Connectome based modelling to reveal multi-scale mechanisms in stroke

• Applicants: Professor Dr. Christian Gerloff; Professorin Dr. Petra Ritter
• Subject Area: Cognitive, Systems and Behavioural Neurobiology
• Term: from 2017 to 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 347469655

• Final Report Year: 2022

Final Report Abstract

Stroke is a devastating medical condition with high socioeconomic burden. Current treatment and rehabilitation strategies have improved but do not account sufficiently for individual disease patterns. This may partly explain that current treatment results are not satisfactory. Advanced neuroimaging provides the necessary new technology to create personalized disease assessment. In this project, we aimed at applying and refining an open-source analysis and brain network-modelling framework that creates whole-brain simulations from multimodal brain imaging data for individualized clinical use in stroke patients. The technological resource, called The Virtual Brain (TVB), has been developed on a community standard platform, allowing usability and flexibility for implementation across multiple sites. In the current project, we used an existing large longitudinal cohort of stroke patients to extract the information required for personalized brain network modelling. Our specific achievements were: 1) The development of an open-source processing pipeline for multimodal imaging data of stroke brains and virtualization of the brains of individual patients with stroke at the acute and chronic stages. 2) Advancement of the existing modelling engine towards a multi-scale simulation framework. 3) Provision of proof of principle that brain network modelling reveals candidate disease biomarkers improving classification accuracy over imaging derived features. 4) Development of an in-silico multi-scale brain stimulation framework and its validation. 5) Provision of all developed tools for re-use in the EBRAINS research infrastructure Cloud. The use of TVB in the setting of stroke shall ultimately result in a clinically relevant application enabling to simulate individual patient brains. This will allow for selection of individually tailored therapies and will better predict trajectories of recovery. We have helped approaching this goal by 1) developing an open-source pipeline to generate connectome-based stroke - brain network models, 2) developing a novel multi-scale simulation framework that allows identifying generic principles and mechanisms below the spatial and temporal resolution of non-invasive imaging, i.e., micro-scale processes which can be inferred from the TVB models, and 3) implementing virtual brain stimulation for multi-scale models to enable patient-specific in silico optimization of stimulation protocols.

Publications

• Inferring multi-scale neural mechanisms with brain network modelling. eLife, 7(c(2018, 1, 8)).
  Schirner, Michael; McIntosh, Anthony Randal; Jirsa, Viktor; Deco, Gustavo & Ritter, Petra
  
• Are unimanual movements bilateral?. Neuroscience & Biobehavioral Reviews, 113(c(2020, 6)), 39-50.
  Chettouf, Sabrina; Rueda-Delgado, Laura M.; de Vries, Ralph; Ritter, Petra & Daffertshofer, Andreas
  
• Dynamic Functional Connectivity between order and randomness and its evolution across the human adult lifespan. NeuroImage, 222(c(2020, 11)), 117156.
  Battaglia, Demian; Boudou, Thomas; Hansen, Enrique C.A.; Lombardo, Diego; Chettouf, Sabrina; Daffertshofer, Andreas; McIntosh, Anthony R.; Zimmermann, Joelle; Ritter, Petra & Jirsa, Viktor
  
• Movement disorders after hypoxic brain injury following cardiac arrest in adults. European Journal of Neurology, 27(10), 1937-1947.
  Scheibe, F.; Neumann, W. J.; Lange, C.; Scheel, M.; Furth, C.; Köhnlein, M.; Mergenthaler, P.; Schultze‐Amberger, J.; Triebkorn, P.; Ritter, P.; Kühn, A. A. & Meisel, A.
  
• The Virtual Brain and focal lesions - advancing processing for longitudinal multi-modal stroke data. OHBM poster
  Bey; Triebkorn; Feldheim; Gerloff & Ritter
  
• Corticospinal Tract Microstructure Correlates With Beta Oscillatory Activity in the Primary Motor Cortex After Stroke. Stroke, 52(12), 3839-3847.
  Schulz, Robert; Bönstrup, Marlene; Guder, Stephanie; Liu, Jingchun; Frey, Benedikt; Quandt, Fanny; Krawinkel, Lutz A.; Cheng, Bastian; Thomalla, Götz & Gerloff, Christian
  
• Brain network topology early after stroke relates to recovery. Brain Communications, 4(2).
  Nemati, Paul R.; Backhaus, Winifried; Feldheim, Jan; Bönstrup, Marlene; Cheng, Bastian; Thomalla, Götz; Gerloff, Christian & Schulz, Robert
  
• Brain simulation as a cloud service: The Virtual Brain on EBRAINS. NeuroImage, 251(c(2022, 5)), 118973.
  Schirner, Michael; Domide, Lia; Perdikis, Dionysios; Triebkorn, Paul; Stefanovski, Leon; Pai, Roopa; Prodan, Paula; Valean, Bogdan; Palmer, Jessica; Langford, Chloê; Blickensdörfer, André; van der Vlag, Michiel; Diaz-Pier, Sandra; Peyser, Alexander; Klijn, Wouter; Pleiter, Dirk; Nahm, Anne; Schmid, Oliver; Woodman, Marmaduke; ... & Ritter, Petra
  
• Brain simulation augments machine‐learning–based classification of dementia. Alzheimer's & Dementia: Translational Research & Clinical Interventions, 8(1).
  Triebkorn, Paul; Stefanovski, Leon; Dhindsa, Kiret; Diaz‐Cortes, Margarita‐Arimatea; Bey, Patrik; Bülau, Konstantin; Pai, Roopa; Spiegler, Andreas; Solodkin, Ana; Jirsa, Viktor; McIntosh, Anthony Randal & Ritter, Petra
  
• Cost function masking artificially inflates group level differences in processing of magnetic resonance imaging data for pathological patient populations. FENS abstract
  Bey; Dhindsa & Ritter
  
• Virtual deep brain stimulation: Multiscale co-simulation of a spiking basal ganglia model and a whole-brain mean-field model with The Virtual Brain. Experimental Neurology, 354(c(2022, 8)), 114111.
  Meier, Jil M.; Perdikis, Dionysios; Blickensdörfer, André; Stefanovski, Leon; Liu, Qin; Maith, Oliver; Dinkelbach, Helge Ü.; Baladron, Javier; Hamker, Fred H. & Ritter, Petra