A general framework for face reconstruction using single still image based on 2D-to-3D transformation kernel.

PubMed

Fooprateepsiri, Rerkchai; Kurutach, Werasak

2014-03-01

Face authentication is a biometric classification method that verifies the identity of a user based on image of their face. Accuracy of the authentication is reduced when the pose, illumination and expression of the training face images are different than the testing image. The methods in this paper are designed to improve the accuracy of a features-based face recognition system when the pose between the input images and training images are different. First, an efficient 2D-to-3D integrated face reconstruction approach is introduced to reconstruct a personalized 3D face model from a single frontal face image with neutral expression and normal illumination. Second, realistic virtual faces with different poses are synthesized based on the personalized 3D face to characterize the face subspace. Finally, face recognition is conducted based on these representative virtual faces. Compared with other related works, this framework has the following advantages: (1) only one single frontal face is required for face recognition, which avoids the burdensome enrollment work; and (2) the synthesized face samples provide the capability to conduct recognition under difficult conditions like complex pose, illumination and expression. From the experimental results, we conclude that the proposed method improves the accuracy of face recognition by varying the pose, illumination and expression. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Facial Expression Influences Face Identity Recognition During the Attentional Blink

PubMed Central

2014-01-01

Emotional stimuli (e.g., negative facial expressions) enjoy prioritized memory access when task relevant, consistent with their ability to capture attention. Whether emotional expression also impacts on memory access when task-irrelevant is important for arbitrating between feature-based and object-based attentional capture. Here, the authors address this question in 3 experiments using an attentional blink task with face photographs as first and second target (T1, T2). They demonstrate reduced neutral T2 identity recognition after angry or happy T1 expression, compared to neutral T1, and this supports attentional capture by a task-irrelevant feature. Crucially, after neutral T1, T2 identity recognition was enhanced and not suppressed when T2 was angry—suggesting that attentional capture by this task-irrelevant feature may be object-based and not feature-based. As an unexpected finding, both angry and happy facial expressions suppress memory access for competing objects, but only angry facial expression enjoyed privileged memory access. This could imply that these 2 processes are relatively independent from one another. PMID:25286076

Facial expression influences face identity recognition during the attentional blink.

PubMed

Bach, Dominik R; Schmidt-Daffy, Martin; Dolan, Raymond J

2014-12-01

Emotional stimuli (e.g., negative facial expressions) enjoy prioritized memory access when task relevant, consistent with their ability to capture attention. Whether emotional expression also impacts on memory access when task-irrelevant is important for arbitrating between feature-based and object-based attentional capture. Here, the authors address this question in 3 experiments using an attentional blink task with face photographs as first and second target (T1, T2). They demonstrate reduced neutral T2 identity recognition after angry or happy T1 expression, compared to neutral T1, and this supports attentional capture by a task-irrelevant feature. Crucially, after neutral T1, T2 identity recognition was enhanced and not suppressed when T2 was angry-suggesting that attentional capture by this task-irrelevant feature may be object-based and not feature-based. As an unexpected finding, both angry and happy facial expressions suppress memory access for competing objects, but only angry facial expression enjoyed privileged memory access. This could imply that these 2 processes are relatively independent from one another.

iFER: facial expression recognition using automatically selected geometric eye and eyebrow features

NASA Astrophysics Data System (ADS)

Oztel, Ismail; Yolcu, Gozde; Oz, Cemil; Kazan, Serap; Bunyak, Filiz

2018-03-01

Facial expressions have an important role in interpersonal communications and estimation of emotional states or intentions. Automatic recognition of facial expressions has led to many practical applications and became one of the important topics in computer vision. We present a facial expression recognition system that relies on geometry-based features extracted from eye and eyebrow regions of the face. The proposed system detects keypoints on frontal face images and forms a feature set using geometric relationships among groups of detected keypoints. Obtained feature set is refined and reduced using the sequential forward selection (SFS) algorithm and fed to a support vector machine classifier to recognize five facial expression classes. The proposed system, iFER (eye-eyebrow only facial expression recognition), is robust to lower face occlusions that may be caused by beards, mustaches, scarves, etc. and lower face motion during speech production. Preliminary experiments on benchmark datasets produced promising results outperforming previous facial expression recognition studies using partial face features, and comparable results to studies using whole face information, only slightly lower by ˜ 2.5 % compared to the best whole face facial recognition system while using only ˜ 1 / 3 of the facial region.

Quantitative expression and immunogenicity of MAGE-3 and -6 in upper aerodigestive tract cancer.

PubMed

Filho, Pedro A Andrade; López-Albaitero, Andrés; Xi, Liqiang; Gooding, William; Godfrey, Tony; Ferris, Robert L

2009-10-15

The MAGE antigens are frequently expressed cancer vaccine targets. However, quantitative analysis of MAGE expression in upper aerodigestive tract (UADT) tumor cells and its association with T-cell recognition has not been performed, hindering the selection of appropriate candidates for MAGE-specific immunotherapy. Using quantitative RT-PCR (QRT-PCR), we evaluated the expression of MAGE-3/6 in 65 UADT cancers, 48 normal samples from tumor matched sites and 7 HLA-A*0201+ squamous cell carcinoma of the head and neck (SCCHN) cell lines. Expression results were confirmed using Western blot. HLA-A*0201:MAGE-3- (271-279) specific cytotoxic T lymphocytes (MAGE-CTL) from SCCHN patients and healthy donors showed that MAGE-3/6 expression was highly associated with CTL recognition in vitro. On the basis of the MAGE-3/6 expression, we could identify 31 (47%) of the 65 UADT tumors, which appeared to express MAGE-3/6 at levels that correlated with efficient CTL recognition. To confirm that the level of MAGE-3 expression was responsible for CTL recognition, 2 MAGE-3/6 mRNA(high) SCCHN cell lines, PCI-13 and PCI-30, were subjected to MAGE-3/6-specific knockdown. RNAi-transfected cells showed that MAGE expression and MAGE-CTL recognition were significantly reduced. Furthermore, treatment of cells expressing low MAGE-3/6 mRNA with a demethylating agent, 5-aza-2'-deoxycytidine (DAC), increased the expression of MAGE-3/6 and CTL recognition. Thus, using QRT-PCR UADT cancers frequently express MAGE-3/6 at levels sufficient for CTL recognition, supporting the use of a QRT-PCR-based assay for the selection of candidates likely to respond to MAGE-3/6 immunotherapy. Demethylating agents could increase the number of patients amenable for targeting epigenetically modified tumor antigens in vaccine trials.

Towards Multimodal Emotion Recognition in E-Learning Environments

ERIC Educational Resources Information Center

Bahreini, Kiavash; Nadolski, Rob; Westera, Wim

2016-01-01

This paper presents a framework (FILTWAM (Framework for Improving Learning Through Webcams And Microphones)) for real-time emotion recognition in e-learning by using webcams. FILTWAM offers timely and relevant feedback based upon learner's facial expressions and verbalizations. FILTWAM's facial expression software module has been developed and…

A New Method of Facial Expression Recognition Based on SPE Plus SVM

NASA Astrophysics Data System (ADS)

Ying, Zilu; Huang, Mingwei; Wang, Zhen; Wang, Zhewei

A novel method of facial expression recognition (FER) is presented, which uses stochastic proximity embedding (SPE) for data dimension reduction, and support vector machine (SVM) for expression classification. The proposed algorithm is applied to Japanese Female Facial Expression (JAFFE) database for FER, better performance is obtained compared with some traditional algorithms, such as PCA and LDA etc.. The result have further proved the effectiveness of the proposed algorithm.

The recognition of emotional expression in prosopagnosia: decoding whole and part faces.

PubMed

Stephan, Blossom Christa Maree; Breen, Nora; Caine, Diana

2006-11-01

Prosopagnosia is currently viewed within the constraints of two competing theories of face recognition, one highlighting the analysis of features, the other focusing on configural processing of the whole face. This study investigated the role of feature analysis versus whole face configural processing in the recognition of facial expression. A prosopagnosic patient, SC made expression decisions from whole and incomplete (eyes-only and mouth-only) faces where features had been obscured. SC was impaired at recognizing some (e.g., anger, sadness, and fear), but not all (e.g., happiness) emotional expressions from the whole face. Analyses of his performance on incomplete faces indicated that his recognition of some expressions actually improved relative to his performance on the whole face condition. We argue that in SC interference from damaged configural processes seem to override an intact ability to utilize part-based or local feature cues.

Functional integration of the posterior superior temporal sulcus correlates with facial expression recognition.

PubMed

Wang, Xu; Song, Yiying; Zhen, Zonglei; Liu, Jia

2016-05-01

Face perception is essential for daily and social activities. Neuroimaging studies have revealed a distributed face network (FN) consisting of multiple regions that exhibit preferential responses to invariant or changeable facial information. However, our understanding about how these regions work collaboratively to facilitate facial information processing is limited. Here, we focused on changeable facial information processing, and investigated how the functional integration of the FN is related to the performance of facial expression recognition. To do so, we first defined the FN as voxels that responded more strongly to faces than objects, and then used a voxel-based global brain connectivity method based on resting-state fMRI to characterize the within-network connectivity (WNC) of each voxel in the FN. By relating the WNC and performance in the "Reading the Mind in the Eyes" Test across participants, we found that individuals with stronger WNC in the right posterior superior temporal sulcus (rpSTS) were better at recognizing facial expressions. Further, the resting-state functional connectivity (FC) between the rpSTS and right occipital face area (rOFA), early visual cortex (EVC), and bilateral STS were positively correlated with the ability of facial expression recognition, and the FCs of EVC-pSTS and OFA-pSTS contributed independently to facial expression recognition. In short, our study highlights the behavioral significance of intrinsic functional integration of the FN in facial expression processing, and provides evidence for the hub-like role of the rpSTS for facial expression recognition. Hum Brain Mapp 37:1930-1940, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Utterance independent bimodal emotion recognition in spontaneous communication

NASA Astrophysics Data System (ADS)

Tao, Jianhua; Pan, Shifeng; Yang, Minghao; Li, Ya; Mu, Kaihui; Che, Jianfeng

2011-12-01

Emotion expressions sometimes are mixed with the utterance expression in spontaneous face-to-face communication, which makes difficulties for emotion recognition. This article introduces the methods of reducing the utterance influences in visual parameters for the audio-visual-based emotion recognition. The audio and visual channels are first combined under a Multistream Hidden Markov Model (MHMM). Then, the utterance reduction is finished by finding the residual between the real visual parameters and the outputs of the utterance related visual parameters. This article introduces the Fused Hidden Markov Model Inversion method which is trained in the neutral expressed audio-visual corpus to solve the problem. To reduce the computing complexity the inversion model is further simplified to a Gaussian Mixture Model (GMM) mapping. Compared with traditional bimodal emotion recognition methods (e.g., SVM, CART, Boosting), the utterance reduction method can give better results of emotion recognition. The experiments also show the effectiveness of our emotion recognition system when it was used in a live environment.

Low-resolution expression recognition based on central oblique average CS-LBP with adaptive threshold

NASA Astrophysics Data System (ADS)

Han, Sheng; Xi, Shi-qiong; Geng, Wei-dong

2017-11-01

In order to solve the problem of low recognition rate of traditional feature extraction operators under low-resolution images, a novel algorithm of expression recognition is proposed, named central oblique average center-symmetric local binary pattern (CS-LBP) with adaptive threshold (ATCS-LBP). Firstly, the features of face images can be extracted by the proposed operator after pretreatment. Secondly, the obtained feature image is divided into blocks. Thirdly, the histogram of each block is computed independently and all histograms can be connected serially to create a final feature vector. Finally, expression classification is achieved by using support vector machine (SVM) classifier. Experimental results on Japanese female facial expression (JAFFE) database show that the proposed algorithm can achieve a recognition rate of 81.9% when the resolution is as low as 16×16, which is much better than that of the traditional feature extraction operators.

Luminance sticker based facial expression recognition using discrete wavelet transform for physically disabled persons.

PubMed

Nagarajan, R; Hariharan, M; Satiyan, M

2012-08-01

Developing tools to assist physically disabled and immobilized people through facial expression is a challenging area of research and has attracted many researchers recently. In this paper, luminance stickers based facial expression recognition is proposed. Recognition of facial expression is carried out by employing Discrete Wavelet Transform (DWT) as a feature extraction method. Different wavelet families with their different orders (db1 to db20, Coif1 to Coif 5 and Sym2 to Sym8) are utilized to investigate their performance in recognizing facial expression and to evaluate their computational time. Standard deviation is computed for the coefficients of first level of wavelet decomposition for every order of wavelet family. This standard deviation is used to form a set of feature vectors for classification. In this study, conventional validation and cross validation are performed to evaluate the efficiency of the suggested feature vectors. Three different classifiers namely Artificial Neural Network (ANN), k-Nearest Neighborhood (kNN) and Linear Discriminant Analysis (LDA) are used to classify a set of eight facial expressions. The experimental results demonstrate that the proposed method gives very promising classification accuracies.

Towards Real-Time Speech Emotion Recognition for Affective E-Learning

ERIC Educational Resources Information Center

Bahreini, Kiavash; Nadolski, Rob; Westera, Wim

2016-01-01

This paper presents the voice emotion recognition part of the FILTWAM framework for real-time emotion recognition in affective e-learning settings. FILTWAM (Framework for Improving Learning Through Webcams And Microphones) intends to offer timely and appropriate online feedback based upon learner's vocal intonations and facial expressions in order…

Dissociable roles of internal feelings and face recognition ability in facial expression decoding.

PubMed

Zhang, Lin; Song, Yiying; Liu, Ling; Liu, Jia

2016-05-15

The problem of emotion recognition has been tackled by researchers in both affective computing and cognitive neuroscience. While affective computing relies on analyzing visual features from facial expressions, it has been proposed that humans recognize emotions by internally simulating the emotional states conveyed by others' expressions, in addition to perceptual analysis of facial features. Here we investigated whether and how our internal feelings contributed to the ability to decode facial expressions. In two independent large samples of participants, we observed that individuals who generally experienced richer internal feelings exhibited a higher ability to decode facial expressions, and the contribution of internal feelings was independent of face recognition ability. Further, using voxel-based morphometry, we found that the gray matter volume (GMV) of bilateral superior temporal sulcus (STS) and the right inferior parietal lobule was associated with facial expression decoding through the mediating effect of internal feelings, while the GMV of bilateral STS, precuneus, and the right central opercular cortex contributed to facial expression decoding through the mediating effect of face recognition ability. In addition, the clusters in bilateral STS involved in the two components were neighboring yet separate. Our results may provide clues about the mechanism by which internal feelings, in addition to face recognition ability, serve as an important instrument for humans in facial expression decoding. Copyright © 2016 Elsevier Inc. All rights reserved.

Mutual information-based facial expression recognition

NASA Astrophysics Data System (ADS)

Hazar, Mliki; Hammami, Mohamed; Hanêne, Ben-Abdallah

2013-12-01

This paper introduces a novel low-computation discriminative regions representation for expression analysis task. The proposed approach relies on interesting studies in psychology which show that most of the descriptive and responsible regions for facial expression are located around some face parts. The contributions of this work lie in the proposition of new approach which supports automatic facial expression recognition based on automatic regions selection. The regions selection step aims to select the descriptive regions responsible or facial expression and was performed using Mutual Information (MI) technique. For facial feature extraction, we have applied Local Binary Patterns Pattern (LBP) on Gradient image to encode salient micro-patterns of facial expressions. Experimental studies have shown that using discriminative regions provide better results than using the whole face regions whilst reducing features vector dimension.

An audiovisual emotion recognition system

NASA Astrophysics Data System (ADS)

Han, Yi; Wang, Guoyin; Yang, Yong; He, Kun

2007-12-01

Human emotions could be expressed by many bio-symbols. Speech and facial expression are two of them. They are both regarded as emotional information which is playing an important role in human-computer interaction. Based on our previous studies on emotion recognition, an audiovisual emotion recognition system is developed and represented in this paper. The system is designed for real-time practice, and is guaranteed by some integrated modules. These modules include speech enhancement for eliminating noises, rapid face detection for locating face from background image, example based shape learning for facial feature alignment, and optical flow based tracking algorithm for facial feature tracking. It is known that irrelevant features and high dimensionality of the data can hurt the performance of classifier. Rough set-based feature selection is a good method for dimension reduction. So 13 speech features out of 37 ones and 10 facial features out of 33 ones are selected to represent emotional information, and 52 audiovisual features are selected due to the synchronization when speech and video fused together. The experiment results have demonstrated that this system performs well in real-time practice and has high recognition rate. Our results also show that the work in multimodules fused recognition will become the trend of emotion recognition in the future.

Human fatigue expression recognition through image-based dynamic multi-information and bimodal deep learning

NASA Astrophysics Data System (ADS)

Zhao, Lei; Wang, Zengcai; Wang, Xiaojin; Qi, Yazhou; Liu, Qing; Zhang, Guoxin

2016-09-01

Human fatigue is an important cause of traffic accidents. To improve the safety of transportation, we propose, in this paper, a framework for fatigue expression recognition using image-based facial dynamic multi-information and a bimodal deep neural network. First, the landmark of face region and the texture of eye region, which complement each other in fatigue expression recognition, are extracted from facial image sequences captured by a single camera. Then, two stacked autoencoder neural networks are trained for landmark and texture, respectively. Finally, the two trained neural networks are combined by learning a joint layer on top of them to construct a bimodal deep neural network. The model can be used to extract a unified representation that fuses landmark and texture modalities together and classify fatigue expressions accurately. The proposed system is tested on a human fatigue dataset obtained from an actual driving environment. The experimental results demonstrate that the proposed method performs stably and robustly, and that the average accuracy achieves 96.2%.

Robust kernel representation with statistical local features for face recognition.

PubMed

Yang, Meng; Zhang, Lei; Shiu, Simon Chi-Keung; Zhang, David

2013-06-01

Factors such as misalignment, pose variation, and occlusion make robust face recognition a difficult problem. It is known that statistical features such as local binary pattern are effective for local feature extraction, whereas the recently proposed sparse or collaborative representation-based classification has shown interesting results in robust face recognition. In this paper, we propose a novel robust kernel representation model with statistical local features (SLF) for robust face recognition. Initially, multipartition max pooling is used to enhance the invariance of SLF to image registration error. Then, a kernel-based representation model is proposed to fully exploit the discrimination information embedded in the SLF, and robust regression is adopted to effectively handle the occlusion in face images. Extensive experiments are conducted on benchmark face databases, including extended Yale B, AR (A. Martinez and R. Benavente), multiple pose, illumination, and expression (multi-PIE), facial recognition technology (FERET), face recognition grand challenge (FRGC), and labeled faces in the wild (LFW), which have different variations of lighting, expression, pose, and occlusions, demonstrating the promising performance of the proposed method.

Appearance-based human gesture recognition using multimodal features for human computer interaction

NASA Astrophysics Data System (ADS)

Luo, Dan; Gao, Hua; Ekenel, Hazim Kemal; Ohya, Jun

2011-03-01

The use of gesture as a natural interface plays an utmost important role for achieving intelligent Human Computer Interaction (HCI). Human gestures include different components of visual actions such as motion of hands, facial expression, and torso, to convey meaning. So far, in the field of gesture recognition, most previous works have focused on the manual component of gestures. In this paper, we present an appearance-based multimodal gesture recognition framework, which combines the different groups of features such as facial expression features and hand motion features which are extracted from image frames captured by a single web camera. We refer 12 classes of human gestures with facial expression including neutral, negative and positive meanings from American Sign Languages (ASL). We combine the features in two levels by employing two fusion strategies. At the feature level, an early feature combination can be performed by concatenating and weighting different feature groups, and LDA is used to choose the most discriminative elements by projecting the feature on a discriminative expression space. The second strategy is applied on decision level. Weighted decisions from single modalities are fused in a later stage. A condensation-based algorithm is adopted for classification. We collected a data set with three to seven recording sessions and conducted experiments with the combination techniques. Experimental results showed that facial analysis improve hand gesture recognition, decision level fusion performs better than feature level fusion.

Face recognition using facial expression: a novel approach

NASA Astrophysics Data System (ADS)

Singh, Deepak Kumar; Gupta, Priya; Tiwary, U. S.

2008-04-01

Facial expressions are undoubtedly the most effective nonverbal communication. The face has always been the equation of a person's identity. The face draws the demarcation line between identity and extinction. Each line on the face adds an attribute to the identity. These lines become prominent when we experience an emotion and these lines do not change completely with age. In this paper we have proposed a new technique for face recognition which focuses on the facial expressions of the subject to identify his face. This is a grey area on which not much light has been thrown earlier. According to earlier researches it is difficult to alter the natural expression. So our technique will be beneficial for identifying occluded or intentionally disguised faces. The test results of the experiments conducted prove that this technique will give a new direction in the field of face recognition. This technique will provide a strong base to the area of face recognition and will be used as the core method for critical defense security related issues.

System for face recognition under expression variations of neutral-sampled individuals using recognized expression warping and a virtual expression-face database

NASA Astrophysics Data System (ADS)

Petpairote, Chayanut; Madarasmi, Suthep; Chamnongthai, Kosin

2018-01-01

The practical identification of individuals using facial recognition techniques requires the matching of faces with specific expressions to faces from a neutral face database. A method for facial recognition under varied expressions against neutral face samples of individuals via recognition of expression warping and the use of a virtual expression-face database is proposed. In this method, facial expressions are recognized and the input expression faces are classified into facial expression groups. To aid facial recognition, the virtual expression-face database is sorted into average facial-expression shapes and by coarse- and fine-featured facial textures. Wrinkle information is also employed in classification by using a process of masking to adjust input faces to match the expression-face database. We evaluate the performance of the proposed method using the CMU multi-PIE, Cohn-Kanade, and AR expression-face databases, and we find that it provides significantly improved results in terms of face recognition accuracy compared to conventional methods and is acceptable for facial recognition under expression variation.

Annotation: Development of facial expression recognition from childhood to adolescence: behavioural and neurological perspectives.

PubMed

Herba, Catherine; Phillips, Mary

2004-10-01

Intact emotion processing is critical for normal emotional development. Recent advances in neuroimaging have facilitated the examination of brain development, and have allowed for the exploration of the relationships between the development of emotion processing abilities, and that of associated neural systems. A literature review was performed of published studies examining the development of emotion expression recognition in normal children and psychiatric populations, and of the development of neural systems important for emotion processing. Few studies have explored the development of emotion expression recognition throughout childhood and adolescence. Behavioural studies suggest continued development throughout childhood and adolescence (reflected by accuracy scores and speed of processing), which varies according to the category of emotion displayed. Factors such as sex, socio-economic status, and verbal ability may also affect this development. Functional neuroimaging studies in adults highlight the role of the amygdala in emotion processing. Results of the few neuroimaging studies in children have focused on the role of the amygdala in the recognition of fearful expressions. Although results are inconsistent, they provide evidence throughout childhood and adolescence for the continued development of and sex differences in amygdalar function in response to fearful expressions. Studies exploring emotion expression recognition in psychiatric populations of children and adolescents suggest deficits that are specific to the type of disorder and to the emotion displayed. Results from behavioural and neuroimaging studies indicate continued development of emotion expression recognition and neural regions important for this process throughout childhood and adolescence. Methodological inconsistencies and disparate findings make any conclusion difficult, however. Further studies are required examining the relationship between the development of emotion expression recognition and that of underlying neural systems, in particular subcortical and prefrontal cortical structures. These will inform understanding of the neural bases of normal and abnormal emotional development, and aid the development of earlier interventions for children and adolescents with psychiatric disorders.

[Prosopagnosia and facial expression recognition].

PubMed

Koyama, Shinichi

2014-04-01

This paper reviews clinical neuropsychological studies that have indicated that the recognition of a person's identity and the recognition of facial expressions are processed by different cortical and subcortical areas of the brain. The fusiform gyrus, especially the right fusiform gyrus, plays an important role in the recognition of identity. The superior temporal sulcus, amygdala, and medial frontal cortex play important roles in facial-expression recognition. Both facial recognition and facial-expression recognition are highly intellectual processes that involve several regions of the brain.

Effects of exposure to facial expression variation in face learning and recognition.

PubMed

Liu, Chang Hong; Chen, Wenfeng; Ward, James

2015-11-01

Facial expression is a major source of image variation in face images. Linking numerous expressions to the same face can be a huge challenge for face learning and recognition. It remains largely unknown what level of exposure to this image variation is critical for expression-invariant face recognition. We examined this issue in a recognition memory task, where the number of facial expressions of each face being exposed during a training session was manipulated. Faces were either trained with multiple expressions or a single expression, and they were later tested in either the same or different expressions. We found that recognition performance after learning three emotional expressions had no improvement over learning a single emotional expression (Experiments 1 and 2). However, learning three emotional expressions improved recognition compared to learning a single neutral expression (Experiment 3). These findings reveal both the limitation and the benefit of multiple exposures to variations of emotional expression in achieving expression-invariant face recognition. The transfer of expression training to a new type of expression is likely to depend on a relatively extensive level of training and a certain degree of variation across the types of expressions.

[Association between intelligence development and facial expression recognition ability in children with autism spectrum disorder].

PubMed

Pan, Ning; Wu, Gui-Hua; Zhang, Ling; Zhao, Ya-Fen; Guan, Han; Xu, Cai-Juan; Jing, Jin; Jin, Yu

2017-03-01

To investigate the features of intelligence development, facial expression recognition ability, and the association between them in children with autism spectrum disorder (ASD). A total of 27 ASD children aged 6-16 years (ASD group, full intelligence quotient >70) and age- and gender-matched normally developed children (control group) were enrolled. Wechsler Intelligence Scale for Children Fourth Edition and Chinese Static Facial Expression Photos were used for intelligence evaluation and facial expression recognition test. Compared with the control group, the ASD group had significantly lower scores of full intelligence quotient, verbal comprehension index, perceptual reasoning index (PRI), processing speed index（PSI), and working memory index (WMI) (P<0.05). The ASD group also had a significantly lower overall accuracy rate of facial expression recognition and significantly lower accuracy rates of the recognition of happy, angry, sad, and frightened expressions than the control group (P<0.05). In the ASD group, the overall accuracy rate of facial expression recognition and the accuracy rates of the recognition of happy and frightened expressions were positively correlated with PRI (r=0.415, 0.455, and 0.393 respectively; P<0.05). The accuracy rate of the recognition of angry expression was positively correlated with WMI (r=0.397; P<0.05). ASD children have delayed intelligence development compared with normally developed children and impaired expression recognition ability. Perceptual reasoning and working memory abilities are positively correlated with expression recognition ability, which suggests that insufficient perceptual reasoning and working memory abilities may be important factors affecting facial expression recognition ability in ASD children.

Automatic Facial Expression Recognition and Operator Functional State

NASA Technical Reports Server (NTRS)

Blanson, Nina

2012-01-01

The prevalence of human error in safety-critical occupations remains a major challenge to mission success despite increasing automation in control processes. Although various methods have been proposed to prevent incidences of human error, none of these have been developed to employ the detection and regulation of Operator Functional State (OFS), or the optimal condition of the operator while performing a task, in work environments due to drawbacks such as obtrusiveness and impracticality. A video-based system with the ability to infer an individual's emotional state from facial feature patterning mitigates some of the problems associated with other methods of detecting OFS, like obtrusiveness and impracticality in integration with the mission environment. This paper explores the utility of facial expression recognition as a technology for inferring OFS by first expounding on the intricacies of OFS and the scientific background behind emotion and its relationship with an individual's state. Then, descriptions of the feedback loop and the emotion protocols proposed for the facial recognition program are explained. A basic version of the facial expression recognition program uses Haar classifiers and OpenCV libraries to automatically locate key facial landmarks during a live video stream. Various methods of creating facial expression recognition software are reviewed to guide future extensions of the program. The paper concludes with an examination of the steps necessary in the research of emotion and recommendations for the creation of an automatic facial expression recognition program for use in real-time, safety-critical missions

Automatic Facial Expression Recognition and Operator Functional State

NASA Technical Reports Server (NTRS)

Blanson, Nina

2011-01-01

The prevalence of human error in safety-critical occupations remains a major challenge to mission success despite increasing automation in control processes. Although various methods have been proposed to prevent incidences of human error, none of these have been developed to employ the detection and regulation of Operator Functional State (OFS), or the optimal condition of the operator while performing a task, in work environments due to drawbacks such as obtrusiveness and impracticality. A video-based system with the ability to infer an individual's emotional state from facial feature patterning mitigates some of the problems associated with other methods of detecting OFS, like obtrusiveness and impracticality in integration with the mission environment. This paper explores the utility of facial expression recognition as a technology for inferring OFS by first expounding on the intricacies of OFS and the scientific background behind emotion and its relationship with an individual's state. Then, descriptions of the feedback loop and the emotion protocols proposed for the facial recognition program are explained. A basic version of the facial expression recognition program uses Haar classifiers and OpenCV libraries to automatically locate key facial landmarks during a live video stream. Various methods of creating facial expression recognition software are reviewed to guide future extensions of the program. The paper concludes with an examination of the steps necessary in the research of emotion and recommendations for the creation of an automatic facial expression recognition program for use in real-time, safety-critical missions.

Schematic drawings of facial expressions for emotion recognition and interpretation by preschool-aged children.

PubMed

MacDonald, P M; Kirkpatrick, S W; Sullivan, L A

1996-11-01

Schematic drawings of facial expressions were evaluated as a possible assessment tool for research on emotion recognition and interpretation involving young children. A subset of Ekman and Friesen's (1976) Pictures of Facial Affect was used as the standard for comparison. Preschool children (N = 138) were shown drawing and photographs in two context conditions for six emotions (anger, disgust, fear, happiness, sadness, and surprise). The overall correlation between accuracy for the photographs and drawings was .677. A significant difference was found for the stimulus condition (photographs vs. drawings) but not for the administration condition (label-based vs. context-based). Children were significantly more accurate in interpreting drawings than photographs and tended to be more accurate in identifying facial expressions in the label-based administration condition for both photographs and drawings than in the context-based administration condition.

Postsurgical Disfigurement Influences Disgust Recognition: A Case-Control Study.

PubMed

Lisan, Quentin; George, Nathalie; Hans, Stephane; Laccourreye, Ollivier; Lemogne, Cédric

Little is known about how emotion recognition may be modified in individuals prone to elicit disgust. We sought to determine if subjects with total laryngectomy would present a modified recognition of facial expressions of disgust. A total of 29 patients presenting with a history of advanced-stage laryngeal cancer were recruited, 17 being surgically treated (total laryngectomy) and 12 treated with chemoradiation therapy only. Based on a validated set of images of facial expressions of fear, disgust, surprise, happiness, sadness and anger displayed by 6 actors, we presented participants with expressions of each emotion at 5 levels of increasing intensity and measured their ability to recognize these emotions. Participants with (vs without) laryngectomy showed a higher threshold for the recognition of disgust (3.2. vs 2.7 images needed before emotion recognition, p = 0.03) and a lower success rate of correct recognition (75.5% vs 88.9%, p = 0.03). Subjects presenting with an aesthetic impairment of the head and neck showed poorer performance in disgust recognition when compared with those without disfigurement. These findings might relate either to some perceptual adaptation, habituation phenomenon, or to some higher-level processes related to emotion regulation strategies. Copyright © 2018 Academy of Consultation-Liaison Psychiatry. Published by Elsevier Inc. All rights reserved.

