Prof. Dr. Robert Schmidt, Neural Data Science, Faculty of Computer Science, Institute for Neural Computation

Robert Schmidt

In my group we study cognitive functions by applying advanced data analysis methods and computational modelling to large electrophysiological and behavioural data sets, often in close collaboration with experimental groups. Our goal is to identify neural mechanisms underlying cognitive functions, in particular in cortical and basal ganglia circuits. We use a variety of analysis and computational modelling techniques, such as machine learning approaches and numerical simulations of single neuron and network activity. Possible PhD projects include the following topics:

Stopping actions

Decision-making does not just include the selection of an action, but it also often involves suppressing actions that are undesired or even potentially harmful. This cognitive ability is also known as inhibitory control and is often affected in pathological contexts such as drug addiction, impulsivity, or Parkinson’s disease. We study inhibitory control by developing computational models of neural activity and behaviour based on experimental data.


Dopamine is a fascinating neuromodulator that has been closely related to a teaching signal in a neural implementation of reinforcement learning, but also to motivation in goal-directed behaviour. To study the function of dopamine in basal ganglia and prefrontal circuits we use reinforcement learning models and also more detailed biophysical models that describe the different components of dopamine signalling, including its release, diffusion, and receptor binding.


Oscillations in the brain are often associated with cognitive functions. We examine them in the spiking activity of single neurons as well in neural populations, where they can be measured in the local field potential and in EEG recordings. Interestingly, recent studies indicate that neural oscillations often occur in brief bursts instead of being sustained during a cognitive process such as working memory. To better understand the functions of such transient oscillations we develop new analysis methods and apply them to electrophysiological recordings.