Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A real-world size organization of object responses in occipitotemporal cortex.

ABSTRACT: While there are selective regions of occipitotemporal cortex that respond to faces, letters, and bodies, the large-scale neural organization of most object categories remains unknown. Here, we find that object representations can be differentiated along the ventral temporal cortex by their real-world size. In a functional neuroimaging experiment, observers were shown pictures of big and small real-world objects (e.g., table, bathtub; paperclip, cup), presented at the same retinal size. We observed a consistent medial-to-lateral organization of big and small object preferences in the ventral temporal cortex, mirrored along the lateral surface. Regions in the lateral-occipital, inferotemporal, and parahippocampal cortices showed strong peaks of differential real-world size selectivity and maintained these preferences over changes in retinal size and in mental imagery. These data demonstrate that the real-world size of objects can provide insight into the spatial topography of object representation.

SUBMITTER: Konkle T

PROVIDER: S-EPMC3391318 | biostudies-literature | 2012 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

A real-world size organization of object responses in occipitotemporal cortex.

Konkle Talia T Oliva Aude A

Neuron 20120601 6

While there are selective regions of occipitotemporal cortex that respond to faces, letters, and bodies, the large-scale neural organization of most object categories remains unknown. Here, we find that object representations can be differentiated along the ventral temporal cortex by their real-world size. In a functional neuroimaging experiment, observers were shown pictures of big and small real-world objects (e.g., table, bathtub; paperclip, cup), presented at the same retinal size. We observ ...[more]

PMID: 22726840

Similar Datasets

A neural basis for real-world visual search in human occipitotemporal cortex.

Project description:Mammals are highly skilled in rapidly detecting objects in cluttered natural environments, a skill necessary for survival. What are the neural mechanisms mediating detection of objects in natural scenes? Here, we use human brain imaging to address the role of top-down preparatory processes in the detection of familiar object categories in real-world environments. Brain activity was measured while participants were preparing to detect highly variable depictions of people or cars in natural scenes that were new to the participants. The preparation to detect objects of the target category, in the absence of visual input, evoked activity patterns in visual cortex that resembled the response to actual exemplars of the target category. Importantly, the selectivity of multivoxel preparatory activity patterns in object-selective cortex (OSC) predicted target detection performance. By contrast, preparatory activity in early visual cortex (V1) was negatively related to search performance. Additional behavioral results suggested that the dissociation between OSC and V1 reflected the use of different search strategies, linking OSC preparatory activity to relatively abstract search preparation and V1 to more specific imagery-like preparation. Finally, whole-brain searchlight analyses revealed that, in addition to OSC, response patterns in medial prefrontal cortex distinguished the target categories based on the search cues alone, suggesting that this region may constitute a top-down source of preparatory activity observed in visual cortex. These results indicate that in naturalistic situations, when the precise visual characteristics of target objects are not known in advance, preparatory activity at higher levels of the visual hierarchy selectively mediates visual search.

| S-EPMC3141945 | biostudies-literature

Evaluating the correspondence between face-, scene-, and object-selectivity and retinotopic organization within lateral occipitotemporal cortex.

Project description:The organization of human lateral occipitotemporal cortex (lOTC) has been characterized largely according to two distinct principles: retinotopy and category-selectivity. Whereas category-selective regions were originally thought to exist beyond retinotopic maps, recent evidence highlights overlap. Here, we combined detailed mapping of retinotopy, using population receptive fields (pRF), and category-selectivity to examine and contrast the retinotopic profiles of scene- (occipital place area, OPA), face- (occipital face area, OFA) and object- (lateral occipital cortex, LO) selective regions of lOTC. We observe striking differences in the relationship each region has to underlying retinotopy. Whereas OPA overlapped multiple retinotopic maps (including V3A, V3B, LO1, and LO2), and LO overlapped two maps (LO1 and LO2), OFA overlapped almost none. There appears no simple consistent relationship between category-selectivity and retinotopic maps, meaning category-selective regions are not constrained spatially to retinotopic map borders consistently. The multiple maps that overlap OPA suggests it is likely not appropriate to conceptualize it as a single scene-selective region, whereas the inconsistency in any systematic map overlapping OFA suggests it may constitute a more uniform area. Beyond their relationship to retinotopy, all three regions evidenced strongly retinotopic voxels, with pRFs exhibiting a significant bias towards the contralateral lower visual field, despite differences in pRF size, contributing to an emerging literature suggesting this bias is present across much of lOTC. Taken together, these results suggest that whereas category-selective regions are not constrained to consistently contain ordered retinotopic maps, they nonetheless likely inherit retinotopic characteristics of the maps from which they draw information.

| S-EPMC4898275 | biostudies-literature

Real-world size of objects serves as an axis of object space.

