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Abstract:
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While a great deal of emphasis has been placed on the analysis of multimodal and multisequence neuroimaging data, the many multimodal modeling strategies involve separate analysis of each modality followed by an integrative model. Furthermore, those models that truly integrate images across modalities for studying clinical outcomes or development focus on the mean structure in each image, and aim to quantify information in the images by integrating this information across modalities. In intermodal coupling analysis (IMCo), we aim to study the local covariance structure across modalities at the subject level, and we show that there is complementary population-level information in IMCo maps across space. We use this approach to study the relationship between functional and structural measures of brain maturation in a large neurodevelopmental cohort, and further investigate IMCo for assessing the relationship between brain networks in functional magnetic resonance imaging studies.
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