Identifying brain networks in synaptic density PET (11C-UCB-J) with independent component analysis

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Takuya Toyonaga¹  Christopher H. van Dyck²  Sophie E. Holmes³  Adam P. Mecca³  Irina Esterlis⁴  Deepak Cyril D'Souza⁴  Patrick D. Worhunsky⁴  Richard E. Carson⁴  David Matuskey⁵  Rajiv Radhakrishnan⁵  Xiaotian T. Fang⁵  Ansel T. Hillmer⁵ 

[1] Corresponding author.;Department of Neurology, Yale School of Medicine, New Haven, CT, USA;Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA;Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA;Yale PET Center, Department of Radiology and Biomedical Imaging, Yale University, 801 Howard Avenue, New Haven, CT 06520, USA;

关键词: ICA;    SV2A;    Aging;    Positron emission tomography;    Synapse;    Neuroimaging;   

DOI  :  

来源: DOAJ

【 摘 要 】

Background: The human brain is inherently organized into distinct networks, as reported widely by resting-state functional magnetic resonance imaging (rs-fMRI), which are based on blood-oxygen-level-dependent (BOLD) signal fluctuations. 11C-UCB-J PET maps synaptic density via synaptic vesicle protein 2A, which is a more direct structural measure underlying brain networks than BOLD rs-fMRI. Methods: The aim of this study was to identify maximally independent brain source networks, i.e., “spatial patterns with common covariance across subjects”, in 11C-UCB-J data using independent component analysis (ICA), a data-driven analysis method. Using a population of 80 healthy controls, we applied ICA to two 40-sample subsets and compared source network replication across samples. We examined the identified source networks at multiple model orders, as the ideal number of maximally independent components (IC) is unknown. In addition, we investigated the relationship between the strength of the loading weights for each source network and age and sex. Results: Thirteen source networks replicated across both samples. We determined that a model order of 18 components provided stable, replicable components, whereas estimations above 18 were not stable. Effects of sex were found in two ICs. Nine ICs showed age-related change, with 4 remaining significant after correction for multiple comparison. Conclusion: This study provides the first evidence that human brain synaptic density can be characterized into organized covariance patterns. Furthermore, we demonstrated that multiple synaptic density source networks are associated with age, which supports the potential utility of ICA to identify biologically relevant synaptic density source networks.

【 授权许可】

Unknown