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Connectivity analyses for task-based fMRI
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DOI：10.1016/j.plrev.2024.04.012.png)
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Abstract
En 中文
Functional connectivity is conventionally defined by measuring the similarity between brain signals from two regions. The technique has become widely adopted in the analysis of functional magnetic resonance imaging (fMRI) data, where it has provided cognitive neuroscientists with abundant information on how brain regions interact to support complex cognition. However, in the past decade the notion of connectivity has expanded in both the complexity and heterogeneity of its application to cognitive neuroscience, resulting in greater difficulty of interpretation, replication, and cross -study comparisons. In this paper, we begin with the canonical notions of functional connectivity and then introduce recent methodological developments that either estimate some alternative form of connectivity or extend the analytical framework, with the hope of bringing better clarity for cognitive neuroscience researchers.
Keywords:
fMRI
Functional connectivity
Multivariate pattern analysis
Representational similarity analysis
Graph theory
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