I am interested in understanding how neural hardware (neuron, synapse and connectivity patterns) shape network activity and thereby brain function. Specifically, we are exploring the following questions:
- What role do the network connectivity and network dynamics play in the transfer of information from one network to another?
- How neuronal and synapse properties interact with network structure to shape the network activity dynamics?
- How the activity dynamics of the network and information transfer can be controlled by external stimulation?
In a way we use the ‘static’ data about the brain in the for neuron properties, synapse properties (which are determined largely by gene expressions) and convert it to dynamic data.
We use analytical methods from statistical mechanics, probability theory, graph theory and control systems theory, and combine them with numerical simulations of large-scale neuronal networks of different brain regions.
One of the goals of our research is to develop mathematical models of brain diseases and create a theoretical framework to understand the mechanisms underlying the emergence of disease related aberrant activity dynamics in diseases (e.g. Parkinson’s diseases, epilepsy, anxiety). Eventually such a quantitative understanding of brain diseases would pave the way for the development of novel brain stimulation protocols to control or correct the disease-related brain activity. Therefore, we are neuralizing the control system theory and developing tools to control the dynamics of neuronal networks by external stimulations methods.
Group Members
Archishman Biswas | PhD Student
Satarupa Chakrabarti | Postdoc
Movitz Lenninger | Postdoc
Hauke Wernecke | PhD Student
Moritz Pesl | Visiting internship student