Abstract
Functional MRI (fMRI) experiments rely on precise characterization of the blood oxygen level dependent (BOLD) signal. As the spatial resolution of fMRI reaches the sub-millimeter range, the need for quantitative modelling of spatiotemporal properties of this hemodynamic signal has become pressing. Here, we find that a detailed physiologically-based model of spatiotemporal BOLD responses predicts traveling waves with velocities and spatial ranges in empirically observable ranges. Two measurable parameters, related to physiology, characterize these waves: wave velocity and damping rate. To test these predictions, high-resolution fMRI data are acquired from subjects viewing discrete visual stimuli. Predictions and experiment show strong agreement, in particular confirming BOLD waves propagating for at least 5–10 mm across the cortical surface at speeds of 2–12 mm s-1. These observations enable fundamentally new approaches to fMRI analysis, crucial for fMRI data acquired at high spatial resolution.
Highlights
Functional magnetic resonance imaging experiments have substantially advanced our understanding of the structure and function of the human brain [1]
Hemodynamic responses to neuronal activity are observed experimentally in Functional magnetic resonance imaging (fMRI) data via the blood oxygenation dependent (BOLD) signal, which provides a noninvasive measure of neuronal activity
Functional magnetic resonance imaging experiments have advanced our understanding of the structure and function of the human brain
Summary
Functional magnetic resonance imaging (fMRI) experiments have substantially advanced our understanding of the structure and function of the human brain [1]. Understanding the mechanisms that drive this BOLD response, combined with detailed characterization of its spatial and temporal properties, is fundamental for accurately inferring the underlying neuronal activity [2]. Such an understanding has clear benefits for many areas of neuroscience, those concerned with detailed functional mapping of the cortex [3], those using multivariate classifiers that implicitly incorporate the spatial distribution of BOLD [4,5], and those that focus on understanding and modeling spatiotemporal cortical activity [6,7,8,9,10]. The spatial response of BOLD has been characterized experimentally via hemodynamic point spread functions [15,16,17,18], it is commonly agreed that the spatial and spatiotemporal properties are relatively poorly understood [19,20]
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