title: Temporal reliability of ultra-high field resting-state MRI for single-subject sensorimotor and language mapping.
abstract: Resting-state fMRI is a well-suited technique to map functional networks in the brain because unlike task-based approaches it requires little collaboration from subjects. This is especially relevant in clinical settings where a number of subjects cannot comply with task demands. Previous studies using conventional scanner fields have shown that resting-state fMRI is able to map functional networks in single subjects, albeit with moderate temporal reliability. Ultra-high resolution (7T) imaging provides higher signal-to-noise ratio and better spatial resolution and is thus well suited to assess the temporal reliability of mapping results, and to determine if resting-state fMRI can be applied in clinical decision making including preoperative planning. We used resting-state fMRI at ultra-high resolution to examine whether the sensorimotor and language networks are reliable over time - same session and one week after. Resting-state networks were identified for all subjects and sessions with good accuracy. Both networks were well delimited within classical regions of interest. Mapping was temporally reliable at short and medium time-scales as demonstrated by high values of overlap in the same session and one week after for both networks. Results were stable independently of data quality metrics and physiological variables. Taken together, these findings provide strong support for the suitability of ultra-high field resting-state fMRI mapping at the single-subject level.
authors.affiliation: Faculty of Medicine, University of Porto, Portugal; Centre for Psychology at University of Porto, Portugal.
authors.forename: Paulo
authors.initials: P
authors.lastname: Branco
authors.affiliation: Dept. of Experimental Biology, Faculty of Medicine, University of Porto, Portugal; Department of Imaging, Centro Hospitalar de Vila Nova de Gaia/Espinho, Vila Nova de Gaia, Portugal.
authors.forename: Daniela
authors.initials: D
authors.lastname: Seixas
authors.affiliation: Centre for Psychology at University of Porto, Portugal; Faculty of Psychology and Educational Sciences, University of Porto, Portugal. Electronic address: slcastro@fpce.up.pt.
authors.forename: São Luís
authors.initials: SL
authors.lastname: Castro
mesh_terms: D000328:Adult; D001931:Brain Mapping / Q000592:standards*; D005260:Female; D006801:Humans; D007802:Language; D008279:Magnetic Resonance Imaging / Q000592:standards*; D008297:Male; D009043:Motor Activity / Q000502:physiology*; D009415:Nerve Net / Q000000981:diagnostic imaging*; D010465:Perception / Q000502:physiology*; D015203:Reproducibility of Results; D013997:Time Factors; D055815:Young Adult
keywords: Independent component analysis; Language network; Reliability; Resting-state fMRI; Sensorimotor network; Ultra-high resolution