schöner from memory before moving on to harder problems.

Reference excerpt

Gregor Schöner (born 1958 in Sindelfingen) is a German computational neuroscientist. He is a professor of the theory of cognitive systems at the Ruhr University Bochum and the director of the Institute for Neuroinformatics.

Life and work From 1983 to 1985, Gregor Schöner studied physics and mathematics at Saarland University. In 1985, he received his PhD in theoretical physics from the University of Stuttgart under Herrmann Haken. For the next four years, he devoted himself to applications of the theory of stochastic dynamical systems to the coordination of biological motion under J. A. Scott Kelso at Florida Atlantic University. From 1989 to 1994, he led a research group for the first time at the Institute of Neuroinformatics at Ruhr University in Bochum. In that time, he and his group extended the application of dynamical systems to models of perception, motion, and autonomous robotics. After a six-year stay at the Centre de Recherche en Neurosciences Cognitives in Marseille, Gregor Schöner returned to the institute in 2001. He took over its leadership in 2003, succeeding Christoph von der Malsburg, and has remained in this position until today. Since September 2022, he has been the chairman of the Society for Cognitive Science in Germany. Gregor Schöner and his research group are known for the scientific development, applications, and software packages on Dynamic Field Theory (DFT). DFT provides a neurally plausible framework for the mathematical modeling of human cognition according to the theories of embodied cognition. The theory builds upon the continuous attractor networks models of Hugh R. Wilson and Jack D. Cowan (the "Wilson-Cowan model") and Shun'ichi Amari (the "neural field model"), which describe the interaction between excitatory and inhibitory coupled populations of cortical neurons. Schöner's research group publishes on visual search, spatial and relational language, and autonomous robotics.

Publications Gregor Schöner, John P. Spencer and the DFT Research Group (2015). A primer on dynamic field theory. Oxford University Press, ISBN 978-0-19-930056-3 Esther Thelen, Gregor Schöner, Christian Scheier, and Linda B. Smith (2001). "The dynamics of embodiment: A field theory of infant perseverative reaching". Behavioral and Brain Sciences 24(1), 1–34. doi:10.1017/s0140525x01003910

References

External links Publication list on the website of the Institute for Neuroinformatics at the Ruhr University Bochum

Worked examples

Example 1 — a first encounter with Gregor Schöner

Start with the simplest possible case. Write down what Gregor Schöner claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In biology, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Gregor Schöner before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Gregor Schöner ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Gregor Schöner

In research: Gregor Schöner appears in biology research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Gregor Schöner in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Gregor Schöner is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1958 births, Computational neuroscientists, German cognitive neuroscientists, so understanding it makes those chapters shorter.
In everyday life: Look for Gregor Schöner outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Gregor Schöner in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Gregor Schöner means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Gregor Schöner out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Gregor Schöner in simple terms?

Why does Gregor Schöner matter?

Because it connects several biology ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Gregor Schöner?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Gregor Schöner.