LOCAL SPATIAL FLOWS AND PROPAGATIVE ATTRACTORS: A NOVEL 'FLOWNECTOME' FRAMEWORK FOR ANALYZING BOLD FMRI DYNAMICS

Although the analysis of temporal signal fluctuations and co-fluctuations has long been a fixture of blood oxygenation-level dependent (BOLD) functional magnetic resonance imaging (fMRI) research, the role of local directional flows in both signal propagation and healthy functional integration remains almost entirely neglected. We are introducing an extensible framework, based on localized directional signal flows, to capture and analyze spatial signal propagation and propagative attractor patterns in BOLD fMRI. Novel features derived from this approach are validated in a large resting-state fMRI schizophrenia study where they reveal significant relationships between spatially directional flows, propagative attractor patterns and subject diagnostic status. Plausibly, we find that spatial signal inflow to functional regions tends to positively correlate with net gain/loss in the region's temporal contribution BOLD signal reconstruction. We also find that group ICA (pdGICA) performed on time-varying propagative density maps, which are whole-brain maps of spatial signal inflow to each voxel on successive 30 second windows (ie. propagative attractor maps), produce components that tend to concentrate predominantly in at most six or seven functional regions, in some cases focusing on as few as two. The relationship between the propagative attractor group ICA component maps and functional regions is not sharp, but is focused enough to render the pdGICA component maps functionally tractable. Temporal correlations between pdGICA component timeseries and net gain/loss functional region timeseries on corresponding windows echoes those traditionally observed between functional region timeseries when aligning each pdGICA component with the functional region with which it has greatest spatial overlap. Schizophrenia strongly disrupts the average correlative relationship between pdGICA components and certain functional regions, some of which tend to be implicated in schizophrenia e.g. the thalamus and the anterior cingulate cortex. Schizophrenia also strongly and pervasively linked to the importance of specific pdGICA components in reconstructing subjects' observed time-varying propagative density maps. Over half of the 35 pdGICA component make significantly different average contributions to patient propagative density maps than to those of controls, with the functional footprints of impacted pdGICA components spreading over diverse functional domains. Finally, the magnitudes of local directional flows that carry propagation have spatially structured averages and structured, pervasive schizophrenia effects. The framework introduced here follows a new and fundamentally different data-driven approach to the BOLD fMRI signal. We believe that the empirical measurement of local directional flows and wider spatial signal propagation opens a plethora of new avenues through which to investigate healthy and disordered brain function using BOLD fMRI.