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FOR 1581:  Extinction Learning: Behavioural, Neural and Clinical Mechanisms

Subject Area Social and Behavioural Sciences
Humanities
Medicine
Term from 2011 to 2018
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 179167628
 
We can learn new information and are subsequently able to remember it. However, we are equally able to learn that once acquired information is no longer valid and cease to respond to it. While the initial process of acquisition of new knowledge is well studied, the process of extinction is far less understood. Extinction is known to involve a new learning process that is different and more complex than the initial acquisition of the CS-US-association. Extinguished responses do not disappear but can return following manipulations such as a change in context as in renewal paradigms.
Within the scope of our Research Unit, we plan to explore the neural, the behavioural and the clinical mechanisms of extinction in various species, including humans. The diversity of our approaches at the systems and at the technical level will be combined with a high level of uniformity at conceptual, experimental, structural and technical levels: At the experimental design level, all participants within the Research Unit will utilise the renewal approach in their experiments. This will enable us to study the role of contextual cues and to analyse the common signatures of extinction learning from rodents to men with a single procedure. At the structural level, all neurobiological and most clinical groups will concentrate in at least a part of their experiments on the prefrontal cortex, the hippocampus and the amygdala, since previous studies had identified these areas to be critical for extinction learning.
All studies with human subjects will employ comparable predictive learning tasks in at least a part of their experiments. At the neurochemical level, we plan to study overlapping transmitter- und receptor-systems during extinction learning in several projects. Using this strategy, we intend to harvest deep insights into both the common and the distinct mechanisms of extinction learning in different systems and organisms. We believe that such an approach is the most promising one to achieve translational insights between basic and clinical science.
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