During the past decade, mapping complex structural and functional connectomics in living human brains using non-invasive neuroimaging technologies has been widely developed and employed on a variety of cognitive and clinical neuroscience researches. Among all modern neuroimaging technologies, MRI has been considered as one of the most reliable and reproducible neuroimaging modalities for exploring the complex brain networks with adequate spatial and temporal resolutions. In this educational talk, I will introduce the methodologies and analysis approaches of functional MRI (fMRI) data for mapping the functional connectomics [1]. The methods to calculate the functional connectivity using resting-state or task-based fMRI data and how it can be used for deriving the brain network metrics using graph theoretical analysis or other computational methods will be reviewed. Furthermore, recent technological advances for mapping the functional connectomics and their use on clinical and cognitive neuroscience applications will be also introduced and discussed [2, 3].

Acknowledgements

This work was supported by the National Health Research Institutes of Taiwan (NHRI-111-PP-06).

References

[1] Smith, S.M., et al., Functional connectomics from resting-state fMRI. Trends Cogn Sci, 2013. 17(12): p. 666-82. [2] Lin, S.Y., et al., Investigation of functional brain network reconfiguration during vocal emotional processing using graph-theoretical analysis. Soc Cogn Affect Neurosci, 2019. 14(5): p. 529-538. [3] Lin, S.Y., et al., Multiparametric graph theoretical analysis reveals altered structural and functional network topology in Alzheimer's disease. Neuroimage Clin, 2019. 22: p. 101680.