A systematic review of the relationship between magnetic resonance imaging based resting-state and structural networks in the rodent brain

Frontiers in Neuroscience

Neuroscience

Mathias Hoehn¹  Fatemeh S. N. Mahani²  Markus Aswendt²  Gereon R. Fink²  Aref Kalantari³ 

[1] Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Centre Juelich, Juelich, Germany;Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Centre Juelich, Juelich, Germany;Department of Neurology, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany;Department of Neurology, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany;

关键词: rat;    mouse;    MRI;    DTI;    rs-fMRI;    graph theory;    connectivity;   

DOI  :  10.3389/fnins.2023.1194630

 received in 2023-03-27, accepted in 2023-07-05,  发布年份 2023

来源: Frontiers

【 摘 要 】

Recent developments in rodent brain imaging have enabled translational characterization of functional and structural connectivity at the whole brain level in vivo. Nevertheless, fundamental questions about the link between structural and functional networks remain unsolved. In this review, we systematically searched for experimental studies in rodents investigating both structural and functional network measures, including studies correlating functional connectivity using resting-state functional MRI with diffusion tensor imaging or viral tracing data. We aimed to answer whether functional networks reflect the architecture of the structural connectome, how this reciprocal relationship changes throughout a disease, how structural and functional changes relate to each other, and whether changes follow the same timeline. We present the knowledge derived exclusively from studies that included in vivo imaging of functional and structural networks. The limited number of available reports makes it difficult to draw general conclusions besides finding a spatial and temporal decoupling between structural and functional networks during brain disease. Data suggest that when overcoming the currently limited evidence through future studies with combined imaging in various disease models, it will be possible to explore the interaction between both network systems as a disease or recovery biomarker.

【 授权许可】

Unknown   
Copyright © 2023 Mahani, Kalantari, Fink, Hoehn and Aswendt.