The Typicality Ranking Task: A New Method to Derive Typicality Judgments from Children.
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ABSTRACT:
SUBMITTER: Djalal FM
PROVIDER: S-EPMC4913967 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The typicality effect during categorization describes a phenomenon whereby typical items are more easily judged as members of a category than atypical items. Prior studies of the typicality effect have often used an inclusion task, which asks participants to assess whether an item belongs to a category. However, the correct exclusion of non-members is also an important component of effective categorization, which has yet to be directly investigated. Thus, the present study investigated how categorization method (inclusion vs. exclusion) modulates the typicality effect via behavioral and electrophysiological measures. Thirty-two participants (16 in the inclusion and 16 in the exclusion group) were shown six consecutive words that all shared one feature. Then, a seventh word was presented. The inclusion group judged whether the seventh word also possessed the feature, whereas the exclusion group judged whether the word did not possess the feature. The seventh word could be typical, atypical, or a nonmember of the category. Behavioral and event-related potential (ERP) data were collected. Behavioral results showed that the two groups did not differ in accuracy. However, typical items elicited shorter response times than atypical items, and this effect was more pronounced in the inclusion than the exclusion group. With regard to ERPs, interactions between item type and group were shown for the P2, N2, and N400 periods. Within the inclusion group, a typicality effect (indicated by a main effect of item type) was present in the P2 and N400 time windows, while the exclusion group elicited a typicality effect only in the N2 time window. These results provide electrophysiological evidence that an inclusion judgment task is more sensitive to category typicality than is an exclusion task.
| S-EPMC4756294 | biostudies-literature
Project description:Musical rhythm and the grammatical structure of language share a surprising number of characteristics that may be intrinsically related in child development. The current study aimed to understand the potential influence of musical rhythmic priming on subsequent spoken grammar task performance in children with typical development who were native speakers of English. Participants (ages 5-8?years) listened to rhythmically regular and irregular musical sequences (within-participants design) followed by blocks of grammatically correct and incorrect sentences upon which they were asked to perform a grammaticality judgment task. Rhythmically regular musical sequences improved performance in grammaticality judgment compared with rhythmically irregular musical sequences. No such effect of rhythmic priming was found in two nonlinguistic control tasks, suggesting a neural overlap between rhythm processing and mechanisms recruited during grammar processing. These findings build on previous research investigating the effect of rhythmic priming by extending the paradigm to a different language, testing a younger population, and employing nonlanguage control tasks. These findings of an immediate influence of rhythm on grammar states (temporarily augmented grammaticality judgment performance) also converge with previous findings of associations between rhythm and grammar traits (stable generalized grammar abilities) in children. Taken together, the results of this study provide additional evidence for shared neural processing for language and music and warrant future investigations of potentially beneficial effects of innovative musical material on language processing.
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Project description:In the present research, we took advantage of geometric morphometrics to propose a data-driven method for estimating the individual degree of facial typicality/distinctiveness for cross-cultural (and other cross-group) comparisons. Looking like a stranger in one's home culture may be somewhat stressful. The same facial appearance, however, might become advantageous within an outgroup population. To address this fit between facial appearance and cultural setting, we propose a simple measure of distinctiveness/typicality based on position of an individual along the axis connecting the facial averages of two populations under comparison. The more distant a face is from its ingroup population mean toward the outgroup mean the more distinct it is (vis-à-vis the ingroup) and the more it resembles the outgroup standards. We compared this new measure with an alternative measure based on distance from outgroup mean. The new measure showed stronger association with rated facial distinctiveness than distance from outgroup mean. Subsequently, we manipulated facial stimuli to reflect different levels of ingroup-outgroup distinctiveness and tested them in one of the target cultures. Perceivers were able to successfully distinguish outgroup from ingroup faces in a two-alternative forced-choice task. There was also some evidence that this task was harder when the two faces were closer along the axis connecting the facial averages from the two cultures. Future directions and potential applications of our proposed approach are discussed.
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Project description:Automated analysis of microscope images is necessitated by the increased need for high-resolution follow up of events in time. Manually finding the right images to be analyzed, or eliminated from data analysis are common day-to-day problems in microscopy research today, and the constantly growing size of image datasets does not help the matter. We propose a simple method and a software tool for sorting images within a dataset, according to their relative quality. We demonstrate the applicability of our method in finding good quality images in a STED microscope sample preparation optimization image dataset. The results are validated by comparisons to subjective opinion scores, as well as five state-of-the-art blind image quality assessment methods. We also show how our method can be applied to eliminate useless out-of-focus images in a High-Content-Screening experiment. We further evaluate the ability of our image quality ranking method to detect out-of-focus images, by extensive simulations, and by comparing its performance against previously published, well-established microscopy autofocus metrics.
