TY - JOUR
T1 - Estimation of brain functional connectivity from hypercapnia BOLD MRI data
T2 - Validation in a lifespan cohort of 170 subjects
AU - Hou, Xirui
AU - Liu, Peiying
AU - Gu, Hong
AU - Chan, Micaela
AU - Li, Yang
AU - Peng, Shin Lei
AU - Wig, Gagan
AU - Yang, Yihong
AU - Park, Denise
AU - Lu, Hanzhang
N1 - Funding Information:
This work was supported by the National Institutes of Health (grant numbers R37 AG006265 , R01 AG042753 , R01 MH084021 , R01 NS106711 , R01 NS106702 , NIH R21 NS095342 , P41 EB015909 , and R00 AG036848 ). H.G. and Y.Y. are supported by the Intramural Research Program of the National Institute on Drug Abuse, the National Institutes of Health .
Publisher Copyright:
© 2018 Elsevier Inc.
PY - 2019/2/1
Y1 - 2019/2/1
N2 - Functional connectivity MRI, based on Blood-Oxygenation-Level-Dependent (BOLD) signals, is typically performed while the subject is at rest. On the other hand, BOLD is also widely used in physiological imaging such as cerebrovascular reactivity (CVR) mapping using hypercapnia (HC) as a modulator. We therefore hypothesize that hypercapnia BOLD data can be used to extract FC metrics after factoring out the effects of the physiological modulation, which will allow simultaneous assessment of neural and vascular function and may be particularly important in populations such as aging and cerebrovascular diseases. The present work aims to systematically examine the feasibility of hypercapnia BOLD-based FC mapping using three commonly applied analysis methods, specifically dual-regression Independent Component Analysis (ICA), region-based FC matrix analysis, and graph-theory based network analysis, in a large cohort of 170 healthy subjects ranging from 20 to 88 years old. To validate the hypercapnia BOLD results, we also compared these FC metrics with those obtained from conventional resting-state data. ICA analysis of the hypercapnia BOLD data revealed FC maps that strongly resembled those reported in the literature. FC matrix using region-based analysis showed a correlation of 0.97 on the group-level and 0.54 ± 0.10 on the individual-level, when comparing between hypercapnia and resting-state results. Although the correspondence on the individual-level was moderate, this was primarily attributed to variations intrinsic to FC mapping, because a corresponding resting-vs-resting comparison in a sub-cohort (N = 39) revealed a similar correlation of 0.57 ± 0.09. Graph-theory computations were also feasible in hypercapnia BOLD data and indices of global efficiency, clustering coefficient, modularity, and segregation were successfully derived. Hypercapnia FC results revealed age-dependent differences in which within-network connections generally exhibited an age-dependent decrease while between-network connections showed an age-dependent increase.
AB - Functional connectivity MRI, based on Blood-Oxygenation-Level-Dependent (BOLD) signals, is typically performed while the subject is at rest. On the other hand, BOLD is also widely used in physiological imaging such as cerebrovascular reactivity (CVR) mapping using hypercapnia (HC) as a modulator. We therefore hypothesize that hypercapnia BOLD data can be used to extract FC metrics after factoring out the effects of the physiological modulation, which will allow simultaneous assessment of neural and vascular function and may be particularly important in populations such as aging and cerebrovascular diseases. The present work aims to systematically examine the feasibility of hypercapnia BOLD-based FC mapping using three commonly applied analysis methods, specifically dual-regression Independent Component Analysis (ICA), region-based FC matrix analysis, and graph-theory based network analysis, in a large cohort of 170 healthy subjects ranging from 20 to 88 years old. To validate the hypercapnia BOLD results, we also compared these FC metrics with those obtained from conventional resting-state data. ICA analysis of the hypercapnia BOLD data revealed FC maps that strongly resembled those reported in the literature. FC matrix using region-based analysis showed a correlation of 0.97 on the group-level and 0.54 ± 0.10 on the individual-level, when comparing between hypercapnia and resting-state results. Although the correspondence on the individual-level was moderate, this was primarily attributed to variations intrinsic to FC mapping, because a corresponding resting-vs-resting comparison in a sub-cohort (N = 39) revealed a similar correlation of 0.57 ± 0.09. Graph-theory computations were also feasible in hypercapnia BOLD data and indices of global efficiency, clustering coefficient, modularity, and segregation were successfully derived. Hypercapnia FC results revealed age-dependent differences in which within-network connections generally exhibited an age-dependent decrease while between-network connections showed an age-dependent increase.
KW - Aging
KW - CO inhalation
KW - Cerebrovascular reactivity
KW - Functional connectivity
KW - Hypercapnia
KW - Resting-state functional MRI
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UR - http://www.scopus.com/inward/citedby.url?scp=85056860932&partnerID=8YFLogxK
U2 - 10.1016/j.neuroimage.2018.11.028
DO - 10.1016/j.neuroimage.2018.11.028
M3 - Article
C2 - 30463025
AN - SCOPUS:85056860932
SN - 1053-8119
VL - 186
SP - 455
EP - 463
JO - NeuroImage
JF - NeuroImage
ER -