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TP9 Computational consequences of interneuron plasticity

Prof. Dr. Henning Sprekeler

It is widely believed that the neural underpinning of learning and memory lies in long-term changes of synaptic connections between neurons. While most studies on synaptic plasticity have focused on the plasticity of excitatory synapses among principal cells, much less is known about synaptic plasticity in inhibitory interneuron (IN) circuits and its functional consequences. The main Aim of this project is to use a three-pronged computational approach to characterize the activity-dependence of synaptic plasticity in IN circuits and to provide functional interpretations for it. Firstly, we will use a ‘top-down’ approach to predict properties of interneuron plasticity that support desired computational functions, particularly the formation of sparse and uncorrelated neural representations. Secondly, the will use model-based data analysis methods to infer the activity-dependence of interneuron plasticity from activity and connectivity data acquired within the RU. Finally, we will apply a ‘bottom-up’ approach to shed light on the functional consequences of IN circuit plasticity, both on the network and the computational level, using the well-characterized network of the dentate gyrus as a model system.


Prof. Dr. Marlene Bartos

Physiologisches Institut I

Universität Freiburg

Hermann-Herder-Str. 7

79104 Freiburg



Prof. Dr. Imre Vida

NeuroCure Cluster of Excellence

Institut für Integrative Neuroanatomie

Charité- Universitätsmedizin Berlin

Philippstraße 12

10115 Berlin


Prof. Dr. Peer Wulff

Physiologisches Institut

Universität Kiel

Hermann-Rodewald-Straße 5

24118 Kiel


Dagmar Sonntag

Physiologisches Institut I

Universität Freiburg

Hermann-Herder-Str. 7

79104 Freiburg

Tel: +49(761) 203-67310

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