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Published on: August 5, 2014
Review of methods for functional brain connectivity detection using fMRI.
Kaiming Li1, Lei Guo, Jingxin Nie
1Department of Automation, Northwestern Polytechnical University, Xi'an, China.
Summary
Functional connectivity studies using fMRI (fcMRI) reveal brain networks. This review categorizes computational methods, including model-driven and data-driven approaches like decomposition and clustering, for fcMRI analysis.
Area of Science:
- Neuroscience
- Computer Science
- Medical Imaging
Background:
- Functional connectivity Magnetic Resonance Imaging (fcMRI) has emerged as a key technique since the mid-1990s for exploring human brain networks.
- fcMRI offers high-resolution insights into brain function, attracting significant interest from neuroscientists and computer scientists.
- Numerous computational methodologies have been developed to analyze fcMRI data.
Purpose of the Study:
- To provide a comprehensive technical review of computational methodologies for functional connectivity Magnetic Resonance Imaging (fcMRI) analysis.
- To classify and discuss the principles, contributors, advantages, and drawbacks of various fcMRI computational methods.
- To overview potential applications of fcMRI in neuroscience and related fields.
Main Methods:
- Methods are broadly categorized into model-driven and data-driven approaches.
- Data-driven methods are further sub-classified into decomposition-based techniques and clustering analysis.
- The review details the underlying principles and comparative performance of these computational strategies.
Main Results:
- The study classifies existing computational methods for fcMRI analysis.
- It highlights the distinctions between model-driven and data-driven approaches, with a focus on the latter's subcategories.
- Advantages and limitations of each method are discussed to guide researchers.
Conclusions:
- A structured understanding of fcMRI computational methodologies is crucial for advancing brain network research.
- The review provides a framework for selecting appropriate analytical techniques based on research questions.
- Future directions and applications of fcMRI are suggested, emphasizing its growing importance.
