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Frank Tong, David J. Kim; Transformation from position-specific to position-invariant coding of objects across the human visual pathway. Journal of Vision 2005;5(8):91. doi: 10.1167/5.8.91.
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© ARVO (1962-2015); The Authors (2016-present)
Recent fMRI studies have shown that object categories can be distinguished based on the differential patterns of activity that they evoke in ventral temporal object areas (Haxby et al., 2001) and also retinotopic visual areas (Cox & Savoy, 2003). These results raise the question of whether successful object classification depends on neural representations of local low-level features or position-invariant properties of objects. We investigated if activity patterns in early visual areas and anterior ventral areas can effectively discriminate objects across changes in location. Subjects viewed stimuli from 8 different categories (e.g., chairs, faces, houses) in the left and right visual field. We performed correlational analyses to evaluate if different object categories could be reliably classified by comparing activity patterns on individual test trials to those observed on training trials. Activity patterns in areas V1–V3 were highly effective at classifying objects when training and test stimuli were presented at the same location (∼75% correct, chance 50%), but unable to classify objects reliably across changes in location. These results indicate that successful classification of objects presented at a single location may not necessarily indicate neural selectivity for object categories. Higher visual areas (V3A and V4) were equally effective at classifying objects presented in the same location or across locations (∼70% correct), indicating that position-invariant coding of object properties emerges at a remarkably early stage in the human visual pathway. Finally, anterior ventral areas also showed position-invariant classification with even higher levels performance (87% correct), consistent with the notion that ventral areas are important for flexible position-invariant coding of objects. Our results reveal a transformation across the human visual pathway, from position-specific coding of low-level features to position-invariant coding of object properties.
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