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| Conserved neural circuits for survival Emotions engender survival-relevant behaviours, in humans and non-human animals. We take a cross-species perspective and develop human research paradigms that are comparable to animal set ups. Thus we seek to make comparative statements on the neural circuits supporting survival behaviours in humans, and their relation to more classical accounts of emotions |
Algorithms for survival We study survival-oriented and emotional behaviour with the toolkit of computational neuroscience. We combine Bayesian Decision Theory, Reinforcement Learning Theory, psychophysics, and neuroinformatics, to specify the goals of emotional behaviour, find out the algorithms controlling it, and investigate its neural implementation. |
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| Behavioural research methods Fear memory quantification in humans is currently noisy. As an example, a sample size of N>300 is needed to demonstrate with 95% power that an intervention suppresses fear memory, when using classical SCR measures in a retention test. We have brought down this sample size to around 50, by combining experimental improvements with Psychophysiological Modelling (PsPM). We work on reducing the required sample size to a level that affords high-throughput screening of fear-suppressing interventions in humans. |
Emotion circuit malfunction Emotions are presumably adaptive, but many people suffer from excessive anxiety, fear, or anhedonia. We seek to understand this in terms of underlying control algorithms and circuits, with the aim of improving therapies for major depression, phobias, post-traumatic stress disorder, and generalized anxiety disorder. |