Autonomous facial recognition system inspired by human visual system based logarithmical image visualization technique

NASA Astrophysics Data System (ADS)

Wan, Qianwen; Panetta, Karen; Agaian, Sos

2017-05-01

Autonomous facial recognition system is widely used in real-life applications, such as homeland border security, law enforcement identification and authentication, and video-based surveillance analysis. Issues like low image quality, non-uniform illumination as well as variations in poses and facial expressions can impair the performance of recognition systems. To address the non-uniform illumination challenge, we present a novel robust autonomous facial recognition system inspired by the human visual system based, so called, logarithmical image visualization technique. In this paper, the proposed method, for the first time, utilizes the logarithmical image visualization technique coupled with the local binary pattern to perform discriminative feature extraction for facial recognition system. The Yale database, the Yale-B database and the ATT database are used for computer simulation accuracy and efficiency testing. The extensive computer simulation demonstrates the method's efficiency, accuracy, and robustness of illumination invariance for facial recognition.

Elastic Face, An Anatomy-Based Biometrics Beyond Visible Cue

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tsap, L V; Zhang, Y; Kundu, S J

2004-03-29

This paper describes a face recognition method that is designed based on the consideration of anatomical and biomechanical characteristics of facial tissues. Elastic strain pattern inferred from face expression can reveal an individual's biometric signature associated with the underlying anatomical structure, and thus has the potential for face recognition. A method based on the continuum mechanics in finite element formulation is employed to compute the strain pattern. Experiments show very promising results. The proposed method is quite different from other face recognition methods and both its advantages and limitations, as well as future research for improvement are discussed.

LBP and SIFT based facial expression recognition

NASA Astrophysics Data System (ADS)

Sumer, Omer; Gunes, Ece O.

2015-02-01

This study compares the performance of local binary patterns (LBP) and scale invariant feature transform (SIFT) with support vector machines (SVM) in automatic classification of discrete facial expressions. Facial expression recognition is a multiclass classification problem and seven classes; happiness, anger, sadness, disgust, surprise, fear and comtempt are classified. Using SIFT feature vectors and linear SVM, 93.1% mean accuracy is acquired on CK+ database. On the other hand, the performance of LBP-based classifier with linear SVM is reported on SFEW using strictly person independent (SPI) protocol. Seven-class mean accuracy on SFEW is 59.76%. Experiments on both databases showed that LBP features can be used in a fairly descriptive way if a good localization of facial points and partitioning strategy are followed.

[Emotional facial expression recognition impairment in Parkinson disease].

PubMed

Lachenal-Chevallet, Karine; Bediou, Benoit; Bouvard, Martine; Thobois, Stéphane; Broussolle, Emmanuel; Vighetto, Alain; Krolak-Salmon, Pierre

2006-03-01

some behavioral disturbances observed in Parkinson's disease (PD) could be related to impaired recognition of various social messages particularly emotional facial expressions. facial expression recognition was assessed using morphed faces (five emotions: happiness, fear, anger, disgust, neutral), and compared to gender recognition and general cognitive assessment in 12 patients with Parkinson's disease and 14 controls subjects. facial expression recognition was impaired among patients, whereas gender recognitions, visuo-perceptive capacities and total efficiency were preserved. Post hoc analyses disclosed a deficit for fear and disgust recognition compared to control subjects. the impairment of emotional facial expression recognition in PD appears independent of other cognitive deficits. This impairment may be related to the dopaminergic depletion in basal ganglia and limbic brain regions. They could take a part in psycho-behavioral disorders and particularly in communication disorders observed in Parkinson's disease patients.

Recognition of chemical entities: combining dictionary-based and grammar-based approaches.

PubMed

Akhondi, Saber A; Hettne, Kristina M; van der Horst, Eelke; van Mulligen, Erik M; Kors, Jan A

2015-01-01

The past decade has seen an upsurge in the number of publications in chemistry. The ever-swelling volume of available documents makes it increasingly hard to extract relevant new information from such unstructured texts. The BioCreative CHEMDNER challenge invites the development of systems for the automatic recognition of chemicals in text (CEM task) and for ranking the recognized compounds at the document level (CDI task). We investigated an ensemble approach where dictionary-based named entity recognition is used along with grammar-based recognizers to extract compounds from text. We assessed the performance of ten different commercial and publicly available lexical resources using an open source indexing system (Peregrine), in combination with three different chemical compound recognizers and a set of regular expressions to recognize chemical database identifiers. The effect of different stop-word lists, case-sensitivity matching, and use of chunking information was also investigated. We focused on lexical resources that provide chemical structure information. To rank the different compounds found in a text, we used a term confidence score based on the normalized ratio of the term frequencies in chemical and non-chemical journals. The use of stop-word lists greatly improved the performance of the dictionary-based recognition, but there was no additional benefit from using chunking information. A combination of ChEBI and HMDB as lexical resources, the LeadMine tool for grammar-based recognition, and the regular expressions, outperformed any of the individual systems. On the test set, the F-scores were 77.8% (recall 71.2%, precision 85.8%) for the CEM task and 77.6% (recall 71.7%, precision 84.6%) for the CDI task. Missed terms were mainly due to tokenization issues, poor recognition of formulas, and term conjunctions. We developed an ensemble system that combines dictionary-based and grammar-based approaches for chemical named entity recognition, outperforming any of the individual systems that we considered. The system is able to provide structure information for most of the compounds that are found. Improved tokenization and better recognition of specific entity types is likely to further improve system performance.

Recognition of chemical entities: combining dictionary-based and grammar-based approaches

PubMed Central

2015-01-01

Background The past decade has seen an upsurge in the number of publications in chemistry. The ever-swelling volume of available documents makes it increasingly hard to extract relevant new information from such unstructured texts. The BioCreative CHEMDNER challenge invites the development of systems for the automatic recognition of chemicals in text (CEM task) and for ranking the recognized compounds at the document level (CDI task). We investigated an ensemble approach where dictionary-based named entity recognition is used along with grammar-based recognizers to extract compounds from text. We assessed the performance of ten different commercial and publicly available lexical resources using an open source indexing system (Peregrine), in combination with three different chemical compound recognizers and a set of regular expressions to recognize chemical database identifiers. The effect of different stop-word lists, case-sensitivity matching, and use of chunking information was also investigated. We focused on lexical resources that provide chemical structure information. To rank the different compounds found in a text, we used a term confidence score based on the normalized ratio of the term frequencies in chemical and non-chemical journals. Results The use of stop-word lists greatly improved the performance of the dictionary-based recognition, but there was no additional benefit from using chunking information. A combination of ChEBI and HMDB as lexical resources, the LeadMine tool for grammar-based recognition, and the regular expressions, outperformed any of the individual systems. On the test set, the F-scores were 77.8% (recall 71.2%, precision 85.8%) for the CEM task and 77.6% (recall 71.7%, precision 84.6%) for the CDI task. Missed terms were mainly due to tokenization issues, poor recognition of formulas, and term conjunctions. Conclusions We developed an ensemble system that combines dictionary-based and grammar-based approaches for chemical named entity recognition, outperforming any of the individual systems that we considered. The system is able to provide structure information for most of the compounds that are found. Improved tokenization and better recognition of specific entity types is likely to further improve system performance. PMID:25810767

Emotional facial expressions differentially influence predictions and performance for face recognition.

PubMed

Nomi, Jason S; Rhodes, Matthew G; Cleary, Anne M

2013-01-01

This study examined how participants' predictions of future memory performance are influenced by emotional facial expressions. Participants made judgements of learning (JOLs) predicting the likelihood that they would correctly identify a face displaying a happy, angry, or neutral emotional expression in a future two-alternative forced-choice recognition test of identity (i.e., recognition that a person's face was seen before). JOLs were higher for studied faces with happy and angry emotional expressions than for neutral faces. However, neutral test faces with studied neutral expressions had significantly higher identity recognition rates than neutral test faces studied with happy or angry expressions. Thus, these data are the first to demonstrate that people believe happy and angry emotional expressions will lead to better identity recognition in the future relative to neutral expressions. This occurred despite the fact that neutral expressions elicited better identity recognition than happy and angry expressions. These findings contribute to the growing literature examining the interaction of cognition and emotion.

Impact of Childhood Maltreatment on the Recognition of Facial Expressions of Emotions.

PubMed

Ardizzi, Martina; Martini, Francesca; Umiltà, Maria Alessandra; Evangelista, Valentina; Ravera, Roberto; Gallese, Vittorio

2015-01-01

The development of the explicit recognition of facial expressions of emotions can be affected by childhood maltreatment experiences. A previous study demonstrated the existence of an explicit recognition bias for angry facial expressions among a population of adolescent Sierra Leonean street-boys exposed to high levels of maltreatment. In the present study, the recognition bias for angry facial expressions was investigated in a younger population of street-children and age-matched controls. Participants performed a forced-choice facial expressions recognition task. Recognition bias was measured as participants' tendency to over-attribute anger label to other negative facial expressions. Participants' heart rate was assessed and related to their behavioral performance, as index of their stress-related physiological responses. Results demonstrated the presence of a recognition bias for angry facial expressions among street-children, also pinpointing a similar, although significantly less pronounced, tendency among controls. Participants' performance was controlled for age, cognitive and educational levels and for naming skills. None of these variables influenced the recognition bias for angry facial expressions. Differently, a significant effect of heart rate on participants' tendency to use anger label was evidenced. Taken together, these results suggest that childhood exposure to maltreatment experiences amplifies children's "pre-existing bias" for anger labeling in forced-choice emotion recognition task. Moreover, they strengthen the thesis according to which the recognition bias for angry facial expressions is a manifestation of a functional adaptive mechanism that tunes victim's perceptive and attentive focus on salient environmental social stimuli.

Impact of Childhood Maltreatment on the Recognition of Facial Expressions of Emotions

PubMed Central

Ardizzi, Martina; Martini, Francesca; Umiltà, Maria Alessandra; Evangelista, Valentina; Ravera, Roberto; Gallese, Vittorio

2015-01-01

The development of the explicit recognition of facial expressions of emotions can be affected by childhood maltreatment experiences. A previous study demonstrated the existence of an explicit recognition bias for angry facial expressions among a population of adolescent Sierra Leonean street-boys exposed to high levels of maltreatment. In the present study, the recognition bias for angry facial expressions was investigated in a younger population of street-children and age-matched controls. Participants performed a forced-choice facial expressions recognition task. Recognition bias was measured as participants’ tendency to over-attribute anger label to other negative facial expressions. Participants’ heart rate was assessed and related to their behavioral performance, as index of their stress-related physiological responses. Results demonstrated the presence of a recognition bias for angry facial expressions among street-children, also pinpointing a similar, although significantly less pronounced, tendency among controls. Participants’ performance was controlled for age, cognitive and educational levels and for naming skills. None of these variables influenced the recognition bias for angry facial expressions. Differently, a significant effect of heart rate on participants’ tendency to use anger label was evidenced. Taken together, these results suggest that childhood exposure to maltreatment experiences amplifies children’s “pre-existing bias” for anger labeling in forced-choice emotion recognition task. Moreover, they strengthen the thesis according to which the recognition bias for angry facial expressions is a manifestation of a functional adaptive mechanism that tunes victim’s perceptive and attentive focus on salient environmental social stimuli. PMID:26509890

Improvement of emotional healthcare system with stress detection from ECG signal.

PubMed

Tivatansakul, S; Ohkura, M

2015-01-01

Our emotional healthcare system is designed to cope with users' negative emotions in daily life. To make the system more intelligent, we integrated emotion recognition by facial expression to provide appropriate services based on user's current emotional state. Our emotion recognition by facial expression has confusion issue to recognize some positive, neutral and negative emotions that make the emotional healthcare system provide a relaxation service even though users don't have negative emotions. Therefore, to increase the effectiveness of the system to provide the relaxation service, we integrate stress detection from ECG signal. The stress detection might be able to address the confusion issue of emotion recognition by facial expression to provide the service. Indeed, our results show that integration of stress detection increases the effectiveness and efficiency of the emotional healthcare system to provide services.

Audio-visual affective expression recognition

NASA Astrophysics Data System (ADS)

Huang, Thomas S.; Zeng, Zhihong

2007-11-01

Automatic affective expression recognition has attracted more and more attention of researchers from different disciplines, which will significantly contribute to a new paradigm for human computer interaction (affect-sensitive interfaces, socially intelligent environments) and advance the research in the affect-related fields including psychology, psychiatry, and education. Multimodal information integration is a process that enables human to assess affective states robustly and flexibly. In order to understand the richness and subtleness of human emotion behavior, the computer should be able to integrate information from multiple sensors. We introduce in this paper our efforts toward machine understanding of audio-visual affective behavior, based on both deliberate and spontaneous displays. Some promising methods are presented to integrate information from both audio and visual modalities. Our experiments show the advantage of audio-visual fusion in affective expression recognition over audio-only or visual-only approaches.

Using online handwriting and audio streams for mathematical expressions recognition: a bimodal approach

NASA Astrophysics Data System (ADS)

Medjkoune, Sofiane; Mouchère, Harold; Petitrenaud, Simon; Viard-Gaudin, Christian

2013-01-01

The work reported in this paper concerns the problem of mathematical expressions recognition. This task is known to be a very hard one. We propose to alleviate the difficulties by taking into account two complementary modalities. The modalities referred to are handwriting and audio ones. To combine the signals coming from both modalities, various fusion methods are explored. Performances evaluated on the HAMEX dataset show a significant improvement compared to a single modality (handwriting) based system.

Embodied emotion impairment in Huntington's Disease.

PubMed

Trinkler, Iris; Devignevielle, Sévérine; Achaibou, Amal; Ligneul, Romain V; Brugières, Pierre; Cleret de Langavant, Laurent; De Gelder, Beatrice; Scahill, Rachael; Schwartz, Sophie; Bachoud-Lévi, Anne-Catherine

2017-07-01

Theories of embodied cognition suggest that perceiving an emotion involves somatovisceral and motoric re-experiencing. Here we suggest taking such an embodied stance when looking at emotion processing deficits in patients with Huntington's Disease (HD), a neurodegenerative motor disorder. The literature on these patients' emotion recognition deficit has recently been enriched by some reports of impaired emotion expression. The goal of the study was to find out if expression deficits might be linked to a more motoric level of impairment. We used electromyography (EMG) to compare voluntary emotion expression from words to emotion imitation from static face images, and spontaneous emotion mimicry in 28 HD patients and 24 matched controls. For the latter two imitation conditions, an underlying emotion understanding is not imperative (even though performance might be helped by it). EMG measures were compared to emotion recognition and to the capacity to identify and describe emotions using alexithymia questionnaires. Alexithymia questionnaires tap into the more somato-visceral or interoceptive aspects of emotion perception. Furthermore, we correlated patients' expression and recognition scores to cerebral grey matter volume using voxel-based morphometry (VBM). EMG results replicated impaired voluntary emotion expression in HD. Critically, voluntary imitation and spontaneous mimicry were equally impaired and correlated with impaired recognition. By contrast, alexithymia scores were normal, suggesting that emotion representations on the level of internal experience might be spared. Recognition correlated with brain volume in the caudate as well as in areas previously associated with shared action representations, namely somatosensory, posterior parietal, posterior superior temporal sulcus (pSTS) and subcentral sulcus. Together, these findings indicate that in these patients emotion deficits might be tied to the "motoric level" of emotion expression. Such a double-sided recognition and expression impairment may have important consequences, interrupting empathy in nonverbal communication both ways (understanding and being understood), independently of intact internal experience of emotion. Copyright © 2017 Elsevier Ltd. All rights reserved.

Facial expression recognition under partial occlusion based on fusion of global and local features

NASA Astrophysics Data System (ADS)

Wang, Xiaohua; Xia, Chen; Hu, Min; Ren, Fuji

2018-04-01

Facial expression recognition under partial occlusion is a challenging research. This paper proposes a novel framework for facial expression recognition under occlusion by fusing the global and local features. In global aspect, first, information entropy are employed to locate the occluded region. Second, principal Component Analysis (PCA) method is adopted to reconstruct the occlusion region of image. After that, a replace strategy is applied to reconstruct image by replacing the occluded region with the corresponding region of the best matched image in training set, Pyramid Weber Local Descriptor (PWLD) feature is then extracted. At last, the outputs of SVM are fitted to the probabilities of the target class by using sigmoid function. For the local aspect, an overlapping block-based method is adopted to extract WLD features, and each block is weighted adaptively by information entropy, Chi-square distance and similar block summation methods are then applied to obtain the probabilities which emotion belongs to. Finally, fusion at the decision level is employed for the data fusion of the global and local features based on Dempster-Shafer theory of evidence. Experimental results on the Cohn-Kanade and JAFFE databases demonstrate the effectiveness and fault tolerance of this method.

Robust kernel collaborative representation for face recognition

NASA Astrophysics Data System (ADS)

Huang, Wei; Wang, Xiaohui; Ma, Yanbo; Jiang, Yuzheng; Zhu, Yinghui; Jin, Zhong

2015-05-01

One of the greatest challenges of representation-based face recognition is that the training samples are usually insufficient. In other words, the training set usually does not include enough samples to show varieties of high-dimensional face images caused by illuminations, facial expressions, and postures. When the test sample is significantly different from the training samples of the same subject, the recognition performance will be sharply reduced. We propose a robust kernel collaborative representation based on virtual samples for face recognition. We think that the virtual training set conveys some reasonable and possible variations of the original training samples. Hence, we design a new object function to more closely match the representation coefficients generated from the original and virtual training sets. In order to further improve the robustness, we implement the corresponding representation-based face recognition in kernel space. It is noteworthy that any kind of virtual training samples can be used in our method. We use noised face images to obtain virtual face samples. The noise can be approximately viewed as a reflection of the varieties of illuminations, facial expressions, and postures. Our work is a simple and feasible way to obtain virtual face samples to impose Gaussian noise (and other types of noise) specifically to the original training samples to obtain possible variations of the original samples. Experimental results on the FERET, Georgia Tech, and ORL face databases show that the proposed method is more robust than two state-of-the-art face recognition methods, such as CRC and Kernel CRC.

Person-independent facial expression analysis by fusing multiscale cell features

NASA Astrophysics Data System (ADS)

Zhou, Lubing; Wang, Han

2013-03-01

Automatic facial expression recognition is an interesting and challenging task. To achieve satisfactory accuracy, deriving a robust facial representation is especially important. A novel appearance-based feature, the multiscale cell local intensity increasing patterns (MC-LIIP), to represent facial images and conduct person-independent facial expression analysis is presented. The LIIP uses a decimal number to encode the texture or intensity distribution around each pixel via pixel-to-pixel intensity comparison. To boost noise resistance, MC-LIIP carries out comparison computation on the average values of scalable cells instead of individual pixels. The facial descriptor fuses region-based histograms of MC-LIIP features from various scales, so as to encode not only textural microstructures but also the macrostructures of facial images. Finally, a support vector machine classifier is applied for expression recognition. Experimental results on the CK+ and Karolinska directed emotional faces databases show the superiority of the proposed method.

False recognition of facial expressions of emotion: causes and implications.

PubMed

Fernández-Dols, José-Miguel; Carrera, Pilar; Barchard, Kimberly A; Gacitua, Marta

2008-08-01

This article examines the importance of semantic processes in the recognition of emotional expressions, through a series of three studies on false recognition. The first study found a high frequency of false recognition of prototypical expressions of emotion when participants viewed slides and video clips of nonprototypical fearful and happy expressions. The second study tested whether semantic processes caused false recognition. The authors found that participants made significantly higher error rates when asked to detect expressions that corresponded to semantic labels than when asked to detect visual stimuli. Finally, given that previous research reported that false memories are less prevalent in younger children, the third study tested whether false recognition of prototypical expressions increased with age. The authors found that 67% of eight- to nine-year-old children reported nonpresent prototypical expressions of fear in a fearful context, but only 40% of 6- to 7-year-old children did so. Taken together, these three studies demonstrate the importance of semantic processes in the detection and categorization of prototypical emotional expressions.

Recognition of cyclic-di-GMP by a riboswitch conducts translational repression through masking the ribosome-binding site distant from the aptamer domain.

PubMed

Inuzuka, Saki; Kakizawa, Hitoshi; Nishimura, Kei-Ichiro; Naito, Takuto; Miyazaki, Katsushi; Furuta, Hiroyuki; Matsumura, Shigeyoshi; Ikawa, Yoshiya

2018-06-01

The riboswitch is a class of RNA-based gene regulatory machinery that is dependent on recognition of its target ligand by RNA tertiary structures. Ligand recognition is achieved by the aptamer domain, and ligand-dependent structural changes of the expression platform then usually mediate termination of transcription or translational initiation. Ligand-dependent structural changes of the aptamer domain and expression platform have been reported for several riboswitches with short (<40 nucleotides) expression platforms. In this study, we characterized structural changes of the Vc2 c-di-GMP riboswitch that represses translation of downstream open reading frames in a ligand-dependent manner. The Vc2 riboswitch has a long (97 nucleotides) expression platform, but its structure and function are largely unknown. Through mutational analysis and chemical probing, we identified its secondary structures that are possibly responsible for switch-OFF and switch-ON states of translational initiation. © 2018 Molecular Biology Society of Japan and John Wiley & Sons Australia, Ltd.

Perceptual and affective mechanisms in facial expression recognition: An integrative review.

PubMed

Calvo, Manuel G; Nummenmaa, Lauri

2016-09-01

Facial expressions of emotion involve a physical component of morphological changes in a face and an affective component conveying information about the expresser's internal feelings. It remains unresolved how much recognition and discrimination of expressions rely on the perception of morphological patterns or the processing of affective content. This review of research on the role of visual and emotional factors in expression recognition reached three major conclusions. First, behavioral, neurophysiological, and computational measures indicate that basic expressions are reliably recognized and discriminated from one another, albeit the effect may be inflated by the use of prototypical expression stimuli and forced-choice responses. Second, affective content along the dimensions of valence and arousal is extracted early from facial expressions, although this coarse affective representation contributes minimally to categorical recognition of specific expressions. Third, the physical configuration and visual saliency of facial features contribute significantly to expression recognition, with "emotionless" computational models being able to reproduce some of the basic phenomena demonstrated in human observers. We conclude that facial expression recognition, as it has been investigated in conventional laboratory tasks, depends to a greater extent on perceptual than affective information and mechanisms.

Face memory and face recognition in children and adolescents with attention deficit hyperactivity disorder: A systematic review.

PubMed

Romani, Maria; Vigliante, Miriam; Faedda, Noemi; Rossetti, Serena; Pezzuti, Lina; Guidetti, Vincenzo; Cardona, Francesco

2018-06-01

This review focuses on facial recognition abilities in children and adolescents with attention deficit hyperactivity disorder (ADHD). A systematic review, using PRISMA guidelines, was conducted to identify original articles published prior to May 2017 pertaining to memory, face recognition, affect recognition, facial expression recognition and recall of faces in children and adolescents with ADHD. The qualitative synthesis based on different studies shows a particular focus of the research on facial affect recognition without paying similar attention to the structural encoding of facial recognition. In this review, we further investigate facial recognition abilities in children and adolescents with ADHD, providing synthesis of the results observed in the literature, while detecting face recognition tasks used on face processing abilities in ADHD and identifying aspects not yet explored. Copyright © 2018 Elsevier Ltd. All rights reserved.

Analysis of differences between Western and East-Asian faces based on facial region segmentation and PCA for facial expression recognition

NASA Astrophysics Data System (ADS)

Benitez-Garcia, Gibran; Nakamura, Tomoaki; Kaneko, Masahide

2017-01-01

Darwin was the first one to assert that facial expressions are innate and universal, which are recognized across all cultures. However, recent some cross-cultural studies have questioned this assumed universality. Therefore, this paper presents an analysis of the differences between Western and East-Asian faces of the six basic expressions (anger, disgust, fear, happiness, sadness and surprise) focused on three individual facial regions of eyes-eyebrows, nose and mouth. The analysis is conducted by applying PCA for two feature extraction methods: appearance-based by using the pixel intensities of facial parts, and geometric-based by handling 125 feature points from the face. Both methods are evaluated using 4 standard databases for both racial groups and the results are compared with a cross-cultural human study applied to 20 participants. Our analysis reveals that differences between Westerns and East-Asians exist mainly on the regions of eyes-eyebrows and mouth for expressions of fear and disgust respectively. This work presents important findings for a better design of automatic facial expression recognition systems based on the difference between two racial groups.

Impaired recognition of happy facial expressions in bipolar disorder.

PubMed

Lawlor-Savage, Linette; Sponheim, Scott R; Goghari, Vina M

2014-08-01

The ability to accurately judge facial expressions is important in social interactions. Individuals with bipolar disorder have been found to be impaired in emotion recognition; however, the specifics of the impairment are unclear. This study investigated whether facial emotion recognition difficulties in bipolar disorder reflect general cognitive, or emotion-specific, impairments. Impairment in the recognition of particular emotions and the role of processing speed in facial emotion recognition were also investigated. Clinically stable bipolar patients (n = 17) and healthy controls (n = 50) judged five facial expressions in two presentation types, time-limited and self-paced. An age recognition condition was used as an experimental control. Bipolar patients' overall facial recognition ability was unimpaired. However, patients' specific ability to judge happy expressions under time constraints was impaired. Findings suggest a deficit in happy emotion recognition impacted by processing speed. Given the limited sample size, further investigation with a larger patient sample is warranted.

Recognition of facial expressions and prosodic cues with graded emotional intensities in adults with Asperger syndrome.

PubMed

Doi, Hirokazu; Fujisawa, Takashi X; Kanai, Chieko; Ohta, Haruhisa; Yokoi, Hideki; Iwanami, Akira; Kato, Nobumasa; Shinohara, Kazuyuki

2013-09-01

This study investigated the ability of adults with Asperger syndrome to recognize emotional categories of facial expressions and emotional prosodies with graded emotional intensities. The individuals with Asperger syndrome showed poorer recognition performance for angry and sad expressions from both facial and vocal information. The group difference in facial expression recognition was prominent for stimuli with low or intermediate emotional intensities. In contrast to this, the individuals with Asperger syndrome exhibited lower recognition accuracy than typically-developed controls mainly for emotional prosody with high emotional intensity. In facial expression recognition, Asperger and control groups showed an inversion effect for all categories. The magnitude of this effect was less in the Asperger group for angry and sad expressions, presumably attributable to reduced recruitment of the configural mode of face processing. The individuals with Asperger syndrome outperformed the control participants in recognizing inverted sad expressions, indicating enhanced processing of local facial information representing sad emotion. These results suggest that the adults with Asperger syndrome rely on modality-specific strategies in emotion recognition from facial expression and prosodic information.

Facial Affect Recognition Using Regularized Discriminant Analysis-Based Algorithms

NASA Astrophysics Data System (ADS)

Lee, Chien-Cheng; Huang, Shin-Sheng; Shih, Cheng-Yuan

2010-12-01

This paper presents a novel and effective method for facial expression recognition including happiness, disgust, fear, anger, sadness, surprise, and neutral state. The proposed method utilizes a regularized discriminant analysis-based boosting algorithm (RDAB) with effective Gabor features to recognize the facial expressions. Entropy criterion is applied to select the effective Gabor feature which is a subset of informative and nonredundant Gabor features. The proposed RDAB algorithm uses RDA as a learner in the boosting algorithm. The RDA combines strengths of linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA). It solves the small sample size and ill-posed problems suffered from QDA and LDA through a regularization technique. Additionally, this study uses the particle swarm optimization (PSO) algorithm to estimate optimal parameters in RDA. Experiment results demonstrate that our approach can accurately and robustly recognize facial expressions.

[The Relationship Between Emotion Recognition and the Symptoms of Attention Deficit and Impulsivity in Adult Patients With Attention Deficit Hyperactivity Disorder].

PubMed

Baran Tatar, Zeynep; Yargıç, İlhan; Oflaz, Serap; Büyükgök, Deniz

2015-01-01

Interpersonal relationship disorders in adults with Attention Deficit Hyperactivity Disorder (ADHD) can be associated with the impairment of non-verbal communication. The purpose of our study was to compare the emotion recognition, facial recognition and neuropsychological assessments of adult ADHD patients with those of healthy controls, and to thus determine the effect of neuropsychological data on the recognition of emotional expressions. This study, which was based on a case-control model, was conducted with patients diagnosed with ADHD according to the DSM-IV-TR, being followed and monitored at the adult ADHD clinic of the Psychiatry Department of the Istanbul University Istanbul Medical Faculty Hospital. The study group consisted of 40 adults (27.5% female) between the ages of 20-65 (mean age 25.96 ± 6.07; education level: 15.02±2.34 years) diagnosed with ADHD, and 40 controls who were matched/similar with the study group with respect to age, gender, and education level. In the ADHD group, 14 (35%) of the patients had concomitant diseases. Pictures of Facial Affect, the Benton Face Recognition Test, and the Continuous Performance Test were used to respectively evaluate emotion recognition, facial recognition, and attention deficit and impulsivity of the patients. It was determined that, in comparison to the control group, the ADHD group made more mistakes in recognizing all types of emotional expressions and neutral expressions. The ADHD group also demonstrated more cognitive mistakes. Facial recognition was similar in both groups. It was determined that impulsivity had a significant effect on facial recognition. The social relationship disorders observed in ADHD can be affected by emotion recognition processes. In future studies, it may be possible to investigate the effects that early psychopharmacological and psychotherapeutic interventions administered for the main symptoms of ADHD have on the impairment of emotion recognition.

Eye-Gaze Analysis of Facial Emotion Recognition and Expression in Adolescents with ASD.

PubMed

Wieckowski, Andrea Trubanova; White, Susan W

2017-01-01

Impaired emotion recognition and expression in individuals with autism spectrum disorder (ASD) may contribute to observed social impairment. The aim of this study was to examine the role of visual attention directed toward nonsocial aspects of a scene as a possible mechanism underlying recognition and expressive ability deficiency in ASD. One recognition and two expression tasks were administered. Recognition was assessed in force-choice paradigm, and expression was assessed during scripted and free-choice response (in response to emotional stimuli) tasks in youth with ASD (n = 20) and an age-matched sample of typically developing youth (n = 20). During stimulus presentation prior to response in each task, participants' eye gaze was tracked. Youth with ASD were less accurate at identifying disgust and sadness in the recognition task. They fixated less to the eye region of stimuli showing surprise. A group difference was found during the free-choice response task, such that those with ASD expressed emotion less clearly but not during the scripted task. Results suggest altered eye gaze to the mouth region but not the eye region as a candidate mechanism for decreased ability to recognize or express emotion. Findings inform our understanding of the association between social attention and emotion recognition and expression deficits.

