We aim to define whether there is a distinction between the information quality which is sent out from the medial PFC (mPFC) via certain thalamic routes and how this relates to the flexible formation of task-dependent and output-dependent ensembles in mPFC.
We will provide and optimize genetically encoded light-regulated actuators and neural probes that in combination will serve to elucidate the neural circuitry underpinning movement control triggered by internal and external cues.
The project aims at elucidating the role of outgoing projections of the PFC subsections to their subcortical targets with a focus on network analyses. For this, we will combine in vivo extracellular recordings with optogenetic manipulation of the projections, connectivity analysis and modeling.
Using different approaches, the proposed project will provide detailed information on the impact of PVI-specific synaptic plasticity and PVI activity on cognitive movement control and learning and thereby bridge the gap between synaptic plasticity, neuronal activity, and behaviour.
We aim to develop paradigms which allow powerful interactions with the brain with clinical relevance.
We apply artificial neural networks (Deep Learning) for automatic object recognition and precise behavior tracking. (Collaboration with Professor Thomas Brox, Computer Vision Laboratory, University of Freiburg, Germany)
We develop ways to predict body motion from neural recordings (decoding) and vice-versa (encoding) using latest deep learning methods.
How does the local organization of motor cortex look like in terms of encoding of different movement types? We address this question with a combination of experimental and computational tools.
How are different outputs of motor cortex organized and coordinated?
What makes us start or stop a movement? Prefrontal areas are executively involved in this process. In this project, we investigate the impact of prefrontal input on motor cortex activity.
What drives a movement locally? The role of different cell types are investigated.