Project description:Our mind can represent various objects from physical world in an abstract and complex high-dimensional object space, with axes encoding critical features to quickly and accurately recognize objects. Among object features identified in previous neurophysiological and fMRI studies that may serve as the axes, objects' real-world size is of particular interest because it provides not only visual information for broad conceptual distinctions between objects but also ecological information for objects' affordance. Here we use deep convolutional neural networks (DCNNs), which enable direct manipulation of visual experience and units' activation, to explore how objects' real-world size is extracted to construct the axis of object space. Like the human brain, the DCNNs pre-trained for object recognition also encode objects' size as an independent axis of the object space. Further, we find that the shape of objects, rather than retinal size, context, task demands or texture features, is critical to inferring objects' size for both DCNNs and humans. In short, with DCNNs as a brain-like model, our study devises a paradigm supplemental to conventional approaches to explore the structure of object space, which provides computational support for empirical observations on human perceptual and neural representations of objects.

| S-EPMC9329427 | biostudies-literature

Object grouping based on real-world regularities facilitates perception by reducing competitive interactions in visual cortex.

Project description:In virtually every real-life situation humans are confronted with complex and cluttered visual environments that contain a multitude of objects. Because of the limited capacity of the visual system, objects compete for neural representation and cognitive processing resources. Previous work has shown that such attentional competition is partly object based, such that competition among elements is reduced when these elements perceptually group into an object based on low-level cues. Here, using functional MRI (fMRI) and behavioral measures, we show that the attentional benefit of grouping extends to higher-level grouping based on the relative position of objects as experienced in the real world. An fMRI study designed to measure competitive interactions among objects in human visual cortex revealed reduced neural competition between objects when these were presented in commonly experienced configurations, such as a lamp above a table, relative to the same objects presented in other configurations. In behavioral visual search studies, we then related this reduced neural competition to improved target detection when distracter objects were shown in regular configurations. Control studies showed that low-level grouping could not account for these results. We interpret these findings as reflecting the grouping of objects based on higher-level spatial-relational knowledge acquired through a lifetime of seeing objects in specific configurations. This interobject grouping effectively reduces the number of objects that compete for representation and thereby contributes to the efficiency of real-world perception.

| S-EPMC4121846 | biostudies-other

Coding of Object Size and Object Category in Human Visual Cortex.

Project description:A salient aspect of objects is their real-world size. Large objects tend to be fixed in the world and can act as navigational barriers and landmarks, whereas small objects tend to be moveable and manipulable. Previous work has identified regions of visual cortex that respond differentially to large versus small objects, but the role of size in organizing representations of object categories has not been fully explored. To address this issue, we scanned subjects while they viewed large and small objects drawn from 20 categories, with retinotopic extent equated across size classes. Univariate analyses replicated previous results showing a greater response to large than small objects in scene-responsive regions and the converse effect in the left occipitotemporal sulcus. Critically, multivariate analyses revealed organization-by-size both within and across functional regions, as evidenced by activation patterns that were more similar for object categories of the same size than for object categories of different size. This effect was observed in both scene- and object-responsive regions and across high-level visual cortex as a whole, but not in early visual cortex. We hypothesize that real-world size is an important dimension for object category organization because of the many ecologically significant differences between large and small objects.

| S-EPMC6059234 | biostudies-literature

Neural activity in human visual cortex is transformed by learning real world size.

Project description:The way that our brain processes visual information is directly affected by our experience. Repeated exposure to a visual stimulus triggers experience-dependent plasticity in the visual cortex of many species. Humans also have the unique ability to acquire visual knowledge through instruction. We introduced human participants to the real-world size of previously unfamiliar species, and to the functional motion of novel tools, during a functional magnetic resonance imaging scan. Using machine learning, we compared activity patterns evoked by images of the new items, before and after participants learned the animals' real-world size or tools' motion. We found that, after acquiring size information, participants' visual activity patterns for the new animals became more confusable with activity patterns evoked by similar-sized known animals in early visual cortex, but not in ventral temporal cortex, reflecting an influence of new size knowledge on posterior, but not anterior, components of the ventral stream. In contrast, learning the functional motion of new tools did not lead to an equivalent change in recorded activity. Finally, the time-points marked by evidence of new size information in early visual cortex were more likely to show size information and greater activation in the right angular gyrus, a key hub of semantic knowledge and spatial cognition. Overall, these findings suggest that learning an item's real-world size by instruction influences subsequent activity in visual cortex and in a region that is central to semantic and spatial brain systems.

| S-EPMC6345670 | biostudies-literature

Why is real-world visual object recognition hard?

