Asymmetric interference between the perception of shape and the perception of surface properties

Reciprocal interactions among parietal and occipito-temporal representations support everyday object-directed actions

Everyday interactions with common manipulable objects require the integration of conceptual knowledge about objects and actions with real-time sensory information about the position, orientation and volumetric structure of the grasp target. The ability to successfully interact with everyday objects involves analysis of visual form and shape, surface texture, material properties, conceptual attributes such as identity, function and typical context, and visuomotor processing supporting hand transport, grasp form, and object manipulation. Functionally separable brain regions across the dorsal and ventral visual pathways support the processing of these different object properties and, in cohort, are necessary for functional object use. Object-directed grasps display end-state-comfort: they anticipate in form and force the shape and material properties of the grasp target, and how the object will be manipulated after it is grasped. End-state-comfort is the default for everyday interactions with manipulable objects and implies integration of information across the ventral and dorsal visual pathways. We propose a model of how visuomotor and action representations in parietal cortex interact with object representations in ventral and lateral occipito-temporal cortex. One pathway, from the supramarginal gyrus to the middle and inferior temporal gyrus, supports the integration of action-related information, including hand and limb position (supramarginal gyrus) with conceptual attributes and an appreciation of the action goal (middle temporal gyrus). A second pathway, from posterior IPS to the fusiform gyrus and collateral sulcus supports the integration of grasp parameters (IPS) with the surface texture and material properties (e.g., weight distribution) of the grasp target. Reciprocal interactions among these regions are part of a broader network of regions that support everyday functional object interactions.

Shared cognitive mechanisms involved in the processing of scene texture and scene shape

Recent research has demonstrated that the parahippocampal place area represents both the shape and texture features of scenes, with the importance of each feature varying according to perceived scene category. Namely, shape features are predominately more diagnostic to the processing of artificial human–made scenes, while shape and texture are equally diagnostic in natural scene processing. However, to date little is known regarding the degree of interactivity or independence observed in the processing of these scene features. Furthermore, manipulating the scope of visual attention (i.e., globally vs. locally) when processing ensembles of multiple objects—stimuli that share a functional neuroanatomical link with scenes—has been shown to affect their cognitive visual representation. It remains unknown whether manipulating the scope of attention impacts scene processing in a similar manner. Using the well-established Garner speeded-classification behavioral paradigm, we investigated the influence of both feature diagnosticity and the scope of visual attention on potential interactivity or independence in the shape and texture processing of artificial human–made scenes. The results revealed asymmetric interference between scene shape and texture processing, with the more diagnostic feature (i.e., shape) interfering with the less diagnostic feature (i.e., texture), but not vice versa. Furthermore, this interference was attenuated and enhanced with more local and global visual processing strategies, respectively. These findings suggest that the scene shape and texture processing are mediated by shared cognitive mechanisms and that, although these representations are governed primarily via feature diagnosticity, they can nevertheless be influenced by the scope of visual attention.

Predicting how surface texture and shape combine in the human visual system to direct attention

Objects differ from one another along a multitude of visual features. The more distinct an object is from other objects in its surroundings, the easier it is to find it. However, it is still unknown how this distinctiveness advantage emerges in human vision. Here, we studied how visual distinctiveness signals along two feature dimensions—shape and surface texture—combine to determine the overall distinctiveness of an object in the scene. Distinctiveness scores between a target object and distractors were measured separately for shape and texture using a search task. These scores were then used to predict search times when a target differed from distractors along both shape and texture. Model comparison showed that the overall object distinctiveness was best predicted when shape and texture combined using a Euclidian metric, confirming the brain is computing independent distinctiveness scores for shape and texture and combining them to direct attention.