The nonverbal expression of pride: evidence for cross-cultural recognition.

PubMed

Tracy, Jessica L; Robins, Richard W

2008-03-01

The present research tests whether recognition for the nonverbal expression of pride generalizes across cultures. Study 1 provided the first evidence for cross-cultural recognition of pride, demonstrating that the expression generalizes across Italy and the United States. Study 2 found that the pride expression generalizes beyond Western cultures; individuals from a preliterate, highly isolated tribe in Burkina Faso, West Africa, reliably recognized pride, regardless of whether it was displayed by African or American targets. These Burkinabe participants were unlikely to have learned the pride expression through cross-cultural transmission, so their recognition suggests that pride may be a human universal. Studies 3 and 4 used drawn figures to systematically manipulate the ethnicity and gender of targets showing the expression, and demonstrated that pride recognition generalizes across male and female targets of African, Asian, and Caucasian descent. Discussion focuses on the implications of the findings for the universality of the pride expression.

Joint recognition-expression impairment of facial emotions in Huntington's disease despite intact understanding of feelings.

PubMed

Trinkler, Iris; Cleret de Langavant, Laurent; Bachoud-Lévi, Anne-Catherine

2013-02-01

Patients with Huntington's disease (HD), a neurodegenerative disorder that causes major motor impairments, also show cognitive and emotional deficits. While their deficit in recognising emotions has been explored in depth, little is known about their ability to express emotions and understand their feelings. If these faculties were impaired, patients might not only mis-read emotion expressions in others but their own emotions might be mis-interpreted by others as well, or thirdly, they might have difficulties understanding and describing their feelings. We compared the performance of recognition and expression of facial emotions in 13 HD patients with mild motor impairments but without significant bucco-facial abnormalities, and 13 controls matched for age and education. Emotion recognition was investigated in a forced-choice recognition test (FCR), and emotion expression by filming participants while they mimed the six basic emotional facial expressions (anger, disgust, fear, surprise, sadness and joy) to the experimenter. The films were then segmented into 60 stimuli per participant and four external raters performed a FCR on this material. Further, we tested understanding of feelings in self (alexithymia) and others (empathy) using questionnaires. Both recognition and expression were impaired across different emotions in HD compared to controls and recognition and expression scores were correlated. By contrast, alexithymia and empathy scores were very similar in HD and controls. This might suggest that emotion deficits in HD might be tied to the expression itself. Because similar emotion recognition-expression deficits are also found in Parkinson's Disease and vascular lesions of the striatum, our results further confirm the importance of the striatum for emotion recognition and expression, while access to the meaning of feelings relies on a different brain network, and is spared in HD. Copyright © 2011 Elsevier Ltd. All rights reserved.

Exploring the Effect of Illumination on Automatic Expression Recognition using the ICT-3DRFE Database

DTIC Science & Technology

2011-11-04

environmen- tal lighting conditions that one can actually come across. L7 and L8 are also cases of low illumination intensity. To produce our experimental...Graphics (Proceedings of ACM SIGGRAPH), 26(3). [9] Riklin- Raviv T., Shashua A., (1999). The quotient image: class based recognition and synthesis under

Facial Expression Recognition Deficits and Faulty Learning: Implications for Theoretical Models and Clinical Applications

ERIC Educational Resources Information Center

Sheaffer, Beverly L.; Golden, Jeannie A.; Averett, Paige

2009-01-01

The ability to recognize facial expressions of emotion is integral in social interaction. Although the importance of facial expression recognition is reflected in increased research interest as well as in popular culture, clinicians may know little about this topic. The purpose of this article is to discuss facial expression recognition literature…

Mismatched expressions decrease face recognition and corresponding ERP old/new effects in schizophrenia.

PubMed

Guillaume, Fabrice; Guillem, François; Tiberghien, Guy; Stip, Emmanuel

2012-09-01

The objective was to investigate the electrophysiological (ERP) correlates of mismatched expression on face recognition in schizophrenia. Expression-change effects and associated ERPs were explored in patients with schizophrenia (n = 20) and paired comparison participants (n = 20) on a long-term face-recognition task. A facial-expression change decreased discriminability for patients with schizophrenia than for healthy participants. The patients' recognition deficit was accompanied by the absence of the midfrontal FN400 and late parietal ERP old/new effects in the mismatched-expression condition. By contrast, preserved midfrontal FN400 and late parietal ERP old/new effects were found in both groups in the unchanged-expression condition. Thus, the preserved parietal old/new effect previously observed in schizophrenia was no longer found here in the situation in which expression changes took place between the study and recognition phases. These findings suggest that, when they are not supposed to take the change of expression into account, the recognition deficit observed here in patients with schizophrenia resulted from an impairment in the mechanisms underlying the emergence, assessment, or utilization of familiarity--as indexed by the ERP old/new effects. In these natural conditions, the impact of the expression change on the implementation of retrieval processes offers new insight into schizophrenia-linked deficits in face recognition, with substantial phenomenological differences with respect to the emergence of familiarity.

Anatomical Entity Recognition with a Hierarchical Framework Augmented by External Resources

PubMed Central

Xu, Yan; Hua, Ji; Ni, Zhaoheng; Chen, Qinlang; Fan, Yubo; Ananiadou, Sophia; Chang, Eric I-Chao; Tsujii, Junichi

2014-01-01

References to anatomical entities in medical records consist not only of explicit references to anatomical locations, but also other diverse types of expressions, such as specific diseases, clinical tests, clinical treatments, which constitute implicit references to anatomical entities. In order to identify these implicit anatomical entities, we propose a hierarchical framework, in which two layers of named entity recognizers (NERs) work in a cooperative manner. Each of the NERs is implemented using the Conditional Random Fields (CRF) model, which use a range of external resources to generate features. We constructed a dictionary of anatomical entity expressions by exploiting four existing resources, i.e., UMLS, MeSH, RadLex and BodyPart3D, and supplemented information from two external knowledge bases, i.e., Wikipedia and WordNet, to improve inference of anatomical entities from implicit expressions. Experiments conducted on 300 discharge summaries showed a micro-averaged performance of 0.8509 Precision, 0.7796 Recall and 0.8137 F1 for explicit anatomical entity recognition, and 0.8695 Precision, 0.6893 Recall and 0.7690 F1 for implicit anatomical entity recognition. The use of the hierarchical framework, which combines the recognition of named entities of various types (diseases, clinical tests, treatments) with information embedded in external knowledge bases, resulted in a 5.08% increment in F1. The resources constructed for this research will be made publicly available. PMID:25343498

Unseen stimuli modulate conscious visual experience: evidence from inter-hemispheric summation.

PubMed

de Gelder, B; Pourtois, G; van Raamsdonk, M; Vroomen, J; Weiskrantz, L

2001-02-12

Emotional facial expression can be discriminated despite extensive lesions of striate cortex. Here we report differential performance with recognition of facial stimuli in the intact visual field depending on simultaneous presentation of congruent or incongruent stimuli in the blind field. Three experiments were based on inter-hemispheric summation. Redundant stimulation in the blind field led to shorter latencies for stimulus detection in the intact field. Recognition of the expression of a half-face expression in the intact field was faster when the other half of the face presented to the blind field had a congruent expression. Finally, responses to the expression of whole faces to the intact field were delayed for incongruent facial expressions presented in the blind field. These results indicate that the neuro-anatomical pathways (extra-striate cortical and sub-cortical) sustaining inter-hemispheric summation can operate in the absence of striate cortex.

Local Context Finder (LCF) reveals multidimensional relationships among mRNA expression profiles of Arabidopsis responding to pathogen infection

PubMed Central

Katagiri, Fumiaki; Glazebrook, Jane

2003-01-01

A major task in computational analysis of mRNA expression profiles is definition of relationships among profiles on the basis of similarities among them. This is generally achieved by pattern recognition in the distribution of data points representing each profile in a high-dimensional space. Some drawbacks of commonly used pattern recognition algorithms stem from their use of a globally linear space and/or limited degrees of freedom. A pattern recognition method called Local Context Finder (LCF) is described here. LCF uses nonlinear dimensionality reduction for pattern recognition. Then it builds a network of profiles based on the nonlinear dimensionality reduction results. LCF was used to analyze mRNA expression profiles of the plant host Arabidopsis interacting with the bacterial pathogen Pseudomonas syringae. In one case, LCF revealed two dimensions essential to explain the effects of the NahG transgene and the ndr1 mutation on resistant and susceptible responses. In another case, plant mutants deficient in responses to pathogen infection were classified on the basis of LCF analysis of their profiles. The classification by LCF was consistent with the results of biological characterization of the mutants. Thus, LCF is a powerful method for extracting information from expression profile data. PMID:12960373

Gene expression pattern recognition algorithm inferences to classify samples exposed to chemical agents

NASA Astrophysics Data System (ADS)

Bushel, Pierre R.; Bennett, Lee; Hamadeh, Hisham; Green, James; Ableson, Alan; Misener, Steve; Paules, Richard; Afshari, Cynthia

2002-06-01

We present an analysis of pattern recognition procedures used to predict the classes of samples exposed to pharmacologic agents by comparing gene expression patterns from samples treated with two classes of compounds. Rat liver mRNA samples following exposure for 24 hours with phenobarbital or peroxisome proliferators were analyzed using a 1700 rat cDNA microarray platform. Sets of genes that were consistently differentially expressed in the rat liver samples following treatment were stored in the MicroArray Project System (MAPS) database. MAPS identified 238 genes in common that possessed a low probability (P < 0.01) of being randomly detected as differentially expressed at the 95% confidence level. Hierarchical cluster analysis on the 238 genes clustered specific gene expression profiles that separated samples based on exposure to a particular class of compound.

Online handwritten mathematical expression recognition

NASA Astrophysics Data System (ADS)

Büyükbayrak, Hakan; Yanikoglu, Berrin; Erçil, Aytül

2007-01-01

We describe a system for recognizing online, handwritten mathematical expressions. The system is designed with a user-interface for writing scientific articles, supporting the recognition of basic mathematical expressions as well as integrals, summations, matrices etc. A feed-forward neural network recognizes symbols which are assumed to be single-stroke and a recursive algorithm parses the expression by combining neural network output and the structure of the expression. Preliminary results show that writer-dependent recognition rates are very high (99.8%) while writer-independent symbol recognition rates are lower (75%). The interface associated with the proposed system integrates the built-in recognition capabilities of the Microsoft's Tablet PC API for recognizing textual input and supports conversion of hand-drawn figures into PNG format. This enables the user to enter text, mathematics and draw figures in a single interface. After recognition, all output is combined into one LATEX code and compiled into a PDF file.

A study on facial expressions recognition

NASA Astrophysics Data System (ADS)

Xu, Jingjing

2017-09-01

In terms of communication, postures and facial expressions of such feelings like happiness, anger and sadness play important roles in conveying information. With the development of the technology, recently a number of algorithms dealing with face alignment, face landmark detection, classification, facial landmark localization and pose estimation have been put forward. However, there are a lot of challenges and problems need to be fixed. In this paper, a few technologies have been concluded and analyzed, and they all relate to handling facial expressions recognition and poses like pose-indexed based multi-view method for face alignment, robust facial landmark detection under significant head pose and occlusion, partitioning the input domain for classification, robust statistics face formalization.

Sex differences in facial emotion recognition across varying expression intensity levels from videos.

PubMed

Wingenbach, Tanja S H; Ashwin, Chris; Brosnan, Mark

2018-01-01

There has been much research on sex differences in the ability to recognise facial expressions of emotions, with results generally showing a female advantage in reading emotional expressions from the face. However, most of the research to date has used static images and/or 'extreme' examples of facial expressions. Therefore, little is known about how expression intensity and dynamic stimuli might affect the commonly reported female advantage in facial emotion recognition. The current study investigated sex differences in accuracy of response (Hu; unbiased hit rates) and response latencies for emotion recognition using short video stimuli (1sec) of 10 different facial emotion expressions (anger, disgust, fear, sadness, surprise, happiness, contempt, pride, embarrassment, neutral) across three variations in the intensity of the emotional expression (low, intermediate, high) in an adolescent and adult sample (N = 111; 51 male, 60 female) aged between 16 and 45 (M = 22.2, SD = 5.7). Overall, females showed more accurate facial emotion recognition compared to males and were faster in correctly recognising facial emotions. The female advantage in reading expressions from the faces of others was unaffected by expression intensity levels and emotion categories used in the study. The effects were specific to recognition of emotions, as males and females did not differ in the recognition of neutral faces. Together, the results showed a robust sex difference favouring females in facial emotion recognition using video stimuli of a wide range of emotions and expression intensity variations.

Sex differences in facial emotion recognition across varying expression intensity levels from videos

PubMed Central

2018-01-01

There has been much research on sex differences in the ability to recognise facial expressions of emotions, with results generally showing a female advantage in reading emotional expressions from the face. However, most of the research to date has used static images and/or ‘extreme’ examples of facial expressions. Therefore, little is known about how expression intensity and dynamic stimuli might affect the commonly reported female advantage in facial emotion recognition. The current study investigated sex differences in accuracy of response (Hu; unbiased hit rates) and response latencies for emotion recognition using short video stimuli (1sec) of 10 different facial emotion expressions (anger, disgust, fear, sadness, surprise, happiness, contempt, pride, embarrassment, neutral) across three variations in the intensity of the emotional expression (low, intermediate, high) in an adolescent and adult sample (N = 111; 51 male, 60 female) aged between 16 and 45 (M = 22.2, SD = 5.7). Overall, females showed more accurate facial emotion recognition compared to males and were faster in correctly recognising facial emotions. The female advantage in reading expressions from the faces of others was unaffected by expression intensity levels and emotion categories used in the study. The effects were specific to recognition of emotions, as males and females did not differ in the recognition of neutral faces. Together, the results showed a robust sex difference favouring females in facial emotion recognition using video stimuli of a wide range of emotions and expression intensity variations. PMID:29293674

Emotional expression recognition and attribution bias among sexual and violent offenders: a signal detection analysis

PubMed Central

Gillespie, Steven M.; Rotshtein, Pia; Satherley, Rose-Marie; Beech, Anthony R.; Mitchell, Ian J.

2015-01-01

Research with violent offenders has consistently shown impaired recognition of other’s facial expressions of emotion. However, the extent to which similar problems can be observed among sexual offenders remains unknown. Using a computerized task, we presented sexual and violent offenders, and non-offenders, with male and female expressions of anger, disgust, fear, happiness, sadness, and surprise, morphed with neutral expressions at varying levels of intensity (10, 55, and 90% expressive). Based on signal detection theory, we used hit rates and false alarms to calculate the sensitivity index d-prime (d′) and criterion (c) for each emotional expression. Overall, sexual offenders showed reduced sensitivity to emotional expressions across intensity, sex, and type of expression, compared with non-offenders, while both sexual and violent offenders showed particular reduced sensitivity to fearful expressions. We also observed specific effects for high (90%) intensity female faces, with sexual offenders showing reduced sensitivity to anger compared with non-offenders and violent offenders, and reduced sensitivity to disgust compared with non-offenders. Furthermore, both sexual and violent offenders showed impaired sensitivity to high intensity female fearful expressions compared with non-offenders. Violent offenders also showed a higher criterion for classifying moderate and high intensity male expressions as fearful, indicative of a more conservative response style, compared with angry, happy, or sad. These results suggest that both types of offender show problems in emotion recognition, and may have implications for understanding the inhibition of violent and sexually violent behaviors. PMID:26029137

Emotional expression recognition and attribution bias among sexual and violent offenders: a signal detection analysis.

PubMed

Gillespie, Steven M; Rotshtein, Pia; Satherley, Rose-Marie; Beech, Anthony R; Mitchell, Ian J

2015-01-01

Research with violent offenders has consistently shown impaired recognition of other's facial expressions of emotion. However, the extent to which similar problems can be observed among sexual offenders remains unknown. Using a computerized task, we presented sexual and violent offenders, and non-offenders, with male and female expressions of anger, disgust, fear, happiness, sadness, and surprise, morphed with neutral expressions at varying levels of intensity (10, 55, and 90% expressive). Based on signal detection theory, we used hit rates and false alarms to calculate the sensitivity index d-prime (d') and criterion (c) for each emotional expression. Overall, sexual offenders showed reduced sensitivity to emotional expressions across intensity, sex, and type of expression, compared with non-offenders, while both sexual and violent offenders showed particular reduced sensitivity to fearful expressions. We also observed specific effects for high (90%) intensity female faces, with sexual offenders showing reduced sensitivity to anger compared with non-offenders and violent offenders, and reduced sensitivity to disgust compared with non-offenders. Furthermore, both sexual and violent offenders showed impaired sensitivity to high intensity female fearful expressions compared with non-offenders. Violent offenders also showed a higher criterion for classifying moderate and high intensity male expressions as fearful, indicative of a more conservative response style, compared with angry, happy, or sad. These results suggest that both types of offender show problems in emotion recognition, and may have implications for understanding the inhibition of violent and sexually violent behaviors.

Facial recognition in education system

NASA Astrophysics Data System (ADS)

Krithika, L. B.; Venkatesh, K.; Rathore, S.; Kumar, M. Harish

2017-11-01

Human beings exploit emotions comprehensively for conveying messages and their resolution. Emotion detection and face recognition can provide an interface between the individuals and technologies. The most successful applications of recognition analysis are recognition of faces. Many different techniques have been used to recognize the facial expressions and emotion detection handle varying poses. In this paper, we approach an efficient method to recognize the facial expressions to track face points and distances. This can automatically identify observer face movements and face expression in image. This can capture different aspects of emotion and facial expressions.

Impaired Perception of Emotional Expression in Amyotrophic Lateral Sclerosis.

PubMed

Oh, Seong Il; Oh, Ki Wook; Kim, Hee Jin; Park, Jin Seok; Kim, Seung Hyun

2016-07-01

The increasing recognition that deficits in social emotions occur in amyotrophic lateral sclerosis (ALS) is helping to explain the spectrum of neuropsychological dysfunctions, thus supporting the view of ALS as a multisystem disorder involving neuropsychological deficits as well as motor deficits. The aim of this study was to characterize the emotion perception abilities of Korean patients with ALS based on the recognition of facial expressions. Twenty-four patients with ALS and 24 age- and sex-matched healthy controls completed neuropsychological tests and facial emotion recognition tasks [ChaeLee Korean Facial Expressions of Emotions (ChaeLee-E)]. The ChaeLee-E test includes facial expressions for seven emotions: happiness, sadness, anger, disgust, fear, surprise, and neutral. The ability to perceive facial emotions was significantly worse among ALS patients performed than among healthy controls [65.2±18.0% vs. 77.1±6.6% (mean±SD), p=0.009]. Eight of the 24 patients (33%) scored below the 5th percentile score of controls for recognizing facial emotions. Emotion perception deficits occur in Korean ALS patients, particularly regarding facial expressions of emotion. These findings expand the spectrum of cognitive and behavioral dysfunction associated with ALS into emotion processing dysfunction.

Emotional recognition from dynamic facial, vocal and musical expressions following traumatic brain injury.

PubMed

Drapeau, Joanie; Gosselin, Nathalie; Peretz, Isabelle; McKerral, Michelle

2017-01-01

To assess emotion recognition from dynamic facial, vocal and musical expressions in sub-groups of adults with traumatic brain injuries (TBI) of different severities and identify possible common underlying mechanisms across domains. Forty-one adults participated in this study: 10 with moderate-severe TBI, nine with complicated mild TBI, 11 with uncomplicated mild TBI and 11 healthy controls, who were administered experimental (emotional recognition, valence-arousal) and control tasks (emotional and structural discrimination) for each domain. Recognition of fearful faces was significantly impaired in moderate-severe and in complicated mild TBI sub-groups, as compared to those with uncomplicated mild TBI and controls. Effect sizes were medium-large. Participants with lower GCS scores performed more poorly when recognizing fearful dynamic facial expressions. Emotion recognition from auditory domains was preserved following TBI, irrespective of severity. All groups performed equally on control tasks, indicating no perceptual disorders. Although emotional recognition from vocal and musical expressions was preserved, no correlation was found across auditory domains. This preliminary study may contribute to improving comprehension of emotional recognition following TBI. Future studies of larger samples could usefully include measures of functional impacts of recognition deficits for fearful facial expressions. These could help refine interventions for emotional recognition following a brain injury.

Dual Temporal Scale Convolutional Neural Network for Micro-Expression Recognition.

PubMed

Peng, Min; Wang, Chongyang; Chen, Tong; Liu, Guangyuan; Fu, Xiaolan

2017-01-01

Facial micro-expression is a brief involuntary facial movement and can reveal the genuine emotion that people try to conceal. Traditional methods of spontaneous micro-expression recognition rely excessively on sophisticated hand-crafted feature design and the recognition rate is not high enough for its practical application. In this paper, we proposed a Dual Temporal Scale Convolutional Neural Network (DTSCNN) for spontaneous micro-expressions recognition. The DTSCNN is a two-stream network. Different of stream of DTSCNN is used to adapt to different frame rate of micro-expression video clips. Each stream of DSTCNN consists of independent shallow network for avoiding the overfitting problem. Meanwhile, we fed the networks with optical-flow sequences to ensure that the shallow networks can further acquire higher-level features. Experimental results on spontaneous micro-expression databases (CASME I/II) showed that our method can achieve a recognition rate almost 10% higher than what some state-of-the-art method can achieve.

Anodal tDCS targeting the right orbitofrontal cortex enhances facial expression recognition

PubMed Central

Murphy, Jillian M.; Ridley, Nicole J.; Vercammen, Ans

2015-01-01

The orbitofrontal cortex (OFC) has been implicated in the capacity to accurately recognise facial expressions. The aim of the current study was to determine if anodal transcranial direct current stimulation (tDCS) targeting the right OFC in healthy adults would enhance facial expression recognition, compared with a sham condition. Across two counterbalanced sessions of tDCS (i.e. anodal and sham), 20 undergraduate participants (18 female) completed a facial expression labelling task comprising angry, disgusted, fearful, happy, sad and neutral expressions, and a control (social judgement) task comprising the same expressions. Responses on the labelling task were scored for accuracy, median reaction time and overall efficiency (i.e. combined accuracy and reaction time). Anodal tDCS targeting the right OFC enhanced facial expression recognition, reflected in greater efficiency and speed of recognition across emotions, relative to the sham condition. In contrast, there was no effect of tDCS to responses on the control task. This is the first study to demonstrate that anodal tDCS targeting the right OFC boosts facial expression recognition. This finding provides a solid foundation for future research to examine the efficacy of this technique as a means to treat facial expression recognition deficits, particularly in individuals with OFC damage or dysfunction. PMID:25971602

Emotional facial recognition in proactive and reactive violent offenders.

PubMed

Philipp-Wiegmann, Florence; Rösler, Michael; Retz-Junginger, Petra; Retz, Wolfgang

2017-10-01

The purpose of this study is to analyse individual differences in the ability of emotional facial recognition in violent offenders, who were characterised as either reactive or proactive in relation to their offending. In accordance with findings of our previous study, we expected higher impairments in facial recognition in reactive than proactive violent offenders. To assess the ability to recognize facial expressions, the computer-based Facial Emotional Expression Labeling Test (FEEL) was performed. Group allocation of reactive und proactive violent offenders and assessment of psychopathic traits were performed by an independent forensic expert using rating scales (PROREA, PCL-SV). Compared to proactive violent offenders and controls, the performance of emotion recognition in the reactive offender group was significantly lower, both in total and especially in recognition of negative emotions such as anxiety (d = -1.29), sadness (d = -1.54), and disgust (d = -1.11). Furthermore, reactive violent offenders showed a tendency to interpret non-anger emotions as anger. In contrast, proactive violent offenders performed as well as controls. General and specific deficits in reactive violent offenders are in line with the results of our previous study and correspond to predictions of the Integrated Emotion System (IES, 7) and the hostile attribution processes (21). Due to the different error pattern in the FEEL test, the theoretical distinction between proactive and reactive aggression can be supported based on emotion recognition, even though aggression itself is always a heterogeneous act rather than a distinct one-dimensional concept.

Multimodal emotional state recognition using sequence-dependent deep hierarchical features.

PubMed

Barros, Pablo; Jirak, Doreen; Weber, Cornelius; Wermter, Stefan

2015-12-01

Emotional state recognition has become an important topic for human-robot interaction in the past years. By determining emotion expressions, robots can identify important variables of human behavior and use these to communicate in a more human-like fashion and thereby extend the interaction possibilities. Human emotions are multimodal and spontaneous, which makes them hard to be recognized by robots. Each modality has its own restrictions and constraints which, together with the non-structured behavior of spontaneous expressions, create several difficulties for the approaches present in the literature, which are based on several explicit feature extraction techniques and manual modality fusion. Our model uses a hierarchical feature representation to deal with spontaneous emotions, and learns how to integrate multiple modalities for non-verbal emotion recognition, making it suitable to be used in an HRI scenario. Our experiments show that a significant improvement of recognition accuracy is achieved when we use hierarchical features and multimodal information, and our model improves the accuracy of state-of-the-art approaches from 82.5% reported in the literature to 91.3% for a benchmark dataset on spontaneous emotion expressions. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Relative preservation of the recognition of positive facial expression "happiness" in Alzheimer disease.

PubMed

Maki, Yohko; Yoshida, Hiroshi; Yamaguchi, Tomoharu; Yamaguchi, Haruyasu

2013-01-01

Positivity recognition bias has been reported for facial expression as well as memory and visual stimuli in aged individuals, whereas emotional facial recognition in Alzheimer disease (AD) patients is controversial, with possible involvement of confounding factors such as deficits in spatial processing of non-emotional facial features and in verbal processing to express emotions. Thus, we examined whether recognition of positive facial expressions was preserved in AD patients, by adapting a new method that eliminated the influences of these confounding factors. Sensitivity of six basic facial expressions (happiness, sadness, surprise, anger, disgust, and fear) was evaluated in 12 outpatients with mild AD, 17 aged normal controls (ANC), and 25 young normal controls (YNC). To eliminate the factors related to non-emotional facial features, averaged faces were prepared as stimuli. To eliminate the factors related to verbal processing, the participants were required to match the images of stimulus and answer, avoiding the use of verbal labels. In recognition of happiness, there was no difference in sensitivity between YNC and ANC, and between ANC and AD patients. AD patients were less sensitive than ANC in recognition of sadness, surprise, and anger. ANC were less sensitive than YNC in recognition of surprise, anger, and disgust. Within the AD patient group, sensitivity of happiness was significantly higher than those of the other five expressions. In AD patient, recognition of happiness was relatively preserved; recognition of happiness was most sensitive and was preserved against the influences of age and disease.

Decoding facial expressions based on face-selective and motion-sensitive areas.

PubMed

Liang, Yin; Liu, Baolin; Xu, Junhai; Zhang, Gaoyan; Li, Xianglin; Wang, Peiyuan; Wang, Bin

2017-06-01

Humans can easily recognize others' facial expressions. Among the brain substrates that enable this ability, considerable attention has been paid to face-selective areas; in contrast, whether motion-sensitive areas, which clearly exhibit sensitivity to facial movements, are involved in facial expression recognition remained unclear. The present functional magnetic resonance imaging (fMRI) study used multi-voxel pattern analysis (MVPA) to explore facial expression decoding in both face-selective and motion-sensitive areas. In a block design experiment, participants viewed facial expressions of six basic emotions (anger, disgust, fear, joy, sadness, and surprise) in images, videos, and eyes-obscured videos. Due to the use of multiple stimulus types, the impacts of facial motion and eye-related information on facial expression decoding were also examined. It was found that motion-sensitive areas showed significant responses to emotional expressions and that dynamic expressions could be successfully decoded in both face-selective and motion-sensitive areas. Compared with static stimuli, dynamic expressions elicited consistently higher neural responses and decoding performance in all regions. A significant decrease in both activation and decoding accuracy due to the absence of eye-related information was also observed. Overall, the findings showed that emotional expressions are represented in motion-sensitive areas in addition to conventional face-selective areas, suggesting that motion-sensitive regions may also effectively contribute to facial expression recognition. The results also suggested that facial motion and eye-related information played important roles by carrying considerable expression information that could facilitate facial expression recognition. Hum Brain Mapp 38:3113-3125, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

EMOTION RECOGNITION OF VIRTUAL AGENTS FACIAL EXPRESSIONS: THE EFFECTS OF AGE AND EMOTION INTENSITY

PubMed Central

Beer, Jenay M.; Fisk, Arthur D.; Rogers, Wendy A.

2014-01-01

People make determinations about the social characteristics of an agent (e.g., robot or virtual agent) by interpreting social cues displayed by the agent, such as facial expressions. Although a considerable amount of research has been conducted investigating age-related differences in emotion recognition of human faces (e.g., Sullivan, & Ruffman, 2004), the effect of age on emotion identification of virtual agent facial expressions has been largely unexplored. Age-related differences in emotion recognition of facial expressions are an important factor to consider in the design of agents that may assist older adults in a recreational or healthcare setting. The purpose of the current research was to investigate whether age-related differences in facial emotion recognition can extend to emotion-expressive virtual agents. Younger and older adults performed a recognition task with a virtual agent expressing six basic emotions. Larger age-related differences were expected for virtual agents displaying negative emotions, such as anger, sadness, and fear. In fact, the results indicated that older adults showed a decrease in emotion recognition accuracy for a virtual agent's emotions of anger, fear, and happiness. PMID:25552896

3D facial expression recognition using maximum relevance minimum redundancy geometrical features

NASA Astrophysics Data System (ADS)

Rabiu, Habibu; Saripan, M. Iqbal; Mashohor, Syamsiah; Marhaban, Mohd Hamiruce

2012-12-01

In recent years, facial expression recognition (FER) has become an attractive research area, which besides the fundamental challenges, it poses, finds application in areas, such as human-computer interaction, clinical psychology, lie detection, pain assessment, and neurology. Generally the approaches to FER consist of three main steps: face detection, feature extraction and expression recognition. The recognition accuracy of FER hinges immensely on the relevance of the selected features in representing the target expressions. In this article, we present a person and gender independent 3D facial expression recognition method, using maximum relevance minimum redundancy geometrical features. The aim is to detect a compact set of features that sufficiently represents the most discriminative features between the target classes. Multi-class one-against-one SVM classifier was employed to recognize the seven facial expressions; neutral, happy, sad, angry, fear, disgust, and surprise. The average recognition accuracy of 92.2% was recorded. Furthermore, inter database homogeneity was investigated between two independent databases the BU-3DFE and UPM-3DFE the results showed a strong homogeneity between the two databases.