Project description:Progress in understanding the brain mechanisms underlying vision requires the construction of computational models that not only emulate the brain's anatomy and physiology, but ultimately match its performance on visual tasks. In recent years, "natural" images have become popular in the study of vision and have been used to show apparently impressive progress in building such models. Here, we challenge the use of uncontrolled "natural" images in guiding that progress. In particular, we show that a simple V1-like model--a neuroscientist's "null" model, which should perform poorly at real-world visual object recognition tasks--outperforms state-of-the-art object recognition systems (biologically inspired and otherwise) on a standard, ostensibly natural image recognition test. As a counterpoint, we designed a "simpler" recognition test to better span the real-world variation in object pose, position, and scale, and we show that this test correctly exposes the inadequacy of the V1-like model. Taken together, these results demonstrate that tests based on uncontrolled natural images can be seriously misleading, potentially guiding progress in the wrong direction. Instead, we reexamine what it means for images to be natural and argue for a renewed focus on the core problem of object recognition--real-world image variation.

| S-EPMC2211529 | biostudies-literature

Different neural mechanisms within occipitotemporal cortex underlie repetition suppression across same and different-size faces.

Project description:Repetition suppression (RS) (or functional magnetic resonance imaging adaptation) refers to the reduction in blood oxygen level-dependent signal following repeated presentation of a stimulus. RS is frequently used to investigate the role of face-selective regions in human visual cortex and is commonly thought to be a "localized" effect, reflecting fatigue of a neuronal population representing a given stimulus. In contrast, predictive coding theories characterize RS as a consequence of "top-down" changes in between-region modulation. Differentiating between these accounts is crucial for the correct interpretation of RS effects in the face-processing network. Here, dynamic causal modeling revealed that different mechanisms underlie different forms of RS to faces in occipitotemporal cortex. For both familiar and unfamiliar faces, repetition of identical face images (same size) was associated with changes in "forward" connectivity between the occipital face area (OFA) and the fusiform face area (FFA) (OFA-to-FFA). In contrast, RS across image size was characterized by altered "backward" connectivity (FFA-to-OFA). In addition, evidence was higher for models in which information projected directly into both OFA and FFA, challenging the role of OFA as the input stage of the face-processing network. These findings suggest "size-invariant" RS to faces is a consequence of interactions between regions rather than being a localized effect.

| S-EPMC3615345 | biostudies-literature

Constructing scenes from objects in human occipitotemporal cortex.

Project description:We used functional magnetic resonance imaging (fMRI) to demonstrate the existence of a mechanism in the human lateral occipital (LO) cortex that supports recognition of real-world visual scenes through parallel analysis of within-scene objects. Neural activity was recorded while subjects viewed four categories of scenes and eight categories of 'signature' objects strongly associated with the scenes in three experiments. Multivoxel patterns evoked by scenes in the LO cortex were well predicted by the average of the patterns elicited by their signature objects. By contrast, there was no relationship between scene and object patterns in the parahippocampal place area (PPA), even though this region responds strongly to scenes and is believed to be crucial for scene identification. By combining information about multiple objects within a scene, the LO cortex may support an object-based channel for scene recognition that complements the processing of global scene properties in the PPA.

| S-EPMC6815103 | biostudies-literature

Relating retinotopic and object-selective responses in human lateral occipital cortex.

Project description:What is the relationship between retinotopy and object selectivity in human lateral occipital (LO) cortex? We used functional magnetic resonance imaging (fMRI) to examine sensitivity to retinal position and category in LO, an object-selective region positioned posterior to MT along the lateral cortical surface. Six subjects participated in phase-encoded retinotopic mapping experiments as well as block-design experiments in which objects from six different categories were presented at six distinct positions in the visual field. We found substantial position modulation in LO using standard nonobject retinotopic mapping stimuli; this modulation extended beyond the boundaries of visual field maps LO-1 and LO-2. Further, LO showed a pronounced lower visual field bias: more LO voxels represented the lower contralateral visual field, and the mean LO response was higher to objects presented below fixation than above fixation. However, eccentricity effects produced by retinotopic mapping stimuli and objects differed. Whereas LO voxels preferred a range of eccentricities lying mostly outside the fovea in the retinotopic mapping experiment, LO responses were strongest to foveally presented objects. Finally, we found a stronger effect of position than category on both the mean LO response, as well as the distributed response across voxels. Overall these results demonstrate that retinal position exhibits strong effects on neural response in LO and indicates that these position effects may be explained by retinotopic organization.

| S-EPMC2493478 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data