title: Functional Mechanisms of Recovery after Chronic Stroke: Modeling with the Virtual Brain.
abstract: We have seen important strides in our understanding of mechanisms underlying stroke recovery, yet effective translational links between basic and applied sciences, as well as from big data to individualized therapies, are needed to truly develop a cure for stroke. We present such an approach using The Virtual Brain (TVB), a neuroinformatics platform that uses empirical neuroimaging data to create dynamic models of an individual's human brain; specifically, we simulate fMRI signals by modeling parameters associated with brain dynamics after stroke. In 20 individuals with stroke and 11 controls, we obtained rest fMRI, T1w, and diffusion tensor imaging (DTI) data. Motor performance was assessed pre-therapy, post-therapy, and 6-12 months post-therapy. Based on individual structural connectomes derived from DTI, the following steps were performed in the TVB platform: (1) optimization of local and global parameters (conduction velocity, global coupling); (2) simulation of BOLD signal using optimized parameter values; (3) validation of simulated time series by comparing frequency, amplitude, and phase of the simulated signal with empirical time series; and (4) multivariate linear regression of model parameters with clinical phenotype. Compared with controls, individuals with stroke demonstrated a consistent reduction in conduction velocity, increased local dynamics, and reduced local inhibitory coupling. A negative relationship between local excitation and motor recovery, and a positive correlation between local dynamics and motor recovery were seen. TVB reveals a disrupted post-stroke system favoring excitation-over-inhibition and local-over-global dynamics, consistent with existing mammal literature on stroke mechanisms. Our results point to the potential of TVB to determine individualized biomarkers of stroke recovery.
authors.affiliation: Department of Anatomy and Neurobiology, UC Irvine School of Medicine , Irvine, California 92697.
authors.forename: Maria Inez
authors.initials: MI
authors.lastname: Falcon
authors.affiliation: Department of Anatomy and Neurobiology, UC Irvine School of Medicine , Irvine, California 92697.
authors.forename: Jeffrey D
authors.initials: JD
authors.lastname: Riley
authors.affiliation: Institut de Neurosciences des Systèmes, Aix-Marseille Université, Faculté de Médecine, Marseille F-13000, France; Inserm UMR1106, Marseille F-13000, France.
authors.forename: Viktor
authors.initials: V
authors.lastname: Jirsa
authors.affiliation: Rotman Research Institute , Baycrest Health Sciences, M6A 2E1 University of Toronto , Toronto, Canada.
authors.forename: Anthony R
authors.initials: AR
authors.lastname: McIntosh
authors.affiliation: Department of Anatomy and Neurobiology, UC Irvine School of Medicine , Irvine, California 92697.
authors.forename: E Elinor
authors.initials: EE
authors.lastname: Chen
authors.affiliation: Department of Anatomy and Neurobiology, UC Irvine School of Medicine, Irvine, California 92697; Department of Neurology, UC Irvine School of Medicine, Irvine, California 92697.
authors.forename: Ana
authors.initials: A
authors.lastname: Solodkin
mesh_terms: D000328:Adult; D000368:Aged; D001921:Brain / Q000000981:diagnostic imaging / Q000502:physiology*; D016022:Case-Control Studies; D002908:Chronic Disease; D063132:Connectome; D056324:Diffusion Tensor Imaging; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D008959:Models, Neurological; D011597:Psychomotor Performance / Q000502:physiology; D020127:Recovery of Function / Q000502:physiology*; D013269:Stochastic Processes; D020521:Stroke / Q000000981:diagnostic imaging / Q000473:pathology* / Q000503:physiopathology; D055815:Young Adult
keywords: brain dynamics; brain networks; computational biophysical modeling; connectome; imaging; stroke