Classification images reveal the information sensitivity of brain voxels in fMRI

Neuroimage. 2008 May 1;40(4):1643-54. doi: 10.1016/j.neuroimage.2008.01.029. Epub 2008 Feb 1.

Abstract

Reverse correlation methods have been widely used in neuroscience for many years and have recently been applied to study the sensitivity of human brain signals (EEG, MEG) to complex visual stimuli. Here we employ one such method, Bubbles (Gosselin, F., Schyns, P.G., 2001. Bubbles: A technique to reveal the use of information in recognition tasks. Vis. Res. 41, 2261-2271), in conjunction with fMRI in the context of a 3AFC facial expression categorization task. We highlight the regions of the brain showing significant sensitivity with respect to the critical visual information required to perform the categorization judgments. Moreover, we reveal the actual subset of visual information which modulates BOLD sensitivity within each such brain region. Finally, we show the potential which lies within analyzing brain function in terms of the information states of different brain regions. Thus, we can now analyse human brain function in terms of the specific visual information different brain regions process.

MeSH terms

  • Adult
  • Brain / physiology*
  • Emotions
  • Facial Expression
  • Fear / psychology
  • Humans
  • Image Processing, Computer-Assisted / classification*
  • Image Processing, Computer-Assisted / statistics & numerical data
  • Magnetic Resonance Imaging / classification*
  • Magnetic Resonance Imaging / statistics & numerical data
  • Mental Processes / physiology*
  • Photic Stimulation
  • Social Perception
  • Visual Perception / physiology