Classification images reveal the information sensitivity of brain voxels in fMRI

Fraser W. Smith, Lars Muckli, David Brennan, Cyril Pernet, Marie L. Smith, Pascal Belin, Frederic Gosselin, Donald M. Hadley, Jonathan Cavanagh, Philippe G. Schyns

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18 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)1643-1654
Number of pages12
Issue number4
Early online date1 Feb 2008
Publication statusPublished - 1 May 2008

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