Cortical Regions Involved in Perceiving Object Shape

By Zoe Kourtzi, Nancy Kanwisher. 2000

707 citations recorded by the source corpus.

The studies described here use functional magnetic resonance imaging to test whether common or distinct cognitive and/or neural mechanisms are involved in extracting object structure from the different image cues defining an object's shape, such as contours, shading, and monocular depth cues. We found overlapping activations in the lateral and ventral occipital cortex [known as the lateral occipital complex (LOC)] for objects defined by different visual cues (e.g., grayscale photographs and line drawings) when each was compared with its own scrambled-object control. In a second experiment we found a reduced response when objects were repeated, independent of whether they appeared in the same or a different format (i.e., grayscale images vs line drawings). A third experiment showed that activation in the LOC was no stronger for three-dimensional shapes defined by contours or monocular depth cues, such as occlusion, than for two-dimensional shapes, suggesting that these regions are not selectively involved in processing three-dimensional shape information. These results suggest that common regions in the LOC are involved in extracting and/or representing information about object structure from different image cues.

Subfields: Cognitive Neuroscience

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Citations in the corpus

This Looks Like That, Because ... Explaining Prototypes for Interpretable Image Recognition (2020, background): “Research in neuroscience therefore also emphasizes the importance of texture for classifying objects in the natural world [8, 23].”
Deep image reconstruction from human brain activity (2017, methodology): “The lateral occipital complex (LOC), the fusiform face area (FFA), and the parahippocampal place area (PPA) were identified using conventional functional localizers (Kanwisher et al., 1997; Kourtzi and Kanwisher, 2000; Epstein & Kanwisher, 1998).”
The lateral occipital complex and its role in object recognition. (2001, methodology): “To test these hypotheses, Kourtzi and Kanwisher (2000b) asked whether adaptation in the LOC would be observed for (a) objects that have the same shape but different contours and (b) objects that have different shape but share the same contours.”
Perceived Shape Similarity among Unfamiliar Objects and the Organization of the Human Object Vision Pathway (2008, background): “The overall LOC response depends on the perception of a coherent object shape (Grill-Spector et al., 1998a; Kourtzi and Kanwisher, 2000, 2001; Lerner et al., 2002; Hayworth and Biederman, 2006), and the shape representations in LOC are relatively invariant to image transformations such as size,…”
Repetition and the brain: neural models of stimulus-specific effects. (2006, methodology): “46], object format [ 36 ], perceived shape [79], contour completion [48] and face representation [7,80,81].”
The neural basis of object perception. (2003, background): “Other studies have shown that activation of object-selective areas is independent of object format (gray-scale or line drawings [28,29]) and these regions are also activated when subjects perceived simple shapes that are defined with illusory contours [30].”
Charting the Lower Superior Temporal Region, a New Motion-Sensitive Region in Monkey Superior Temporal Sulcus (2006, methodology): “In the moving shapes test (M3 and M5, each 3600 volumes in one or two sessions ), we used the grayscale images from the study by Kourtzi and Kanwisher (2000) (see also Denys et al., 2004), but they were reduced in size to 7° diameter.”
Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence (2016, background): “…object selective responses in dorsal stream in monkeys 37,38 and humans 39,40 , it is still debated whether dorsal visual representations are better explained by differential motor action associations or ability to engage attention, rather than category membership or shape representation 41,42 .”
Comparative mapping of higher visual areas in monkeys and humans. (2004, methodology): “scrambled greyscale (SG) images and intact (L) and scrambled (SL) drawings of objects (stimuli used in [ 38 ]) in V1 and inferotemporal cortex (IT) of the monkey (c) and V1 and lateral occipital complex (LOC) of humans (d).”
Neuroimaging studies of priming. (2003, methodology): “The issue of repetition lag (the interval between prime and target) is relevant to the use repetition suppression as a tool because some studies have used immediate repetition (with no intervening stimuli, e.g. Grill-Spector et al., 1999; Kourtzi and Kanwisher, 2000), whereas others have used long-l”
The human visual cortex. (2004, background): “Other studies have shown that activation is independent of object format [gray scale or line drawing (Ishai et al. 2000)] and that these regions are also activated when subjects perceived simple shapes created via illusory contours (Kourtzi & Kanwisher 2000, Mendola 1999, Stanley & Rubin 2003).”
Neural Decoding of Visual Imagery During Sleep (2013, methodology): “Region of interest (ROI) selection V1, V2, and V3 were delineated in the standard retinotopy experiment (38, 39), and the lateral occipital complex (LOC), the fusiform face area (FFA), and the parahippocampal place area (PPA) were identified using conventional functional localizers (22, 23, 40).”