| S-EPMC4929473 | biostudies-literature
Project description:MotivationThe recent advance in high-throughput sequencing technologies is generating a huge amount of data that are becoming an important resource for deciphering the genotype underlying a given phenotype. Genome sequencing has been extensively applied to the study of the cancer genomes. Although a few methods have been already proposed for the detection of cancer-related genes, their automatic identification is still a challenging task. Using the genomic data made available by The Cancer Genome Atlas Consortium (TCGA), we propose a new prioritization approach based on the analysis of the distribution of putative deleterious variants in a large cohort of cancer samples.ResultsIn this paper, we present ContastRank, a new method for the prioritization of putative impaired genes in cancer. The method is based on the comparison of the putative defective rate of each gene in tumor versus normal and 1000 genome samples. We show that the method is able to provide a ranked list of putative impaired genes for colon, lung and prostate adenocarcinomas. The list significantly overlaps with the list of known cancer driver genes previously published. More importantly, by using our scoring approach, we can successfully discriminate between TCGA normal and tumor samples. A binary classifier based on ContrastRank score reaches an overall accuracy >90% and the area under the curve (AUC) of receiver operating characteristics (ROC) >0.95 for all the three types of adenocarcinoma analyzed in this paper. In addition, using ContrastRank score, we are able to discriminate the three tumor types with a minimum overall accuracy of 77% and AUC of 0.83.ConclusionsWe describe ContrastRank, a method for prioritizing putative impaired genes in cancer. The method is based on the comparison of exome sequencing data from different cohorts and can detect putative cancer driver genes. ContrastRank can also be used to estimate a global score for an individual genome about the risk of adenocarcinoma based on the genetic variants information from a whole-exome VCF (Variant Calling Format) file. We believe that the application of ContrastRank can be an important step in genomic medicine to enable genome-based diagnosis.Availability and implementationThe lists of ContrastRank scores of all genes in each tumor type are available as supplementary materials. A webserver for evaluating the risk of the three studied adenocarcinomas starting from whole-exome VCF file is under development.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC4147919 | biostudies-literature
Project description:Honeybees forage on diverse flowers which vary in the amount and type of rewards they offer, and bees are challenged with maximizing the resources they gather for their colony. That bees are effective foragers is clear, but how bees solve this type of complex multi-choice task is unknown. Here, we set bees a five-comparison choice task in which five colours differed in their probability of offering reward and punishment. The colours were ranked such that high ranked colours were more likely to offer reward, and the ranking was unambiguous. Bees' choices in unrewarded tests matched their individual experiences of reward and punishment of each colour, indicating bees solved this test not by comparing or ranking colours but by basing their colour choices on their history of reinforcement for each colour. Computational modelling suggests a structure like the honeybee mushroom body with reinforcement-related plasticity at both input and output can be sufficient for this cognitive strategy. We discuss how probability matching enables effective choices to be made without a need to compare any stimuli directly, and the use and limitations of this simple cognitive strategy for foraging animals.
| S-EPMC7542781 | biostudies-literature
Project description:Others' perceptual judgments tend to have strong effects on our own, and can improve perceptual judgments when task partners engage in communication. The present study investigated whether individuals benefit from others' perceptual judgments in indirect interactions, where outcomes of individual decisions can be observed in a shared environment. Participants located a target in a 2D projection of a 3D container either from two complementary viewpoints (Experiment 1), or from a single viewpoint (Experiment 2). Uncertainty about the target location was high on the front-back dimension and low on the left-right dimension. The results showed that pairs of participants benefitted from taking turns in providing judgments. When each member of the pair had access to one complementary perspective, the pair achieved the same level of accuracy as when the two individuals had access to both complimentary perspectives and better performance than when the two individuals had access to only one perspective. These findings demonstrate the important role of a shared environment for successful integration of perceptual information while highlighting limitations in assigning appropriate weights to others' judgments.
| S-EPMC5667753 | biostudies-literature
Project description:Purpose:The study examines the typicality effect in Spanish-English bilingual children and adults in their 2 languages. Method:Two studies were conducted using a category-generation task to compare the typical items generated by children with those generated by adults. Children in the 1st study differed orthogonally with respect to age (older, younger) and language use (higher Spanish use, higher English use). In the 2nd study, the older and younger children were matched with adults on their current Spanish use to delineate the influence of test language and age. Results:Children with higher English use generated more typical items, and these occurred earlier in their word lists in English than in Spanish. Participants at all levels of Spanish experience generated fewer typical items in Spanish than in English. Thus, there was less convergence of items considered typical among participants in Spanish. Older and younger children did not differ in the number of typical items generated. However, when participants were matched for language use, older children produced typical items earlier in their word lists than did younger children. Conclusion:This study demonstrates the influence of language use and test language in generation of typical items in bilingual children.Supplemental Materials: https://doi.org/10.23641/asha.5089888.
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Project description:Maximum-entropy ensembles are key primitives in statistical mechanics. Several approaches have been developed in order to justify the use of these ensembles in statistical descriptions. However, there is still no full consensus on the precise reasoning justifying the use of such ensembles. In this work, we provide an approach to derive maximum-entropy ensembles, taking a strictly operational perspective. We investigate the set of possible transitions that a system can undergo together with an environment, when one only has partial information about the system and its environment. The set of these transitions encodes thermodynamic laws and limitations on thermodynamic tasks as particular cases. Our main result is that the possible transitions are exactly those that are possible if both system and environment are assigned the maximum-entropy state compatible with the partial information. This justifies the overwhelming success of such ensembles and provides a derivation independent of typicality or information-theoretic measures.
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Project description:Genome-wide association studies (GWAS) analyze genetic variation (SNPs) across the entire human genome, searching for SNPs that are associated with certain phenotypes, most often diseases, such as breast cancer. In GWAS, we seek a ranking of SNPs in terms of their relevance to the given phenotype. However, because certain SNPs are known to be highly correlated with one another across individuals, it can be beneficial to take into account these correlations when ranking. If a SNP appears associated with the phenotype, and we question whether this association is real, the extent to which its neighbors (correlated SNPs) also appear associated can be informative. Therefore, we propose CollectRank, a ranking approach which allows SNPs to reinforce one another via the correlation structure. CollectRank is loosely analogous to the well-known PageRank algorithm. We first evaluate CollectRank on synthetic data generated from a variety of genetic models under different settings. The numerical results suggest CollectRank can significantly outperform common GWAS methods at the cost of a small amount of extra computation. We further evaluate CollectRank on two real-world GWAS on breast cancer and atrial fibrillation/flutter, and CollectRank performs well in both studies. We finally provide a theoretical analysis that also suggests CollectRank's advantages.
| S-EPMC7191672 | biostudies-literature