Abstract: In the cognitive-, behavioral- or neuro-sciences we often match a computational model to observations and then, analyzing the model, hope to find results that generalize to the underlying system.
What's on a mouse's mind? Behavioral measures to understand experiences and needs of an animal Lars Lewejohann, Freie Universität Berlin, German Federal Institute for Risk Assessment (BfR), German Centre for
"Harnessing machine learning to model biological systems" Abstract: Classically, models of biological systems follow two different approaches. In bottom-up approaches, biological data are used to constrain a phenomenological model of
One fundamental difference between human and non-human animals is the ability of humans to instantaneously implement instructed behaviour. While other animals acquire new behaviour via effortful trial-and-error learning or extensive
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Abstract: I will discuss research on a powerful biological model system, the natural clonal fish Amazon molly. Mothers in this female-only species produce genetically identical offspring, allowing us to employ
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Abstract: Collective behavior, as exhibited by bird flocks, fish schools or insect swarms, is a fascinating example of self-organized behavior in biology. Mathematical models of flocking were key for the
Abstract: Anthropomorphic robot features are intended to trigger the activation of social scripts from human-human interaction, thereby offering an intuitive approach to interact with robots. Whereas this seems to be
This Thursday 15 September (2-5pm) is SCIoI’s Open Day! On this day, SCIoI offers visitors the chance to catch a glimpse of our cluster, its activities, and open positions. During
Abstract The collective behaviour of animals has attracted considerable attention in recent years, with many studies exploring how local interactions between individuals can give rise to global group properties. The
Abstract: The brain is a complex dynamical system with processes operating on different spatial scales. At the macroscopic end one observes global dynamical phenomena, which are called „brain states“ and
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