The material-weight illusion disappears or inverts in objects made of two materials

The material-weight illusion (MWI) occurs when an object that looks heavy (e.g., stone) and one that looks light (e.g., Styrofoam) have the same mass. When such stimuli are lifted, the heavier-looking object feels lighter than the lighter-looking object, presumably because well-learned priors about the density of different materials are violated. We examined whether a similar illusion occurs when a certain weight distribution is expected (such as the metal end of a hammer being heavier), but weight is uniformly distributed. In experiment 1, participants lifted bipartite objects that appeared to be made of two materials (combinations of stone, Styrofoam, and wood) but were manipulated to have a uniform weight distribution. Most participants experienced an inverted MWI (i.e., the heavier-looking side felt heavier), suggesting an integration of incoming sensory information with density priors. However, a replication of the classic MWI was found when the objects appeared to be uniformly made of just one of the materials (experiment 2). Both illusions seemed to be independent of the forces used when the objects were lifted. When lifting bipartite objects but asked to judge the weight of the whole object, participants experienced no illusion (experiment 3). In experiment 4, we investigated weight perception in objects with a nonuniform weight distribution and again found evidence for an integration of prior and sensory information. Taken together, our seemingly contradictory results challenge most theories about the MWI. However, Bayesian integration of competing density priors with the likelihood of incoming sensory information may explain the opposing illusions.

NEW & NOTEWORTHY We report a novel weight illusion that contradicts all current explanations of the material-weight illusion: When lifting an object composed of two materials, the heavier-looking side feels heavier, even when the true weight distribution is uniform. The opposite (classic) illusion is found when the same materials are lifted in two separate objects. Identifying the common mechanism underlying both illusions will have implications for perception more generally. A potential candidate is Bayesian inference with competing priors.

Getting a handle on virtual tools: An examination of the neuronal activity associated with virtual tool use

Tool use is associated with three visual streams-dorso-dorsal, ventro-dorsal, and ventral visual streams. These streams are involved in processing online motor planning, action semantics, and tool semantics features, respectively. Little is known about the way in which the brain represents virtual tools. To directly assess this question, a virtual tool paradigm was created that provided the ability to manipulate tool components in isolation of one another. During functional magnetic resonance imaging (fMRI), adult participants performed a series of virtual tool manipulation tasks in which vision and movement kinematics of the tool were manipulated. Reaction time and hand movement direction were monitored while the tasks were performed. Functional imaging revealed that activity within all three visual streams was present, in a similar pattern to what would be expected with physical tool use. However, a previously unreported network of right-hemisphere activity was found including right inferior parietal lobule, middle and superior temporal gyri and supramarginal gyrus - regions well known to be associated with tool processing within the left hemisphere. These results provide evidence that both virtual and physical tools are processed within the same brain regions, though virtual tools recruit bilateral tool processing regions to a greater extent than physical tools.

Color-Biased Regions of the Ventral Visual Pathway Lie between Face- and Place-Selective Regions in Humans, as in Macaques

The existence of color-processing regions in the human ventral visual pathway (VVP) has long been known from patient and imaging studies, but their location in the cortex relative to other regions, their selectivity for color compared with other properties (shape and object category), and their relationship to color-processing regions found in nonhuman primates remain unclear. We addressed these questions by scanning 13 subjects with fMRI while they viewed two versions of movie clips (colored, achromatic) of five different object classes (faces, scenes, bodies, objects, scrambled objects). We identified regions in each subject that were selective for color, faces, places, and object shape, and measured responses within these regions to the 10 conditions in independently acquired data. We report two key findings. First, the three previously reported color-biased regions (located within a band running posterior-anterior along the VVP, present in most of our subjects) were sandwiched between face-selective cortex and place-selective cortex, forming parallel bands of face, color, and place selectivity that tracked the fusiform gyrus/collateral sulcus. Second, the posterior color-biased regions showed little or no selectivity for object shape or for particular stimulus categories and showed no interaction of color preference with stimulus category, suggesting that they code color independently of shape or stimulus category; moreover, the shape-biased lateral occipital region showed no significant color bias. These observations mirror results in macaque inferior temporal cortex (Lafer-Sousa and Conway, 2013), and taken together, these results suggest a homology in which the entire tripartite face/color/place system of primates migrated onto the ventral surface in humans over the course of evolution.

