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Yonsei Cognitive Science

Context-dependent visual object representation in human parietal cortex

 

일시: 2월 6일 (월) 오후 4시

장소: 위당관 209호

주관: 인지과학연구소 및 휴먼과학기술센터

연사: 정수근(Senior Researcher, Korea Brain Research Institute)

 

강연소개:

Both monkey neurophysiology and human fMRI studies have shown that in occipital-temporal cortex, neural response to multiple visual objects shown simultaneously can be reliably predicted by the averaged neural response of the component objects shown alone. Besides occipital-temporal cortex, visual object representation has also been shown in the primate parietal cortex. Does a similar representation for multiple visual objects exist in the primate parietal cortex? Using multi-voxel pattern analysis, we examined object representation in human inferior and superior intra-parietal sulcus (IPS), two parietal regions implicated in visual object individuation and identification, respectively. As a comparison, object shape processing region in lateral occipital (LO) cortex was also examined. The participants saw either a pair of objects shown above and below the fixation, or a single object shown either above or below the fixation. fMRI response patterns were extracted for object pairs and single objects. In all three regions, distinctive response patterns were found for the different single objects and object pairs, confirming visual object representation in these brain regions. Replicating previous findings, in LO, object pair patterns were indistinguishable from the averaged patterns of the component objects shown alone. In both inferior and superior IPS, however, object pair patterns differed significantly from the averaged patterns of the component objects. This difference could be attributed to task difference between single and pair object conditions, because the average of two object pairs was not distinguishable from the average of another two object pairs that contained the same four component objects but at different locations. Taken together, the representation of multiple objects can be predicted by linear addition of the representation of the components objects in human parietal cortex, but only under the same task context.

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