期刊
CEREBRAL CORTEX
卷 26, 期 8, 页码 3563-3579出版社
OXFORD UNIV PRESS INC
DOI: 10.1093/cercor/bhw135
关键词
fMRI; MEG; multimodal integration; representational similarity analysis; visual object recognition
资金
- National Eye Institute [EY020484]
- Google Research Faculty Award
- McGovern Institute Neurotechnology Program
- Humboldt Foundation
- Emmy Noether grant of the DFG CI [241/1-1]
- NEI [EY020484]
- Athinoula A. Martinos Imaging Center at the McGovern Institute for Brain Research, Massachusetts Institute of Technology
Every human cognitive function, such as visual object recognition, is realized in a complex spatio-temporal activity pattern in the brain. Current brain imaging techniques in isolation cannot resolve the brain's spatio-temporal dynamics, because they provide either high spatial or temporal resolution but not both. To overcome this limitation, we developed an integration approach that uses representational similarities to combine measurements of magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) to yield a spatially and temporally integrated characterization of neuronal activation. Applying this approach to 2 independent MEG-fMRI data sets, we observed that neural activity first emerged in the occipital pole at 50-80 ms, before spreading rapidly and progressively in the anterior direction along the ventral and dorsal visual streams. Further region-of-interest analyses established that dorsal and ventral regions showed MEG-fMRI correspondence in representations later than early visual cortex. Together, these results provide a novel and comprehensive, spatio-temporally resolved view of the rapid neural dynamics during the first few hundred milliseconds of object vision. They further demonstrate the feasibility of spatially unbiased representational similarity-based fusion of MEG and fMRI, promising new insights into how the brain computes complex cognitive functions.
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