Altered Kinematics of Facial Emotion Expression and Emotion Recognition Deficits Are Unrelated in Parkinson's Disease.

PubMed

Bologna, Matteo; Berardelli, Isabella; Paparella, Giulia; Marsili, Luca; Ricciardi, Lucia; Fabbrini, Giovanni; Berardelli, Alfredo

2016-01-01

Altered emotional processing, including reduced emotion facial expression and defective emotion recognition, has been reported in patients with Parkinson's disease (PD). However, few studies have objectively investigated facial expression abnormalities in PD using neurophysiological techniques. It is not known whether altered facial expression and recognition in PD are related. To investigate possible deficits in facial emotion expression and emotion recognition and their relationship, if any, in patients with PD. Eighteen patients with PD and 16 healthy controls were enrolled in this study. Facial expressions of emotion were recorded using a 3D optoelectronic system and analyzed using the facial action coding system. Possible deficits in emotion recognition were assessed using the Ekman test. Participants were assessed in one experimental session. Possible relationship between the kinematic variables of facial emotion expression, the Ekman test scores, and clinical and demographic data in patients were evaluated using the Spearman's test and multiple regression analysis. The facial expression of all six basic emotions had slower velocity and lower amplitude in patients in comparison to healthy controls (all P s < 0.05). Patients also yielded worse Ekman global score and disgust, sadness, and fear sub-scores than healthy controls (all P s < 0.001). Altered facial expression kinematics and emotion recognition deficits were unrelated in patients (all P s > 0.05). Finally, no relationship emerged between kinematic variables of facial emotion expression, the Ekman test scores, and clinical and demographic data in patients (all P s > 0.05). The results in this study provide further evidence of altered emotional processing in PD. The lack of any correlation between altered facial emotion expression kinematics and emotion recognition deficits in patients suggests that these abnormalities are mediated by separate pathophysiological mechanisms.

Background feature descriptor for offline handwritten numeral recognition

NASA Astrophysics Data System (ADS)

Ming, Delie; Wang, Hao; Tian, Tian; Jie, Feiran; Lei, Bo

2011-11-01

This paper puts forward an offline handwritten numeral recognition method based on background structural descriptor (sixteen-value numerical background expression). Through encoding the background pixels in the image according to a certain rule, 16 different eigenvalues were generated, which reflected the background condition of every digit, then reflected the structural features of the digits. Through pattern language description of images by these features, automatic segmentation of overlapping digits and numeral recognition can be realized. This method is characterized by great deformation resistant ability, high recognition speed and easy realization. Finally, the experimental results and conclusions are presented. The experimental results of recognizing datasets from various practical application fields reflect that with this method, a good recognition effect can be achieved.

3D face recognition based on multiple keypoint descriptors and sparse representation.

PubMed

Zhang, Lin; Ding, Zhixuan; Li, Hongyu; Shen, Ying; Lu, Jianwei

2014-01-01

Recent years have witnessed a growing interest in developing methods for 3D face recognition. However, 3D scans often suffer from the problems of missing parts, large facial expressions, and occlusions. To be useful in real-world applications, a 3D face recognition approach should be able to handle these challenges. In this paper, we propose a novel general approach to deal with the 3D face recognition problem by making use of multiple keypoint descriptors (MKD) and the sparse representation-based classification (SRC). We call the proposed method 3DMKDSRC for short. Specifically, with 3DMKDSRC, each 3D face scan is represented as a set of descriptor vectors extracted from keypoints by meshSIFT. Descriptor vectors of gallery samples form the gallery dictionary. Given a probe 3D face scan, its descriptors are extracted at first and then its identity can be determined by using a multitask SRC. The proposed 3DMKDSRC approach does not require the pre-alignment between two face scans and is quite robust to the problems of missing data, occlusions and expressions. Its superiority over the other leading 3D face recognition schemes has been corroborated by extensive experiments conducted on three benchmark databases, Bosphorus, GavabDB, and FRGC2.0. The Matlab source code for 3DMKDSRC and the related evaluation results are publicly available at http://sse.tongji.edu.cn/linzhang/3dmkdsrcface/3dmkdsrc.htm.

Inertial Sensor-Based Touch and Shake Metaphor for Expressive Control of 3D Virtual Avatars

PubMed Central

Patil, Shashidhar; Chintalapalli, Harinadha Reddy; Kim, Dubeom; Chai, Youngho

2015-01-01

In this paper, we present an inertial sensor-based touch and shake metaphor for expressive control of a 3D virtual avatar in a virtual environment. An intuitive six degrees-of-freedom wireless inertial motion sensor is used as a gesture and motion control input device with a sensor fusion algorithm. The algorithm enables user hand motions to be tracked in 3D space via magnetic, angular rate, and gravity sensors. A quaternion-based complementary filter is implemented to reduce noise and drift. An algorithm based on dynamic time-warping is developed for efficient recognition of dynamic hand gestures with real-time automatic hand gesture segmentation. Our approach enables the recognition of gestures and estimates gesture variations for continuous interaction. We demonstrate the gesture expressivity using an interactive flexible gesture mapping interface for authoring and controlling a 3D virtual avatar and its motion by tracking user dynamic hand gestures. This synthesizes stylistic variations in a 3D virtual avatar, producing motions that are not present in the motion database using hand gesture sequences from a single inertial motion sensor. PMID:26094629

A unified probabilistic framework for spontaneous facial action modeling and understanding.

PubMed

Tong, Yan; Chen, Jixu; Ji, Qiang

2010-02-01

Facial expression is a natural and powerful means of human communication. Recognizing spontaneous facial actions, however, is very challenging due to subtle facial deformation, frequent head movements, and ambiguous and uncertain facial motion measurements. Because of these challenges, current research in facial expression recognition is limited to posed expressions and often in frontal view. A spontaneous facial expression is characterized by rigid head movements and nonrigid facial muscular movements. More importantly, it is the coherent and consistent spatiotemporal interactions among rigid and nonrigid facial motions that produce a meaningful facial expression. Recognizing this fact, we introduce a unified probabilistic facial action model based on the Dynamic Bayesian network (DBN) to simultaneously and coherently represent rigid and nonrigid facial motions, their spatiotemporal dependencies, and their image measurements. Advanced machine learning methods are introduced to learn the model based on both training data and subjective prior knowledge. Given the model and the measurements of facial motions, facial action recognition is accomplished through probabilistic inference by systematically integrating visual measurements with the facial action model. Experiments show that compared to the state-of-the-art techniques, the proposed system yields significant improvements in recognizing both rigid and nonrigid facial motions, especially for spontaneous facial expressions.

On Assisting a Visual-Facial Affect Recognition System with Keyboard-Stroke Pattern Information

NASA Astrophysics Data System (ADS)

Stathopoulou, I.-O.; Alepis, E.; Tsihrintzis, G. A.; Virvou, M.

Towards realizing a multimodal affect recognition system, we are considering the advantages of assisting a visual-facial expression recognition system with keyboard-stroke pattern information. Our work is based on the assumption that the visual-facial and keyboard modalities are complementary to each other and that their combination can significantly improve the accuracy in affective user models. Specifically, we present and discuss the development and evaluation process of two corresponding affect recognition subsystems, with emphasis on the recognition of 6 basic emotional states, namely happiness, sadness, surprise, anger and disgust as well as the emotion-less state which we refer to as neutral. We find that emotion recognition by the visual-facial modality can be aided greatly by keyboard-stroke pattern information and the combination of the two modalities can lead to better results towards building a multimodal affect recognition system.

Facial Emotion Recognition in Bipolar Disorder and Healthy Aging.

PubMed

Altamura, Mario; Padalino, Flavia A; Stella, Eleonora; Balzotti, Angela; Bellomo, Antonello; Palumbo, Rocco; Di Domenico, Alberto; Mammarella, Nicola; Fairfield, Beth

2016-03-01

Emotional face recognition is impaired in bipolar disorder, but it is not clear whether this is specific for the illness. Here, we investigated how aging and bipolar disorder influence dynamic emotional face recognition. Twenty older adults, 16 bipolar patients, and 20 control subjects performed a dynamic affective facial recognition task and a subsequent rating task. Participants pressed a key as soon as they were able to discriminate whether the neutral face was assuming a happy or angry facial expression and then rated the intensity of each facial expression. Results showed that older adults recognized happy expressions faster, whereas bipolar patients recognized angry expressions faster. Furthermore, both groups rated emotional faces more intensely than did the control subjects. This study is one of the first to compare how aging and clinical conditions influence emotional facial recognition and underlines the need to consider the role of specific and common factors in emotional face recognition.

Applying Suffix Rules to Organization Name Recognition

NASA Astrophysics Data System (ADS)

Inui, Takashi; Murakami, Koji; Hashimoto, Taiichi; Utsumi, Kazuo; Ishikawa, Masamichi

This paper presents a method for boosting the performance of the organization name recognition, which is a part of named entity recognition (NER). Although gazetteers (lists of the NEs) have been known as one of the effective features for supervised machine learning approaches on the NER task, the previous methods which have applied the gazetteers to the NER were very simple. The gazetteers have been used just for searching the exact matches between input text and NEs included in them. The proposed method generates regular expression rules from gazetteers, and, with these rules, it can realize a high-coverage searches based on looser matches between input text and NEs. To generate these rules, we focus on the two well-known characteristics of NE expressions; 1) most of NE expressions can be divided into two parts, class-reference part and instance-reference part, 2) for most of NE expressions the class-reference parts are located at the suffix position of them. A pattern mining algorithm runs on the set of NEs in the gazetteers, and some frequent word sequences from which NEs are constructed are found. Then, we employ only word sequences which have the class-reference part at the suffix position as suffix rules. Experimental results showed that our proposed method improved the performance of the organization name recognition, and achieved the 84.58 F-value for evaluation data.

Comparison of emotion recognition from facial expression and music.

PubMed

Gaspar, Tina; Labor, Marina; Jurić, Iva; Dumancić, Dijana; Ilakovac, Vesna; Heffer, Marija

2011-01-01

The recognition of basic emotions in everyday communication involves interpretation of different visual and auditory clues. The ability to recognize emotions is not clearly determined as their presentation is usually very short (micro expressions), whereas the recognition itself does not have to be a conscious process. We assumed that the recognition from facial expressions is selected over the recognition of emotions communicated through music. In order to compare the success rate in recognizing emotions presented as facial expressions or in classical music works we conducted a survey which included 90 elementary school and 87 high school students from Osijek (Croatia). The participants had to match 8 photographs of different emotions expressed on the face and 8 pieces of classical music works with 8 offered emotions. The recognition of emotions expressed through classical music pieces was significantly less successful than the recognition of emotional facial expressions. The high school students were significantly better at recognizing facial emotions than the elementary school students, whereas girls were better than boys. The success rate in recognizing emotions from music pieces was associated with higher grades in mathematics. Basic emotions are far better recognized if presented on human faces than in music, possibly because the understanding of facial emotions is one of the oldest communication skills in human society. Female advantage in emotion recognition was selected due to the necessity of their communication with the newborns during early development. The proficiency in recognizing emotional content of music and mathematical skills probably share some general cognitive skills like attention, memory and motivation. Music pieces were differently processed in brain than facial expressions and consequently, probably differently evaluated as relevant emotional clues.

Younger and Older Users’ Recognition of Virtual Agent Facial Expressions

PubMed Central

Beer, Jenay M.; Smarr, Cory-Ann; Fisk, Arthur D.; Rogers, Wendy A.

2015-01-01

As technology advances, robots and virtual agents will be introduced into the home and healthcare settings to assist individuals, both young and old, with everyday living tasks. Understanding how users recognize an agent’s social cues is therefore imperative, especially in social interactions. Facial expression, in particular, is one of the most common non-verbal cues used to display and communicate emotion in on-screen agents (Cassell, Sullivan, Prevost, & Churchill, 2000). Age is important to consider because age-related differences in emotion recognition of human facial expression have been supported (Ruffman et al., 2008), with older adults showing a deficit for recognition of negative facial expressions. Previous work has shown that younger adults can effectively recognize facial emotions displayed by agents (Bartneck & Reichenbach, 2005; Courgeon et al. 2009; 2011; Breazeal, 2003); however, little research has compared in-depth younger and older adults’ ability to label a virtual agent’s facial emotions, an import consideration because social agents will be required to interact with users of varying ages. If such age-related differences exist for recognition of virtual agent facial expressions, we aim to understand if those age-related differences are influenced by the intensity of the emotion, dynamic formation of emotion (i.e., a neutral expression developing into an expression of emotion through motion), or the type of virtual character differing by human-likeness. Study 1 investigated the relationship between age-related differences, the implication of dynamic formation of emotion, and the role of emotion intensity in emotion recognition of the facial expressions of a virtual agent (iCat). Study 2 examined age-related differences in recognition expressed by three types of virtual characters differing by human-likeness (non-humanoid iCat, synthetic human, and human). Study 2 also investigated the role of configural and featural processing as a possible explanation for age-related differences in emotion recognition. First, our findings show age-related differences in the recognition of emotions expressed by a virtual agent, with older adults showing lower recognition for the emotions of anger, disgust, fear, happiness, sadness, and neutral. These age-related difference might be explained by older adults having difficulty discriminating similarity in configural arrangement of facial features for certain emotions; for example, older adults often mislabeled the similar emotions of fear as surprise. Second, our results did not provide evidence for the dynamic formation improving emotion recognition; but, in general, the intensity of the emotion improved recognition. Lastly, we learned that emotion recognition, for older and younger adults, differed by character type, from best to worst: human, synthetic human, and then iCat. Our findings provide guidance for design, as well as the development of a framework of age-related differences in emotion recognition. PMID:25705105

Dual Temporal Scale Convolutional Neural Network for Micro-Expression Recognition

PubMed Central

Peng, Min; Wang, Chongyang; Chen, Tong; Liu, Guangyuan; Fu, Xiaolan

2017-01-01

Facial micro-expression is a brief involuntary facial movement and can reveal the genuine emotion that people try to conceal. Traditional methods of spontaneous micro-expression recognition rely excessively on sophisticated hand-crafted feature design and the recognition rate is not high enough for its practical application. In this paper, we proposed a Dual Temporal Scale Convolutional Neural Network (DTSCNN) for spontaneous micro-expressions recognition. The DTSCNN is a two-stream network. Different of stream of DTSCNN is used to adapt to different frame rate of micro-expression video clips. Each stream of DSTCNN consists of independent shallow network for avoiding the overfitting problem. Meanwhile, we fed the networks with optical-flow sequences to ensure that the shallow networks can further acquire higher-level features. Experimental results on spontaneous micro-expression databases (CASME I/II) showed that our method can achieve a recognition rate almost 10% higher than what some state-of-the-art method can achieve. PMID:29081753

2D DOST based local phase pattern for face recognition

NASA Astrophysics Data System (ADS)

Moniruzzaman, Md.; Alam, Mohammad S.

2017-05-01

A new two dimensional (2-D) Discrete Orthogonal Stcokwell Transform (DOST) based Local Phase Pattern (LPP) technique has been proposed for efficient face recognition. The proposed technique uses 2-D DOST as preliminary preprocessing and local phase pattern to form robust feature signature which can effectively accommodate various 3D facial distortions and illumination variations. The S-transform, is an extension of the ideas of the continuous wavelet transform (CWT), is also known for its local spectral phase properties in time-frequency representation (TFR). It provides a frequency dependent resolution of the time-frequency space and absolutely referenced local phase information while maintaining a direct relationship with the Fourier spectrum which is unique in TFR. After utilizing 2-D Stransform as the preprocessing and build local phase pattern from extracted phase information yield fast and efficient technique for face recognition. The proposed technique shows better correlation discrimination compared to alternate pattern recognition techniques such as wavelet or Gabor based face recognition. The performance of the proposed method has been tested using the Yale and extended Yale facial database under different environments such as illumination variation and 3D changes in facial expressions. Test results show that the proposed technique yields better performance compared to alternate time-frequency representation (TFR) based face recognition techniques.

Locality constrained joint dynamic sparse representation for local matching based face recognition.

PubMed

Wang, Jianzhong; Yi, Yugen; Zhou, Wei; Shi, Yanjiao; Qi, Miao; Zhang, Ming; Zhang, Baoxue; Kong, Jun

2014-01-01

Recently, Sparse Representation-based Classification (SRC) has attracted a lot of attention for its applications to various tasks, especially in biometric techniques such as face recognition. However, factors such as lighting, expression, pose and disguise variations in face images will decrease the performances of SRC and most other face recognition techniques. In order to overcome these limitations, we propose a robust face recognition method named Locality Constrained Joint Dynamic Sparse Representation-based Classification (LCJDSRC) in this paper. In our method, a face image is first partitioned into several smaller sub-images. Then, these sub-images are sparsely represented using the proposed locality constrained joint dynamic sparse representation algorithm. Finally, the representation results for all sub-images are aggregated to obtain the final recognition result. Compared with other algorithms which process each sub-image of a face image independently, the proposed algorithm regards the local matching-based face recognition as a multi-task learning problem. Thus, the latent relationships among the sub-images from the same face image are taken into account. Meanwhile, the locality information of the data is also considered in our algorithm. We evaluate our algorithm by comparing it with other state-of-the-art approaches. Extensive experiments on four benchmark face databases (ORL, Extended YaleB, AR and LFW) demonstrate the effectiveness of LCJDSRC.

Evidence for Anger Saliency during the Recognition of Chimeric Facial Expressions of Emotions in Underage Ebola Survivors

PubMed Central

Ardizzi, Martina; Evangelista, Valentina; Ferroni, Francesca; Umiltà, Maria A.; Ravera, Roberto; Gallese, Vittorio

2017-01-01

One of the crucial features defining basic emotions and their prototypical facial expressions is their value for survival. Childhood traumatic experiences affect the effective recognition of facial expressions of negative emotions, normally allowing the recruitment of adequate behavioral responses to environmental threats. Specifically, anger becomes an extraordinarily salient stimulus unbalancing victims’ recognition of negative emotions. Despite the plethora of studies on this topic, to date, it is not clear whether this phenomenon reflects an overall response tendency toward anger recognition or a selective proneness to the salience of specific facial expressive cues of anger after trauma exposure. To address this issue, a group of underage Sierra Leonean Ebola virus disease survivors (mean age 15.40 years, SE 0.35; years of schooling 8.8 years, SE 0.46; 14 males) and a control group (mean age 14.55, SE 0.30; years of schooling 8.07 years, SE 0.30, 15 males) performed a forced-choice chimeric facial expressions recognition task. The chimeric facial expressions were obtained pairing upper and lower half faces of two different negative emotions (selected from anger, fear and sadness for a total of six different combinations). Overall, results showed that upper facial expressive cues were more salient than lower facial expressive cues. This priority was lost among Ebola virus disease survivors for the chimeric facial expressions of anger. In this case, differently from controls, Ebola virus disease survivors recognized anger regardless of the upper or lower position of the facial expressive cues of this emotion. The present results demonstrate that victims’ performance in the recognition of the facial expression of anger does not reflect an overall response tendency toward anger recognition, but rather the specific greater salience of facial expressive cues of anger. Furthermore, the present results show that traumatic experiences deeply modify the perceptual analysis of philogenetically old behavioral patterns like the facial expressions of emotions. PMID:28690565

Evidence for Anger Saliency during the Recognition of Chimeric Facial Expressions of Emotions in Underage Ebola Survivors.

PubMed

Ardizzi, Martina; Evangelista, Valentina; Ferroni, Francesca; Umiltà, Maria A; Ravera, Roberto; Gallese, Vittorio

2017-01-01

One of the crucial features defining basic emotions and their prototypical facial expressions is their value for survival. Childhood traumatic experiences affect the effective recognition of facial expressions of negative emotions, normally allowing the recruitment of adequate behavioral responses to environmental threats. Specifically, anger becomes an extraordinarily salient stimulus unbalancing victims' recognition of negative emotions. Despite the plethora of studies on this topic, to date, it is not clear whether this phenomenon reflects an overall response tendency toward anger recognition or a selective proneness to the salience of specific facial expressive cues of anger after trauma exposure. To address this issue, a group of underage Sierra Leonean Ebola virus disease survivors (mean age 15.40 years, SE 0.35; years of schooling 8.8 years, SE 0.46; 14 males) and a control group (mean age 14.55, SE 0.30; years of schooling 8.07 years, SE 0.30, 15 males) performed a forced-choice chimeric facial expressions recognition task. The chimeric facial expressions were obtained pairing upper and lower half faces of two different negative emotions (selected from anger, fear and sadness for a total of six different combinations). Overall, results showed that upper facial expressive cues were more salient than lower facial expressive cues. This priority was lost among Ebola virus disease survivors for the chimeric facial expressions of anger. In this case, differently from controls, Ebola virus disease survivors recognized anger regardless of the upper or lower position of the facial expressive cues of this emotion. The present results demonstrate that victims' performance in the recognition of the facial expression of anger does not reflect an overall response tendency toward anger recognition, but rather the specific greater salience of facial expressive cues of anger. Furthermore, the present results show that traumatic experiences deeply modify the perceptual analysis of philogenetically old behavioral patterns like the facial expressions of emotions.

Face recognition via edge-based Gabor feature representation for plastic surgery-altered images

NASA Astrophysics Data System (ADS)

Chude-Olisah, Chollette C.; Sulong, Ghazali; Chude-Okonkwo, Uche A. K.; Hashim, Siti Z. M.

2014-12-01

Plastic surgery procedures on the face introduce skin texture variations between images of the same person (intra-subject), thereby making the task of face recognition more difficult than in normal scenario. Usually, in contemporary face recognition systems, the original gray-level face image is used as input to the Gabor descriptor, which translates to encoding some texture properties of the face image. The texture-encoding process significantly degrades the performance of such systems in the case of plastic surgery due to the presence of surgically induced intra-subject variations. Based on the proposition that the shape of significant facial components such as eyes, nose, eyebrow, and mouth remains unchanged after plastic surgery, this paper employs an edge-based Gabor feature representation approach for the recognition of surgically altered face images. We use the edge information, which is dependent on the shapes of the significant facial components, to address the plastic surgery-induced texture variation problems. To ensure that the significant facial components represent useful edge information with little or no false edges, a simple illumination normalization technique is proposed for preprocessing. Gabor wavelet is applied to the edge image to accentuate on the uniqueness of the significant facial components for discriminating among different subjects. The performance of the proposed method is evaluated on the Georgia Tech (GT) and the Labeled Faces in the Wild (LFW) databases with illumination and expression problems, and the plastic surgery database with texture changes. Results show that the proposed edge-based Gabor feature representation approach is robust against plastic surgery-induced face variations amidst expression and illumination problems and outperforms the existing plastic surgery face recognition methods reported in the literature.

Synergistic Modification Induced Specific Recognition between Histone and TRIM24 via Fluctuation Correlation Network Analysis

NASA Astrophysics Data System (ADS)

Zhang, Jinmai; Luo, Huajie; Liu, Hao; Ye, Wei; Luo, Ray; Chen, Hai-Feng

2016-04-01

Histone modification plays a key role in gene regulation and gene expression. TRIM24 as a histone reader can recognize histone modification. However the specific recognition mechanism between TRIM24 and histone modification is unsolved. Here, systems biology method of dynamics correlation network based on molecular dynamics simulation was used to answer the question. Our network analysis shows that the dynamics correlation network of H3K23ac is distinctly different from that of wild type and other modifications. A hypothesis of “synergistic modification induced recognition” is then proposed to link histone modification and TRIM24 binding. These observations were further confirmed from community analysis of networks with mutation and network perturbation. Finally, a possible recognition pathway is also identified based on the shortest path search for H3K23ac. Significant difference of recognition pathway was found among different systems due to methylation and acetylation modifications. The analysis presented here and other studies show that the dynamic network-based analysis might be a useful general strategy to study the biology of protein post-translational modification and associated recognition.

Mapping correspondence between facial mimicry and emotion recognition in healthy subjects.

PubMed

Ponari, Marta; Conson, Massimiliano; D'Amico, Nunzia Pina; Grossi, Dario; Trojano, Luigi

2012-12-01

We aimed at verifying the hypothesis that facial mimicry is causally and selectively involved in emotion recognition. For this purpose, in Experiment 1, we explored the effect of tonic contraction of muscles in upper or lower half of participants' face on their ability to recognize emotional facial expressions. We found that the "lower" manipulation specifically impaired recognition of happiness and disgust, the "upper" manipulation impaired recognition of anger, while both manipulations affected recognition of fear; recognition of surprise and sadness were not affected by either blocking manipulations. In Experiment 2, we verified whether emotion recognition is hampered by stimuli in which an upper or lower half-face showing an emotional expression is combined with a neutral half-face. We found that the neutral lower half-face interfered with recognition of happiness and disgust, whereas the neutral upper half impaired recognition of anger; recognition of fear and sadness was impaired by both manipulations, whereas recognition of surprise was not affected by either manipulation. Taken together, the present findings support simulation models of emotion recognition and provide insight into the role of mimicry in comprehension of others' emotional facial expressions. PsycINFO Database Record (c) 2012 APA, all rights reserved.

Expression intensity, gender and facial emotion recognition: Women recognize only subtle facial emotions better than men.

PubMed

Hoffmann, Holger; Kessler, Henrik; Eppel, Tobias; Rukavina, Stefanie; Traue, Harald C

2010-11-01

Two experiments were conducted in order to investigate the effect of expression intensity on gender differences in the recognition of facial emotions. The first experiment compared recognition accuracy between female and male participants when emotional faces were shown with full-blown (100% emotional content) or subtle expressiveness (50%). In a second experiment more finely grained analyses were applied in order to measure recognition accuracy as a function of expression intensity (40%-100%). The results show that although women were more accurate than men in recognizing subtle facial displays of emotion, there was no difference between male and female participants when recognizing highly expressive stimuli. Copyright © 2010 Elsevier B.V. All rights reserved.

Fusion of Visible and Thermal Descriptors Using Genetic Algorithms for Face Recognition Systems.

PubMed

Hermosilla, Gabriel; Gallardo, Francisco; Farias, Gonzalo; San Martin, Cesar

2015-07-23

The aim of this article is to present a new face recognition system based on the fusion of visible and thermal features obtained from the most current local matching descriptors by maximizing face recognition rates through the use of genetic algorithms. The article considers a comparison of the performance of the proposed fusion methodology against five current face recognition methods and classic fusion techniques used commonly in the literature. These were selected by considering their performance in face recognition. The five local matching methods and the proposed fusion methodology are evaluated using the standard visible/thermal database, the Equinox database, along with a new database, the PUCV-VTF, designed for visible-thermal studies in face recognition and described for the first time in this work. The latter is created considering visible and thermal image sensors with different real-world conditions, such as variations in illumination, facial expression, pose, occlusion, etc. The main conclusions of this article are that two variants of the proposed fusion methodology surpass current face recognition methods and the classic fusion techniques reported in the literature, attaining recognition rates of over 97% and 99% for the Equinox and PUCV-VTF databases, respectively. The fusion methodology is very robust to illumination and expression changes, as it combines thermal and visible information efficiently by using genetic algorithms, thus allowing it to choose optimal face areas where one spectrum is more representative than the other.

Fusion of Visible and Thermal Descriptors Using Genetic Algorithms for Face Recognition Systems

PubMed Central

Hermosilla, Gabriel; Gallardo, Francisco; Farias, Gonzalo; San Martin, Cesar

2015-01-01

The aim of this article is to present a new face recognition system based on the fusion of visible and thermal features obtained from the most current local matching descriptors by maximizing face recognition rates through the use of genetic algorithms. The article considers a comparison of the performance of the proposed fusion methodology against five current face recognition methods and classic fusion techniques used commonly in the literature. These were selected by considering their performance in face recognition. The five local matching methods and the proposed fusion methodology are evaluated using the standard visible/thermal database, the Equinox database, along with a new database, the PUCV-VTF, designed for visible-thermal studies in face recognition and described for the first time in this work. The latter is created considering visible and thermal image sensors with different real-world conditions, such as variations in illumination, facial expression, pose, occlusion, etc. The main conclusions of this article are that two variants of the proposed fusion methodology surpass current face recognition methods and the classic fusion techniques reported in the literature, attaining recognition rates of over 97% and 99% for the Equinox and PUCV-VTF databases, respectively. The fusion methodology is very robust to illumination and expression changes, as it combines thermal and visible information efficiently by using genetic algorithms, thus allowing it to choose optimal face areas where one spectrum is more representative than the other. PMID:26213932

Micro-Expression Recognition Using Color Spaces.

PubMed

Wang, Su-Jing; Yan, Wen-Jing; Li, Xiaobai; Zhao, Guoying; Zhou, Chun-Guang; Fu, Xiaolan; Yang, Minghao; Tao, Jianhua

2015-12-01

Micro-expressions are brief involuntary facial expressions that reveal genuine emotions and, thus, help detect lies. Because of their many promising applications, they have attracted the attention of researchers from various fields. Recent research reveals that two perceptual color spaces (CIELab and CIELuv) provide useful information for expression recognition. This paper is an extended version of our International Conference on Pattern Recognition paper, in which we propose a novel color space model, tensor independent color space (TICS), to help recognize micro-expressions. In this paper, we further show that CIELab and CIELuv are also helpful in recognizing micro-expressions, and we indicate why these three color spaces achieve better performance. A micro-expression color video clip is treated as a fourth-order tensor, i.e., a four-dimension array. The first two dimensions are the spatial information, the third is the temporal information, and the fourth is the color information. We transform the fourth dimension from RGB into TICS, in which the color components are as independent as possible. The combination of dynamic texture and independent color components achieves a higher accuracy than does that of RGB. In addition, we define a set of regions of interests (ROIs) based on the facial action coding system and calculated the dynamic texture histograms for each ROI. Experiments are conducted on two micro-expression databases, CASME and CASME 2, and the results show that the performances for TICS, CIELab, and CIELuv are better than those for RGB or gray.

The look of fear and anger: facial maturity modulates recognition of fearful and angry expressions.

PubMed

Sacco, Donald F; Hugenberg, Kurt

2009-02-01

The current series of studies provide converging evidence that facial expressions of fear and anger may have co-evolved to mimic mature and babyish faces in order to enhance their communicative signal. In Studies 1 and 2, fearful and angry facial expressions were manipulated to have enhanced babyish features (larger eyes) or enhanced mature features (smaller eyes) and in the context of a speeded categorization task in Study 1 and a visual noise paradigm in Study 2, results indicated that larger eyes facilitated the recognition of fearful facial expressions, while smaller eyes facilitated the recognition of angry facial expressions. Study 3 manipulated facial roundness, a stable structure that does not vary systematically with expressions, and found that congruency between maturity and expression (narrow face-anger; round face-fear) facilitated expression recognition accuracy. Results are discussed as representing a broad co-evolutionary relationship between facial maturity and fearful and angry facial expressions. (c) 2009 APA, all rights reserved

Transfer between pose and expression training in face recognition.

