We propose to develop statistical methods for the analysis of the local covariance structure between measurements in multimodal biomedical imaging studies. Despite the rise of multi-modal imaging studies and the proliferation of derived measures available from each modality, very little work has explored relationships between modalities. Notably, brain structure and function evolve dramatically in the context of adolescent brain development, but typical analyses usually evaluate each imaging phenotype separately. We propose to develop tools for measuring relationships between brain imaging phenotypes provided by disparate imaging modalities. Covariance structures at the subject level will allow identification of local relationships between measures, through weighted regressions and singular value decomposition-based techniques. These techniques will be extended to accommodate any number of imaging modalities and incorporate repeated measures. We will use extensive test-retest data provided by the Consortium of Reproducibility and Reliability (CORR) for validation, and to identify coupling measures that are particularly reliable. The rich multi-modal imaging data and associated clinical phenotypes from the Philadelphia Neurodevelopmental Cohort (PNC) will allow us to delineate how inter- modal coupling evolves in normal brain development, and also establish how such relationships are altered in association with psychosis-spectrum symptoms. This proposal builds upon established collaboration between the PIs and capitalizes on their complimentary expertise in imaging statistics, developmental neuroimaging, psychopathology, and intimate familiarity with the PNC dataset. Upon completion, this project will provide powerful new tools for the neuroscience community, as well as novel insights regarding brain development and early psychosis-spectrum symptoms.
The overarching goal of this proposal is to develop new tools for integrative analysis of local relationships among brain imaging measures. Despite the rise of multi-modal imaging studies and the proliferation of derived measures available from each modality, very little work has explored relationships between modalities. The methods developed as part of this proposal will fill this critical gap in the field, and will lead to more sensitive and specific biomarkers of brain pathology and healthy development.
| Xia, Cedric Huchuan; Ma, Zongming; Ciric, Rastko et al. (2018) Linked dimensions of psychopathology and connectivity in functional brain networks. Nat Commun 9:3003 |
| Rosen, Adon F G; Roalf, David R; Ruparel, Kosha et al. (2018) Quantitative assessment of structural image quality. Neuroimage 169:407-418 |
| Shah, Preya; Bassett, Danielle S; Wisse, Laura E M et al. (2018) Mapping the structural and functional network architecture of the medial temporal lobe using 7T MRI. Hum Brain Mapp 39:851-865 |
| Dworkin, J D; Sati, P; Solomon, A et al. (2018) Automated Integration of Multimodal MRI for the Probabilistic Detection of the Central Vein Sign in White Matter Lesions. AJNR Am J Neuroradiol 39:1806-1813 |
| Bassett, Danielle S; Xia, Cedric Huchuan; Satterthwaite, Theodore D (2018) Understanding the Emergence of Neuropsychiatric Disorders With Network Neuroscience. Biol Psychiatry Cogn Neurosci Neuroimaging 3:742-753 |
| Valcarcel, Alessandra M; Linn, Kristin A; Vandekar, Simon N et al. (2018) MIMoSA: An Automated Method for Intermodal Segmentation Analysis of Multiple Sclerosis Brain Lesions. J Neuroimaging 28:389-398 |
| Valcarcel, Alessandra M; Linn, Kristin A; Khalid, Fariha et al. (2018) A dual modeling approach to automatic segmentation of cerebral T2 hyperintensities and T1 black holes in multiple sclerosis. Neuroimage Clin 20:1211-1221 |
| Reardon, P K; Seidlitz, Jakob; Vandekar, Simon et al. (2018) Normative brain size variation and brain shape diversity in humans. Science 360:1222-1227 |
| Medaglia, John D; Satterthwaite, Theodore D; Kelkar, Apoorva et al. (2018) Brain state expression and transitions are related to complex executive cognition in normative neurodevelopment. Neuroimage 166:293-306 |
| Alexander-Bloch, Aaron F; Shou, Haochang; Liu, Siyuan et al. (2018) On testing for spatial correspondence between maps of human brain structure and function. Neuroimage 178:540-551 |
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