Processing Objects at Different Levels of Specificity

Tyler, Lorraine K.; Stamatakis, Emmanuel A.; Bright, Peter; Acres, Kadia; Abdallah, Samer A.; Rodd, Jennifer M; Moss, Helen E.

doi:10.1162/089892904322926692

Cited by 246 publications

(220 citation statements)

References 49 publications

Supporting

Mentioning

196

Contrasting

Unclassified

Order By: Relevance

“…Some of these features refer to visual features (e.g., has eyes, has tail), whereas others refer to nonvisual properties (e.g., growls, hunts). Recent fMRI studies have demonstrated greater perirhinal cortex activation during the visual processing of living compared with nonliving things, consistent with a role of this structure in complex visual integration processes necessary to discriminate and identify more visually complex living objects (7,8). However, the category effect in the crossmodal Fig.…”

Section: Discussionmentioning

confidence: 68%

“…Lerner et al (6) demonstrated that the sensitivity of ventral occipitotemporal regions to the scrambling of car images increased significantly from posterior (V1, V2, V3, V4͞V8) to more anteriorly situated sites (lateral occipital sulcus and posterior fusiform gyrus; lateral occipital complex), with scrambled images predicting activity in more posterior sites and intact images predicting activity in the more anterior regions. The hypothesized role of anteromedial structures in complex visual discriminations was confirmed in another series of fMRI experiments and in neuropsychological studies with brain-damaged patients (7,8). In the fMRI studies, tasks that did not require complex feature conjunctions (e.g., distinguishing living from nonliving things, which can be accomplished on the basis of general featural differences, such as curvature) only activated posterior temporal and occipital regions, whereas tasks that required complex conjunctions of features (e.g., the combination of features necessary to distinguish between highly similar objects, such as a lion and a tiger) additionally activated the anteromedial temporal lobe, including the perirhinal cortex.…”

mentioning

confidence: 71%

“…Importantly, activity in the perirhinal cortex was also greater during the crossmodal integration of living compared with nonliving things. A number of studies have shown that living things have many more features than nonliving things and that living things share more features with one another than nonliving things (7,8). Some of these features refer to visual features (e.g., has eyes, has tail), whereas others refer to nonvisual properties (e.g., growls, hunts).…”

Section: Discussionmentioning

confidence: 99%

“…Because these crossmodal sets of features must be integrated with one another to perform the task, we predicted that the greater size and ambiguity of the sets of semantic features associated with living things would tax the crossmodal integration processes of the perirhinal cortex (18) to a greater extent than those of nonliving things, leading to increased perirhinal cortex activity. The unimodal visual baseline task ensured that the perirhinal cortex activity could be attributed to the complexity of crossmodal, and not only intramodal, visual feature integration processes (8).…”

mentioning

confidence: 99%

See 3 more Smart Citations

Binding crossmodal object features in perirhinal cortex

Taylor

Moss

Stamatakis

et al. 2006

Proc. Natl. Acad. Sci. U.S.A.

233

226

View full text Add to dashboard Cite

Knowledge of objects in the world is stored in our brains as rich, multimodal representations. Because the neural pathways that process this diverse sensory information are largely anatomically distinct, a fundamental challenge to cognitive neuroscience is to explain how the brain binds the different sensory features that comprise an object to form meaningful, multimodal object representations. Studies with nonhuman primates suggest that a structure at the culmination of the object recognition system (the perirhinal cortex) performs this critical function. In contrast, human neuroimaging studies implicate the posterior superior temporal sulcus (pSTS). The results of the functional MRI study reported here resolve this apparent discrepancy by demonstrating that both pSTS and the perirhinal cortex contribute to crossmodal binding in humans, but in different ways. Significantly, only perirhinal cortex activity is modulated by meaning variables (e.g., semantic congruency and semantic category), suggesting that these two regions play complementary functional roles, with pSTS acting as a presemantic, heteromodal region for crossmodal perceptual features, and perirhinal cortex integrating these features into higher-level conceptual representations. This interpretation is supported by the results of our behavioral study: Patients with lesions, including the perirhinal cortex, but not patients with damage restricted to frontal cortex, were impaired on the same crossmodal integration task, and their performance was significantly influenced by the same semantic factors, mirroring the functional MRI findings. These results integrate nonhuman and human primate research by providing converging evidence that human perirhinal cortex is also critically involved in processing meaningful aspects of multimodal object representations.conceptual knowledge ͉ hierarchical object processing ͉ ventral stream A major outstanding question in the cognitive neurosciences is how different unimodal object features are integrated into coherent, multimodal object representations. Hierarchical models of object processing based on studies with nonhuman primates suggest that the perirhinal cortex, located at the culmination of the ventral occipitotemporal object-processing stream, performs this critical function. Within this stream, increasingly more complex combinations of visual object features are processed from posterior to anterior ventral temporal lobe sites (1-3), with perirhinal cortex of the anteromedial temporal lobe integrating the most complex combinations of features required for fine-grained visual discriminations between objects (4, 5). Recent functional MRI (fMRI) and lesion studies generally support this model in the human system. Lerner et al. (6) demonstrated that the sensitivity of ventral occipitotemporal regions to the scrambling of car images increased significantly from posterior (V1, V2, V3, V4͞V8) to more anteriorly situated sites (lateral occipital sulcus and posterior fusiform gyrus; lateral occipital complex), with scr...

