Department of Neuroscience, University of Minnesota, Minneapolis, United States; Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, United States
Department of Psychiatry & Behavioral Sciences , University of Minnesota, Minneapolis, United States; Medical Discovery Team on Addiction, University of Minnesota, Minneapolis, United States
Kamil Ugurbil
Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, United States; Department of Radiology, University of Minnesota, Minneapolis, United States
Sarah R Heilbronner
Department of Neuroscience, University of Minnesota, Minneapolis, United States; Medical Discovery Team on Addiction, University of Minnesota, Minneapolis, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, United States
Jan Zimmermann
Department of Neuroscience, University of Minnesota, Minneapolis, United States; Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, United States; Medical Discovery Team on Addiction, University of Minnesota, Minneapolis, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, United States; Department of Biomedical Engineering, University of Minnesota, Minneapolis, United States
Hierarchical temporal dynamics are a fundamental computational property of the brain; however, there are no whole brain, noninvasive investigations into timescales of neural processing in animal models. To that end, we used the spatial resolution and sensitivity of ultrahigh field functional magnetic resonance imaging (fMRI) performed at 10.5 T to probe timescales across the whole macaque brain. We uncovered within-species consistency between timescales estimated from fMRI and electrophysiology. Crucially, we extended existing electrophysiological hierarchies to whole-brain topographies. Our results validate the complementary use of hemodynamic and electrophysiological intrinsic timescales, establishing a basis for future translational work. Further, with these results in hand, we were able to show that one facet of the high-dimensional functional connectivity (FC) topography of any region in the brain is closely related to hierarchical temporal dynamics. We demonstrated that intrinsic timescales are organized along spatial gradients that closely match FC gradient topographies across the whole brain. We conclude that intrinsic timescales are a unifying organizational principle of neural processing across the whole brain.