Benchmarking methods for mapping functional connectivity in the brain

2025/06/06 by Zhen-Qi Liu, Andrea I. Luppi, Justine Y. Hansen +5 · 1 voice · 26 citations
Mathematics · Medicine · Neuroscience · #Advanced Neuroimaging Techniques and Applications #Artificial intelligence #Benchmark (surveying) #Benchmarking #Biology #Cartography #Computer science #Covariance #Data mining #Functional Brain Connectivity Studies #Machine learning #Mathematics #Neural dynamics and brain function #Neurophysiology #Neuroscience #Pairwise comparison #Pattern recognition (psychology) #Statistic #Statistics

paper · pdf · doi:10.1038/s41592-025-02704-4

published in Nature Methods 22(7), 1593-1602 (Nature Portfolio)

openalex publication_date 2025/06/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06

Abstract

The networked architecture of the brain promotes synchrony among neuronal populations. These communication patterns can be mapped using functional imaging, yielding functional connectivity (FC) networks. While most studies use Pearson's correlations by default, numerous pairwise interaction statistics exist in the scientific literature. How does the organization of the FC matrix vary with the choice of pairwise statistic? Here we use a library of 239 pairwise statistics to benchmark canonical features of FC networks, including hub mapping, weight-distance trade-offs, structure-function coupling, correspondence with other neurophysiological networks, individual fingerprinting and brain-behavior prediction. We find substantial quantitative and qualitative variation across FC methods. Measures such as covariance, precision and distance display multiple desirable properties, including correspondence with structural connectivity and the capacity to differentiate individuals and predict individual differences in behavior. Our report highlights how FC mapping can be optimized by tailoring pairwise statistics to specific neurophysiological mechanisms and research questions.

Citations

• The organization of the human cerebral cortex estimated by intrinsic functional connectivity
• Does the brain behave like a (complex) network? I. Dynamics
• Extracting interpretable signatures of whole-brain dynamics through systematic comparison

Cited by

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• Convergent transcriptomic and connectomic controllers of information integration and its anaesthetic breakdown across mammalian brains. [europepmc]
• Mapping Functional Brain Organization Using Artificial Intelligence. [europepmc]
• Benchmarking resting state fMRI connectivity pipelines for classification: robust accuracy despite processing variability in cross-site eye state prediction. [europepmc]
• Synergistic and redundant information dynamics exhibit dissociable alterations across schizophrenia and neurodevelopmental conditions. [europepmc]
• Common Phenomenal and Neural Substrate Geometry in Visual Motion Perception [europepmc]

Discussions

• Benchmarking methods for mapping functional connectivity in the brain | doi.org/10.1038/s415... What is the best measure of functional connectivity (FC)? led by @zhenqi.bsky.social in @natmethods.na [bsky, 88 points, 4 comments]

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