Haptic Shape Processing in Visual Cortex

2014 ◽  
Vol 26 (5) ◽  
pp. 1154-1167 ◽  
Author(s):  
Jacqueline C. Snow ◽  
Lars Strother ◽  
Glyn W. Humphreys

Humans typically rely upon vision to identify object shape, but we can also recognize shape via touch (haptics). Our haptic shape recognition ability raises an intriguing question: To what extent do visual cortical shape recognition mechanisms support haptic object recognition? We addressed this question using a haptic fMRI repetition design, which allowed us to identify neuronal populations sensitive to the shape of objects that were touched but not seen. In addition to the expected shape-selective fMRI responses in dorsal frontoparietal areas, we observed widespread shape-selective responses in the ventral visual cortical pathway, including primary visual cortex. Our results indicate that shape processing via touch engages many of the same neural mechanisms as visual object recognition. The shape-specific repetition effects we observed in primary visual cortex show that visual sensory areas are engaged during the haptic exploration of object shape, even in the absence of concurrent shape-related visual input. Our results complement related findings in visually deprived individuals and highlight the fundamental role of the visual system in the processing of object shape.

2019 ◽  
Vol 31 (9) ◽  
pp. 1354-1367
Author(s):  
Yael Holzinger ◽  
Shimon Ullman ◽  
Daniel Harari ◽  
Marlene Behrmann ◽  
Galia Avidan

Visual object recognition is performed effortlessly by humans notwithstanding the fact that it requires a series of complex computations, which are, as yet, not well understood. Here, we tested a novel account of the representations used for visual recognition and their neural correlates using fMRI. The rationale is based on previous research showing that a set of representations, termed “minimal recognizable configurations” (MIRCs), which are computationally derived and have unique psychophysical characteristics, serve as the building blocks of object recognition. We contrasted the BOLD responses elicited by MIRC images, derived from different categories (faces, objects, and places), sub-MIRCs, which are visually similar to MIRCs, but, instead, result in poor recognition and scrambled, unrecognizable images. Stimuli were presented in blocks, and participants indicated yes/no recognition for each image. We confirmed that MIRCs elicited higher recognition performance compared to sub-MIRCs for all three categories. Whereas fMRI activation in early visual cortex for both MIRCs and sub-MIRCs of each category did not differ from that elicited by scrambled images, high-level visual regions exhibited overall greater activation for MIRCs compared to sub-MIRCs or scrambled images. Moreover, MIRCs and sub-MIRCs from each category elicited enhanced activation in corresponding category-selective regions including fusiform face area and occipital face area (faces), lateral occipital cortex (objects), and parahippocampal place area and transverse occipital sulcus (places). These findings reveal the psychological and neural relevance of MIRCs and enable us to make progress in developing a more complete account of object recognition.


2020 ◽  
Vol 14 (4) ◽  
pp. 1-15
Author(s):  
J. Farley Norman

In contrast to many machine vision systems, we human observers can readily recognize solid objects and visually discriminate their 3-D shapes even under changes in viewpoint and variations in object orientation and lighting.  While the importance of binocular disparity has been known since the 1830's, the importance and perceptual informativeness of visual contours for object recognition and discrimination is not adequately appreciated.  This article will review those scientific contributions that demonstrate that visual contours and their deformations over time (in response to object or observer motion) carry as much or more information about object shape than other forms of visual information.


2020 ◽  
Author(s):  
Jiaming Hu ◽  
Xue Mei Song ◽  
Qiannan Wang ◽  
Anna Wang Roe

AbstractAn important aspect of visual object recognition is the ability to perceive object shape. How the brain encodes fundamental aspects of shape information remains poorly understood. Models of object shape representation describe a multi-stage process that includes encoding of contour orientation and curvature. While modules encoding contour orientation are well established (orientation domains in V1 and V2 visual cortical areas), whether there are modules for curvature is unknown. In this study, we identify a module for curvature representation in area V4 of monkey visual cortex and illustrate a systematic representation of low to high curvature and of curvature orientation, indicative of curvature hypercolumns in V4. We suggest that identifying systematic modular organizations at each stage of the visual cortical hierarchy signifies the key computations performed.SignificanceWe use intrinsic signal optical imaging in area V4 of anesthetized macaque monkey to study the functional organization of curvature representation. We find a modular basis for cue-invariant curvature representation in area V4 of monkey visual cortex and illustrate a systematic representation from low to high curvature and of curvature orientation, replete with curvature pinwheels. This is the first report of systematic functional organization for curvature representation in the visual system. The use of optical imaging has revealed at a population level spatial details of cortical responses, something which has not been evident from previous studies of single neurons. These data support a representational architecture underlying a ‘curvature hypercolumn’ in V4.


2007 ◽  
Author(s):  
K. Suzanne Scherf ◽  
Marlene Behrmann ◽  
Kate Humphreys ◽  
Beatriz Luna

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