show abstract

Section: Discussionmentioning

confidence: 68%

mentioning

confidence: 71%

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Binding crossmodal object features in perirhinal cortex

Taylor

Moss

Stamatakis

et al. 2006

Proc. Natl. Acad. Sci. U.S.A.

233

226

View full text Add to dashboard Cite

show abstract

“…Previous studies have compared object-naming activation to reading [Bookheimer et al, 1995;Moore and Price, 1999b], color naming [Price et al, 1996], verbal fluency [Etard et al, 2000], semantic categorization [Tyler et al, 2004], or a range of baselines [Murtha et al, 1999]. Other studies have investigated how the activation pattern changes for overt and covert naming [Zelkowicz et al, 1998], for object category [Chao et al, 1999[Chao et al, , 2002Chao and Martin, 2000;Damasio et al, 1996;Grabowski et al, 1998;Kawashima et al, 2001;Martin et al, 1996;Moore and Price, 1999a;Smith et al, 2001], by scanning modality [Votaw et al, 1999], across languages [Vingerhoets et al, 2003], with name agreement [Kan and Thompson-Schill, 2004], with gender of subjects [Grabowski et al, 2003], and during object learning [van Turennout et al, 2000[van Turennout et al, , 2003.…”

Section: Introductionmentioning

confidence: 99%

Meta‐analyses of object naming: Effect of baseline

Price¹,

Devlin²,

Moore³

et al. 2005

Human Brain Mapping

180

128

View full text Add to dashboard Cite

Abstract:The neural systems sustaining object naming were examined using the activation likelihood estimation (ALE) meta-analysis approach on the results of 16 previously published studies. The activation task in each study required subjects to name pictures of objects or animals, but the baseline tasks varied. Separate meta-analyses were carried out on studies that used: (1) high-level baselines to control for speech processing and visual input; and (2) low-level baselines that did not control for speech or complex visual processing. The results of the two meta-analyses were then compared directly, revealing a double dissociation in the activation pattern for studies using high and low baselines. To interpret the differential activations, we report two new functional imaging experiments. The aim of the first was to characterize activation differences associated with visual stimuli that are typically used in baseline conditions (complex visual features, simple structures, or fixation). The aim of the second was to classify object-naming regions in terms of whether they were engaged preferentially by semantic or phonological processes. The results reveal a remarkably precise correspondence between the areas identified by the meta-analyses as affected differentially by baseline and the areas that are affected differentially by non-object structure, semantics or phonology. As expected, high-level baselines reduced object-naming activation in areas associated with the processing of complex visual features and speech production. In addition, high-level baselines increased sensitivity to activation in areas associated with semantic processing, visual-speech integration and response selection. For example, activation in the anterior temporal areas that neuropsychological studies have associated with semantic processing was more strongly activated in the context of high-level baselines. These results therefore have implications for understanding the convergence of functional imaging and neuropsychological findings. Hum Brain Mapp 25:70 -82, 2005.

show abstract

Semantic Memory

Yee¹,

Jones

Masamune

2018

Stevens' Handbook of Experimental Psychology and Cognitive Neuroscience

View full text Add to dashboard Cite

How is it that we know what a dog and a tree are, or, for that matter, what knowledge is? Our semantic memory consists of knowledge about the world, including concepts, facts, and beliefs. This knowledge is essential for recognizing entities and objects, and for making inferences and predictions about the world. In essence, our semantic knowledge determines how we understand and interact with the world around us. In this chapter, we examine semantic memory from cognitive, sensorimotor, cognitive neuroscientific, and computational perspectives. We consider the cognitive and neural processes (and biases) that allow people to learn and represent concepts, and discuss how and where in the brain sensory and motor information may be integrated to allow for the perception of a coherent “concept.” We suggest that our understanding of semantic memory can be enriched by considering how semantic knowledge develops across the life span within individuals.

show abstract

Processing Objects at Different Levels of Specificity

Cited by 246 publications

References 49 publications

Binding crossmodal object features in perirhinal cortex

Binding crossmodal object features in perirhinal cortex

Meta‐analyses of object naming: Effect of baseline

Semantic Memory

Contact Info

Product

Resources

About