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

Brain Topogr. 2020 Jan;33(1):22-36. doi: 10.1007/s10548-019-00728-6. Epub 2019 Sep 14.

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

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Bayes Theorem
  • Brain Mapping / methods
  • Female
  • Fingers / physiology
  • Fourier Analysis
  • Humans
  • Linear Models
  • Magnetic Resonance Imaging / methods*
  • Male
  • Somatosensory Cortex / physiology*