title: Exploring functional connectivity networks with multichannel brain array coils.
abstract: The use of multichannel array head coils in functional and structural magnetic resonance imaging (MRI) provides increased signal-to-noise ratio (SNR), higher sensitivity, and parallel imaging capabilities. However, their benefits remain to be systematically explored in the context of resting-state functional connectivity MRI (fcMRI). In this study, we compare signal detectability within and between commercially available multichannel brain coils, a 32-Channel (32Ch), and a 12-Channel (12Ch) at 3T, in a high-resolution regime to accurately map resting-state networks. We investigate whether the 32Ch coil can extract and map fcMRI more efficiently and robustly than the 12Ch coil using seed-based and graph-theory-based analyses. Our findings demonstrate that although the 12Ch coil can be used to reveal resting-state connectivity maps, the 32Ch coil provides increased detailed functional connectivity maps (using seed-based analysis) as well as increased global and local efficiency, and cost (using graph-theory-based analysis), in a number of widely reported resting-state networks. The exploration of subcortical networks, which are scarcely reported due to limitations in spatial-resolution and coil sensitivity, also proved beneficial with the 32Ch coil. Further, comparisons regarding the data acquisition time required to successfully map these networks indicated that scan time can be significantly reduced by 50% when a coil with increased number of channels (i.e., 32Ch) is used. Switching to multichannel arrays in resting-state fcMRI could, therefore, provide both detailed functional connectivity maps and acquisition time reductions, which could further benefit imaging special subject populations, such as patients or pediatrics who have less tolerance in lengthy imaging sessions.
authors.affiliation: Athinoula A. Martinos Imaging Center at McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts MA 02139, USA. sheeba@mit.edu
authors.forename: Sheeba Arnold
authors.initials: SA
authors.lastname: Anteraper
authors.forename: Susan
authors.initials: S
authors.lastname: Whitfield-Gabrieli
authors.forename: Boris
authors.initials: B
authors.lastname: Keil
authors.forename: Steven
authors.initials: S
authors.lastname: Shannon
authors.forename: John D
authors.initials: JD
authors.lastname: Gabrieli
authors.forename: Christina
authors.initials: C
authors.lastname: Triantafyllou
mesh_terms: D000328:Adult; D001921:Brain / Q000098:blood supply / Q000502:physiology*; D001931:Brain Mapping; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D008959:Models, Neurological; D009434:Neural Pathways / Q000098:blood supply / Q000502:physiology; D010100:Oxygen / Q000097:blood; D012146:Rest / Q000502:physiology; D059629:Signal-To-Noise Ratio; D055815:Young Adult
chemical_list: D010100:Oxygen