VirtualBrainCloud utilizes computational modeling developed in The Virtual Brain research project for simulating brain dynamics stemming from individual subjects’ or patients’ brain structure. Now, the researchers aim to turn this platform into a cloud-based software solution combining detailed information on the function and structure of individual’s brain networks. In addition, computational modelling connects clinical, cognitive and genetic data to individual information on the structure and function of the brain produced by methods of neuroscience and systems biology, and through which brain function and its deviations can be simulated in great detail.
“Our goal is a computational model that simulates brain function and dynamics very accurately, which will help improve the diagnostics of neurodegenerative diseases, Alzheimer’s in particular, and to plan increasingly personalised therapies for patients,” Satu Palva explains.
The progress of Alzheimer’s disease varies greatly between patients, making individualised treatment highly desirable. Currently, however, the tools required to reliably predict the course of the disease are lacking.
Support from state-of-the-art brain measurement and imaging techniques
Satu and Matias Palva’s research groups specialise in electrophysiological brain function measurements and the mapping of functional connections in the brain by employing electroencephalography (EEG) and magnetoencephalography (MEG) techniques.
“In this project, our mission is to chart the signalling networks between different brain regions, as well as to measure and determine their function. These are systemic mechanisms of brain functioning and dynamics – important to validating brain modelling, while their deviations can also directly serve as biomarkers in the early diagnosis of Alzheimer’s disease,” says Matias Palva.
To survey the functional networks of the brain, the researchers are acquiring data through MEG imaging and stereotactic EEG measurements. Data is collected from both healthy individuals and patients who suffer from Alzheimer’s disease and epilepsy. This work is being conducted in collaboration with researchers from Complutense University of Madrid and the University of Genoa.
In addition to the electrophysiological insight gained through the MEG and EEG methods, the VirtualBrainCloud model will employ information on neural networks produced by functional magnetic resonance imaging, as well as cellular and molecular information collected by utilising methods of systems biology.
“Should this project achieve its goals, this consortium will be able to establish entirely new possibilities in the diagnosis and treatment of brain diseases – genuine personalised and targeted medicine,” Satu Palva says.
VirtualBrainCloud is a four-year project with altogether 17 European universities and research institutes participating. The project is coordinated by Charité – Universitätsmedizin Berlin.