title: Topographical Information-Based High-Order Functional Connectivity and Its Application in Abnormality Detection for Mild Cognitive Impairment.
abstract: Temporal synchronization-based functional connectivity (FC) has long been used by the neuroscience community. However, topographical FC information may provide additional information to characterize the advanced relationship between two brain regions. Accordingly, we proposed a novel method, namely high-order functional connectivity (HOFC), to capture this second-level relationship using inter-regional resemblance of the FC topographical profiles. Specifically, HOFC first calculates an FC profile for each brain region, notably between the given brain region and other brain regions. Based on these FC profiles, a second layer of correlations is computed between all pairs of brain regions (i.e., correlation's correlation). On this basis, we generated an HOFC network, where "high-order" network properties were computed. We found that HOFC was discordant with the traditional FC in several links, indicating additional information being revealed by the new metrics. We applied HOFC to identify biomarkers for early detection of Alzheimer's disease by comparing 77 mild cognitive impairment patients with 89 healthy individuals (control group). Sensitivity in detection of group difference was consistently improved by ∼25% using HOFC compared to using FC. An HOFC network analysis also provided complementary information to an FC network analysis. For example, HOFC between olfactory and orbitofrontal cortices was found significantly reduced in patients, besides extensive alterations in HOFC network properties. In conclusion, our results showed promise in using HOFC to comprehensively map the human brain connectome.
authors: Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
authors: Han
authors: H
authors: Zhang
authors: Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
authors: Xiaobo
authors: X
authors: Chen
authors: Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
authors: Feng
authors: F
authors: Shi
authors: Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
authors: Gang
authors: G
authors: Li
authors: Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
authors: Minjeong
authors: M
authors: Kim
authors: Department of Psychiatry, Faculty of Medicine of the University of Geneva, Geneva, Switzerland.
authors: Panteleimon
authors: P
authors: Giannakopoulos
authors: Affidea Centre de Diagnostique Radiologique de Carouge CDRC, Switzerland.|Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden.|Department of Neuroradiology, University Hospital Freiburg, Germany.|Faculty of Medicine of the University of Geneva, Switzerland.
authors: Sven
authors: S
authors: Haller
authors: Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.|Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea.
authors: Dinggang
authors: D
authors: Shen
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000000981:diagnostic imaging / Q000523:psychology; D001921:Brain / Q000000981:diagnostic imaging*; D001931:Brain Mapping / Q000379:methods*; D060825:Cognitive Dysfunction / Q000000981:diagnostic imaging* / Q000523:psychology; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009415:Nerve Net / Q000000981:diagnostic imaging*
keywords: Alzheimer’s disease; biomarker; early detection; functional connectivity; functional magnetic resonance imaging (fMRI); high-order connectivity; mild cognitive impairment; resting state fMRI