SIGNIFICANCE STATEMENT

Here we report that color-biased cortex is sandwiched between face-selective and place-selective cortex on the bottom surface of the brain in humans. This face/color/place organization mirrors that seen on the lateral surface of the temporal lobe in macaques, suggesting that the entire tripartite system is homologous between species. This result validates the use of macaques as a model for human vision, making possible more powerful investigations into the connectivity, precise neural codes, and development of this part of the brain. In addition, we find substantial segregation of color from shape selectivity in posterior regions, as observed in macaques, indicating a considerable dissociation of the processing of shape and color in both species.

Distinct cognitive mechanisms involved in the processing of single objects and object ensembles

Behavioral research has demonstrated that the shape and texture of single objects can be processed independently. Similarly, neuroimaging results have shown that an object's shape and texture are processed in distinct brain regions with shape in the lateral occipital area and texture in parahippocampal cortex. Meanwhile, objects are not always seen in isolation and are often grouped together as an ensemble. We recently showed that the processing of ensembles also involves parahippocampal cortex and that the shape and texture of ensemble elements are processed together within this region. These neural data suggest that the independence seen between shape and texture in single-object perception would not be observed in object-ensemble perception. Here we tested this prediction by examining whether observers could attend to the shape of ensemble elements while ignoring changes in an unattended texture feature and vice versa. Across six behavioral experiments, we replicated previous findings of independence between shape and texture in single-object perception. In contrast, we observed that changes in an unattended ensemble feature negatively impacted the processing of an attended ensemble feature only when ensemble features were attended globally. When they were attended locally, thereby making ensemble processing similar to single-object processing, interference was abolished. Overall, these findings confirm previous neuroimaging results and suggest that distinct cognitive mechanisms may be involved in single-object and object-ensemble perception. Additionally, they show that the scope of visual attention plays a critical role in determining which type of object processing (ensemble or single object) is engaged by the visual system.

Human visual cortical responses to specular and matte motion flows

Determining the compositional properties of surfaces in the environment is an important visual capacity. One such property is specular reflectance, which encompasses the range from matte to shiny surfaces. Visual estimation of specular reflectance can be informed by characteristic motion profiles; a surface with a specular reflectance that is difficult to determine while static can be confidently disambiguated when set in motion. Here, we used fMRI to trace the sensitivity of human visual cortex to such motion cues, both with and without photometric cues to specular reflectance. Participants viewed rotating blob-like objects that were rendered as images (photometric) or dots (kinematic) with either matte-consistent or shiny-consistent specular reflectance profiles. We were unable to identify any areas in low and mid-level human visual cortex that responded preferentially to surface specular reflectance from motion. However, univariate and multivariate analyses identified several visual areas; V1, V2, V3, V3A/B, and hMT+, capable of differentiating shiny from matte surface flows. These results indicate that the machinery for extracting kinematic cues is present in human visual cortex, but the areas involved in integrating such information with the photometric cues necessary for surface specular reflectance remain unclear.

Scratching beneath the surface: new insights into the functional properties of the lateral occipital area and parahippocampal place area

We used fMRI on neurologically intact humans to investigate whether or not there are different neural substrates for the different kinds of information that a visual surface signals (shape from texture vs material properties from texture). Participants attended to differences in the shape (flat/convex), texture and color (wood/rock), or material properties (soft/hard) of a set of circular surfaces. Attending to shape activated the contour-sensitive lateral occipital (LO) area, and attending to texture activated a region of the collateral sulcus (CoS) that overlaps with the parahippocampal place area (PPA). Interestingly, attending to material properties activated the same texture-sensitive region in the CoS. These results demonstrate the existence of different neural substrates for the different types of information that a visual surface signals. With regard to object shape, the organization of the LO area may be complex, with neurons tuned not only to the outline shape of objects, but also to their surface curvature independent of contour. Moreover, to our knowledge, this is the first study to demonstrate that processing surface texture, which occurs within the scene-sensitive PPA, is a route to accessing knowledge about an object's material properties. With this in mind, we propose that models of visual cortical organization should focus not only on the particular stimulus category to which a region maximally responds (e.g., objects, scenes), but also on the stimulus attributes that best support the processing of that category (e.g., shape, texture, material properties).