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Neuronal and Physiological Correlation to Hemodynamic Resting-State Fluctuations in Health and Disease

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Title
Neuronal and Physiological Correlation to Hemodynamic Resting-State Fluctuations in Health and Disease
Author(s)
Alberto L. Vazquez; Matthew C. Murphy; Seong Gi Kim
Publication Date
2014-11
Journal
BRAIN CONNECTIVITY, v.4, no.9, pp.727 - 740
Publisher
Mary Ann Liebert, Inc.
Abstract
Low-frequency, spatially coherent fluctuations present in functional magnetic resonance imaging time series have had a tremendous impact on brain connectomics. This work aims to explore the degree with which hemodynamic connectivity is associated with neuronal, metabolic, and vascular connectivity measures. For this purpose, GCaMP and nontransgenic mice were used to image neuronal activity and oxidative metabolism activity, respectively, along with blood-oxygenation- and cerebral blood volume (CBV)–sensitive hemodynamic changes from the same animals. Although network clusters calculated using either GCaMP (neuronal activity) or optical imaging of intrinsic signal (OIS)–BOLD (blood oxygenation) data did not exhibit strong spatial similarity, the strengths of node-to-node connectivity measured with these modalities were strongly correlated with one another. This finding suggests that hemodynamic connectivity as measured by blood oxygenation measurements, such as functional connectivity magnetic resonance imaging, is a valuable surrogate for the underlying neuronal connectivity. In nontransgenic animals, greater connectivity correlation was observed between tissue oxidative metabolism (flavoprotein autofluorescence imaging [FAI]) and blood oxygenation measurements, suggesting that metabolic contributions to hemodynamic signals are likely responsible for its significant correlation with neuronal connectivity. Lastly, a mouse model of Alzheimer’s disease was used to explore the source of decreases in connectivity reported in these mice, a finding that is thought to be associated with amyloid load-driven metabolic decline. The intercluster connectivity measured by metabolic-sensitive measurements (FAI and OISBOLD) was maintained while vascular-only signals (OIS-CBV) provided negligible correlation. Therefore, metabolism-sensitive measurements as used in this work are better positioned to capture changes in neuronal connectivity, such that decreases in hemodynamic connectivity likely reflect decreases in oxidative metabolic function.
URI
https://pr.ibs.re.kr/handle/8788114/1446
ISSN
2158-0014
Appears in Collections:
Center for Neuroscience Imaging Research (뇌과학 이미징 연구단) > Journal Papers (저널논문)
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