Combining region- and network-level brain-behavior relationships in a structural equation model
| Autor: | Emily B. Prince, Daniel S. Messinger, Jason S. Nomi, Taylor Bolt, Lucina Q. Uddin, Maria M. Llabre |
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| Rok vydání: | 2018 |
| Předmět: |
Adult
Male Cognitive Neuroscience Brain behavior Models Neurological Image processing computer.software_genre 050105 experimental psychology Structural equation modeling Task (project management) Young Adult 03 medical and health sciences 0302 clinical medicine Task Performance and Analysis Network level Image Processing Computer-Assisted Humans 0501 psychology and cognitive sciences Association (psychology) Brain Mapping Working memory 05 social sciences Brain Flexibility (personality) Magnetic Resonance Imaging Neurology Female Data mining Nerve Net Psychology computer 030217 neurology & neurosurgery |
| Zdroj: | NeuroImage. 165:158-169 |
| ISSN: | 1053-8119 |
| Popis: | Brain-behavior associations in fMRI studies are typically restricted to a single level of analysis: either a circumscribed brain region-of-interest (ROI) or a larger network of brain regions. However, this common practice may not always account for the interdependencies among ROIs of the same network or potentially unique information at the ROI-level, respectively. To account for both sources of information, we combined measurement and structural components of structural equation modeling (SEM) approaches to empirically derive networks from ROI activity, and to assess the association of both individual ROIs and their respective whole-brain activation networks with task performance using three large task-fMRI datasets and two separate brain parcellation schemes. The results for working memory and relational tasks revealed that well-known ROI-performance associations are either non-significant or reversed when accounting for the ROI's common association with its corresponding network, and that the network as a whole is instead robustly associated with task performance. The results for the arithmetic task revealed that in certain cases, an ROI can be robustly associated with task performance, even when accounting for its associated network. The SEM framework described in this study provides researchers additional flexibility in testing brain-behavior relationships, as well as a principled way to combine ROI- and network-levels of analysis. |
| Databáze: | OpenAIRE |
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