Online Neuronal Connectivity Estimation and Neurofeedback with Transcranial Magnetic Stimulation

• Applicant: Professor Dr.-Ing. Jens Haueisen
• Subject Area: Cognitive, Systems and Behavioural Neurobiology ; Biomedical Systems Technology ; Medical Physics, Biomedical Technology
• Term: from 2018 to 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 397686322

Magnetoencephalography (MEG) and Electroencephalography (EEG) enable researchers to investigate fast spatial and temporal changes of electrophysiological activity in the human brain. In parallel, with advances in off-line MEG/EEG analysis there is a growing interest in online data processing. Online processing paves the way for a faster and intuitive insight on instantaneous brain functions and at the same time creates the foundation for a wide range of neurofeedback scenarios. During a prior DFG funded project we established and investigated methods for estimating cortical activity online. In the following, we present the renewal proposal as a joint effort with an Austrian partner group. Firstly, we aim to establish novel online connectivity estimation methods for analyzing brain network structures. With the novel online connectivity estimation, we aim to provide input for robust feature extraction in neurofeedback scenarios. Moreover, we aim to visualize the results in an online 3D display for a more imminent analysis. Secondly, we want to include brain state dependent cortical stimulation into our online processing pipeline. Little work on directly integrating cortical stimulation into a neurofeedback or Brain Computer Interface (BCI) scenario has been proposed so far. By including the new online methods into Transcranial Magnetic Stimulation (TMS) we want to prepare for upcoming EEG/TMS studies and the integration of TMS into neurofeedback scenarios.

• DFG Programme: Research Grants
• International Connection: Austria
• Partner Organisation: Fonds zur Förderung der wissenschaftlichen Forschung (FWF)
• Co-Investigator: Professor Dr.-Ing. Daniel Baumgarten