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A Data-Driven Multi-scale Technique for fMRI Mapping of the Human Somatosensory Cortex

  • Selene Da Rocha AmaralEmail author
  • Rosa Maria Sanchez Panchuelo
  • Susan Francis
Original Paper
  • 115 Downloads

Abstract

A previously introduced Bayesian non-parametric multi-scale technique, called iterated Multigrid Priors (iMGP) method, is used to map the topographic organization of human primary somatosensory cortex (S1). We analyze high spatial resolution fMRI data acquired at ultra-high field (UHF, 7T) in individual subjects during vibrotactile stimulation applied to each distal phalange of the left hand digits using both a travelling-wave (TW) and event-related (ER) paradigm design. We compare the somatotopic digit representations generated in S1 using the iMGP method with those obtained using established fMRI paradigms and analysis techniques: Fourier-based analysis of travelling-wave data and General Linear Model (GLM) analysis of event-related data. Maps derived with the iMGP method are similar to those derived with the standard analysis, but in contrast to the Fourier-based analysis, the iMGP method reveals overlap of activity from adjacent digit representations in S1. These findings validate the use of the iMGP method as an alternative to study digit representations in S1, particularly with the TW design as an attractive means to study cortical reorganization in patient populations such dystonia and carpal tunnel syndrome, where the degree of spatial overlap of cortical finger representations is of interest.

Keywords

Prior information Bayesian approach High-spatial-resolution fMRI Ultra-high field Digit somatotopy 

Notes

Acknowledgements

This work received the financial support of both The University of Nottingham and MCTI/CNPq and FAPEG. Dr. Sanchez Panchuelo is a Leverhulme Early Career Fellow. This work was funded by the MRC grant Medical Research Council [Grant Number MR/M022722/1] and BBSRC Research Council [Grant Number BB/G008906/1].

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Instituto de FísicaUniversidade Federal de GoiásGoiásBrazil
  2. 2.School of Physics and Astronomy, Sir Peter Mansfield Imaging CentreUniversity of NottinghamNottinghamUK

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