Dataset Information

A sharp image or a sharp knife: norms for the modality-exclusivity of 774 concept-property items.

ABSTRACT: According to recent embodied cognition theories, mental concepts are represented by modality-specific sensory-motor systems. Much of the evidence for modality-specificity in conceptual processing comes from the property-verification task. When applying this and other tasks, it is important to select items based on their modality-exclusivity. We collected modality ratings for a set of 387 properties, each of which was paired with two different concepts, yielding a total of 774 concept-property items. For each item, participants rated the degree to which the property could be experienced through five perceptual modalities (vision, audition, touch, smell, and taste). Based on these ratings, we computed a measure of modality exclusivity, the degree to which a property is perceived exclusively through one sensory modality. In this paper, we briefly sketch the theoretical background of conceptual knowledge, discuss the use of the property-verification task in cognitive research, provide our norms and statistics, and validate the norms in a memory experiment. We conclude that our norms are important for researchers studying modality-specific effects in conceptual processing.

SUBMITTER: van Dantzig S

PROVIDER: S-EPMC3048290 | biostudies-literature | 2011 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A sharp image or a sharp knife: norms for the modality-exclusivity of 774 concept-property items.

van Dantzig Saskia S Cowell Rosemary A RA Zeelenberg René R Pecher Diane D

Behavior research methods 20110301 1

According to recent embodied cognition theories, mental concepts are represented by modality-specific sensory-motor systems. Much of the evidence for modality-specificity in conceptual processing comes from the property-verification task. When applying this and other tasks, it is important to select items based on their modality-exclusivity. We collected modality ratings for a set of 387 properties, each of which was paired with two different concepts, yielding a total of 774 concept-property it ...[more]

PMID: 21287109

Similar Datasets

Project description:The Leksell GammaPlan software version 10 introduces a CT image-based segmentation tool for automatic skull definition and a convolution dose calculation algorithm for tissue inhomogeneity correction. The purpose of this work was to evaluate the impact of these new approaches on routine clinical Gamma Knife treatment planning. Sixty-five patients who underwent CT image-guided Gamma Knife radiosurgeries at the University of Pittsburgh Medical Center in recent years were retrospectively investigated. The diagnoses for these cases include trigeminal neuralgia, meningioma, acoustic neuroma, AVM, glioma, and benign and metastatic brain tumors. Dose calculations were performed for each patient with the same dose prescriptions and the same shot arrangements using three different approaches: 1) TMR 10 dose calculation with imaging skull definition; 2) convolution dose calculation with imaging skull definition; 3) TMR 10 dose calculation with conventional measurement-based skull definition. For each treatment matrix, the total treatment time, the target coverage index, the selectivity index, the gradient index, and a set of dose statistics parameters were compared between the three calculations. The dose statistics parameters investigated include the prescription isodose volume, the 12 Gy isodose volume, the minimum, maximum and mean doses on the treatment targets, and the critical structures under consideration. The difference between the convolution and the TMR 10 dose calculations for the 104 treatment matrices were found to vary with the patient anatomy, location of the treatment shots, and the tissue inhomogeneities around the treatment target. An average difference of 8.4% was observed for the total treatment times between the convolution and the TMR algorithms. The maximum differences in the treatment times, the prescription isodose volumes, the 12 Gy isodose volumes, the target coverage indices, the selectivity indices, and the gradient indices from the convolution and the TMR 10 calculations are 14.9%, 16.4%, 11.1%, 16.8, 6.9%, and 11.4%, respectively. The maximum differences in the minimum and the mean target doses between the two calculation algorithms are 8.1% and 4.2% of the corresponding prescription doses. The maximum differences in the maximum and the mean doses for the critical structures between the two calculation algorithms are 1.3 Gy and 0.7 Gy. The results from the two skull definition methods with the TMR 10 algorithm agree either within ± 2.5% or 0.3 Gy for the dose values, except for a 4.9% difference in the treatment times for a lower cerebellar lesion. The imaging skull definition method does not affect Gamma Knife dose calculation considerably when compared to the conventional measurement-based skull definition method, except in some extreme cases. Large differences were observed between the TMR 10 and the convolution calculation method for the same dose prescription and the same shot arrangements, indicating that the implementation of the convolution algorithm in routine clinical use might be desirable for optimal dose calculation results.

Project description:BackgroundInducible defenses are a common and widespread form of phenotypic plasticity. A fundamental factor driving their evolution is an unpredictable and heterogeneous predation pressure. This heterogeneity is often used synonymously to quantitative changes in predation risk, depending on the abundance and impact of predators. However, differences in 'modality', that is, the qualitative aspect of natural selection caused by predators, can also cause heterogeneity. For instance, predators of the small planktonic crustacean Daphnia have been divided into two functional groups of predators: vertebrates and invertebrates. Predators of both groups are known to cause different defenses, yet predators of the same group are considered to cause similar responses. In our study we question that thought and address the issue of how multiple predators affect the expression and evolution of inducible defenses.ResultsWe exposed D. barbata to chemical cues released by Triops cancriformis and Notonecta glauca, respectively. We found for the first time that two invertebrate predators induce different shapes of the same morphological defensive traits in Daphnia, rather than showing gradual or opposing reaction norms. Additionally, we investigated the adaptive value of those defenses in direct predation trials, pairing each morphotype (non-induced, Triops-induced, Notonecta-induced) against the other two and exposed them to one of the two predators. Interestingly, against Triops, both induced morphotypes offered equal protection. To explain this paradox we introduce a 'concept of modality' in multipredator regimes. Our concept categorizes two-predator-prey systems into three major groups (functionally equivalent, functionally inverse and functionally diverse). Furthermore, the concept includes optimal responses and costs of maladaptions of prey phenotypes in environments where both predators co-occur or where they alternate.ConclusionWith D. barbata, we introduce a new multipredator-prey system with a wide array of morphological inducible defenses. Based on a 'concept of modality', we give possible explanations how evolution can favor specialized defenses over a general defense. Additionally, our concept not only helps to classify different multipredator-systems, but also stresses the significance of costs of phenotype-environment mismatching in addition to classic 'costs of plasticity'. With that, we suggest that 'modality' matters as an important factor in understanding and explaining the evolution of inducible defenses.

Dataset Information

A sharp image or a sharp knife: norms for the modality-exclusivity of 774 concept-property items.

Publications

A sharp image or a sharp knife: norms for the modality-exclusivity of 774 concept-property items.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets