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Covariance-based vs. correlation-based functional connectivity dissociates healthy aging from Alzheimer disease

Prior studies of aging and Alzheimer disease have evaluated resting state functional connectivity (FC) using either seed-based correlation (SBC) or independent component analysis (ICA), with a focus on particular functional systems. SBC and ICA both are insensitive to differences in signal amplitude...

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Autores principales: Strain, Jeremy F., Brier, Matthew R., Tanenbaum, Aaron, Gordon, Brian A., McCarthy, John E., Dincer, Aylin, Marcus, Daniel S., Chhatwal, Jasmeer P., Graff-Radford, Neill R., Day, Gregory S., la Fougère, Christian, Perrin, Richard J., Salloway, Stephen, Schofield, Peter R., Yakushev, Igor, Ikeuchi, Takeshi, Vöglein, Jonathan, Morris, John C., Benzinger, Tammie L.S., Bateman, Randall J., Ances, Beau M., Snyder, Abraham Z.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9750733/
https://www.ncbi.nlm.nih.gov/pubmed/35914670
http://dx.doi.org/10.1016/j.neuroimage.2022.119511
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author Strain, Jeremy F.
Brier, Matthew R.
Tanenbaum, Aaron
Gordon, Brian A.
McCarthy, John E.
Dincer, Aylin
Marcus, Daniel S.
Chhatwal, Jasmeer P.
Graff-Radford, Neill R.
Day, Gregory S.
la Fougère, Christian
Perrin, Richard J.
Salloway, Stephen
Schofield, Peter R.
Yakushev, Igor
Ikeuchi, Takeshi
Vöglein, Jonathan
Morris, John C.
Benzinger, Tammie L.S.
Bateman, Randall J.
Ances, Beau M.
Snyder, Abraham Z.
author_facet Strain, Jeremy F.
Brier, Matthew R.
Tanenbaum, Aaron
Gordon, Brian A.
McCarthy, John E.
Dincer, Aylin
Marcus, Daniel S.
Chhatwal, Jasmeer P.
Graff-Radford, Neill R.
Day, Gregory S.
la Fougère, Christian
Perrin, Richard J.
Salloway, Stephen
Schofield, Peter R.
Yakushev, Igor
Ikeuchi, Takeshi
Vöglein, Jonathan
Morris, John C.
Benzinger, Tammie L.S.
Bateman, Randall J.
Ances, Beau M.
Snyder, Abraham Z.
author_sort Strain, Jeremy F.
collection PubMed
description Prior studies of aging and Alzheimer disease have evaluated resting state functional connectivity (FC) using either seed-based correlation (SBC) or independent component analysis (ICA), with a focus on particular functional systems. SBC and ICA both are insensitive to differences in signal amplitude. At the same time, accumulating evidence indicates that the amplitude of spontaneous BOLD signal fluctuations is physiologically meaningful. We systematically compared covariance-based FC, which is sensitive to amplitude, vs. correlation-based FC, which is not, in affected individuals and controls drawn from two cohorts of participants including autosomal dominant Alzheimer disease (ADAD), late onset Alzheimer disease (LOAD), and age-matched controls. Functional connectivity was computed over 222 regions of interest and group differences were evaluated in terms of components projected onto a space of lower dimension. Our principal observations are: (1) Aging is associated with global loss of resting state fMRI signal amplitude that is approximately uniform across resting state networks. (2) Thus, covariance FC measures decrease with age whereas correlation FC is relatively preserved in healthy aging. (3) In contrast, symptomatic ADAD and LOAD both lead to loss of spontaneous activity amplitude as well as severely degraded correlation structure. These results demonstrate a double dissociation between age vs. Alzheimer disease and the amplitude vs. correlation structure of resting state BOLD signals. Modeling results suggest that the AD-associated loss of correlation structure is attributable to a relative increase in the fraction of locally restricted as opposed to widely shared variance.
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spelling pubmed-97507332022-12-14 Covariance-based vs. correlation-based functional connectivity dissociates healthy aging from Alzheimer disease Strain, Jeremy F. Brier, Matthew R. Tanenbaum, Aaron Gordon, Brian A. McCarthy, John E. Dincer, Aylin Marcus, Daniel S. Chhatwal, Jasmeer P. Graff-Radford, Neill R. Day, Gregory S. la Fougère, Christian Perrin, Richard J. Salloway, Stephen Schofield, Peter R. Yakushev, Igor Ikeuchi, Takeshi Vöglein, Jonathan Morris, John C. Benzinger, Tammie L.S. Bateman, Randall J. Ances, Beau M. Snyder, Abraham Z. Neuroimage Article Prior studies of aging and Alzheimer disease have evaluated resting state functional connectivity (FC) using either seed-based correlation (SBC) or independent component analysis (ICA), with a focus on particular functional systems. SBC and ICA both are insensitive to differences in signal amplitude. At the same time, accumulating evidence indicates that the amplitude of spontaneous BOLD signal fluctuations is physiologically meaningful. We systematically compared covariance-based FC, which is sensitive to amplitude, vs. correlation-based FC, which is not, in affected individuals and controls drawn from two cohorts of participants including autosomal dominant Alzheimer disease (ADAD), late onset Alzheimer disease (LOAD), and age-matched controls. Functional connectivity was computed over 222 regions of interest and group differences were evaluated in terms of components projected onto a space of lower dimension. Our principal observations are: (1) Aging is associated with global loss of resting state fMRI signal amplitude that is approximately uniform across resting state networks. (2) Thus, covariance FC measures decrease with age whereas correlation FC is relatively preserved in healthy aging. (3) In contrast, symptomatic ADAD and LOAD both lead to loss of spontaneous activity amplitude as well as severely degraded correlation structure. These results demonstrate a double dissociation between age vs. Alzheimer disease and the amplitude vs. correlation structure of resting state BOLD signals. Modeling results suggest that the AD-associated loss of correlation structure is attributable to a relative increase in the fraction of locally restricted as opposed to widely shared variance. 2022-11-01 2022-07-30 /pmc/articles/PMC9750733/ /pubmed/35914670 http://dx.doi.org/10.1016/j.neuroimage.2022.119511 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) )
spellingShingle Article
Strain, Jeremy F.
Brier, Matthew R.
Tanenbaum, Aaron
Gordon, Brian A.
McCarthy, John E.
Dincer, Aylin
Marcus, Daniel S.
Chhatwal, Jasmeer P.
Graff-Radford, Neill R.
Day, Gregory S.
la Fougère, Christian
Perrin, Richard J.
Salloway, Stephen
Schofield, Peter R.
Yakushev, Igor
Ikeuchi, Takeshi
Vöglein, Jonathan
Morris, John C.
Benzinger, Tammie L.S.
Bateman, Randall J.
Ances, Beau M.
Snyder, Abraham Z.
Covariance-based vs. correlation-based functional connectivity dissociates healthy aging from Alzheimer disease
title Covariance-based vs. correlation-based functional connectivity dissociates healthy aging from Alzheimer disease
title_full Covariance-based vs. correlation-based functional connectivity dissociates healthy aging from Alzheimer disease
title_fullStr Covariance-based vs. correlation-based functional connectivity dissociates healthy aging from Alzheimer disease
title_full_unstemmed Covariance-based vs. correlation-based functional connectivity dissociates healthy aging from Alzheimer disease
title_short Covariance-based vs. correlation-based functional connectivity dissociates healthy aging from Alzheimer disease
title_sort covariance-based vs. correlation-based functional connectivity dissociates healthy aging from alzheimer disease
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9750733/
https://www.ncbi.nlm.nih.gov/pubmed/35914670
http://dx.doi.org/10.1016/j.neuroimage.2022.119511
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