Prof. Dr. Robert Schmidt

Research interest

We develop advanced analysis methods to apply them to neural and behavioural data, and combine them with computational models. In close collaboration with experimental research groups we analyse and model large data sets of electrophysiological recordings. Our goal is to identify the neural mechanisms underlying cognitive control, in particular in prefrontal and basal ganglia circuits, and to determine how the neuromodulator dopamine contributes to them. We use a variety of analysis and computational modelling techniques, such as machine learning approaches and numerical simulations of single neuron and network activity.

Methods

• Analysis and modelling of large data sets of electrophysiological recordings
• Numerical simulations of single neuron and network activity
• Machine learning (e.g. reinforcement learning)
• Computational models of dopamine signalling
• Computational models of cognitive control

Master theses

Requirements:

• Programming skills (e.g. Python)
• Knowledge of linear algebra, calculus and statistics (depending on project)
• Neuroscience

Suggestions for Master projects in the department Neural Data Science

Website

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