Project Collaborations
Learning inhibition for pattern separation



| PI:

Christian Leibold

The dentate gyrus is thought to be crucially involved in pattern separation. Therefore, during continual learning, new patterns need to  minimize their overlap to existing patterns.

Here we explore synaptic plasticity at all connections of a circuit model of the DG-hilar loop including somatostatin positive and parvalbumin positive inhibitory interneurons as well as hilar mossy cells upon its capacity to learn such pattern separation online. The outcomes are evaluated by comparison to experimental recordings from the consortium using neural manifold techniques.

Graphical Abstract | Smart Figures


Christian Leibold


Sven Goedeke