Mapping the structural and functional network architecture of the medial temporal lobe using 7T MRI
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- Preya Shah
- Department of Bioengineering University of Pennsylvania Philadelphia Pennsylvania 19104
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- Danielle S. Bassett
- Department of Bioengineering University of Pennsylvania Philadelphia Pennsylvania 19104
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- Laura E.M. Wisse
- Penn Image Computing and Science Laboratory University of Pennsylvania Philadelphia Pennsylvania 19104
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- John A. Detre
- Department of Radiology University of Pennsylvania Philadelphia Pennsylvania 19104
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- Joel M. Stein
- Department of Radiology University of Pennsylvania Philadelphia Pennsylvania 19104
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- Paul A. Yushkevich
- Penn Image Computing and Science Laboratory University of Pennsylvania Philadelphia Pennsylvania 19104
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- Russell T. Shinohara
- Department of Biostatistics Epidemiology and Informatics, University of Pennsylvania Philadelphia Pennsylvania 19104
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- John B. Pluta
- Penn Image Computing and Science Laboratory University of Pennsylvania Philadelphia Pennsylvania 19104
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- Elijah Valenciano
- Penn Image Computing and Science Laboratory University of Pennsylvania Philadelphia Pennsylvania 19104
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- Molly Daffner
- Department of Neurology University of Pennsylvania Philadelphia Pennsylvania 19104
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- David A. Wolk
- Department of Neurology University of Pennsylvania Philadelphia Pennsylvania 19104
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- Mark A. Elliott
- Department of Radiology University of Pennsylvania Philadelphia Pennsylvania 19104
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- Brian Litt
- Department of Bioengineering University of Pennsylvania Philadelphia Pennsylvania 19104
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- Kathryn A. Davis
- Center for Neuroengineering and Therapeutics University of Pennsylvania Philadelphia Pennsylvania 19104
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- Sandhitsu R. Das
- Penn Image Computing and Science Laboratory University of Pennsylvania Philadelphia Pennsylvania 19104
抄録
<jats:title>Abstract</jats:title><jats:p>Medial temporal lobe (MTL) subregions play integral roles in memory function and are differentially affected in various neurological and psychiatric disorders. The ability to structurally and functionally characterize these subregions may be important to understanding MTL physiology and diagnosing diseases involving the MTL. In this study, we characterized network architecture of the MTL in healthy subjects (<jats:italic>n</jats:italic> = 31) using both resting state functional MRI and MTL‐focused T2‐weighted structural MRI at 7 tesla. Ten MTL subregions per hemisphere, including hippocampal subfields and cortical regions of the parahippocampal gyrus, were segmented for each subject using a multi‐atlas algorithm. Both structural covariance matrices from correlations of subregion volumes across subjects, and functional connectivity matrices from correlations between subregion BOLD time series were generated. We found a moderate structural and strong functional inter‐hemispheric symmetry. Several bilateral hippocampal subregions (CA1, dentate gyrus, and subiculum) emerged as functional network hubs. We also observed that the structural and functional networks naturally separated into two modules closely corresponding to (a) bilateral hippocampal formations, and (b) bilateral extra‐hippocampal structures. Finally, we found a significant correlation in structural and functional connectivity (<jats:italic>r</jats:italic> = 0.25). Our findings represent a comprehensive analysis of network topology of the MTL at the subregion level. We share our data, methods, and findings as a reference for imaging methods and disease‐based research.</jats:p>
収録刊行物
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- Human Brain Mapping
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Human Brain Mapping 39 (2), 851-865, 2017-11-20
Wiley