Slice Acceleration in the 3 Tesla Component of the Human Connectome Project

At the time HCP was initiated, a growing number of studies had revealed important insights through systematic studies of whole-brain connectivity (e.g. [1-6]) using resting-state functional magnetic resonance imaging (rfMRI) and diffusion imaging (dMRI). rfMRI uses correlations in the spontaneous temporal fluctuations in an fMRI time series to deduce ‘functional connectivity’ (e.g. [7-11]) and, dMRI provides the input for tractography algorithms used for the reconstruction of the complex axonal fiber architecture so as to infer ‘structural connectivity’ (e.g. reviews [12, 13]). Despite their promise, however, each of these MR methods faces serious technical limitations. These include a high incidence of false positives and false negatives [13, 14] that arise from the indirect nature of functional imaging signals [15], dependence on neurovascular coupling [16], the presence of confounding long-range correlations of vascular origin [17], and the complexity of water diffusion in the microenvironment of the brain (e.g. [18, 19]). Given these neurobiological and neurophysiological challenges, undertaking significant new methodological developments to overcome or ameliorate these limitations was considered imperative for the success of the HCP.