Spatial coding and invariance in object-selective cortex

Carlson, Thomas A.; Hogendoorn, Hinze; Fonteijn, Hubert; Verstraten, Frans A. J.

doi:10.1016/j.cortex.2009.08.015

Cited by 63 publications

(70 citation statements)

References 31 publications

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“…This suggests that location information not only in the dorsal but also in parts of the ventral stream might be used by the brain during perception (Edelman and Intrator 2000). Thus, our results provide further support for recent studies (MacEvoy and Epstein 2007;Sayres and Grill-Spector 2008;Schwarzlose et al 2008;Carlson et al 2009) that question the description of the ventral visual stream as invariant to changes in object location (Ungerleider and Mishkin 1982).…”

Section: The Role Of High-level Visual Cortex In Object Recognitionsupporting

confidence: 88%

“…In contrast, the role of highlevel ventral visual cortex in the representation of location during imagery remains unknown. Recent studies of object perception indicate that object location is represented in ventral visual cortex beyond low-level visual cortex (MacEvoy and Epstein 2007;Schwarzlose et al 2008;Sayres and GrillSpector 2008;Carlson et al 2009). Thus, here we asked whether perception and imagery share representations of location in low-and high-level ventral visual cortex.…”

Section: Introductionmentioning

confidence: 99%

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Imagery and Perception Share Cortical Representations of Content and Location

2011

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Section: The Role Of High-level Visual Cortex In Object Recognitionsupporting

confidence: 88%

Section: Introductionmentioning

confidence: 99%

Imagery and Perception Share Cortical Representations of Content and Location

2011

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“…The retinotopic layout of early visual cortex might not be sufficient if the visual system relies on spatiotopic coordinates. Finally, higher visual areas involved in object recognition are either position invariant (Rust & Dicarlo, 2010;Ito, Tamura, Fujita, & Tanaka, 1995;Logothetis & Pauls, 1995;Schwartz, Desimone, Albright, & Gross, 1983) or encode position information only in a very coarse manner (Carlson, Hogendoorn, Fonteijn, & Verstraten, 2011;Cichy, Chen, & Haynes, 2011;Macevoy & Epstein, 2007;DiCarlo & Maunsell, 2003). These findings suggest that later ventral areas, which are needed for object identification, have, at best, some location information.…”

Section: Introductionmentioning

confidence: 89%

“…We chose to present the objects to the left or right of fixation in different hemifields because this requires only coarse localization of the objects. Higher visual areas can reliably encode the hemifield locations of objects that they isolate (Carlson, Hogendoorn, Fonteijn et al, 2011;Cichy et al, 2011;Hemond, Kanwisher, & Op de Beeck, 2007;Macevoy & Epstein, 2007;DiCarlo & Maunsell, 2003). This allowed us to directly test the two hypotheses regarding the nature and time course of coarse location representation in the brain.…”

Section: Methodsmentioning

confidence: 99%

The Temporal Evolution of Coarse Location Coding of Objects: Evidence for Feedback

Chakravarthi

Carlson

Chaffin

et al. 2014

Journal of Cognitive Neuroscience

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Abstract■ Objects occupy space. How does the brain represent the spatial location of objects? Retinotopic early visual cortex has precise location information but can only segment simple objects. On the other hand, higher visual areas can resolve complex objects but only have coarse location information. Thus coarse location of complex objects might be represented by either (a) feedback from higher areas to early retinotopic areas or (b) coarse position encoding in higher areas. We tested these alternatives by presenting various kinds of first-(edgedefined) and second-order (texture) objects. We applied multivariate classifiers to the pattern of EEG amplitudes across the scalp at a range of time points to trace the temporal dynamics of coarse location representation. For edge-defined objects, peak classification performance was high and early and thus attributable to the retinotopic layout of early visual cortex. For texture objects, it was low and late. Crucially, despite these differences in peak performance and timing, training a classifier on one object and testing it on others revealed that the topography at peak performance was the same for both first-and second-order objects. That is, the same location information, encoded by early visual areas, was available for both edge-defined and texture objects at different time points. These results indicate that locations of complex objects such as textures, although not represented in the bottom-up sweep, are encoded later by neural patterns resembling the bottom-up ones. We conclude that feedback mechanisms play an important role in coarse location representation of complex objects. ■

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“…The shape-relevant region was based in lateral occipital cortex, an area with location-tolerant shape information (Eger et al 2008;Carlson et al 2011). Previous research has shown that this region is modulated by top-down processing (Stokes et al 2009;Reddy et al 2010).…”

Section: Regions Of Interestmentioning

confidence: 99%

Creating Concepts from Converging Features in Human Cortex

2014

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To make sense of the world around us, our brain must remember the overlapping features of millions of objects. Crucially, it must also represent each object's unique feature-convergence. Some theories propose that an integration area (or "convergence zone") binds together separate features. We report an investigation of our knowledge of objects' features and identity, and the link between them. We used functional magnetic resonance imaging to record neural activity, as humans attempted to detect a cued fruit or vegetable in visual noise. Crucially, we analyzed brain activity before a fruit or vegetable was present, allowing us to interrogate top-down activity. We found that pattern-classification algorithms could be used to decode the detection target's identity in the left anterior temporal lobe (ATL), its shape in lateral occipital cortex, and its color in right V4. A novel decoding-dependency analysis revealed that identity information in left ATL was specifically predicted by the temporal convergence of shape and color codes in early visual regions. People with stronger feature-and-identity dependencies had more similar top-down and bottom-up activity patterns. These results fulfill three key requirements for a neural convergence zone: a convergence result (object identity), ingredients (color and shape), and the link between them.

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Spatial coding and invariance in object-selective cortex

Cited by 63 publications

References 31 publications

Imagery and Perception Share Cortical Representations of Content and Location

Imagery and Perception Share Cortical Representations of Content and Location

The Temporal Evolution of Coarse Location Coding of Objects: Evidence for Feedback

Creating Concepts from Converging Features in Human Cortex

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