4 years ago

Can Patel's τ accurately estimate directionality of connections in brain networks from fMRI?

Olivier David, Yunzhi Wang, Xiaoping Hu, Gopikrishna Deshpande
Purpose Investigating directional interactions between brain regions plays a critical role in fully understanding brain function. Consequently, multiple methods have been developed for noninvasively inferring directional connectivity in human brain networks using functional MRI (fMRI). Recent simulations by Smith et al. showed that Patel's τ, a method based on higher-order statistics, was the best approach for inferring directional interactions from fMRI. Because simulations make restrictive assumptions about reality, we set out to verify this finding using experimental fMRI data obtained from a three-region network in a rat model with electrophysiological validation. Methods Previous studies have shown that dynamic causal modeling can correctly estimate the directionality of this three-region network; Granger causality can also work after the deconvolution of the hemodynamic response. Therefore, we set out to test the hypothesis that Patel's τ obtained from either raw or deconvolved fMRI data should correctly estimate the directionality of neuronal influences obtained from intracerebral electroencephalogram in this network. Results Our results indicate that the accuracy of network directionality estimated using Patel's τ was not better than chance. Conclusion First, our results highlight the necessity of experimental validation of simulation results. Second, it is unclear which brain mechanism is modeled by a directionality inferred from Patel's τ. Third, this study shows that a directional connection ascertained by different methods may mean different things and more experimental studies are needed for investigating the neuronal mechanisms underlying the direction of a connection in the brain ascertained by fMRI using different methods. M Magn Reson Med 78:2003–2010, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Publisher URL: http://onlinelibrary.wiley.com/resolve/doi

DOI: 10.1002/mrm.26583

You might also like
Discover & Discuss Important Research

Keeping up-to-date with research can feel impossible, with papers being published faster than you'll ever be able to read them. That's where Researcher comes in: we're simplifying discovery and making important discussions happen. With over 19,000 sources, including peer-reviewed journals, preprints, blogs, universities, podcasts and Live events across 10 research areas, you'll never miss what's important to you. It's like social media, but better. Oh, and we should mention - it's free.

  • Download from Google Play
  • Download from App Store
  • Download from AppInChina

Researcher displays publicly available abstracts and doesn’t host any full article content. If the content is open access, we will direct clicks from the abstracts to the publisher website and display the PDF copy on our platform. Clicks to view the full text will be directed to the publisher website, where only users with subscriptions or access through their institution are able to view the full article.