Trimodal imaging of human brain networks using simultaneous PET/MR/EEG

• Applicants: Professor Dr. Niels Focke; Professor Dr. Christian Jean La Fougère; Professor Dr. Bernd Pichler
• Subject Area: Medical Physics, Biomedical Technology
• Term: from 2018 to 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 403462768

Over the last two decades data-driven processing methods have identified spatially and temporarily distinct functional networks of the human brain that are ‘active’ even at the absence of a specific task in the so-called ‘resting-state’. Many of these resting-state networks (RSN) are remarkably similar between subjects and alterations of RSNs have been associated with brain diseases including epilepsy and dementia. RSN could even be identified in non-human species enabling translational approaches and answering fundamental questions of brain functions. However, the physiological basis of these RSN is only partially understood. The vast majority of RSN studies is based on functional MRI using the blood oxygen level dependent (BOLD) contrast, i.e. minimal MRI signal fluctuations induced by hemodynamic changes. Thus, this approach can only indirectly infer neuronal activity and has limited temporal resolution. Therefore, identification of RSNs from other modalities is considered to be an important step. EEG and MEG probe a neuronal signal, but are usually limited to surface recordings. Still, using adequate processing methods, RSN could be identified that have a similar topology as the networks identified in fMRI. [18F]fluorodeoxyglucose (FDG)-PET imaging can assess regional cerebral glucose metabolism (rCGM) in-vivo and serves as a surrogate for neuronal energy consumption at acceptable spatial but limited temporal resolution, therefore, semi-quantitative static [18F]FDG-PET is generally used for brain imaging. Within this proposal we will acquire fully-simultaneous, dynamic [18F]FDG-PET/fMRI/EEG data in 20 healthy controls in the resting-state and, in addition, using a simple motor-task. We will extract RSN using data-driven methods from all three modalities and specifically analyze the spatial and temporal relation of RSN between the modalities and timescales. In a recent study in rodents we could already show that [18F]FDG-PET and fMRI derived RSNs are not identical and that a better understanding of the physiology of these processes is paramount. We will now translate the methods and findings to the human brain and add another temporal and physiological dimension by acquiring a more direct neuronal signal with parallel EEG. Using intramural funding, we have already established the necessary processing pipeline and solved the technical prerequisite for this project. In addition to scans in healthy volunteers, we will acquire a group of epilepsy patients undergoing the same imaging paradigm to validate RSN alterations described in this disease condition and better define the basis of the commonly observed decrease of rCGM in [18F]FDG-PET related to the epileptogenic focus. The results of this proposal will be of high importance for the whole brain connectivity community and will provide further, fundamental insights into brain functions and the interpretation of brain networks in the distinct imaging modalities.

• DFG Programme: Research Grants