Decoding the orientation of contrast edges from MEG evoked and induced responses

Neuroimage. 2018 Oct 15;180(Pt A):267-279. doi: 10.1016/j.neuroimage.2017.07.022. Epub 2017 Jul 13.

Abstract

Visual gamma oscillations have been proposed to subserve perceptual binding, but their strong modulation by diverse stimulus features confounds interpretations of their precise functional role. Overcoming this challenge necessitates a comprehensive account of the relationship between gamma responses and stimulus features. Here we used multivariate pattern analyses on human MEG data to characterize the relationships between gamma responses and one basic stimulus feature, the orientation of contrast edges. Our findings confirmed we could decode orientation information from induced responses in two dominant frequency bands at 24-32 Hz and 50-58 Hz. Decoding was higher for cardinal than oblique orientations, with similar results also obtained for evoked MEG responses. In contrast to multivariate analyses, orientation information was mostly absent in univariate signals: evoked and induced responses in early visual cortex were similar in all orientations, with only exception an inverse oblique effect observed in induced responses, such that cardinal orientations produced weaker oscillatory signals than oblique orientations. Taken together, our results showed multivariate methods are well suited for the analysis of gamma oscillations, with multivariate patterns robustly encoding orientation information and predominantly discriminating cardinal from oblique stimuli.

Keywords: Feature binding; Gamma oscillations; Gratings; MEG; Multivariate analysis; Oblique effect; Orientation; Pattern classification; Representational similarity analysis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Brain Mapping / methods*
  • Evoked Potentials, Visual / physiology
  • Female
  • Humans
  • Magnetoencephalography / methods
  • Male
  • Multivariate Analysis
  • Orientation / physiology
  • Pattern Recognition, Visual / physiology*
  • Signal Processing, Computer-Assisted*
  • Support Vector Machine
  • Visual Cortex / physiology*
  • Young Adult