PubMed

Chen, Wenfeng; Liu, Chang Hong

2009-02-01

Prior research has shown that recognition of unfamiliar faces is susceptible to image variations due to pose and expression changes. However, little is known about how these variations on a new face are learnt and handled. We aimed to investigate whether exposures to one type of variation facilitate recognition in the untrained variation. In Experiment 1, faces were trained in multiple or single pose but were tested with a new expression. In Experiment 2, faces were trained in multiple or single expression but were tested in a new pose. We found that higher level of exposure to pose information facilitated recognition of the trained face in a new expression. However, multiple-expression training failed to transfer to a new pose. The findings suggest that generalisation of pose training may be extended to different types of variation whereas generalisation of expression training is largely confined within the trained type of variation.

Emotional Faces in Context: Age Differences in Recognition Accuracy and Scanning Patterns

PubMed Central

Noh, Soo Rim; Isaacowitz, Derek M.

2014-01-01

While age-related declines in facial expression recognition are well documented, previous research relied mostly on isolated faces devoid of context. We investigated the effects of context on age differences in recognition of facial emotions and in visual scanning patterns of emotional faces. While their eye movements were monitored, younger and older participants viewed facial expressions (i.e., anger, disgust) in contexts that were emotionally congruent, incongruent, or neutral to the facial expression to be identified. Both age groups had highest recognition rates of facial expressions in the congruent context, followed by the neutral context, and recognition rates in the incongruent context were worst. These context effects were more pronounced for older adults. Compared to younger adults, older adults exhibited a greater benefit from congruent contextual information, regardless of facial expression. Context also influenced the pattern of visual scanning characteristics of emotional faces in a similar manner across age groups. In addition, older adults initially attended more to context overall. Our data highlight the importance of considering the role of context in understanding emotion recognition in adulthood. PMID:23163713

Structural analysis of online handwritten mathematical symbols based on support vector machines

NASA Astrophysics Data System (ADS)

Simistira, Foteini; Papavassiliou, Vassilis; Katsouros, Vassilis; Carayannis, George

2013-01-01

Mathematical expression recognition is still a very challenging task for the research community mainly because of the two-dimensional (2d) structure of mathematical expressions (MEs). In this paper, we present a novel approach for the structural analysis between two on-line handwritten mathematical symbols of a ME, based on spatial features of the symbols. We introduce six features to represent the spatial affinity of the symbols and compare two multi-class classification methods that employ support vector machines (SVMs): one based on the "one-against-one" technique and one based on the "one-against-all", in identifying the relation between a pair of symbols (i.e. subscript, numerator, etc). A dataset containing 1906 spatial relations derived from the Competition on Recognition of Online Handwritten Mathematical Expressions (CROHME) 2012 training dataset is constructed to evaluate the classifiers and compare them with the rule-based classifier of the ILSP-1 system participated in the contest. The experimental results give an overall mean error rate of 2.61% for the "one-against-one" SVM approach, 6.57% for the "one-against-all" SVM technique and 12.31% error rate for the ILSP-1 classifier.

Slowing down presentation of facial movements and vocal sounds enhances facial expression recognition and induces facial-vocal imitation in children with autism.

PubMed

Tardif, Carole; Lainé, France; Rodriguez, Mélissa; Gepner, Bruno

2007-09-01

This study examined the effects of slowing down presentation of facial expressions and their corresponding vocal sounds on facial expression recognition and facial and/or vocal imitation in children with autism. Twelve autistic children and twenty-four normal control children were presented with emotional and non-emotional facial expressions on CD-Rom, under audio or silent conditions, and under dynamic visual conditions (slowly, very slowly, at normal speed) plus a static control. Overall, children with autism showed lower performance in expression recognition and more induced facial-vocal imitation than controls. In the autistic group, facial expression recognition and induced facial-vocal imitation were significantly enhanced in slow conditions. Findings may give new perspectives for understanding and intervention for verbal and emotional perceptive and communicative impairments in autistic populations.

A Modified Sparse Representation Method for Facial Expression Recognition.

PubMed

Wang, Wei; Xu, LiHong

2016-01-01

In this paper, we carry on research on a facial expression recognition method, which is based on modified sparse representation recognition (MSRR) method. On the first stage, we use Haar-like+LPP to extract feature and reduce dimension. On the second stage, we adopt LC-K-SVD (Label Consistent K-SVD) method to train the dictionary, instead of adopting directly the dictionary from samples, and add block dictionary training into the training process. On the third stage, stOMP (stagewise orthogonal matching pursuit) method is used to speed up the convergence of OMP (orthogonal matching pursuit). Besides, a dynamic regularization factor is added to iteration process to suppress noises and enhance accuracy. We verify the proposed method from the aspect of training samples, dimension, feature extraction and dimension reduction methods and noises in self-built database and Japan's JAFFE and CMU's CK database. Further, we compare this sparse method with classic SVM and RVM and analyze the recognition effect and time efficiency. The result of simulation experiment has shown that the coefficient of MSRR method contains classifying information, which is capable of improving the computing speed and achieving a satisfying recognition result.

A Modified Sparse Representation Method for Facial Expression Recognition

PubMed Central

Wang, Wei; Xu, LiHong

2016-01-01

In this paper, we carry on research on a facial expression recognition method, which is based on modified sparse representation recognition (MSRR) method. On the first stage, we use Haar-like+LPP to extract feature and reduce dimension. On the second stage, we adopt LC-K-SVD (Label Consistent K-SVD) method to train the dictionary, instead of adopting directly the dictionary from samples, and add block dictionary training into the training process. On the third stage, stOMP (stagewise orthogonal matching pursuit) method is used to speed up the convergence of OMP (orthogonal matching pursuit). Besides, a dynamic regularization factor is added to iteration process to suppress noises and enhance accuracy. We verify the proposed method from the aspect of training samples, dimension, feature extraction and dimension reduction methods and noises in self-built database and Japan's JAFFE and CMU's CK database. Further, we compare this sparse method with classic SVM and RVM and analyze the recognition effect and time efficiency. The result of simulation experiment has shown that the coefficient of MSRR method contains classifying information, which is capable of improving the computing speed and achieving a satisfying recognition result. PMID:26880878

Impaired Facial Expression Recognition in Children with Temporal Lobe Epilepsy: Impact of Early Seizure Onset on Fear Recognition

ERIC Educational Resources Information Center

Golouboff, Nathalie; Fiori, Nicole; Delalande, Olivier; Fohlen, Martine; Dellatolas, Georges; Jambaque, Isabelle

2008-01-01

The amygdala has been implicated in the recognition of facial emotions, especially fearful expressions, in adults with early-onset right temporal lobe epilepsy (TLE). The present study investigates the recognition of facial emotions in children and adolescents, 8-16 years old, with epilepsy. Twenty-nine subjects had TLE (13 right, 16 left) and…

Facial recognition using multisensor images based on localized kernel eigen spaces.

PubMed

Gundimada, Satyanadh; Asari, Vijayan K

2009-06-01

A feature selection technique along with an information fusion procedure for improving the recognition accuracy of a visual and thermal image-based facial recognition system is presented in this paper. A novel modular kernel eigenspaces approach is developed and implemented on the phase congruency feature maps extracted from the visual and thermal images individually. Smaller sub-regions from a predefined neighborhood within the phase congruency images of the training samples are merged to obtain a large set of features. These features are then projected into higher dimensional spaces using kernel methods. The proposed localized nonlinear feature selection procedure helps to overcome the bottlenecks of illumination variations, partial occlusions, expression variations and variations due to temperature changes that affect the visual and thermal face recognition techniques. AR and Equinox databases are used for experimentation and evaluation of the proposed technique. The proposed feature selection procedure has greatly improved the recognition accuracy for both the visual and thermal images when compared to conventional techniques. Also, a decision level fusion methodology is presented which along with the feature selection procedure has outperformed various other face recognition techniques in terms of recognition accuracy.

Recognition of face identity and emotion in expressive specific language impairment.

PubMed

Merkenschlager, A; Amorosa, H; Kiefl, H; Martinius, J

2012-01-01

To study face and emotion recognition in children with mostly expressive specific language impairment (SLI-E). A test movie to study perception and recognition of faces and mimic-gestural expression was applied to 24 children diagnosed as suffering from SLI-E and an age-matched control group of normally developing children. Compared to a normal control group, the SLI-E children scored significantly worse in both the face and expression recognition tasks with a preponderant effect on emotion recognition. The performance of the SLI-E group could not be explained by reduced attention during the test session. We conclude that SLI-E is associated with a deficiency in decoding non-verbal emotional facial and gestural information, which might lead to profound and persistent problems in social interaction and development. Copyright © 2012 S. Karger AG, Basel.

Wavelet filtered shifted phase-encoded joint transform correlation for face recognition

NASA Astrophysics Data System (ADS)

Moniruzzaman, Md.; Alam, Mohammad S.

2017-05-01

A new wavelet-filtered-based Shifted- phase-encoded Joint Transform Correlation (WPJTC) technique has been proposed for efficient face recognition. The proposed technique uses discrete wavelet decomposition for preprocessing and can effectively accommodate various 3D facial distortions, effects of noise, and illumination variations. After analyzing different forms of wavelet basis functions, an optimal method has been proposed by considering the discrimination capability and processing speed as performance trade-offs. The proposed technique yields better correlation discrimination compared to alternate pattern recognition techniques such as phase-shifted phase-encoded fringe-adjusted joint transform correlator. The performance of the proposed WPJTC has been tested using the Yale facial database and extended Yale facial database under different environments such as illumination variation, noise, and 3D changes in facial expressions. Test results show that the proposed WPJTC yields better performance compared to alternate JTC based face recognition techniques.

Face recognition algorithm based on Gabor wavelet and locality preserving projections

NASA Astrophysics Data System (ADS)

Liu, Xiaojie; Shen, Lin; Fan, Honghui

2017-07-01

In order to solve the effects of illumination changes and differences of personal features on the face recognition rate, this paper presents a new face recognition algorithm based on Gabor wavelet and Locality Preserving Projections (LPP). The problem of the Gabor filter banks with high dimensions was solved effectively, and also the shortcoming of the LPP on the light illumination changes was overcome. Firstly, the features of global image information were achieved, which used the good spatial locality and orientation selectivity of Gabor wavelet filters. Then the dimensions were reduced by utilizing the LPP, which well-preserved the local information of the image. The experimental results shown that this algorithm can effectively extract the features relating to facial expressions, attitude and other information. Besides, it can reduce influence of the illumination changes and the differences in personal features effectively, which improves the face recognition rate to 99.2%.

Identifying and detecting facial expressions of emotion in peripheral vision.

PubMed

Smith, Fraser W; Rossit, Stephanie

2018-01-01

Facial expressions of emotion are signals of high biological value. Whilst recognition of facial expressions has been much studied in central vision, the ability to perceive these signals in peripheral vision has only seen limited research to date, despite the potential adaptive advantages of such perception. In the present experiment, we investigate facial expression recognition and detection performance for each of the basic emotions (plus neutral) at up to 30 degrees of eccentricity. We demonstrate, as expected, a decrease in recognition and detection performance with increasing eccentricity, with happiness and surprised being the best recognized expressions in peripheral vision. In detection however, while happiness and surprised are still well detected, fear is also a well detected expression. We show that fear is a better detected than recognized expression. Our results demonstrate that task constraints shape the perception of expression in peripheral vision and provide novel evidence that detection and recognition rely on partially separate underlying mechanisms, with the latter more dependent on the higher spatial frequency content of the face stimulus.

Identifying and detecting facial expressions of emotion in peripheral vision

PubMed Central

Rossit, Stephanie

2018-01-01

Facial expressions of emotion are signals of high biological value. Whilst recognition of facial expressions has been much studied in central vision, the ability to perceive these signals in peripheral vision has only seen limited research to date, despite the potential adaptive advantages of such perception. In the present experiment, we investigate facial expression recognition and detection performance for each of the basic emotions (plus neutral) at up to 30 degrees of eccentricity. We demonstrate, as expected, a decrease in recognition and detection performance with increasing eccentricity, with happiness and surprised being the best recognized expressions in peripheral vision. In detection however, while happiness and surprised are still well detected, fear is also a well detected expression. We show that fear is a better detected than recognized expression. Our results demonstrate that task constraints shape the perception of expression in peripheral vision and provide novel evidence that detection and recognition rely on partially separate underlying mechanisms, with the latter more dependent on the higher spatial frequency content of the face stimulus. PMID:29847562

Decreased acetylcholine release delays the consolidation of object recognition memory.

PubMed

De Jaeger, Xavier; Cammarota, Martín; Prado, Marco A M; Izquierdo, Iván; Prado, Vania F; Pereira, Grace S

2013-02-01

Acetylcholine (ACh) is important for different cognitive functions such as learning, memory and attention. The release of ACh depends on its vesicular loading by the vesicular acetylcholine transporter (VAChT). It has been demonstrated that VAChT expression can modulate object recognition memory. However, the role of VAChT expression on object recognition memory persistence still remains to be understood. To address this question we used distinct mouse lines with reduced expression of VAChT, as well as pharmacological manipulations of the cholinergic system. We showed that reduction of cholinergic tone impairs object recognition memory measured at 24h. Surprisingly, object recognition memory, measured at 4 days after training, was impaired by substantial, but not moderate, reduction in VAChT expression. Our results suggest that levels of acetylcholine release strongly modulate object recognition memory consolidation and appear to be of particular importance for memory persistence 4 days after training. Copyright © 2012 Elsevier B.V. All rights reserved.

Static facial expression recognition with convolution neural networks

NASA Astrophysics Data System (ADS)

Zhang, Feng; Chen, Zhong; Ouyang, Chao; Zhang, Yifei

2018-03-01

Facial expression recognition is a currently active research topic in the fields of computer vision, pattern recognition and artificial intelligence. In this paper, we have developed a convolutional neural networks (CNN) for classifying human emotions from static facial expression into one of the seven facial emotion categories. We pre-train our CNN model on the combined FER2013 dataset formed by train, validation and test set and fine-tune on the extended Cohn-Kanade database. In order to reduce the overfitting of the models, we utilized different techniques including dropout and batch normalization in addition to data augmentation. According to the experimental result, our CNN model has excellent classification performance and robustness for facial expression recognition.

Functional Connectivity of Multiple Brain Regions Required for the Consolidation of Social Recognition Memory.

PubMed

Tanimizu, Toshiyuki; Kenney, Justin W; Okano, Emiko; Kadoma, Kazune; Frankland, Paul W; Kida, Satoshi

2017-04-12

Social recognition memory is an essential and basic component of social behavior that is used to discriminate familiar and novel animals/humans. Previous studies have shown the importance of several brain regions for social recognition memories; however, the mechanisms underlying the consolidation of social recognition memory at the molecular and anatomic levels remain unknown. Here, we show a brain network necessary for the generation of social recognition memory in mice. A mouse genetic study showed that cAMP-responsive element-binding protein (CREB)-mediated transcription is required for the formation of social recognition memory. Importantly, significant inductions of the CREB target immediate-early genes c-fos and Arc were observed in the hippocampus (CA1 and CA3 regions), medial prefrontal cortex (mPFC), anterior cingulate cortex (ACC), and amygdala (basolateral region) when social recognition memory was generated. Pharmacological experiments using a microinfusion of the protein synthesis inhibitor anisomycin showed that protein synthesis in these brain regions is required for the consolidation of social recognition memory. These findings suggested that social recognition memory is consolidated through the activation of CREB-mediated gene expression in the hippocampus/mPFC/ACC/amygdala. Network analyses suggested that these four brain regions show functional connectivity with other brain regions and, more importantly, that the hippocampus functions as a hub to integrate brain networks and generate social recognition memory, whereas the ACC and amygdala are important for coordinating brain activity when social interaction is initiated by connecting with other brain regions. We have found that a brain network composed of the hippocampus/mPFC/ACC/amygdala is required for the consolidation of social recognition memory. SIGNIFICANCE STATEMENT Here, we identify brain networks composed of multiple brain regions for the consolidation of social recognition memory. We found that social recognition memory is consolidated through CREB-meditated gene expression in the hippocampus, medial prefrontal cortex, anterior cingulate cortex (ACC), and amygdala. Importantly, network analyses based on c-fos expression suggest that functional connectivity of these four brain regions with other brain regions is increased with time spent in social investigation toward the generation of brain networks to consolidate social recognition memory. Furthermore, our findings suggest that hippocampus functions as a hub to integrate brain networks and generate social recognition memory, whereas ACC and amygdala are important for coordinating brain activity when social interaction is initiated by connecting with other brain regions. Copyright © 2017 the authors 0270-6474/17/374103-14$15.00/0.

Facial emotion recognition, socio-occupational functioning and expressed emotions in schizophrenia versus bipolar disorder.

PubMed

Thonse, Umesh; Behere, Rishikesh V; Praharaj, Samir Kumar; Sharma, Podila Sathya Venkata Narasimha

2018-06-01

Facial emotion recognition deficits have been consistently demonstrated in patients with severe mental disorders. Expressed emotion is found to be an important predictor of relapse. However, the relationship between facial emotion recognition abilities and expressed emotions and its influence on socio-occupational functioning in schizophrenia versus bipolar disorder has not been studied. In this study we examined 91 patients with schizophrenia and 71 with bipolar disorder for psychopathology, socio occupational functioning and emotion recognition abilities. Primary caregivers of 62 patients with schizophrenia and 49 with bipolar disorder were assessed on Family Attitude Questionnaire to assess their expressed emotions. Patients of schizophrenia and bipolar disorder performed similarly on the emotion recognition task. Patients with schizophrenia group experienced higher critical comments and had a poorer socio-occupational functioning as compared to patients with bipolar disorder. Poorer socio-occupational functioning in patients with schizophrenia was significantly associated with greater dissatisfaction in their caregivers. In patients with bipolar disorder, poorer emotion recognition scores significantly correlated with poorer adaptive living skills and greater hostility and dissatisfaction in their caregivers. The findings of our study suggest that emotion recognition abilities in patients with bipolar disorder are associated with negative expressed emotions leading to problems in adaptive living skills. Copyright © 2018 Elsevier B.V. All rights reserved.

3D Face Recognition Based on Multiple Keypoint Descriptors and Sparse Representation

PubMed Central

Zhang, Lin; Ding, Zhixuan; Li, Hongyu; Shen, Ying; Lu, Jianwei

2014-01-01

Recent years have witnessed a growing interest in developing methods for 3D face recognition. However, 3D scans often suffer from the problems of missing parts, large facial expressions, and occlusions. To be useful in real-world applications, a 3D face recognition approach should be able to handle these challenges. In this paper, we propose a novel general approach to deal with the 3D face recognition problem by making use of multiple keypoint descriptors (MKD) and the sparse representation-based classification (SRC). We call the proposed method 3DMKDSRC for short. Specifically, with 3DMKDSRC, each 3D face scan is represented as a set of descriptor vectors extracted from keypoints by meshSIFT. Descriptor vectors of gallery samples form the gallery dictionary. Given a probe 3D face scan, its descriptors are extracted at first and then its identity can be determined by using a multitask SRC. The proposed 3DMKDSRC approach does not require the pre-alignment between two face scans and is quite robust to the problems of missing data, occlusions and expressions. Its superiority over the other leading 3D face recognition schemes has been corroborated by extensive experiments conducted on three benchmark databases, Bosphorus, GavabDB, and FRGC2.0. The Matlab source code for 3DMKDSRC and the related evaluation results are publicly available at http://sse.tongji.edu.cn/linzhang/3dmkdsrcface/3dmkdsrc.htm. PMID:24940876

More Pronounced Deficits in Facial Emotion Recognition for Schizophrenia than Bipolar Disorder

PubMed Central

Goghari, Vina M; Sponheim, Scott R

2012-01-01

Schizophrenia and bipolar disorder are typically separated in diagnostic systems. Behavioural, cognitive, and brain abnormalities associated with each disorder nonetheless overlap. We evaluated the diagnostic specificity of facial emotion recognition deficits in schizophrenia and bipolar disorder to determine whether select aspects of emotion recognition differed for the two disorders. The investigation used an experimental task that included the same facial images in an emotion recognition condition and an age recognition condition (to control for processes associated with general face recognition) in 27 schizophrenia patients, 16 bipolar I patients, and 30 controls. Schizophrenia and bipolar patients exhibited both shared and distinct aspects of facial emotion recognition deficits. Schizophrenia patients had deficits in recognizing angry facial expressions compared to healthy controls and bipolar patients. Compared to control participants, both schizophrenia and bipolar patients were more likely to mislabel facial expressions of anger as fear. Given that schizophrenia patients exhibited a deficit in emotion recognition for angry faces, which did not appear due to generalized perceptual and cognitive dysfunction, improving recognition of threat-related expression may be an important intervention target to improve social functioning in schizophrenia. PMID:23218816

Face to face: blocking facial mimicry can selectively impair recognition of emotional expressions.

PubMed

Oberman, Lindsay M; Winkielman, Piotr; Ramachandran, Vilayanur S

2007-01-01

People spontaneously mimic a variety of behaviors, including emotional facial expressions. Embodied cognition theories suggest that mimicry reflects internal simulation of perceived emotion in order to facilitate its understanding. If so, blocking facial mimicry should impair recognition of expressions, especially of emotions that are simulated using facial musculature. The current research tested this hypothesis using four expressions (happy, disgust, fear, and sad) and two mimicry-interfering manipulations (1) biting on a pen and (2) chewing gum, as well as two control conditions. Experiment 1 used electromyography over cheek, mouth, and nose regions. The bite manipulation consistently activated assessed muscles, whereas the chew manipulation activated muscles only intermittently. Further, expressing happiness generated most facial action. Experiment 2 found that the bite manipulation interfered most with recognition of happiness. These findings suggest that facial mimicry differentially contributes to recognition of specific facial expressions, thus allowing for more refined predictions from embodied cognition theories.

[Recognition of facial expression of emotions in Parkinson's disease: a theoretical review].

PubMed

Alonso-Recio, L; Serrano-Rodriguez, J M; Carvajal-Molina, F; Loeches-Alonso, A; Martin-Plasencia, P

2012-04-16

Emotional facial expression is a basic guide during social interaction and, therefore, alterations in their expression or recognition are important limitations for communication. To examine facial expression recognition abilities and their possible impairment in Parkinson's disease. First, we review the studies on this topic which have not found entirely similar results. Second, we analyze the factors that may explain these discrepancies and, in particular, as third objective, we consider the relationship between emotional recognition problems and cognitive impairment associated with the disease. Finally, we propose alternatives strategies for the development of studies that could clarify the state of these abilities in Parkinson's disease. Most studies suggest deficits in facial expression recognition, especially in those with negative emotional content. However, it is possible that these alterations are related to those that also appear in the course of the disease in other perceptual and executive processes. To advance in this issue, we consider necessary to design emotional recognition studies implicating differentially the executive or visuospatial processes, and/or contrasting cognitive abilities with facial expressions and non emotional stimuli. The precision of the status of these abilities, as well as increase our knowledge of the functional consequences of the characteristic brain damage in the disease, may indicate if we should pay special attention in their rehabilitation inside the programs implemented.

Dissociation between recognition and detection advantage for facial expressions: a meta-analysis.

PubMed

Nummenmaa, Lauri; Calvo, Manuel G

2015-04-01

Happy facial expressions are recognized faster and more accurately than other expressions in categorization tasks, whereas detection in visual search tasks is widely believed to be faster for angry than happy faces. We used meta-analytic techniques for resolving this categorization versus detection advantage discrepancy for positive versus negative facial expressions. Effect sizes were computed on the basis of the r statistic for a total of 34 recognition studies with 3,561 participants and 37 visual search studies with 2,455 participants, yielding a total of 41 effect sizes for recognition accuracy, 25 for recognition speed, and 125 for visual search speed. Random effects meta-analysis was conducted to estimate effect sizes at population level. For recognition tasks, an advantage in recognition accuracy and speed for happy expressions was found for all stimulus types. In contrast, for visual search tasks, moderator analysis revealed that a happy face detection advantage was restricted to photographic faces, whereas a clear angry face advantage was found for schematic and "smiley" faces. Robust detection advantage for nonhappy faces was observed even when stimulus emotionality was distorted by inversion or rearrangement of the facial features, suggesting that visual features primarily drive the search. We conclude that the recognition advantage for happy faces is a genuine phenomenon related to processing of facial expression category and affective valence. In contrast, detection advantages toward either happy (photographic stimuli) or nonhappy (schematic) faces is contingent on visual stimulus features rather than facial expression, and may not involve categorical or affective processing. (c) 2015 APA, all rights reserved).

Contributions of feature shapes and surface cues to the recognition of facial expressions.

PubMed

Sormaz, Mladen; Young, Andrew W; Andrews, Timothy J

2016-10-01

Theoretical accounts of face processing often emphasise feature shapes as the primary visual cue to the recognition of facial expressions. However, changes in facial expression also affect the surface properties of the face. In this study, we investigated whether this surface information can also be used in the recognition of facial expression. First, participants identified facial expressions (fear, anger, disgust, sadness, happiness) from images that were manipulated such that they varied mainly in shape or mainly in surface properties. We found that the categorization of facial expression is possible in either type of image, but that different expressions are relatively dependent on surface or shape properties. Next, we investigated the relative contributions of shape and surface information to the categorization of facial expressions. This employed a complementary method that involved combining the surface properties of one expression with the shape properties from a different expression. Our results showed that the categorization of facial expressions in these hybrid images was equally dependent on the surface and shape properties of the image. Together, these findings provide a direct demonstration that both feature shape and surface information make significant contributions to the recognition of facial expressions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Tuning sensitivity of CAR to EGFR density limits recognition of normal tissue while maintaining potent anti-tumor activity

PubMed Central

Caruso, Hillary G.; Hurton, Lenka V.; Najjar, Amer; Rushworth, David; Ang, Sonny; Olivares, Simon; Mi, Tiejuan; Switzer, Kirsten; Singh, Harjeet; Huls, Helen; Lee, Dean A.; Heimberger, Amy B.; Champlin, Richard E.; Cooper, Laurence J. N.

2015-01-01

Many tumors over express tumor-associated antigens relative to normal tissue, such as epidermal growth factor receptor (EGFR). This limits targeting by human T cells modified to express chimeric antigen receptors (CARs) due to potential for deleterious recognition of normal cells. We sought to generate CAR+ T cells capable of distinguishing malignant from normal cells based on the disparate density of EGFR expression by generating two CARs from monoclonal antibodies which differ in affinity. T cells with low affinity Nimo-CAR selectively targeted cells over-expressing EGFR, but exhibited diminished effector function as the density of EGFR decreased. In contrast, the activation of T cells bearing high affinity Cetux-CAR was not impacted by the density of EGFR. In summary, we describe the generation of CARs able to tune T-cell activity to the level of EGFR expression in which a CAR with reduced affinity enabled T cells to distinguish malignant from non-malignant cells. PMID:26330164

Facial recognition in primary focal dystonia.

PubMed

Rinnerthaler, Martina; Benecke, Cord; Bartha, Lisa; Entner, Tanja; Poewe, Werner; Mueller, Joerg

2006-01-01

The basal ganglia seem to be involved in emotional processing. Primary dystonia is a movement disorder considered to result from basal ganglia dysfunction, and the aim of the present study was to investigate emotion recognition in patients with primary focal dystonia. Thirty-two patients with primary cranial (n=12) and cervical (n=20) dystonia were compared to 32 healthy controls matched for age, sex, and educational level on the facially expressed emotion labeling (FEEL) test, a computer-based tool measuring a person's ability to recognize facially expressed emotions. Patients with cognitive impairment or depression were excluded. None of the patients received medication with a possible cognitive side effect profile and only those with mild to moderate dystonia were included. Patients with primary dystonia showed isolated deficits in the recognition of disgust (P=0.007), while no differences between patients and controls were found with regard to the other emotions (fear, happiness, surprise, sadness, and anger). The findings of the present study add further evidence to the conception that dystonia is not only a motor but a complex basal ganglia disorder including selective emotion recognition disturbances. Copyright (c) 2005 Movement Disorder Society.

Novel dynamic Bayesian networks for facial action element recognition and understanding

NASA Astrophysics Data System (ADS)

Zhao, Wei; Park, Jeong-Seon; Choi, Dong-You; Lee, Sang-Woong

2011-12-01

In daily life, language is an important tool of communication between people. Besides language, facial action can also provide a great amount of information. Therefore, facial action recognition has become a popular research topic in the field of human-computer interaction (HCI). However, facial action recognition is quite a challenging task due to its complexity. In a literal sense, there are thousands of facial muscular movements, many of which have very subtle differences. Moreover, muscular movements always occur simultaneously when the pose is changed. To address this problem, we first build a fully automatic facial points detection system based on a local Gabor filter bank and principal component analysis. Then, novel dynamic Bayesian networks are proposed to perform facial action recognition using the junction tree algorithm over a limited number of feature points. In order to evaluate the proposed method, we have used the Korean face database for model training. For testing, we used the CUbiC FacePix, facial expressions and emotion database, Japanese female facial expression database, and our own database. Our experimental results clearly demonstrate the feasibility of the proposed approach.

Not on the Face Alone: Perception of Contextualized Face Expressions in Huntington's Disease

ERIC Educational Resources Information Center

Aviezer, Hillel; Bentin, Shlomo; Hassin, Ran R.; Meschino, Wendy S.; Kennedy, Jeanne; Grewal, Sonya; Esmail, Sherali; Cohen, Sharon; Moscovitch, Morris

2009-01-01

Numerous studies have demonstrated that Huntington's disease mutation-carriers have deficient explicit recognition of isolated facial expressions. There are no studies, however, which have investigated the recognition of facial expressions embedded within an emotional body and scene context. Real life facial expressions are typically embedded in…

Discriminability effect on Garner interference: evidence from recognition of facial identity and expression

PubMed Central

Wang, Yamin; Fu, Xiaolan; Johnston, Robert A.; Yan, Zheng

2013-01-01

Using Garner’s speeded classification task existing studies demonstrated an asymmetric interference in the recognition of facial identity and facial expression. It seems that expression is hard to interfere with identity recognition. However, discriminability of identity and expression, a potential confounding variable, had not been carefully examined in existing studies. In current work, we manipulated discriminability of identity and expression by matching facial shape (long or round) in identity and matching mouth (opened or closed) in facial expression. Garner interference was found either from identity to expression (Experiment 1) or from expression to identity (Experiment 2). Interference was also found in both directions (Experiment 3) or in neither direction (Experiment 4). The results support that Garner interference tends to occur under condition of low discriminability of relevant dimension regardless of facial property. Our findings indicate that Garner interference is not necessarily related to interdependent processing in recognition of facial identity and expression. The findings also suggest that discriminability as a mediating factor should be carefully controlled in future research. PMID:24391609

Using a social robot to teach gestural recognition and production in children with autism spectrum disorders.

