Review of methods for functional brain connectivity detection using fMRI

By Kaiming Li, Lei Guo, Jingxin Nie, Gang Li, Tianming Liu. Comput. Medical Imaging Graph., 2008

309 citations recorded by the source corpus.

Since the mid of 1990s, functional connectivity study using fMRI (fcMRI) has drawn increasing attention of neuroscientists and computer scientists, since it opens a new window to explore functional network of human brain with relatively high resolution. A variety of methods for fcMRI study have been proposed. This paper intends to provide a technical review on computational methodologies developed for fcMRI analysis. From our perspective, these computational methods are classified into two general categories: model-driven methods and data-driven methods. Data-driven methods are a large family, and thus are further sub-classified into decomposition-based methods and clustering analysis methods. For each type of methods, principles, main contributors, and their advantages and drawbacks are discussed. Finally, potential applications of fcMRI are overviewed.

Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/105464b584bfdd29e322a4453427b9facb988539

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In Cognitive Neuroscience

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

Application of Graph Theory for Identifying Connectivity Patterns in Human Brain Networks: A Systematic Review (2019, methodology): “Computational methods for functional brain connectivity are generally divided into model-based and model-free (Li et al., 2009a).”
Resting state fMRI: A review on methods in resting state connectivity analysis and resting state networks (2017, methodology): “A small world network may be termed a densely connected local clustered network having a slight characteristic path length that permits a prompt communication between the nodes in the network.38,45 According to Supekar et al., a large scale network is characterised by slight short range connectivity”
Hierarchical Mixture of Classification Experts Uncovers Interactions between Brain Regions (2009, methodology): “Functional connectivity refers to undirected connections, which can be either model-driven or data-driven [23].”
Medical image analysis with artificial neural networks (2010, methodology): “Since the mid of 1990s, functional connectivity study using fMRI has drawn increasing attention of neuroscientists and computer scientists, which opens a new window to explore functional network of human brain [50].”
Eigenvector Centrality Mapping for Analyzing Connectivity Patterns in fMRI Data of the Human Brain (2010, background): “For comprehensive reviews of the above and related methods see [2,3].”