title: Total activation: fMRI deconvolution through spatio-temporal regularization.
abstract: Confirmatory approaches to fMRI data analysis look for evidence for the presence of pre-defined regressors modeling contributions to the voxel time series, including the BOLD response following neuronal activation. As more complicated questions arise about brain function, such as spontaneous and resting-state activity, new methodologies are required. We propose total activation (TA) as a novel fMRI data analysis method to explore the underlying activity-inducing signal of the BOLD signal without any timing information that is based on sparse spatio-temporal priors and characterization of the hemodynamic system. Within a variational framework, we formulate a convex cost function-including spatial and temporal regularization terms-that is solved by fast iterative shrinkage algorithms. The temporal regularization expresses that the activity-inducing signal is block-type without restrictions on the timing nor duration. The spatial regularization favors coherent activation patterns in anatomically-defined brain regions. TA is evaluated using a software phantom and an event-related fMRI experiment with prolonged resting state periods disturbed by visual stimuli. The results illustrate that both block-type and spike-type activities can be recovered successfully without prior knowledge of the experimental paradigm. Further processing using hierarchical clustering shows that the activity-inducing signals revealed by TA contain information about meaningful task-related and resting-state networks, demonstrating good abilities for the study of non-stationary dynamics of brain activity.
authors: Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland. isik.karahanoglu@epfl.ch
authors: Fikret Işık
authors: FI
authors: Karahanoğlu
authors: César
authors: C
authors: Caballero-Gaudes
authors: François
authors: F
authors: Lazeyras
authors: Dimitri
authors: D
authors: Van de Ville
mesh_terms: D000465:Algorithms; D002560:Cerebrovascular Circulation; D016000:Cluster Analysis; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D006439:Hemodynamics / Q000502:physiology; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015233:Models, Statistical; D010100:Oxygen / Q000097:blood; D010775:Photic Stimulation
chemical_list: D010100:Oxygen