Over 100 years ago, William James (1890) first suggested that “blood very likely may rush to each region of the cortex according as it is most active.” About 80 years ago, John Fulton (1928) presented the first evidence of an association of blood flow and cognition, describing the case of a patient with an arteriovenous malformation (AVM) in the occipital cortex who underwent an unsuccessful surgical removal of the AVM. The bruit of blood flow could be heard through the bony defect resulting from the surgery and was found to be correlated with the patient’s mental activity. These suggestions and empirical observations remained intriguing but inconclusive until the introduction of modern neuroimaging tools for measuring regional cerebral blood flow (rCBF), such as Single-Photon Emission Computed Tomography (SPECT), Positron Emission Tomography (PET), and more recently Magnetic Resonance Imaging (MRI). Compared to SPECT and PET, which rely on radioactive tracers, MRI is noninvasive, more economical and widely available. During the past two decades, functional MRI (fMRI) based on blood-oxygen level dependent (BOLD) contrast has revolutionized the field of functional neuroimaging.
Arterial spin labeling (ASL) perfusion MRI was first introduced by Detre et al. (1992), one year after the seminal BOLD fMRI papers by Kwong et al. (1991) and Ogawa et al. (1991) published in PNAS. Since their advent, the development of ASL and BOLD fMRI for neuroscientific applications has been analogous to the story of the tortoise and the hare. BOLD is stronger (higher sensitivity), faster (higher temporal resolution) yet unstable in certain aspects (baseline drift effects, field inhomogeneity effects). ASL is slower but more persistent and reproducible (with absolute quantification and reduced sensitivity to drift and field inhomogeneity effects). The past two decades have seen a steady increase of publications using ASL to study brain function, partly owing to continuous innovations of MR technologies, which have improved the sensitivity and reliability of ASL. One of the key features of ASL is its capability for absolute rCBF quantification, which greatly facilitates comparisons of imaging results across age groups and between patient and control groups. In this special issue, Kilroy et al. and Hu et al. apply ASL in typically developing and aging populations respectively. They also compare CBF results with analysis of regional cortical volume in order to tease apart the unique changes in brain function and structure. Because of absolute quantification, ASL based fMRI results in clinical populations can be interpreted more accurately than those of BOLD fMRI. As proof of this, Zou et al. apply ASL to systematically study the load effect in N-back working memory tasks. Their results demonstrate both linear and non-linear relationships (quadratic and cubic) between CBF changes and working memory load, laying the foundation for future applications in neuropsychiatric disorders. Finally, resting rCBF may serve as a surrogate of resting brain function based on a phenomenon termed neurovascular coupling. In this special issue, Kilroy et al. and Gillihan et al. investigate the correlation between resting CBF and IQ in typically developing children, and the correlation between resting CBF and weather-related mood variations in healthy adults, respectively.
Although the four papers included in this volume do not cover the entire spectrum of topics related to ASL, we hope they will showcase the potential and promise that ASL brings to the field of cognitive neuroscience. As resting state BOLD fMRI and associated connectivity analysis have become a new standard in the field, one underexploited feature of ASL is its temporal dynamics. We do hope future studies will address this important issue and that ASL may eventually surpass BOLD fMRI for neuroscientific applications, in keeping with the tale of the tortoise and the hare.