PubMed

So, Wing-Chee; Wong, Miranda Kit-Yi; Lam, Carrie Ka-Yee; Lam, Wan-Yi; Chui, Anthony Tsz-Fung; Lee, Tsz-Lok; Ng, Hoi-Man; Chan, Chun-Hung; Fok, Daniel Chun-Wing

2017-07-04

While it has been argued that children with autism spectrum disorders are responsive to robot-like toys, very little research has examined the impact of robot-based intervention on gesture use. These children have delayed gestural development. We used a social robot in two phases to teach them to recognize and produce eight pantomime gestures that expressed feelings and needs. Compared to the children in the wait-list control group (N = 6), those in the intervention group (N = 7) were more likely to recognize gestures and to gesture accurately in trained and untrained scenarios. They also generalized the acquired recognition (but not production) skills to human-to-human interaction. The benefits and limitations of robot-based intervention for gestural learning were highlighted. Implications for Rehabilitation Compared to typically-developing children, children with autism spectrum disorders have delayed development of gesture comprehension and production. Robot-based intervention program was developed to teach children with autism spectrum disorders recognition (Phase I) and production (Phase II) of eight pantomime gestures that expressed feelings and needs. Children in the intervention group (but not in the wait-list control group) were able to recognize more gestures in both trained and untrained scenarios and generalize the acquired gestural recognition skills to human-to-human interaction. Similar findings were reported for gestural production except that there was no strong evidence showing children in the intervention group could produce gestures accurately in human-to-human interaction.

Dynamic Emotional Faces Generalise Better to a New Expression but not to a New View.

PubMed

Liu, Chang Hong; Chen, Wenfeng; Ward, James; Takahashi, Nozomi

2016-08-08

Prior research based on static images has found limited improvement for recognising previously learnt faces in a new expression after several different facial expressions of these faces had been shown during the learning session. We investigated whether non-rigid motion of facial expression facilitates the learning process. In Experiment 1, participants remembered faces that were either presented in short video clips or still images. To assess the effect of exposure to expression variation, each face was either learnt through a single expression or three different expressions. Experiment 2 examined whether learning faces in video clips could generalise more effectively to a new view. The results show that faces learnt from video clips generalised effectively to a new expression with exposure to a single expression, whereas faces learnt from stills showed poorer generalisation with exposure to either single or three expressions. However, although superior recognition performance was demonstrated for faces learnt through video clips, dynamic facial expression did not create better transfer of learning to faces tested in a new view. The data thus fail to support the hypothesis that non-rigid motion enhances viewpoint invariance. These findings reveal both benefits and limitations of exposures to moving expressions for expression-invariant face recognition.

Dynamic Emotional Faces Generalise Better to a New Expression but not to a New View

PubMed Central

Liu, Chang Hong; Chen, Wenfeng; Ward, James; Takahashi, Nozomi

2016-01-01

Prior research based on static images has found limited improvement for recognising previously learnt faces in a new expression after several different facial expressions of these faces had been shown during the learning session. We investigated whether non-rigid motion of facial expression facilitates the learning process. In Experiment 1, participants remembered faces that were either presented in short video clips or still images. To assess the effect of exposure to expression variation, each face was either learnt through a single expression or three different expressions. Experiment 2 examined whether learning faces in video clips could generalise more effectively to a new view. The results show that faces learnt from video clips generalised effectively to a new expression with exposure to a single expression, whereas faces learnt from stills showed poorer generalisation with exposure to either single or three expressions. However, although superior recognition performance was demonstrated for faces learnt through video clips, dynamic facial expression did not create better transfer of learning to faces tested in a new view. The data thus fail to support the hypothesis that non-rigid motion enhances viewpoint invariance. These findings reveal both benefits and limitations of exposures to moving expressions for expression-invariant face recognition. PMID:27499252

Facial Emotions Recognition using Gabor Transform and Facial Animation Parameters with Neural Networks

NASA Astrophysics Data System (ADS)

Harit, Aditya; Joshi, J. C., Col; Gupta, K. K.

2018-03-01

The paper proposed an automatic facial emotion recognition algorithm which comprises of two main components: feature extraction and expression recognition. The algorithm uses a Gabor filter bank on fiducial points to find the facial expression features. The resulting magnitudes of Gabor transforms, along with 14 chosen FAPs (Facial Animation Parameters), compose the feature space. There are two stages: the training phase and the recognition phase. Firstly, for the present 6 different emotions, the system classifies all training expressions in 6 different classes (one for each emotion) in the training stage. In the recognition phase, it recognizes the emotion by applying the Gabor bank to a face image, then finds the fiducial points, and then feeds it to the trained neural architecture.

Four-Channel Biosignal Analysis and Feature Extraction for Automatic Emotion Recognition

NASA Astrophysics Data System (ADS)

Kim, Jonghwa; André, Elisabeth

This paper investigates the potential of physiological signals as a reliable channel for automatic recognition of user's emotial state. For the emotion recognition, little attention has been paid so far to physiological signals compared to audio-visual emotion channels such as facial expression or speech. All essential stages of automatic recognition system using biosignals are discussed, from recording physiological dataset up to feature-based multiclass classification. Four-channel biosensors are used to measure electromyogram, electrocardiogram, skin conductivity and respiration changes. A wide range of physiological features from various analysis domains, including time/frequency, entropy, geometric analysis, subband spectra, multiscale entropy, etc., is proposed in order to search the best emotion-relevant features and to correlate them with emotional states. The best features extracted are specified in detail and their effectiveness is proven by emotion recognition results.

Age-related differences in emotion recognition ability: a cross-sectional study.

PubMed

Mill, Aire; Allik, Jüri; Realo, Anu; Valk, Raivo

2009-10-01

Experimental studies indicate that recognition of emotions, particularly negative emotions, decreases with age. However, there is no consensus at which age the decrease in emotion recognition begins, how selective this is to negative emotions, and whether this applies to both facial and vocal expression. In the current cross-sectional study, 607 participants ranging in age from 18 to 84 years (mean age = 32.6 +/- 14.9 years) were asked to recognize emotions expressed either facially or vocally. In general, older participants were found to be less accurate at recognizing emotions, with the most distinctive age difference pertaining to a certain group of negative emotions. Both modalities revealed an age-related decline in the recognition of sadness and -- to a lesser degree -- anger, starting at about 30 years of age. Although age-related differences in the recognition of expression of emotion were not mediated by personality traits, 2 of the Big 5 traits, openness and conscientiousness, made an independent contribution to emotion-recognition performance. Implications of age-related differences in facial and vocal emotion expression and early onset of the selective decrease in emotion recognition are discussed in terms of previous findings and relevant theoretical models.

Adaptive weighted local textural features for illumination, expression, and occlusion invariant face recognition

NASA Astrophysics Data System (ADS)

Cui, Chen; Asari, Vijayan K.

2014-03-01

Biometric features such as fingerprints, iris patterns, and face features help to identify people and restrict access to secure areas by performing advanced pattern analysis and matching. Face recognition is one of the most promising biometric methodologies for human identification in a non-cooperative security environment. However, the recognition results obtained by face recognition systems are a affected by several variations that may happen to the patterns in an unrestricted environment. As a result, several algorithms have been developed for extracting different facial features for face recognition. Due to the various possible challenges of data captured at different lighting conditions, viewing angles, facial expressions, and partial occlusions in natural environmental conditions, automatic facial recognition still remains as a difficult issue that needs to be resolved. In this paper, we propose a novel approach to tackling some of these issues by analyzing the local textural descriptions for facial feature representation. The textural information is extracted by an enhanced local binary pattern (ELBP) description of all the local regions of the face. The relationship of each pixel with respect to its neighborhood is extracted and employed to calculate the new representation. ELBP reconstructs a much better textural feature extraction vector from an original gray level image in different lighting conditions. The dimensionality of the texture image is reduced by principal component analysis performed on each local face region. Each low dimensional vector representing a local region is now weighted based on the significance of the sub-region. The weight of each sub-region is determined by employing the local variance estimate of the respective region, which represents the significance of the region. The final facial textural feature vector is obtained by concatenating the reduced dimensional weight sets of all the modules (sub-regions) of the face image. Experiments conducted on various popular face databases show promising performance of the proposed algorithm in varying lighting, expression, and partial occlusion conditions. Four databases were used for testing the performance of the proposed system: Yale Face database, Extended Yale Face database B, Japanese Female Facial Expression database, and CMU AMP Facial Expression database. The experimental results in all four databases show the effectiveness of the proposed system. Also, the computation cost is lower because of the simplified calculation steps. Research work is progressing to investigate the effectiveness of the proposed face recognition method on pose-varying conditions as well. It is envisaged that a multilane approach of trained frameworks at different pose bins and an appropriate voting strategy would lead to a good recognition rate in such situation.

Can Automated Facial Expression Analysis Show Differences Between Autism and Typical Functioning?

PubMed

Borsos, Zsófia; Gyori, Miklos

2017-01-01

Exploratory analyses of emotional expressions using a commercially available facial expression recognition software are reported, from the context of a serious game for screening purposes. Our results are based on a comparative analysis of two matched groups of kindergarten-age children (high-functioning children with autism spectrum condition: n=13; typically developing children: n=13). Results indicate that this technology has the potential to identify autism-specific emotion expression features, and may play a role in affective diagnostic and assistive technologies.

Near infrared and visible face recognition based on decision fusion of LBP and DCT features

NASA Astrophysics Data System (ADS)

Xie, Zhihua; Zhang, Shuai; Liu, Guodong; Xiong, Jinquan

2018-03-01

Visible face recognition systems, being vulnerable to illumination, expression, and pose, can not achieve robust performance in unconstrained situations. Meanwhile, near infrared face images, being light- independent, can avoid or limit the drawbacks of face recognition in visible light, but its main challenges are low resolution and signal noise ratio (SNR). Therefore, near infrared and visible fusion face recognition has become an important direction in the field of unconstrained face recognition research. In order to extract the discriminative complementary features between near infrared and visible images, in this paper, we proposed a novel near infrared and visible face fusion recognition algorithm based on DCT and LBP features. Firstly, the effective features in near-infrared face image are extracted by the low frequency part of DCT coefficients and the partition histograms of LBP operator. Secondly, the LBP features of visible-light face image are extracted to compensate for the lacking detail features of the near-infrared face image. Then, the LBP features of visible-light face image, the DCT and LBP features of near-infrared face image are sent to each classifier for labeling. Finally, decision level fusion strategy is used to obtain the final recognition result. The visible and near infrared face recognition is tested on HITSZ Lab2 visible and near infrared face database. The experiment results show that the proposed method extracts the complementary features of near-infrared and visible face images and improves the robustness of unconstrained face recognition. Especially for the circumstance of small training samples, the recognition rate of proposed method can reach 96.13%, which has improved significantly than 92.75 % of the method based on statistical feature fusion.

Lunar Phase-Dependent Expression of Cryptochrome and a Photoperiodic Mechanism for Lunar Phase-Recognition in a Reef Fish, Goldlined Spinefoot

PubMed Central

Fukushiro, Masato; Takeuchi, Takahiro; Takeuchi, Yuki; Hur, Sung-Pyo; Sugama, Nozomi; Takemura, Akihiro; Kubo, Yoko; Okano, Keiko; Okano, Toshiyuki

2011-01-01

Lunar cycle-associated physiology has been found in a wide variety of organisms. Recent study has revealed that mRNA levels of Cryptochrome (Cry), one of the circadian clock genes, were significantly higher on a full moon night than on a new moon night in coral, implying the involvement of a photoreception system in the lunar-synchronized spawning. To better establish the generalities surrounding such a mechanism and explore the underlying molecular mechanism, we focused on the relationship between lunar phase, Cry gene expression, and the spawning behavior in a lunar-synchronized spawner, the goldlined spinefoot (Siganus guttatus), and we identified two kinds of Cry genes in this animal. Their mRNA levels showed lunar cycle-dependent expression in the medial part of the brain (mesencephalon and diencephalon) peaking at the first quarter moon. Since this lunar phase coincided with the reproductive phase of the goldlined spinefoot, Cry gene expression was considered a state variable in the lunar phase recognition system. Based on the expression profiles of SgCrys together with the moonlight's pattern of timing and duration during its nightly lunar cycle, we have further speculated on a model of lunar phase recognition for reproductive control in the goldlined spinefoot, which integrates both moonlight and circadian signals in a manner similar to photoperiodic response. PMID:22163321

Lunar phase-dependent expression of cryptochrome and a photoperiodic mechanism for lunar phase-recognition in a reef fish, goldlined spinefoot.

PubMed

Fukushiro, Masato; Takeuchi, Takahiro; Takeuchi, Yuki; Hur, Sung-Pyo; Sugama, Nozomi; Takemura, Akihiro; Kubo, Yoko; Okano, Keiko; Okano, Toshiyuki

2011-01-01

Lunar cycle-associated physiology has been found in a wide variety of organisms. Recent study has revealed that mRNA levels of Cryptochrome (Cry), one of the circadian clock genes, were significantly higher on a full moon night than on a new moon night in coral, implying the involvement of a photoreception system in the lunar-synchronized spawning. To better establish the generalities surrounding such a mechanism and explore the underlying molecular mechanism, we focused on the relationship between lunar phase, Cry gene expression, and the spawning behavior in a lunar-synchronized spawner, the goldlined spinefoot (Siganus guttatus), and we identified two kinds of Cry genes in this animal. Their mRNA levels showed lunar cycle-dependent expression in the medial part of the brain (mesencephalon and diencephalon) peaking at the first quarter moon. Since this lunar phase coincided with the reproductive phase of the goldlined spinefoot, Cry gene expression was considered a state variable in the lunar phase recognition system. Based on the expression profiles of SgCrys together with the moonlight's pattern of timing and duration during its nightly lunar cycle, we have further speculated on a model of lunar phase recognition for reproductive control in the goldlined spinefoot, which integrates both moonlight and circadian signals in a manner similar to photoperiodic response.

Influence of Emotional Facial Expressions on 3-5-Year-Olds' Face Recognition

ERIC Educational Resources Information Center

Freitag, Claudia; Schwarzer, Gudrun

2011-01-01

Three experiments examined 3- and 5-year-olds' recognition of faces in constant and varied emotional expressions. Children were asked to identify repeatedly presented target faces, distinguishing them from distractor faces, during an immediate recognition test and during delayed assessments after 10 min and one week. Emotional facial expression…

Recognition of emotional facial expressions and broad autism phenotype in parents of children diagnosed with autistic spectrum disorder.

PubMed

Kadak, Muhammed Tayyib; Demirel, Omer Faruk; Yavuz, Mesut; Demir, Türkay

2014-07-01

Research findings debate about features of broad autism phenotype. In this study, we tested whether parents of children with autism have problems recognizing emotional facial expression and the contribution of such an impairment to the broad phenotype of autism. Seventy-two parents of children with autistic spectrum disorder and 38 parents of control group participated in the study. Broad autism features was measured with Autism Quotient (AQ). Recognition of Emotional Face Expression Test was assessed with the Emotion Recognition Test, consisting a set of photographs from Ekman & Friesen's. In a two-tailed analysis of variance of AQ, there was a significant difference for social skills (F(1, 106)=6.095; p<.05). Analyses of variance revealed significant difference in the recognition of happy, surprised and neutral expressions (F(1, 106)=4.068, p=.046; F(1, 106)=4.068, p=.046; F(1, 106)=6.064, p=.016). According to our findings, social impairment could be considered a characteristic feature of BAP. ASD parents had difficulty recognizing neutral expressions, suggesting that ASD parents may have impaired recognition of ambiguous expressions as do autistic children. Copyright © 2014 Elsevier Inc. All rights reserved.

Emotion recognition in borderline personality disorder: effects of emotional information on negative bias.

PubMed

Fenske, Sabrina; Lis, Stefanie; Liebke, Lisa; Niedtfeld, Inga; Kirsch, Peter; Mier, Daniela

2015-01-01

Borderline Personality Disorder (BPD) is characterized by severe deficits in social interactions, which might be linked to deficits in emotion recognition. Research on emotion recognition abilities in BPD revealed heterogeneous results, ranging from deficits to heightened sensitivity. The most stable findings point to an impairment in the evaluation of neutral facial expressions as neutral, as well as to a negative bias in emotion recognition; that is the tendency to attribute negative emotions to neutral expressions, or in a broader sense to report a more negative emotion category than depicted. However, it remains unclear which contextual factors influence the occurrence of this negative bias. Previous studies suggest that priming by preceding emotional information and also constrained processing time might augment the emotion recognition deficit in BPD. To test these assumptions, 32 female BPD patients and 31 healthy females, matched for age and education, participated in an emotion recognition study, in which every facial expression was preceded by either a positive, neutral or negative scene. Furthermore, time constraints for processing were varied by presenting the facial expressions with short (100 ms) or long duration (up to 3000 ms) in two separate blocks. BPD patients showed a significant deficit in emotion recognition for neutral and positive facial expression, associated with a significant negative bias. In BPD patients, this emotion recognition deficit was differentially affected by preceding emotional information and time constraints, with a greater influence of emotional information during long face presentations and a greater influence of neutral information during short face presentations. Our results are in line with previous findings supporting the existence of a negative bias in emotion recognition in BPD patients, and provide further insights into biased social perceptions in BPD patients.

Learning Low-Rank Class-Specific Dictionary and Sparse Intra-Class Variant Dictionary for Face Recognition.

PubMed

Tang, Xin; Feng, Guo-Can; Li, Xiao-Xin; Cai, Jia-Xin

2015-01-01

Face recognition is challenging especially when the images from different persons are similar to each other due to variations in illumination, expression, and occlusion. If we have sufficient training images of each person which can span the facial variations of that person under testing conditions, sparse representation based classification (SRC) achieves very promising results. However, in many applications, face recognition often encounters the small sample size problem arising from the small number of available training images for each person. In this paper, we present a novel face recognition framework by utilizing low-rank and sparse error matrix decomposition, and sparse coding techniques (LRSE+SC). Firstly, the low-rank matrix recovery technique is applied to decompose the face images per class into a low-rank matrix and a sparse error matrix. The low-rank matrix of each individual is a class-specific dictionary and it captures the discriminative feature of this individual. The sparse error matrix represents the intra-class variations, such as illumination, expression changes. Secondly, we combine the low-rank part (representative basis) of each person into a supervised dictionary and integrate all the sparse error matrix of each individual into a within-individual variant dictionary which can be applied to represent the possible variations between the testing and training images. Then these two dictionaries are used to code the query image. The within-individual variant dictionary can be shared by all the subjects and only contribute to explain the lighting conditions, expressions, and occlusions of the query image rather than discrimination. At last, a reconstruction-based scheme is adopted for face recognition. Since the within-individual dictionary is introduced, LRSE+SC can handle the problem of the corrupted training data and the situation that not all subjects have enough samples for training. Experimental results show that our method achieves the state-of-the-art results on AR, FERET, FRGC and LFW databases.

Learning Low-Rank Class-Specific Dictionary and Sparse Intra-Class Variant Dictionary for Face Recognition

PubMed Central

Tang, Xin; Feng, Guo-can; Li, Xiao-xin; Cai, Jia-xin

2015-01-01

Face recognition is challenging especially when the images from different persons are similar to each other due to variations in illumination, expression, and occlusion. If we have sufficient training images of each person which can span the facial variations of that person under testing conditions, sparse representation based classification (SRC) achieves very promising results. However, in many applications, face recognition often encounters the small sample size problem arising from the small number of available training images for each person. In this paper, we present a novel face recognition framework by utilizing low-rank and sparse error matrix decomposition, and sparse coding techniques (LRSE+SC). Firstly, the low-rank matrix recovery technique is applied to decompose the face images per class into a low-rank matrix and a sparse error matrix. The low-rank matrix of each individual is a class-specific dictionary and it captures the discriminative feature of this individual. The sparse error matrix represents the intra-class variations, such as illumination, expression changes. Secondly, we combine the low-rank part (representative basis) of each person into a supervised dictionary and integrate all the sparse error matrix of each individual into a within-individual variant dictionary which can be applied to represent the possible variations between the testing and training images. Then these two dictionaries are used to code the query image. The within-individual variant dictionary can be shared by all the subjects and only contribute to explain the lighting conditions, expressions, and occlusions of the query image rather than discrimination. At last, a reconstruction-based scheme is adopted for face recognition. Since the within-individual dictionary is introduced, LRSE+SC can handle the problem of the corrupted training data and the situation that not all subjects have enough samples for training. Experimental results show that our method achieves the state-of-the-art results on AR, FERET, FRGC and LFW databases. PMID:26571112

Emotional face recognition deficits and medication effects in pre-manifest through stage-II Huntington's disease.

PubMed

Labuschagne, Izelle; Jones, Rebecca; Callaghan, Jenny; Whitehead, Daisy; Dumas, Eve M; Say, Miranda J; Hart, Ellen P; Justo, Damian; Coleman, Allison; Dar Santos, Rachelle C; Frost, Chris; Craufurd, David; Tabrizi, Sarah J; Stout, Julie C

2013-05-15

Facial emotion recognition impairments have been reported in Huntington's disease (HD). However, the nature of the impairments across the spectrum of HD remains unclear. We report on emotion recognition data from 344 participants comprising premanifest HD (PreHD) and early HD patients, and controls. In a test of recognition of facial emotions, we examined responses to six basic emotional expressions and neutral expressions. In addition, and within the early HD sample, we tested for differences on emotion recognition performance between those 'on' vs. 'off' neuroleptic or selective serotonin reuptake inhibitor (SSRI) medications. The PreHD groups showed significant (p<0.05) impaired recognition, compared to controls, on fearful, angry and surprised faces; whereas the early HD groups were significantly impaired across all emotions including neutral expressions. In early HD, neuroleptic use was associated with worse facial emotion recognition, whereas SSRI use was associated with better facial emotion recognition. The findings suggest that emotion recognition impairments exist across the HD spectrum, but are relatively more widespread in manifest HD than in the premanifest period. Commonly prescribed medications to treat HD-related symptoms also appear to affect emotion recognition. These findings have important implications for interpersonal communication and medication usage in HD. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Incongruence Between Observers’ and Observed Facial Muscle Activation Reduces Recognition of Emotional Facial Expressions From Video Stimuli

PubMed Central

Wingenbach, Tanja S. H.; Brosnan, Mark; Pfaltz, Monique C.; Plichta, Michael M.; Ashwin, Chris

2018-01-01

According to embodied cognition accounts, viewing others’ facial emotion can elicit the respective emotion representation in observers which entails simulations of sensory, motor, and contextual experiences. In line with that, published research found viewing others’ facial emotion to elicit automatic matched facial muscle activation, which was further found to facilitate emotion recognition. Perhaps making congruent facial muscle activity explicit produces an even greater recognition advantage. If there is conflicting sensory information, i.e., incongruent facial muscle activity, this might impede recognition. The effects of actively manipulating facial muscle activity on facial emotion recognition from videos were investigated across three experimental conditions: (a) explicit imitation of viewed facial emotional expressions (stimulus-congruent condition), (b) pen-holding with the lips (stimulus-incongruent condition), and (c) passive viewing (control condition). It was hypothesised that (1) experimental condition (a) and (b) result in greater facial muscle activity than (c), (2) experimental condition (a) increases emotion recognition accuracy from others’ faces compared to (c), (3) experimental condition (b) lowers recognition accuracy for expressions with a salient facial feature in the lower, but not the upper face area, compared to (c). Participants (42 males, 42 females) underwent a facial emotion recognition experiment (ADFES-BIV) while electromyography (EMG) was recorded from five facial muscle sites. The experimental conditions’ order was counter-balanced. Pen-holding caused stimulus-incongruent facial muscle activity for expressions with facial feature saliency in the lower face region, which reduced recognition of lower face region emotions. Explicit imitation caused stimulus-congruent facial muscle activity without modulating recognition. Methodological implications are discussed. PMID:29928240

Incongruence Between Observers' and Observed Facial Muscle Activation Reduces Recognition of Emotional Facial Expressions From Video Stimuli.

PubMed

Wingenbach, Tanja S H; Brosnan, Mark; Pfaltz, Monique C; Plichta, Michael M; Ashwin, Chris

2018-01-01

According to embodied cognition accounts, viewing others' facial emotion can elicit the respective emotion representation in observers which entails simulations of sensory, motor, and contextual experiences. In line with that, published research found viewing others' facial emotion to elicit automatic matched facial muscle activation, which was further found to facilitate emotion recognition. Perhaps making congruent facial muscle activity explicit produces an even greater recognition advantage. If there is conflicting sensory information, i.e., incongruent facial muscle activity, this might impede recognition. The effects of actively manipulating facial muscle activity on facial emotion recognition from videos were investigated across three experimental conditions: (a) explicit imitation of viewed facial emotional expressions (stimulus-congruent condition), (b) pen-holding with the lips (stimulus-incongruent condition), and (c) passive viewing (control condition). It was hypothesised that (1) experimental condition (a) and (b) result in greater facial muscle activity than (c), (2) experimental condition (a) increases emotion recognition accuracy from others' faces compared to (c), (3) experimental condition (b) lowers recognition accuracy for expressions with a salient facial feature in the lower, but not the upper face area, compared to (c). Participants (42 males, 42 females) underwent a facial emotion recognition experiment (ADFES-BIV) while electromyography (EMG) was recorded from five facial muscle sites. The experimental conditions' order was counter-balanced. Pen-holding caused stimulus-incongruent facial muscle activity for expressions with facial feature saliency in the lower face region, which reduced recognition of lower face region emotions. Explicit imitation caused stimulus-congruent facial muscle activity without modulating recognition. Methodological implications are discussed.

Gaze Dynamics in the Recognition of Facial Expressions of Emotion.

PubMed

Barabanschikov, Vladimir A

2015-01-01

We studied preferably fixated parts and features of human face in the process of recognition of facial expressions of emotion. Photographs of facial expressions were used. Participants were to categorize these as basic emotions; during this process, eye movements were registered. It was found that variation in the intensity of an expression is mirrored in accuracy of emotion recognition; it was also reflected by several indices of oculomotor function: duration of inspection of certain areas of the face, its upper and bottom or right parts, right and left sides; location, number and duration of fixations, viewing trajectory. In particular, for low-intensity expressions, right side of the face was found to be attended predominantly (right-side dominance); the right-side dominance effect, was, however, absent for expressions of high intensity. For both low- and high-intensity expressions, upper face part was predominantly fixated, though with greater fixation of high-intensity expressions. The majority of trials (70%), in line with findings in previous studies, revealed a V-shaped pattern of inspection trajectory. No relationship, between accuracy of recognition of emotional expressions, was found, though, with either location and duration of fixations or pattern of gaze directedness in the face. © The Author(s) 2015.

Recognition of Immaturity and Emotional Expressions in Blended Faces by Children with Autism and Other Developmental Disabilities

ERIC Educational Resources Information Center

Gross, Thomas F.

2008-01-01

The recognition of facial immaturity and emotional expression by children with autism, language disorders, mental retardation, and non-disabled controls was studied in two experiments. Children identified immaturity and expression in upright and inverted faces. The autism group identified fewer immature faces and expressions than control (Exp. 1 &…

Violent Media Consumption and the Recognition of Dynamic Facial Expressions

ERIC Educational Resources Information Center

Kirsh, Steven J.; Mounts, Jeffrey R. W.; Olczak, Paul V.

2006-01-01

This study assessed the speed of recognition of facial emotional expressions (happy and angry) as a function of violent media consumption. Color photos of calm facial expressions morphed to either an angry or a happy facial expression. Participants were asked to make a speeded identification of the emotion (happiness or anger) during the morph.…

Local binary pattern variants-based adaptive texture features analysis for posed and nonposed facial expression recognition

NASA Astrophysics Data System (ADS)

Sultana, Maryam; Bhatti, Naeem; Javed, Sajid; Jung, Soon Ki

2017-09-01

Facial expression recognition (FER) is an important task for various computer vision applications. The task becomes challenging when it requires the detection and encoding of macro- and micropatterns of facial expressions. We present a two-stage texture feature extraction framework based on the local binary pattern (LBP) variants and evaluate its significance in recognizing posed and nonposed facial expressions. We focus on the parametric limitations of the LBP variants and investigate their effects for optimal FER. The size of the local neighborhood is an important parameter of the LBP technique for its extraction in images. To make the LBP adaptive, we exploit the granulometric information of the facial images to find the local neighborhood size for the extraction of center-symmetric LBP (CS-LBP) features. Our two-stage texture representations consist of an LBP variant and the adaptive CS-LBP features. Among the presented two-stage texture feature extractions, the binarized statistical image features and adaptive CS-LBP features were found showing high FER rates. Evaluation of the adaptive texture features shows competitive and higher performance than the nonadaptive features and other state-of-the-art approaches, respectively.

Facial expressions recognition with an emotion expressive robotic head

NASA Astrophysics Data System (ADS)

Doroftei, I.; Adascalitei, F.; Lefeber, D.; Vanderborght, B.; Doroftei, I. A.

2016-08-01

The purpose of this study is to present the preliminary steps in facial expressions recognition with a new version of an expressive social robotic head. So, in a first phase, our main goal was to reach a minimum level of emotional expressiveness in order to obtain nonverbal communication between the robot and human by building six basic facial expressions. To evaluate the facial expressions, the robot was used in some preliminary user studies, among children and adults.

Recognition Imaging of Acetylated Chromatin Using a DNA Aptamer

PubMed Central

Lin, Liyun; Fu, Qiang; Williams, Berea A.R.; Azzaz, Abdelhamid M.; Shogren-Knaak, Michael A.; Chaput, John C.; Lindsay, Stuart

2009-01-01

Histone acetylation plays an important role in the regulation of gene expression. A DNA aptamer generated by in vitro selection to be highly specific for histone H4 protein acetylated at lysine 16 was used as a recognition element for atomic force microscopy-based recognition imaging of synthetic nucleosomal arrays with precisely controlled acetylation. The aptamer proved to be reasonably specific at recognizing acetylated histones, with recognition efficiencies of 60% on-target and 12% off-target. Though this selectivity is much poorer than the >2000:1 equilibrium specificity of the aptamer, it is a large improvement on the performance of a ChIP-quality antibody, which is not selective at all in this application, and it should permit high-fidelity recognition with repeated imaging. The ability to image the precise location of posttranslational modifications may permit nanometer-scale investigation of their effect on chromatin structure. PMID:19751687

Breastfeeding experience differentially impacts recognition of happiness and anger in mothers.

PubMed

Krol, Kathleen M; Kamboj, Sunjeev K; Curran, H Valerie; Grossmann, Tobias

2014-11-12

Breastfeeding is a dynamic biological and social process based on hormonal regulation involving oxytocin. While there is much work on the role of breastfeeding in infant development and on the role of oxytocin in socio-emotional functioning in adults, little is known about how breastfeeding impacts emotion perception during motherhood. We therefore examined whether breastfeeding influences emotion recognition in mothers. Using a dynamic emotion recognition task, we found that longer durations of exclusive breastfeeding were associated with faster recognition of happiness, providing evidence for a facilitation of processing positive facial expressions. In addition, we found that greater amounts of breastfed meals per day were associated with slower recognition of anger. Our findings are in line with current views of oxytocin function and support accounts that view maternal behaviour as tuned to prosocial responsiveness, by showing that vital elements of maternal care can facilitate the rapid responding to affiliative stimuli by reducing importance of threatening stimuli.

