996 resultados para Expresión facial


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White markings and spotting patterns in animal species are thought to be a result of the domestication process. They often serve for the identification of individuals but sometimes are accompanied by complex pathological syndromes. In the Swiss Franches-Montagnes horse population, white markings increased vastly in size and occurrence during the past 30 years, although the breeding goal demands a horse with as little depigmented areas as possible. In order to improve selection and avoid more excessive depigmentation on the population level, we estimated population parameters and breeding values for white head and anterior and posterior leg markings. Heritabilities and genetic correlations for the traits were high (h(2) > 0.5). A strong positive correlation was found between the chestnut allele at the melanocortin-1-receptor gene locus and the extent of white markings. Segregation analysis revealed that our data fit best to a model including a polygenic effect and a biallelic locus with a dominant-recessive mode of inheritance. The recessive allele was found to be the white trait-increasing allele. Multilocus linkage disequilibrium analysis allowed the mapping of the putative major locus to a chromosomal region on ECA3q harboring the KIT gene.

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Motivated by conflicting evidence in the literature, we re-assessed the role of facial feedback when detecting quantitative or qualitative changes in others’ emotional expressions. Fifty-three healthy adults observed self-paced morph sequences where the emotional facial expression either changed quantitatively (i.e., sad-to-neutral, neutral-to-sad, happy-to-neutral, neutral-to-happy) or qualitatively (i.e. from sad to happy, or from happy to sad). Observers held a pen in their own mouth to induce smiling or frowning during the detection task. When morph sequences started or ended with neutral expressions we replicated a congruency effect: Happiness was perceived longer and sooner while smiling; sadness was perceived longer and sooner while frowning. Interestingly, no such congruency effects occurred for transitions between emotional expressions. These results suggest that facial feedback is especially useful when evaluating the intensity of a facial expression, but less so when we have to recognize which emotion our counterpart is expressing.

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Facial nerve segmentation plays an important role in surgical planning of cochlear implantation. Clinically available CBCT images are used for surgical planning. However, its relatively low resolution renders the identification of the facial nerve difficult. In this work, we present a supervised learning approach to enhance facial nerve image information from CBCT. A supervised learning approach based on multi-output random forest was employed to learn the mapping between CBCT and micro-CT images. Evaluation was performed qualitatively and quantitatively by using the predicted image as input for a previously published dedicated facial nerve segmentation, and cochlear implantation surgical planning software, OtoPlan. Results show the potential of the proposed approach to improve facial nerve image quality as imaged by CBCT and to leverage its segmentation using OtoPlan.

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The present topical review deals with the motor control of facial expressions in humans. Facial expressions are a central part of human communication. Emotional face expressions have a crucial role in human non-verbal behavior, allowing a rapid transfer of information between individuals. Facial expressions can be both voluntarily or emotionally controlled. Recent studies in non-human primates and humans revealed that the motor control of facial expressions has a distributed neural representation. At least 5 cortical regions on the medial and lateral aspects of each hemisphere are involved: the primary motor cortex, the ventral lateral premotor cortex, the supplementary motor area on the medial wall, and, finally, the rostral and caudal cingulate cortex. The results of studies in humans and non-human primates suggest that the innervation of the face is bilaterally controlled for the upper part, and mainly contralaterally controlled for the lower part. Furthermore, the primary motor cortex, the ventral lateral premotor cortex, and the supplementary motor area are essential for the voluntary control of facial expressions. In contrast, the cingulate cortical areas are important for emotional expression, since they receive input from different structures of the limbic system. This article is protected by copyright. All rights reserved.