| Literature DB >> 26223259 |
Dardo Tomasi1, Ehsan Shokri-Kojori1, Nora D Volkow2.
Abstract
Brain regions with high connectivity have high metabolic cost and their disruption is associated with neuropsychiatric disorders. Prior neuroimaging studies have identified at the group-level local functional connectivity density ( L: FCD) hubs, network nodes with high degree of connectivity with neighboring regions, in occipito-parietal cortices. However, the individual patterns and the precision for the location of the hubs were limited by the restricted spatiotemporal resolution of the magnetic resonance imaging (MRI) measures collected at rest. In this work, we show that MRI datasets with higher spatiotemporal resolution (2-mm isotropic; 0.72 s), collected under the Human Connectome Project (HCP), provide a significantly higher precision for hub localization and for the first time reveal L: FCD patterns with gray matter (GM) specificity >96% and sensitivity >75%. High temporal resolution allowed effective 0.01-0.08 Hz band-pass filtering, significantly reducing spurious L: FCD effects in white matter. These high spatiotemporal resolution L: FCD measures had high reliability [intraclass correlation, ICC(3,1) > 0.6] but lower reproducibility (>67%) than the low spatiotemporal resolution equivalents. GM sensitivity and specificity benchmarks showed the robustness of L: FCD to changes in model parameter and preprocessing steps. Mapping individual's brain hubs with high sensitivity, specificity, and reproducibility supports the use of L: FCD as a biomarker for clinical applications in neuropsychiatric disorders. Published by Oxford University Press 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.Entities:
Keywords: FCDM; aging; global signal regression; motion; multiband; physiologic noise; resting state
Mesh:
Year: 2015 PMID: 26223259 PMCID: PMC4898675 DOI: 10.1093/cercor/bhv171
Source DB: PubMed Journal: Cereb Cortex ISSN: 1047-3211 Impact factor: 5.357