Convolutional neural networks with balanced batches for facial expressions recognition

NASA Astrophysics Data System (ADS)

Battini Sönmez, Elena; Cangelosi, Angelo

2017-03-01

This paper considers the issue of fully automatic emotion classification on 2D faces. In spite of the great effort done in recent years, traditional machine learning approaches based on hand-crafted feature extraction followed by the classification stage failed to develop a real-time automatic facial expression recognition system. The proposed architecture uses Convolutional Neural Networks (CNN), which are built as a collection of interconnected processing elements to simulate the brain of human beings. The basic idea of CNNs is to learn a hierarchical representation of the input data, which results in a better classification performance. In this work we present a block-based CNN algorithm, which uses noise, as data augmentation technique, and builds batches with a balanced number of samples per class. The proposed architecture is a very simple yet powerful CNN, which can yield state-of-the-art accuracy on the very competitive benchmark algorithm of the Extended Cohn Kanade database.

Art critic: Multisignal vision and speech interaction system in a gaming context.

PubMed

Reale, Michael J; Liu, Peng; Yin, Lijun; Canavan, Shaun

2013-12-01

True immersion of a player within a game can only occur when the world simulated looks and behaves as close to reality as possible. This implies that the game must correctly read and understand, among other things, the player's focus, attitude toward the objects/persons in focus, gestures, and speech. In this paper, we proposed a novel system that integrates eye gaze estimation, head pose estimation, facial expression recognition, speech recognition, and text-to-speech components for use in real-time games. Both the eye gaze and head pose components utilize underlying 3-D models, and our novel head pose estimation algorithm uniquely combines scene flow with a generic head model. The facial expression recognition module uses the local binary patterns with three orthogonal planes approach on the 2-D shape index domain rather than the pixel domain, resulting in improved classification. Our system has also been extended to use a pan-tilt-zoom camera driven by the Kinect, allowing us to track a moving player. A test game, Art Critic, is also presented, which not only demonstrates the utility of our system but also provides a template for player/non-player character (NPC) interaction in a gaming context. The player alters his/her view of the 3-D world using head pose, looks at paintings/NPCs using eye gaze, and makes an evaluation based on the player's expression and speech. The NPC artist will respond with facial expression and synthetic speech based on its personality. Both qualitative and quantitative evaluations of the system are performed to illustrate the system's effectiveness.

Oxytocin, vasopressin and estrogen receptor gene expression in relation to social recognition in female mice

PubMed Central

Clipperton-Allen, Amy E.; Lee, Anna W.; Reyes, Anny; Devidze, Nino; Phan, Anna; Pfaff, Donald W.; Choleris, Elena

2012-01-01

Inter- and intra-species differences in social behavior and recognition-related hormones and receptors suggest that different distribution and/or expression patterns may relate to social recognition. We used qRT-PCR to investigate naturally occurring differences in expression of estrogen receptor-alpha (ERα), ER-beta (ERβ), progesterone receptor (PR), oxytocin (OT) and receptor, and vasopressin (AVP) and receptors in proestrous female mice. Following four 5 min exposures to the same two conspecifics, one was replaced with a novel mouse in the final trial (T5). Gene expression was examined in mice showing high (85–100%) and low (40–60%) social recognition scores (i.e., preferential novel mouse investigation in T5) in eight socially-relevant brain regions. Results supported OT and AVP involvement in social recognition, and suggest that in the medial preoptic area, increased OT and AVP mRNA, together with ERα and ERβ gene activation, relate to improved social recognition. Initial social investigation correlated with ERs, PR and OTR in the dorsolateral septum, suggesting that these receptors may modulate social interest without affecting social recognition. Finally, increased lateral amygdala gene activation in the LR mice may be associated with general learning impairments, while decreased lateral amygdala activity may indicate more efficient cognitive mechanisms in the HR mice. PMID:22079582

Specific Impairments in the Recognition of Emotional Facial Expressions in Parkinson’s Disease

PubMed Central

Clark, Uraina S.; Neargarder, Sandy; Cronin-Golomb, Alice

2008-01-01

Studies investigating the ability to recognize emotional facial expressions in non-demented individuals with Parkinson’s disease (PD) have yielded equivocal findings. A possible reason for this variability may lie in the confounding of emotion recognition with cognitive task requirements, a confound arising from the lack of a control condition using non-emotional stimuli. The present study examined emotional facial expression recognition abilities in 20 non-demented patients with PD and 23 control participants relative to their performances on a non-emotional landscape categorization test with comparable task requirements. We found that PD participants were normal on the control task but exhibited selective impairments in the recognition of facial emotion, specifically for anger (driven by those with right hemisphere pathology) and surprise (driven by those with left hemisphere pathology), even when controlling for depression level. Male but not female PD participants further displayed specific deficits in the recognition of fearful expressions. We suggest that the neural substrates that may subserve these impairments include the ventral striatum, amygdala, and prefrontal cortices. Finally, we observed that in PD participants, deficiencies in facial emotion recognition correlated with higher levels of interpersonal distress, which calls attention to the significant psychosocial impact that facial emotion recognition impairments may have on individuals with PD. PMID:18485422

Constructive autoassociative neural network for facial recognition.

PubMed

Fernandes, Bruno J T; Cavalcanti, George D C; Ren, Tsang I

2014-01-01

Autoassociative artificial neural networks have been used in many different computer vision applications. However, it is difficult to define the most suitable neural network architecture because this definition is based on previous knowledge and depends on the problem domain. To address this problem, we propose a constructive autoassociative neural network called CANet (Constructive Autoassociative Neural Network). CANet integrates the concepts of receptive fields and autoassociative memory in a dynamic architecture that changes the configuration of the receptive fields by adding new neurons in the hidden layer, while a pruning algorithm removes neurons from the output layer. Neurons in the CANet output layer present lateral inhibitory connections that improve the recognition rate. Experiments in face recognition and facial expression recognition show that the CANet outperforms other methods presented in the literature.

Feature extraction for face recognition via Active Shape Model (ASM) and Active Appearance Model (AAM)

NASA Astrophysics Data System (ADS)

Iqtait, M.; Mohamad, F. S.; Mamat, M.

2018-03-01

Biometric is a pattern recognition system which is used for automatic recognition of persons based on characteristics and features of an individual. Face recognition with high recognition rate is still a challenging task and usually accomplished in three phases consisting of face detection, feature extraction, and expression classification. Precise and strong location of trait point is a complicated and difficult issue in face recognition. Cootes proposed a Multi Resolution Active Shape Models (ASM) algorithm, which could extract specified shape accurately and efficiently. Furthermore, as the improvement of ASM, Active Appearance Models algorithm (AAM) is proposed to extracts both shape and texture of specified object simultaneously. In this paper we give more details about the two algorithms and give the results of experiments, testing their performance on one dataset of faces. We found that the ASM is faster and gains more accurate trait point location than the AAM, but the AAM gains a better match to the texture.

A Web-based Game for Teaching Facial Expressions to Schizophrenic Patients.

PubMed

Gülkesen, Kemal Hakan; Isleyen, Filiz; Cinemre, Buket; Samur, Mehmet Kemal; Sen Kaya, Semiha; Zayim, Nese

2017-07-12

Recognizing facial expressions is an important social skill. In some psychological disorders such as schizophrenia, loss of this skill may complicate the patient's daily life. Prior research has shown that information technology may help to develop facial expression recognition skills through educational software and games. To examine if a computer game designed for teaching facial expressions would improve facial expression recognition skills of patients with schizophrenia. We developed a website composed of eight serious games. Thirty-two patients were given a pre-test composed of 21 facial expression photographs. Eighteen patients were in the study group while 14 were in the control group. Patients in the study group were asked to play the games on the website. After a period of one month, we performed a post-test for all patients. The median score of the correct answers was 17.5 in the control group whereas it was 16.5 in the study group (of 21) in pretest. The median post-test score was 18 in the control group (p=0.052) whereas it was 20 in the study group (p<0.001). Computer games may be used for the purpose of educating people who have difficulty in recognizing facial expressions.

The Right Place at the Right Time: Priming Facial Expressions with Emotional Face Components in Developmental Visual Agnosia

PubMed Central

Aviezer, Hillel; Hassin, Ran. R.; Perry, Anat; Dudarev, Veronica; Bentin, Shlomo

2012-01-01

The current study examined the nature of deficits in emotion recognition from facial expressions in case LG, an individual with a rare form of developmental visual agnosia (DVA). LG presents with profoundly impaired recognition of facial expressions, yet the underlying nature of his deficit remains unknown. During typical face processing, normal sighted individuals extract information about expressed emotions from face regions with activity diagnostic for specific emotion categories. Given LG’s impairment, we sought to shed light on his emotion perception by examining if priming facial expressions with diagnostic emotional face components would facilitate his recognition of the emotion expressed by the face. LG and control participants matched isolated face components with components appearing in a subsequently presented full-face and then categorized the face’s emotion. Critically, the matched components were from regions which were diagnostic or non-diagnostic of the emotion portrayed by the full face. In experiment 1, when the full faces were briefly presented (150 ms), LG’s performance was strongly influenced by the diagnosticity of the components: His emotion recognition was boosted within normal limits when diagnostic components were used and was obliterated when non-diagnostic components were used. By contrast, in experiment 2, when the face-exposure duration was extended (2000 ms), the beneficial effect of the diagnostic matching was diminished as was the detrimental effect of the non-diagnostic matching. These data highlight the impact of diagnostic facial features in normal expression recognition and suggest that impaired emotion recognition in DVA results from deficient visual integration across diagnostic face components. PMID:22349446

Behavioral dissociation between emotional and non-emotional facial expressions in congenital prosopagnosia

PubMed Central

Daini, Roberta; Comparetti, Chiara M.; Ricciardelli, Paola

2014-01-01

Neuropsychological and neuroimaging studies have shown that facial recognition and emotional expressions are dissociable. However, it is unknown if a single system supports the processing of emotional and non-emotional facial expressions. We aimed to understand if individuals with impairment in face recognition from birth (congenital prosopagnosia, CP) can use non-emotional facial expressions to recognize a face as an already seen one, and thus, process this facial dimension independently from features (which are impaired in CP), and basic emotional expressions. To this end, we carried out a behavioral study in which we compared the performance of 6 CP individuals to that of typical development individuals, using upright and inverted faces. Four avatar faces with a neutral expression were presented in the initial phase. The target faces presented in the recognition phase, in which a recognition task was requested (2AFC paradigm), could be identical (neutral) to those of the initial phase or present biologically plausible changes to features, non-emotional expressions, or emotional expressions. After this task, a second task was performed, in which the participants had to detect whether or not the recognized face exactly matched the study face or showed any difference. The results confirmed the CPs' impairment in the configural processing of the invariant aspects of the face, but also showed a spared configural processing of non-emotional facial expression (task 1). Interestingly and unlike the non-emotional expressions, the configural processing of emotional expressions was compromised in CPs and did not improve their change detection ability (task 2). These new results have theoretical implications for face perception models since they suggest that, at least in CPs, non-emotional expressions are processed configurally, can be dissociated from other facial dimensions, and may serve as a compensatory strategy to achieve face recognition. PMID:25520643

Behavioral dissociation between emotional and non-emotional facial expressions in congenital prosopagnosia.

PubMed

Daini, Roberta; Comparetti, Chiara M; Ricciardelli, Paola

2014-01-01

Neuropsychological and neuroimaging studies have shown that facial recognition and emotional expressions are dissociable. However, it is unknown if a single system supports the processing of emotional and non-emotional facial expressions. We aimed to understand if individuals with impairment in face recognition from birth (congenital prosopagnosia, CP) can use non-emotional facial expressions to recognize a face as an already seen one, and thus, process this facial dimension independently from features (which are impaired in CP), and basic emotional expressions. To this end, we carried out a behavioral study in which we compared the performance of 6 CP individuals to that of typical development individuals, using upright and inverted faces. Four avatar faces with a neutral expression were presented in the initial phase. The target faces presented in the recognition phase, in which a recognition task was requested (2AFC paradigm), could be identical (neutral) to those of the initial phase or present biologically plausible changes to features, non-emotional expressions, or emotional expressions. After this task, a second task was performed, in which the participants had to detect whether or not the recognized face exactly matched the study face or showed any difference. The results confirmed the CPs' impairment in the configural processing of the invariant aspects of the face, but also showed a spared configural processing of non-emotional facial expression (task 1). Interestingly and unlike the non-emotional expressions, the configural processing of emotional expressions was compromised in CPs and did not improve their change detection ability (task 2). These new results have theoretical implications for face perception models since they suggest that, at least in CPs, non-emotional expressions are processed configurally, can be dissociated from other facial dimensions, and may serve as a compensatory strategy to achieve face recognition.

Dissociation between facial and bodily expressions in emotion recognition: A case study.

PubMed

Leiva, Samanta; Margulis, Laura; Micciulli, Andrea; Ferreres, Aldo

2017-12-21

Existing single-case studies have reported deficit in recognizing basic emotions through facial expression and unaffected performance with body expressions, but not the opposite pattern. The aim of this paper is to present a case study with impaired emotion recognition through body expressions and intact performance with facial expressions. In this single-case study we assessed a 30-year-old patient with autism spectrum disorder, without intellectual disability, and a healthy control group (n = 30) with four tasks of basic and complex emotion recognition through face and body movements, and two non-emotional control tasks. To analyze the dissociation between facial and body expressions, we used Crawford and Garthwaite's operational criteria, and we compared the patient and the control group performance with a modified one-tailed t-test designed specifically for single-case studies. There were no statistically significant differences between the patient's and the control group's performances on the non-emotional body movement task or the facial perception task. For both kinds of emotions (basic and complex) when the patient's performance was compared to the control group's, statistically significant differences were only observed for the recognition of body expressions. There were no significant differences between the patient's and the control group's correct answers for emotional facial stimuli. Our results showed a profile of impaired emotion recognition through body expressions and intact performance with facial expressions. This is the first case study that describes the existence of this kind of dissociation pattern between facial and body expressions of basic and complex emotions.

A Spiking Neural Network Based Cortex-Like Mechanism and Application to Facial Expression Recognition

PubMed Central

Fu, Si-Yao; Yang, Guo-Sheng; Kuai, Xin-Kai

2012-01-01

In this paper, we present a quantitative, highly structured cortex-simulated model, which can be simply described as feedforward, hierarchical simulation of ventral stream of visual cortex using biologically plausible, computationally convenient spiking neural network system. The motivation comes directly from recent pioneering works on detailed functional decomposition analysis of the feedforward pathway of the ventral stream of visual cortex and developments on artificial spiking neural networks (SNNs). By combining the logical structure of the cortical hierarchy and computing power of the spiking neuron model, a practical framework has been presented. As a proof of principle, we demonstrate our system on several facial expression recognition tasks. The proposed cortical-like feedforward hierarchy framework has the merit of capability of dealing with complicated pattern recognition problems, suggesting that, by combining the cognitive models with modern neurocomputational approaches, the neurosystematic approach to the study of cortex-like mechanism has the potential to extend our knowledge of brain mechanisms underlying the cognitive analysis and to advance theoretical models of how we recognize face or, more specifically, perceive other people's facial expression in a rich, dynamic, and complex environment, providing a new starting point for improved models of visual cortex-like mechanism. PMID:23193391

A spiking neural network based cortex-like mechanism and application to facial expression recognition.

PubMed

Fu, Si-Yao; Yang, Guo-Sheng; Kuai, Xin-Kai

2012-01-01

In this paper, we present a quantitative, highly structured cortex-simulated model, which can be simply described as feedforward, hierarchical simulation of ventral stream of visual cortex using biologically plausible, computationally convenient spiking neural network system. The motivation comes directly from recent pioneering works on detailed functional decomposition analysis of the feedforward pathway of the ventral stream of visual cortex and developments on artificial spiking neural networks (SNNs). By combining the logical structure of the cortical hierarchy and computing power of the spiking neuron model, a practical framework has been presented. As a proof of principle, we demonstrate our system on several facial expression recognition tasks. The proposed cortical-like feedforward hierarchy framework has the merit of capability of dealing with complicated pattern recognition problems, suggesting that, by combining the cognitive models with modern neurocomputational approaches, the neurosystematic approach to the study of cortex-like mechanism has the potential to extend our knowledge of brain mechanisms underlying the cognitive analysis and to advance theoretical models of how we recognize face or, more specifically, perceive other people's facial expression in a rich, dynamic, and complex environment, providing a new starting point for improved models of visual cortex-like mechanism.

Emotion-independent face recognition

NASA Astrophysics Data System (ADS)

De Silva, Liyanage C.; Esther, Kho G. P.

2000-12-01

Current face recognition techniques tend to work well when recognizing faces under small variations in lighting, facial expression and pose, but deteriorate under more extreme conditions. In this paper, a face recognition system to recognize faces of known individuals, despite variations in facial expression due to different emotions, is developed. The eigenface approach is used for feature extraction. Classification methods include Euclidean distance, back propagation neural network and generalized regression neural network. These methods yield 100% recognition accuracy when the training database is representative, containing one image representing the peak expression for each emotion of each person apart from the neutral expression. The feature vectors used for comparison in the Euclidean distance method and for training the neural network must be all the feature vectors of the training set. These results are obtained for a face database consisting of only four persons.

The effects of alcohol on the recognition of facial expressions and microexpressions of emotion: enhanced recognition of disgust and contempt.

PubMed

Felisberti, Fatima; Terry, Philip

2015-09-01

The study compared alcohol's effects on the recognition of briefly displayed facial expressions of emotion (so-called microexpressions) with expressions presented for a longer period. Using a repeated-measures design, we tested 18 participants three times (counterbalanced), after (i) a placebo drink, (ii) a low-to-moderate dose of alcohol (0.17 g/kg women; 0.20 g/kg men) and (iii) a moderate-to-high dose of alcohol (0.52 g/kg women; 0.60 g/kg men). On each session, participants were presented with stimuli representing six emotions (happiness, sadness, anger, fear, disgust and contempt) overlaid on a generic avatar in a six-alternative forced-choice paradigm. A neutral expression (1 s) preceded and followed a target expression presented for 200 ms (microexpressions) or 400 ms. Participants mouse clicked the correct answer. The recognition of disgust was significantly better after the high dose of alcohol than after the low dose or placebo drinks at both durations of stimulus presentation. A similar profile of effects was found for the recognition of contempt. There were no effects on response latencies. Alcohol can increase sensitivity to expressions of disgust and contempt. Such effects are not dependent on stimulus duration up to 400 ms and may reflect contextual modulation of alcohol's effects on emotion recognition. Copyright © 2015 John Wiley & Sons, Ltd.

Social appraisal influences recognition of emotions.

PubMed

Mumenthaler, Christian; Sander, David

2012-06-01

The notion of social appraisal emphasizes the importance of a social dimension in appraisal theories of emotion by proposing that the way an individual appraises an event is influenced by the way other individuals appraise and feel about the same event. This study directly tested this proposal by asking participants to recognize dynamic facial expressions of emotion (fear, happiness, or anger in Experiment 1; fear, happiness, anger, or neutral in Experiment 2) in a target face presented at the center of a screen while a contextual face, which appeared simultaneously in the periphery of the screen, expressed an emotion (fear, happiness, anger) or not (neutral) and either looked at the target face or not. We manipulated gaze direction to be able to distinguish between a mere contextual effect (gaze away from both the target face and the participant) and a specific social appraisal effect (gaze toward the target face). Results of both experiments provided evidence for a social appraisal effect in emotion recognition, which differed from the mere effect of contextual information: Whereas facial expressions were identical in both conditions, the direction of the gaze of the contextual face influenced emotion recognition. Social appraisal facilitated the recognition of anger, happiness, and fear when the contextual face expressed the same emotion. This facilitation was stronger than the mere contextual effect. Social appraisal also allowed better recognition of fear when the contextual face expressed anger and better recognition of anger when the contextual face expressed fear. 2012 APA, all rights reserved

Research of Face Recognition with Fisher Linear Discriminant

NASA Astrophysics Data System (ADS)

Rahim, R.; Afriliansyah, T.; Winata, H.; Nofriansyah, D.; Ratnadewi; Aryza, S.

2018-01-01

Face identification systems are developing rapidly, and these developments drive the advancement of biometric-based identification systems that have high accuracy. However, to develop a good face recognition system and to have high accuracy is something that’s hard to find. Human faces have diverse expressions and attribute changes such as eyeglasses, mustache, beard and others. Fisher Linear Discriminant (FLD) is a class-specific method that distinguishes facial image images into classes and also creates distance between classes and intra classes so as to produce better classification.

Linkage of Recognition and Replication Functions by Assembling Combinatorial Antibody Fab Libraries Along Phage Surfaces

NASA Astrophysics Data System (ADS)

Kang, Angray S.; Barbas, Carlos F.; Janda, Kim D.; Benkovic, Stephen J.; Lerner, Richard A.

1991-05-01

We describe a method based on a phagemid vector with helper phage rescue for the construction and rapid analysis of combinatorial antibody Fab libraries. This approach should allow the generation and selection of many monoclonal antibodies. Antibody genes are expressed in concert with phage morphogenesis, thereby allowing incorporation of functional Fab molecules along the surface of filamentous phage. The power of the method depends upon the linkage of recognition and replication functions and is not limited to antibody molecules.

3 CFR 8380 - Proclamation 8380 of May 14, 2009. Armed Forces Day, 2009

Code of Federal Regulations, 2010 CFR

2010-01-01

... people.” Based on this perspective, I call upon all Americans to learn more about, and express gratitude... the call to service deserve recognition and gratitude. They have endured the most difficult of...

Emotional face processing deficit in schizophrenia: A replication study in a South African Xhosa population.

PubMed

Leppänen, J M; Niehaus, D J H; Koen, L; Du Toit, E; Schoeman, R; Emsley, R

2006-06-01

Schizophrenia is associated with a deficit in the recognition of negative emotions from facial expressions. The present study examined the universality of this finding by studying facial expression recognition in African Xhosa population. Forty-four Xhosa patients with schizophrenia and forty healthy controls were tested with a computerized task requiring rapid perceptual discrimination of matched positive (i.e. happy), negative (i.e. angry), and neutral faces. Patients were equally accurate as controls in recognizing happy faces but showed a marked impairment in recognition of angry faces. The impairment was particularly pronounced for high-intensity (open-mouth) angry faces. Patients also exhibited more false happy and angry responses to neutral faces than controls. No correlation between level of education or illness duration and emotion recognition was found but the deficit in the recognition of negative emotions was more pronounced in familial compared to non-familial cases of schizophrenia. These findings suggest that the deficit in the recognition of negative facial expressions may constitute a universal neurocognitive marker of schizophrenia.

Age, gender, and puberty influence the development of facial emotion recognition.

PubMed

Lawrence, Kate; Campbell, Ruth; Skuse, David

2015-01-01

Our ability to differentiate between simple facial expressions of emotion develops between infancy and early adulthood, yet few studies have explored the developmental trajectory of emotion recognition using a single methodology across a wide age-range. We investigated the development of emotion recognition abilities through childhood and adolescence, testing the hypothesis that children's ability to recognize simple emotions is modulated by chronological age, pubertal stage and gender. In order to establish norms, we assessed 478 children aged 6-16 years, using the Ekman-Friesen Pictures of Facial Affect. We then modeled these cross-sectional data in terms of competence in accurate recognition of the six emotions studied, when the positive correlation between emotion recognition and IQ was controlled. Significant linear trends were seen in children's ability to recognize facial expressions of happiness, surprise, fear, and disgust; there was improvement with increasing age. In contrast, for sad and angry expressions there is little or no change in accuracy over the age range 6-16 years; near-adult levels of competence are established by middle-childhood. In a sampled subset, pubertal status influenced the ability to recognize facial expressions of disgust and anger; there was an increase in competence from mid to late puberty, which occurred independently of age. A small female advantage was found in the recognition of some facial expressions. The normative data provided in this study will aid clinicians and researchers in assessing the emotion recognition abilities of children and will facilitate the identification of abnormalities in a skill that is often impaired in neurodevelopmental disorders. If emotion recognition abilities are a good model with which to understand adolescent development, then these results could have implications for the education, mental health provision and legal treatment of teenagers.

Age, gender, and puberty influence the development of facial emotion recognition

PubMed Central

Lawrence, Kate; Campbell, Ruth; Skuse, David

2015-01-01

Our ability to differentiate between simple facial expressions of emotion develops between infancy and early adulthood, yet few studies have explored the developmental trajectory of emotion recognition using a single methodology across a wide age-range. We investigated the development of emotion recognition abilities through childhood and adolescence, testing the hypothesis that children’s ability to recognize simple emotions is modulated by chronological age, pubertal stage and gender. In order to establish norms, we assessed 478 children aged 6–16 years, using the Ekman-Friesen Pictures of Facial Affect. We then modeled these cross-sectional data in terms of competence in accurate recognition of the six emotions studied, when the positive correlation between emotion recognition and IQ was controlled. Significant linear trends were seen in children’s ability to recognize facial expressions of happiness, surprise, fear, and disgust; there was improvement with increasing age. In contrast, for sad and angry expressions there is little or no change in accuracy over the age range 6–16 years; near-adult levels of competence are established by middle-childhood. In a sampled subset, pubertal status influenced the ability to recognize facial expressions of disgust and anger; there was an increase in competence from mid to late puberty, which occurred independently of age. A small female advantage was found in the recognition of some facial expressions. The normative data provided in this study will aid clinicians and researchers in assessing the emotion recognition abilities of children and will facilitate the identification of abnormalities in a skill that is often impaired in neurodevelopmental disorders. If emotion recognition abilities are a good model with which to understand adolescent development, then these results could have implications for the education, mental health provision and legal treatment of teenagers. PMID:26136697

Processing environmental stimuli in paranoid schizophrenia: recognizing facial emotions and performing executive functions.

PubMed

Yu, Shao Hua; Zhu, Jun Peng; Xu, You; Zheng, Lei Lei; Chai, Hao; He, Wei; Liu, Wei Bo; Li, Hui Chun; Wang, Wei

2012-12-01

To study the contribution of executive function to abnormal recognition of facial expressions of emotion in schizophrenia patients. Abnormal recognition of facial expressions of emotion was assayed according to Japanese and Caucasian facial expressions of emotion (JACFEE), Wisconsin card sorting test (WCST), positive and negative symptom scale, and Hamilton anxiety and depression scale, respectively, in 88 paranoid schizophrenia patients and 75 healthy volunteers. Patients scored higher on the Positive and Negative Symptom Scale and the Hamilton Anxiety and Depression Scales, displayed lower JACFEE recognition accuracies and poorer WCST performances. The JACFEE recognition accuracy of contempt and disgust was negatively correlated with the negative symptom scale score while the recognition accuracy of fear was positively with the positive symptom scale score and the recognition accuracy of surprise was negatively with the general psychopathology score in patients. Moreover, the WCST could predict the JACFEE recognition accuracy of contempt, disgust, and sadness in patients, and the perseverative errors negatively predicted the recognition accuracy of sadness in healthy volunteers. The JACFEE recognition accuracy of sadness could predict the WCST categories in paranoid schizophrenia patients. Recognition accuracy of social-/moral emotions, such as contempt, disgust and sadness is related to the executive function in paranoid schizophrenia patients, especially when regarding sadness. Copyright © 2012 The Editorial Board of Biomedical and Environmental Sciences. Published by Elsevier B.V. All rights reserved.

Self-organized Evaluation of Dynamic Hand Gestures for Sign Language Recognition

NASA Astrophysics Data System (ADS)

Buciu, Ioan; Pitas, Ioannis

Two main theories exist with respect to face encoding and representation in the human visual system (HVS). The first one refers to the dense (holistic) representation of the face, where faces have "holon"-like appearance. The second one claims that a more appropriate face representation is given by a sparse code, where only a small fraction of the neural cells corresponding to face encoding is activated. Theoretical and experimental evidence suggest that the HVS performs face analysis (encoding, storing, face recognition, facial expression recognition) in a structured and hierarchical way, where both representations have their own contribution and goal. According to neuropsychological experiments, it seems that encoding for face recognition, relies on holistic image representation, while a sparse image representation is used for facial expression analysis and classification. From the computer vision perspective, the techniques developed for automatic face and facial expression recognition fall into the same two representation types. Like in Neuroscience, the techniques which perform better for face recognition yield a holistic image representation, while those techniques suitable for facial expression recognition use a sparse or local image representation. The proposed mathematical models of image formation and encoding try to simulate the efficient storing, organization and coding of data in the human cortex. This is equivalent with embedding constraints in the model design regarding dimensionality reduction, redundant information minimization, mutual information minimization, non-negativity constraints, class information, etc. The presented techniques are applied as a feature extraction step followed by a classification method, which also heavily influences the recognition results.

Multimedia Content Development as a Facial Expression Datasets for Recognition of Human Emotions

NASA Astrophysics Data System (ADS)

Mamonto, N. E.; Maulana, H.; Liliana, D. Y.; Basaruddin, T.

2018-02-01

Datasets that have been developed before contain facial expression from foreign people. The development of multimedia content aims to answer the problems experienced by the research team and other researchers who will conduct similar research. The method used in the development of multimedia content as facial expression datasets for human emotion recognition is the Villamil-Molina version of the multimedia development method. Multimedia content developed with 10 subjects or talents with each talent performing 3 shots with each capturing talent having to demonstrate 19 facial expressions. After the process of editing and rendering, tests are carried out with the conclusion that the multimedia content can be used as a facial expression dataset for recognition of human emotions.

Recognition of Facial Expressions and Prosodic Cues with Graded Emotional Intensities in Adults with Asperger Syndrome

ERIC Educational Resources Information Center

Doi, Hirokazu; Fujisawa, Takashi X.; Kanai, Chieko; Ohta, Haruhisa; Yokoi, Hideki; Iwanami, Akira; Kato, Nobumasa; Shinohara, Kazuyuki

2013-01-01

This study investigated the ability of adults with Asperger syndrome to recognize emotional categories of facial expressions and emotional prosodies with graded emotional intensities. The individuals with Asperger syndrome showed poorer recognition performance for angry and sad expressions from both facial and vocal information. The group…

Characterization of two porcine macrophage cell lines for the expression of pathogen-recognition receptors, defensins, cytokines, chemokines, and surface sialic acid

USDA-ARS?s Scientific Manuscript database

Macrophages express various pathogen-recognition receptors (PRRs) which recognize pathogen-associated molecular patterns (PAMPs) and activate genes responsible for host defense. The aim of this study was to characterize two porcine macrophage cell lines (Cdelta+ and Cdelta–) for the expression of P...

