Classification images reveal the information sensitivity of brain voxels in fMRI.

Smith, Fraser W., Muckli, Lars, Brennan, David, Pernet, Cyril, Smith, Marie L., Belin, Pascal, Gosselin, Frederic, Hadley, Donald M., Cavanagh, Jonathan and Schyns, Philippe G. (2008) Classification images reveal the information sensitivity of brain voxels in fMRI. NeuroImage, 40 (4). pp. 1643-1654. ISSN 1053-8119

Full text not available from this repository. (Request a copy)

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.

Item Type: Article
Faculty \ School: Faculty of Social Sciences > School of Psychology
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 21 Aug 2021 00:11
Last Modified: 25 Aug 2021 09:54
URI: https://ueaeprints.uea.ac.uk/id/eprint/81165
DOI: 10.1016/j.neuroimage.2008.01.029

Actions (login required)

View Item View Item