Discovering Structure of Object Representation in the Ventral Visual Pathway from fMRI Data
The method does not make any assumptions about the spatial extent of the selective regions to avoid constraints on the space of possible selectivity patterns. Since no spatial information is used by the method, we can seamlessly analyze multi-subject data without spatial normalization of the subject...
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| Published in | NeuroImage (Orlando, Fla.) Vol. 47; p. S81 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Amsterdam
Elsevier Inc
01.07.2009
Elsevier Limited |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1053-8119 1095-9572 |
| DOI | 10.1016/S1053-8119(09)70581-6 |
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| Abstract | The method does not make any assumptions about the spatial extent of the selective regions to avoid constraints on the space of possible selectivity patterns. Since no spatial information is used by the method, we can seamlessly analyze multi-subject data without spatial normalization of the subjects. Conclusions We presented an exploratory method that enables automatic discovery of the patterns of category selectivity in the visual cortex. |
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| AbstractList | The method does not make any assumptions about the spatial extent of the selective regions to avoid constraints on the space of possible selectivity patterns. Since no spatial information is used by the method, we can seamlessly analyze multi-subject data without spatial normalization of the subjects. Conclusions We presented an exploratory method that enables automatic discovery of the patterns of category selectivity in the visual cortex. |
| Author | Lashkari, D Golland, P Kanwisher, NG Vul, E |
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| Title | Discovering Structure of Object Representation in the Ventral Visual Pathway from fMRI Data |
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