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dc.creatorDennison, Jeff B.
dc.creatorTepfer, Lindsey J.
dc.creatorSmith, David
dc.identifier.citationDennison, J. B., Tepfer, L. J., & Smith, D. V. (2023). Tensorial independent component analysis reveals social and reward networks associated with major depressive disorder. Human Brain Mapping, 44(7), 2905–2920.
dc.description.abstractMajor depressive disorder (MDD) has been associated with changes in functional brain connectivity. Yet, typical analyses of functional connectivity, such as spatial independent components analysis (ICA) for resting-state data, often ignore sources of between-subject variability, which may be crucial for identifying functional connectivity patterns associated with MDD. Typically, methods like spatial ICA will identify a single component to represent a network like the default mode network (DMN), even if groups within the data show differential DMN coactivation. To address this gap, this project applies a tensorial extension of ICA (tensorial ICA)—which explicitly incorporates between-subject variability—to identify functionally connected networks using functional MRI data from the Human Connectome Project (HCP). Data from the HCP included individuals with a diagnosis of MDD, a family history of MDD, and healthy controls performing a gambling and social cognition task. Based on evidence associating MDD with blunted neural activation to rewards and social stimuli, we predicted that tensorial ICA would identify networks associated with reduced spatiotemporal coherence and blunted social and reward-based network activity in MDD. Across both tasks, tensorial ICA identified three networks showing decreased coherence in MDD. All three networks included ventromedial prefrontal cortex, striatum, and cerebellum and showed different activation across the conditions of their respective tasks. However, MDD was only associated with differences in task-based activation in one network from the social task. Additionally, these results suggest that tensorial ICA could be a valuable tool for understanding clinical differences in relation to network activation and connectivity.
dc.format.extent16 pages
dc.relation.ispartofOpen Access Publishing Fund
dc.relation.haspartHuman Brain Mapping, Vol. 44, Iss. 7
dc.relation.isreferencedbyWiley Open Access
dc.rightsAttribution CC BY
dc.subjectIndependent component analysis
dc.subjectFunctional connectivity
dc.subjectHuman Connectome Project
dc.subjectMajor depressive disorder
dc.titleTensorial independent component analysis reveals social and reward networks associated with major depressive disorder
dc.type.genreJournal article
dc.description.departmentPsychology and Neuroscience
dc.ada.noteFor Americans with Disabilities Act (ADA) accommodation, including help with reading this content, please contact
dc.description.schoolcollegeTemple University. College of Liberal Arts
dc.description.sponsorTemple University Libraries Open Access Publishing Fund, 2022-2023 (Philadelphia, Pa.)
dc.temple.creatorDennison, Jeff B.
dc.temple.creatorSmith, David V.

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