Prof. Dr. Sen Cheng

Research interest

My research group investigates the neural mechanisms underlying learning and memory. We are primarily interested in the hippocampus, the brain region that is mainly involved in episodic memory, as well as in the learning and memory of sequences. Our research focuses on the dynamics of these processes, which has received relatively little attention to date.

We employ two complementary approaches. Our first approach is modeling, including mathematic models as well as computer simulation of complex networks. While all models are simplified, we aim to build biologically realistic models that capture the essence of the neural circuit mechanism underlying learning and memory. Our second approach is data-mining. We develop methods for model-based data analysis and apply such methods to experimental data. These data include electrophysiological and EEG recordings as well as behavioral data. We collaborate closely with neuroscientists on the RUB campus and at other universities in Germany and abroad.

Methods

• (spiking) neural networks
• dynamical systems
• reinforcement learning
• data mining 

Master theses

Requirements: advanced programming skills (preferably Python) might be required depending on the project

Suggestions for Master projects in the department Computational Neuroscience

Examples of previously supervised Master theses:

• Storing and retrieving neural sequences in a network model of the hippocampus with spiking neurons and STDP (2018)
• Propagation of sequential activity in feedforward neural networks (2016)

Website

click here to find out more about the department of Computational Neuroscience