Stereotypes and prejudice affect the recognition of emotional body postures.

PubMed

Bijlstra, Gijsbert; Holland, Rob W; Dotsch, Ron; Wigboldus, Daniel H J

2018-03-26

Most research on emotion recognition focuses on facial expressions. However, people communicate emotional information through bodily cues as well. Prior research on facial expressions has demonstrated that emotion recognition is modulated by top-down processes. Here, we tested whether this top-down modulation generalizes to the recognition of emotions from body postures. We report three studies demonstrating that stereotypes and prejudice about men and women may affect how fast people classify various emotional body postures. Our results suggest that gender cues activate gender associations, which affect the recognition of emotions from body postures in a top-down fashion. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Slowing down Presentation of Facial Movements and Vocal Sounds Enhances Facial Expression Recognition and Induces Facial-Vocal Imitation in Children with Autism

ERIC Educational Resources Information Center

Tardif, Carole; Laine, France; Rodriguez, Melissa; Gepner, Bruno

2007-01-01

This study examined the effects of slowing down presentation of facial expressions and their corresponding vocal sounds on facial expression recognition and facial and/or vocal imitation in children with autism. Twelve autistic children and twenty-four normal control children were presented with emotional and non-emotional facial expressions on…

Pattern activation/recognition theory of mind

PubMed Central

du Castel, Bertrand

2015-01-01

In his 2012 book How to Create a Mind, Ray Kurzweil defines a “Pattern Recognition Theory of Mind” that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call “Pattern Activation/Recognition Theory of Mind.” While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation. PMID:26236228

Multi-Task Convolutional Neural Network for Pose-Invariant Face Recognition

NASA Astrophysics Data System (ADS)

Yin, Xi; Liu, Xiaoming

2018-02-01

This paper explores multi-task learning (MTL) for face recognition. We answer the questions of how and why MTL can improve the face recognition performance. First, we propose a multi-task Convolutional Neural Network (CNN) for face recognition where identity classification is the main task and pose, illumination, and expression estimations are the side tasks. Second, we develop a dynamic-weighting scheme to automatically assign the loss weight to each side task, which is a crucial problem in MTL. Third, we propose a pose-directed multi-task CNN by grouping different poses to learn pose-specific identity features, simultaneously across all poses. Last but not least, we propose an energy-based weight analysis method to explore how CNN-based MTL works. We observe that the side tasks serve as regularizations to disentangle the variations from the learnt identity features. Extensive experiments on the entire Multi-PIE dataset demonstrate the effectiveness of the proposed approach. To the best of our knowledge, this is the first work using all data in Multi-PIE for face recognition. Our approach is also applicable to in-the-wild datasets for pose-invariant face recognition and achieves comparable or better performance than state of the art on LFW, CFP, and IJB-A datasets.

Pattern activation/recognition theory of mind.

PubMed

du Castel, Bertrand

2015-01-01

In his 2012 book How to Create a Mind, Ray Kurzweil defines a "Pattern Recognition Theory of Mind" that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call "Pattern Activation/Recognition Theory of Mind." While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation.

The recognition of facial emotion expressions in Parkinson's disease.

PubMed

Assogna, Francesca; Pontieri, Francesco E; Caltagirone, Carlo; Spalletta, Gianfranco

2008-11-01

A limited number of studies in Parkinson's Disease (PD) suggest a disturbance of recognition of facial emotion expressions. In particular, disgust recognition impairment has been reported in unmedicated and medicated PD patients. However, the results are rather inconclusive in the definition of the degree and the selectivity of emotion recognition impairment, and an associated impairment of almost all basic facial emotions in PD is also described. Few studies have investigated the relationship with neuropsychiatric and neuropsychological symptoms with mainly negative results. This inconsistency may be due to many different problems, such as emotion assessment, perception deficit, cognitive impairment, behavioral symptoms, illness severity and antiparkinsonian therapy. Here we review the clinical characteristics and neural structures involved in the recognition of specific facial emotion expressions, and the plausible role of dopamine transmission and dopamine replacement therapy in these processes. It is clear that future studies should be directed to clarify all these issues.

Oxytocin, vasopressin and estrogen receptor gene expression in relation to social recognition in female mice.

PubMed

Clipperton-Allen, Amy E; Lee, Anna W; Reyes, Anny; Devidze, Nino; Phan, Anna; Pfaff, Donald W; Choleris, Elena

2012-02-28

Inter- and intra-species differences in social behavior and recognition-related hormones and receptors suggest that different distribution and/or expression patterns may relate to social recognition. We used qRT-PCR to investigate naturally occurring differences in expression of estrogen receptor-alpha (ERα), ER-beta (ERβ), progesterone receptor (PR), oxytocin (OT) and receptor, and vasopressin (AVP) and receptors in proestrous female mice. Following four 5 min exposures to the same two conspecifics, one was replaced with a novel mouse in the final trial (T5). Gene expression was examined in mice showing high (85-100%) and low (40-60%) social recognition scores (i.e., preferential novel mouse investigation in T5) in eight socially-relevant brain regions. Results supported OT and AVP involvement in social recognition, and suggest that in the medial preoptic area, increased OT and AVP mRNA, together with ERα and ERβ gene activation, relate to improved social recognition. Initial social investigation correlated with ERs, PR and OTR in the dorsolateral septum, suggesting that these receptors may modulate social interest without affecting social recognition. Finally, increased lateral amygdala gene activation in the LR mice may be associated with general learning impairments, while decreased lateral amygdala activity may indicate more efficient cognitive mechanisms in the HR mice. Copyright © 2011 Elsevier Inc. All rights reserved.

The right place at the right time: priming facial expressions with emotional face components in developmental visual agnosia.

PubMed

Aviezer, Hillel; Hassin, Ran R; Perry, Anat; Dudarev, Veronica; Bentin, Shlomo

2012-04-01

The current study examined the nature of deficits in emotion recognition from facial expressions in case LG, an individual with a rare form of developmental visual agnosia (DVA). LG presents with profoundly impaired recognition of facial expressions, yet the underlying nature of his deficit remains unknown. During typical face processing, normal sighted individuals extract information about expressed emotions from face regions with activity diagnostic for specific emotion categories. Given LG's impairment, we sought to shed light on his emotion perception by examining if priming facial expressions with diagnostic emotional face components would facilitate his recognition of the emotion expressed by the face. LG and control participants matched isolated face components with components appearing in a subsequently presented full-face and then categorized the face's emotion. Critically, the matched components were from regions which were diagnostic or non-diagnostic of the emotion portrayed by the full face. In experiment 1, when the full faces were briefly presented (150 ms), LG's performance was strongly influenced by the diagnosticity of the components: his emotion recognition was boosted within normal limits when diagnostic components were used and was obliterated when non-diagnostic components were used. By contrast, in experiment 2, when the face-exposure duration was extended (2000 ms), the beneficial effect of the diagnostic matching was diminished as was the detrimental effect of the non-diagnostic matching. These data highlight the impact of diagnostic facial features in normal expression recognition and suggest that impaired emotion recognition in DVA results from deficient visual integration across diagnostic face components. Copyright © 2012 Elsevier Ltd. All rights reserved.

Orienting to face expression during encoding improves men's recognition of own gender faces.

PubMed

Fulton, Erika K; Bulluck, Megan; Hertzog, Christopher

2015-10-01

It is unclear why women have superior episodic memory of faces, but the benefit may be partially the result of women engaging in superior processing of facial expressions. Therefore, we hypothesized that orienting instructions to attend to facial expression at encoding would significantly improve men's memory of faces and possibly reduce gender differences. We directed 203 college students (122 women) to study 120 faces under instructions to orient to either the person's gender or their emotional expression. They later took a recognition test of these faces by either judging whether they had previously studied the same person or that person with the exact same expression; the latter test evaluated recollection of specific facial details. Orienting to facial expressions during encoding significantly improved men's recognition of own-gender faces and eliminated the advantage that women had for male faces under gender orienting instructions. Although gender differences in spontaneous strategy use when orienting to faces cannot fully account for gender differences in face recognition, orienting men to facial expression during encoding is one way to significantly improve their episodic memory for male faces. Copyright © 2015 Elsevier B.V. All rights reserved.

In-the-wild facial expression recognition in extreme poses

NASA Astrophysics Data System (ADS)

Yang, Fei; Zhang, Qian; Zheng, Chi; Qiu, Guoping

2018-04-01

In the computer research area, facial expression recognition is a hot research problem. Recent years, the research has moved from the lab environment to in-the-wild circumstances. It is challenging, especially under extreme poses. But current expression detection systems are trying to avoid the pose effects and gain the general applicable ability. In this work, we solve the problem in the opposite approach. We consider the head poses and detect the expressions within special head poses. Our work includes two parts: detect the head pose and group it into one pre-defined head pose class; do facial expression recognize within each pose class. Our experiments show that the recognition results with pose class grouping are much better than that of direct recognition without considering poses. We combine the hand-crafted features, SIFT, LBP and geometric feature, with deep learning feature as the representation of the expressions. The handcrafted features are added into the deep learning framework along with the high level deep learning features. As a comparison, we implement SVM and random forest to as the prediction models. To train and test our methodology, we labeled the face dataset with 6 basic expressions.

Gabor-based kernel PCA with fractional power polynomial models for face recognition.

PubMed

Liu, Chengjun

2004-05-01

This paper presents a novel Gabor-based kernel Principal Component Analysis (PCA) method by integrating the Gabor wavelet representation of face images and the kernel PCA method for face recognition. Gabor wavelets first derive desirable facial features characterized by spatial frequency, spatial locality, and orientation selectivity to cope with the variations due to illumination and facial expression changes. The kernel PCA method is then extended to include fractional power polynomial models for enhanced face recognition performance. A fractional power polynomial, however, does not necessarily define a kernel function, as it might not define a positive semidefinite Gram matrix. Note that the sigmoid kernels, one of the three classes of widely used kernel functions (polynomial kernels, Gaussian kernels, and sigmoid kernels), do not actually define a positive semidefinite Gram matrix either. Nevertheless, the sigmoid kernels have been successfully used in practice, such as in building support vector machines. In order to derive real kernel PCA features, we apply only those kernel PCA eigenvectors that are associated with positive eigenvalues. The feasibility of the Gabor-based kernel PCA method with fractional power polynomial models has been successfully tested on both frontal and pose-angled face recognition, using two data sets from the FERET database and the CMU PIE database, respectively. The FERET data set contains 600 frontal face images of 200 subjects, while the PIE data set consists of 680 images across five poses (left and right profiles, left and right half profiles, and frontal view) with two different facial expressions (neutral and smiling) of 68 subjects. The effectiveness of the Gabor-based kernel PCA method with fractional power polynomial models is shown in terms of both absolute performance indices and comparative performance against the PCA method, the kernel PCA method with polynomial kernels, the kernel PCA method with fractional power polynomial models, the Gabor wavelet-based PCA method, and the Gabor wavelet-based kernel PCA method with polynomial kernels.

Recognition of Emotion from Facial Expressions with Direct or Averted Eye Gaze and Varying Expression Intensities in Children with Autism Disorder and Typically Developing Children

PubMed Central

Tell, Dina; Davidson, Denise; Camras, Linda A.

2014-01-01

Eye gaze direction and expression intensity effects on emotion recognition in children with autism disorder and typically developing children were investigated. Children with autism disorder and typically developing children identified happy and angry expressions equally well. Children with autism disorder, however, were less accurate in identifying fear expressions across intensities and eye gaze directions. Children with autism disorder rated expressions with direct eyes, and 50% expressions, as more intense than typically developing children. A trend was also found for sad expressions, as children with autism disorder were less accurate in recognizing sadness at 100% intensity with direct eyes than typically developing children. Although the present research showed that children with autism disorder are sensitive to eye gaze direction, impairments in the recognition of fear, and possibly sadness, exist. Furthermore, children with autism disorder and typically developing children perceive the intensity of emotional expressions differently. PMID:24804098

Emotion Recognition in Frontotemporal Dementia and Alzheimer's Disease: A New Film-Based Assessment

PubMed Central

Goodkind, Madeleine S.; Sturm, Virginia E.; Ascher, Elizabeth A.; Shdo, Suzanne M.; Miller, Bruce L.; Rankin, Katherine P.; Levenson, Robert W.

2015-01-01

Deficits in recognizing others' emotions are reported in many psychiatric and neurological disorders, including autism, schizophrenia, behavioral variant frontotemporal dementia (bvFTD) and Alzheimer's disease (AD). Most previous emotion recognition studies have required participants to identify emotional expressions in photographs. This type of assessment differs from real-world emotion recognition in important ways: Images are static rather than dynamic, include only 1 modality of emotional information (i.e., visual information), and are presented absent a social context. Additionally, existing emotion recognition batteries typically include multiple negative emotions, but only 1 positive emotion (i.e., happiness) and no self-conscious emotions (e.g., embarrassment). We present initial results using a new task for assessing emotion recognition that was developed to address these limitations. In this task, respondents view a series of short film clips and are asked to identify the main characters' emotions. The task assesses multiple negative, positive, and self-conscious emotions based on information that is multimodal, dynamic, and socially embedded. We evaluate this approach in a sample of patients with bvFTD, AD, and normal controls. Results indicate that patients with bvFTD have emotion recognition deficits in all 3 categories of emotion compared to the other groups. These deficits were especially pronounced for negative and self-conscious emotions. Emotion recognition in this sample of patients with AD was indistinguishable from controls. These findings underscore the utility of this approach to assessing emotion recognition and suggest that previous findings that recognition of positive emotion was preserved in dementia patients may have resulted from the limited sampling of positive emotion in traditional tests. PMID:26010574

[Neural mechanisms of facial recognition].

PubMed

Nagai, Chiyoko

2007-01-01

We review recent researches in neural mechanisms of facial recognition in the light of three aspects: facial discrimination and identification, recognition of facial expressions, and face perception in itself. First, it has been demonstrated that the fusiform gyrus has a main role of facial discrimination and identification. However, whether the FFA (fusiform face area) is really a special area for facial processing or not is controversial; some researchers insist that the FFA is related to 'becoming an expert' for some kinds of visual objects, including faces. Neural mechanisms of prosopagnosia would be deeply concerned to this issue. Second, the amygdala seems to be very concerned to recognition of facial expressions, especially fear. The amygdala, connected with the superior temporal sulcus and the orbitofrontal cortex, appears to operate the cortical function. The amygdala and the superior temporal sulcus are related to gaze recognition, which explains why a patient with bilateral amygdala damage could not recognize only a fear expression; the information from eyes is necessary for fear recognition. Finally, even a newborn infant can recognize a face as a face, which is congruent with the innate hypothesis of facial recognition. Some researchers speculate that the neural basis of such face perception is the subcortical network, comprised of the amygdala, the superior colliculus, and the pulvinar. This network would relate to covert recognition that prosopagnosic patients have.

Multivariate Pattern Classification of Facial Expressions Based on Large-Scale Functional Connectivity.

PubMed

Liang, Yin; Liu, Baolin; Li, Xianglin; Wang, Peiyuan

2018-01-01

It is an important question how human beings achieve efficient recognition of others' facial expressions in cognitive neuroscience, and it has been identified that specific cortical regions show preferential activation to facial expressions in previous studies. However, the potential contributions of the connectivity patterns in the processing of facial expressions remained unclear. The present functional magnetic resonance imaging (fMRI) study explored whether facial expressions could be decoded from the functional connectivity (FC) patterns using multivariate pattern analysis combined with machine learning algorithms (fcMVPA). We employed a block design experiment and collected neural activities while participants viewed facial expressions of six basic emotions (anger, disgust, fear, joy, sadness, and surprise). Both static and dynamic expression stimuli were included in our study. A behavioral experiment after scanning confirmed the validity of the facial stimuli presented during the fMRI experiment with classification accuracies and emotional intensities. We obtained whole-brain FC patterns for each facial expression and found that both static and dynamic facial expressions could be successfully decoded from the FC patterns. Moreover, we identified the expression-discriminative networks for the static and dynamic facial expressions, which span beyond the conventional face-selective areas. Overall, these results reveal that large-scale FC patterns may also contain rich expression information to accurately decode facial expressions, suggesting a novel mechanism, which includes general interactions between distributed brain regions, and that contributes to the human facial expression recognition.

Multivariate Pattern Classification of Facial Expressions Based on Large-Scale Functional Connectivity

PubMed Central

Liang, Yin; Liu, Baolin; Li, Xianglin; Wang, Peiyuan

2018-01-01

It is an important question how human beings achieve efficient recognition of others’ facial expressions in cognitive neuroscience, and it has been identified that specific cortical regions show preferential activation to facial expressions in previous studies. However, the potential contributions of the connectivity patterns in the processing of facial expressions remained unclear. The present functional magnetic resonance imaging (fMRI) study explored whether facial expressions could be decoded from the functional connectivity (FC) patterns using multivariate pattern analysis combined with machine learning algorithms (fcMVPA). We employed a block design experiment and collected neural activities while participants viewed facial expressions of six basic emotions (anger, disgust, fear, joy, sadness, and surprise). Both static and dynamic expression stimuli were included in our study. A behavioral experiment after scanning confirmed the validity of the facial stimuli presented during the fMRI experiment with classification accuracies and emotional intensities. We obtained whole-brain FC patterns for each facial expression and found that both static and dynamic facial expressions could be successfully decoded from the FC patterns. Moreover, we identified the expression-discriminative networks for the static and dynamic facial expressions, which span beyond the conventional face-selective areas. Overall, these results reveal that large-scale FC patterns may also contain rich expression information to accurately decode facial expressions, suggesting a novel mechanism, which includes general interactions between distributed brain regions, and that contributes to the human facial expression recognition. PMID:29615882

Reduced Recognition of Dynamic Facial Emotional Expressions and Emotion-Specific Response Bias in Children with an Autism Spectrum Disorder

ERIC Educational Resources Information Center

Evers, Kris; Steyaert, Jean; Noens, Ilse; Wagemans, Johan

2015-01-01

Emotion labelling was evaluated in two matched samples of 6-14-year old children with and without an autism spectrum disorder (ASD; N = 45 and N = 50, resp.), using six dynamic facial expressions. The Emotion Recognition Task proved to be valuable demonstrating subtle emotion recognition difficulties in ASD, as we showed a general poorer emotion…

Exploring Cultural Differences in the Recognition of the Self-Conscious Emotions.

PubMed

Chung, Joanne M; Robins, Richard W

2015-01-01

Recent research suggests that the self-conscious emotions of embarrassment, shame, and pride have distinct, nonverbal expressions that can be recognized in the United States at above-chance levels. However, few studies have examined the recognition of these emotions in other cultures, and little research has been conducted in Asia. Consequently the cross-cultural generalizability of self-conscious emotions has not been firmly established. Additionally, there is no research that examines cultural variability in the recognition of the self-conscious emotions. Cultural values and exposure to Western culture have been identified as contributors to variability in recognition rates for the basic emotions; we sought to examine this for the self-conscious emotions using the University of California, Davis Set of Emotion Expressions (UCDSEE). The present research examined recognition of the self-conscious emotion expressions in South Korean college students and found that recognition rates were very high for pride, low but above chance for shame, and near zero for embarrassment. To examine what might be underlying the recognition rates we found in South Korea, recognition of self-conscious emotions and several cultural values were examined in a U.S. college student sample of European Americans, Asian Americans, and Asian-born individuals. Emotion recognition rates were generally similar between the European Americans and Asian Americans, and higher than emotion recognition rates for Asian-born individuals. These differences were not explained by cultural values in an interpretable manner, suggesting that exposure to Western culture is a more important mediator than values.

Exploring Cultural Differences in the Recognition of the Self-Conscious Emotions

PubMed Central

Chung, Joanne M.; Robins, Richard W.

2015-01-01

Recent research suggests that the self-conscious emotions of embarrassment, shame, and pride have distinct, nonverbal expressions that can be recognized in the United States at above-chance levels. However, few studies have examined the recognition of these emotions in other cultures, and little research has been conducted in Asia. Consequently the cross-cultural generalizability of self-conscious emotions has not been firmly established. Additionally, there is no research that examines cultural variability in the recognition of the self-conscious emotions. Cultural values and exposure to Western culture have been identified as contributors to variability in recognition rates for the basic emotions; we sought to examine this for the self-conscious emotions using the University of California, Davis Set of Emotion Expressions (UCDSEE). The present research examined recognition of the self-conscious emotion expressions in South Korean college students and found that recognition rates were very high for pride, low but above chance for shame, and near zero for embarrassment. To examine what might be underlying the recognition rates we found in South Korea, recognition of self-conscious emotions and several cultural values were examined in a U.S. college student sample of European Americans, Asian Americans, and Asian-born individuals. Emotion recognition rates were generally similar between the European Americans and Asian Americans, and higher than emotion recognition rates for Asian-born individuals. These differences were not explained by cultural values in an interpretable manner, suggesting that exposure to Western culture is a more important mediator than values. PMID:26309215

Emotion recognition in fathers and mothers at high-risk for child physical abuse.

PubMed

Asla, Nagore; de Paúl, Joaquín; Pérez-Albéniz, Alicia

2011-09-01

The present study was designed to determine whether parents at high risk for physical child abuse, in comparison with parents at low risk, show deficits in emotion recognition, as well as to examine the moderator effect of gender and stress on the relationship between risk for physical child abuse and emotion recognition. Based on their scores on the Abuse Scale of the CAP Inventory (Milner, 1986), 64 parents at high risk (24 fathers and 40 mothers) and 80 parents at low risk (40 fathers and 40 mothers) for physical child abuse were selected. The Subtle Expression Training Tool/Micro Expression Training Tool (Ekman, 2004a, 2004b) and the Diagnostic Analysis of Nonverbal Accuracy II (Nowicki & Carton, 1993) were used to assess emotion recognition. As expected, parents at high risk, in contrast to parents at low risk, showed deficits in emotion recognition. However, differences between high- and low-risk participants were observed only for fathers, but not for mothers. Whereas fathers at high risk for physical child abuse made more errors than mothers at high risk, no differences between mothers at low risk and fathers at low risk were found. No interaction between stress, gender, and risk status was observed for errors in emotion recognition. The present findings, if confirmed with physical abusers, could be helpful to further our understanding of deficits in processing information of physically abusive parents and to develop treatment strategies specifically focused on emotion recognition. Moreover, if gender differences can be confirmed, the findings could be helpful to develop specific treatment programs for abusive fathers. Copyright © 2011 Elsevier Ltd. All rights reserved.

Genomic amplification of the human DHFR/MSH3 locus remodels mismatch recognition and repair activities.

PubMed

Drummond, J T

1999-01-01

Mismatch recognition in human cells is mediated by two heterodimers, MutS alpha and MutS beta. MutS alpha appears to shoulder primary responsibility for mismatch correction during replication, based on its relative abundance and ability to recognize a broad spectrum of base-base and base-insertion mismatches. Because MutS alpha and MutS beta share a common component, MSH2, conditions that influence the expression or degradation of MSH3 or MSH6 can redistribute the profile of mismatch recognition and repair. MSH3 is linked by a shared promoter with DHFR, connecting two pathways with key roles in DNA metabolism. In a classic example of gene amplification, the DHFR (and MSH3) locus can become amplified to several hundred copies in the presence of methotrexate. Under these conditions, MutS beta forms at the expense of MutS alpha, and the mutation rate in these tumor cells rises more than 100-fold. The implications for cancer chemotherapy include a potential increase in mutability when tumors are treated with methotrexate, which could increase the frequency of subsequent mutations that influence the tumor's drug sensitivity or aggressiveness. Because processing certain types of DNA damage by the mismatch repair pathway has also been implicated in tumor sensitivity to agents such as cisplatin, changes in expression at the DHFR/MSH3 locus may have further relevance to the outcome of multi-drug treatment regimens.

The automaticity of emotion recognition.

PubMed

Tracy, Jessica L; Robins, Richard W

2008-02-01

Evolutionary accounts of emotion typically assume that humans evolved to quickly and efficiently recognize emotion expressions because these expressions convey fitness-enhancing messages. The present research tested this assumption in 2 studies. Specifically, the authors examined (a) how quickly perceivers could recognize expressions of anger, contempt, disgust, embarrassment, fear, happiness, pride, sadness, shame, and surprise; (b) whether accuracy is improved when perceivers deliberate about each expression's meaning (vs. respond as quickly as possible); and (c) whether accurate recognition can occur under cognitive load. Across both studies, perceivers quickly and efficiently (i.e., under cognitive load) recognized most emotion expressions, including the self-conscious emotions of pride, embarrassment, and shame. Deliberation improved accuracy in some cases, but these improvements were relatively small. Discussion focuses on the implications of these findings for the cognitive processes underlying emotion recognition.

Fashioning the Face: Sensorimotor Simulation Contributes to Facial Expression Recognition.

PubMed

Wood, Adrienne; Rychlowska, Magdalena; Korb, Sebastian; Niedenthal, Paula

2016-03-01

When we observe a facial expression of emotion, we often mimic it. This automatic mimicry reflects underlying sensorimotor simulation that supports accurate emotion recognition. Why this is so is becoming more obvious: emotions are patterns of expressive, behavioral, physiological, and subjective feeling responses. Activation of one component can therefore automatically activate other components. When people simulate a perceived facial expression, they partially activate the corresponding emotional state in themselves, which provides a basis for inferring the underlying emotion of the expresser. We integrate recent evidence in favor of a role for sensorimotor simulation in emotion recognition. We then connect this account to a domain-general understanding of how sensory information from multiple modalities is integrated to generate perceptual predictions in the brain. Copyright © 2016 Elsevier Ltd. All rights reserved.

Effects of facial emotion recognition remediation on visual scanning of novel face stimuli.

PubMed

Marsh, Pamela J; Luckett, Gemma; Russell, Tamara; Coltheart, Max; Green, Melissa J

2012-11-01

Previous research shows that emotion recognition in schizophrenia can be improved with targeted remediation that draws attention to important facial features (eyes, nose, mouth). Moreover, the effects of training have been shown to last for up to one month after training. The aim of this study was to investigate whether improved emotion recognition of novel faces is associated with concomitant changes in visual scanning of these same novel facial expressions. Thirty-nine participants with schizophrenia received emotion recognition training using Ekman's Micro-Expression Training Tool (METT), with emotion recognition and visual scanpath (VSP) recordings to face stimuli collected simultaneously. Baseline ratings of interpersonal and cognitive functioning were also collected from all participants. Post-METT training, participants showed changes in foveal attention to the features of facial expressions of emotion not used in METT training, which were generally consistent with the information about important features from the METT. In particular, there were changes in how participants looked at the features of facial expressions of emotion surprise, disgust, fear, happiness, and neutral, demonstrating that improved emotion recognition is paralleled by changes in the way participants with schizophrenia viewed novel facial expressions of emotion. However, there were overall decreases in foveal attention to sad and neutral faces that indicate more intensive instruction might be needed for these faces during training. Most importantly, the evidence shows that participant gender may affect training outcomes. Copyright © 2012 Elsevier B.V. All rights reserved.

Using Facial Recognition Technology in the Exploration of Student Responses to Conceptual Conflict Phenomenon

ERIC Educational Resources Information Center

Liaw, Hongming Leonard; Chiu, Mei-Hung; Chou, Chin-Cheng

2014-01-01

It has been shown that facial expression states of learners are related to their learning. As part of a continuing research project, the current study delved further for a more detailed description of the relation between facial microexpression state (FMES) changes and learning in conceptual conflict-based instructions. Based on the data gathered…

The Chinese Facial Emotion Recognition Database (CFERD): a computer-generated 3-D paradigm to measure the recognition of facial emotional expressions at different intensities.

PubMed

Huang, Charles Lung-Cheng; Hsiao, Sigmund; Hwu, Hai-Gwo; Howng, Shen-Long

2012-12-30

The Chinese Facial Emotion Recognition Database (CFERD), a computer-generated three-dimensional (3D) paradigm, was developed to measure the recognition of facial emotional expressions at different intensities. The stimuli consisted of 3D colour photographic images of six basic facial emotional expressions (happiness, sadness, disgust, fear, anger and surprise) and neutral faces of the Chinese. The purpose of the present study is to describe the development and validation of CFERD with nonclinical healthy participants (N=100; 50 men; age ranging between 18 and 50 years), and to generate normative data set. The results showed that the sensitivity index d' [d'=Z(hit rate)-Z(false alarm rate), where function Z(p), p∈[0,1

Astrocytic expression of HIV-1 Nef impairs spatial and recognition memory

PubMed Central

Chompre, Gladys; Cruz, Emmanuel; Maldonado, Lucianette; Rivera-Amill, Vanessa; Porter, James T.; Noel, Richard J.

2012-01-01

Despite the widespread use of antiretroviral therapy that effectively limits viral replication, memory impairment remains a dilemma for HIV infected people. In the CNS, HIV infection of astrocytes leads to the production of the HIV-1 Nef protein without viral replication. Post mortem studies have found Nef expression in hippocampal astrocytes of people with HIV associated dementia suggesting that astrocytic Nef may contribute to HIV associated cognitive impairment even when viral replication is suppressed. To test whether astrocytic expression of Nef is sufficient to induce cognitive deficits, we examined the effect of implanting primary rat astrocytes expressing Nef into the hippocampus on spatial and recognition memory. Rats implanted unilaterally with astrocytes expressing Nef showed impaired novel location and novel object recognition in comparison with controls implanted with astrocytes expressing green fluorescent protein (GFP). This impairment was correlated with an increase in chemokine ligand 2 (CCL2) expression and the infiltration of peripheral macrophages into the hippocampus at the site of injection. Furthermore, the Nef exposed rats exhibited a bilateral loss of CA3 neurons. These results suggest that Nef protein expressed by the implanted astrocytes activates the immune system leading to neuronal damage and spatial and recognition memory deficits. Therefore, the continued expression of Nef by astrocytes in the absence of viral replication has the potential to contribute to HIV associated cognitive impairment. PMID:22926191

[Advantages and Application Prospects of Deep Learning in Image Recognition and Bone Age Assessment].

PubMed

Hu, T H; Wan, L; Liu, T A; Wang, M W; Chen, T; Wang, Y H

2017-12-01

Deep learning and neural network models have been new research directions and hot issues in the fields of machine learning and artificial intelligence in recent years. Deep learning has made a breakthrough in the applications of image and speech recognitions, and also has been extensively used in the fields of face recognition and information retrieval because of its special superiority. Bone X-ray images express different variations in black-white-gray gradations, which have image features of black and white contrasts and level differences. Based on these advantages of deep learning in image recognition, we combine it with the research of bone age assessment to provide basic datum for constructing a forensic automatic system of bone age assessment. This paper reviews the basic concept and network architectures of deep learning, and describes its recent research progress on image recognition in different research fields at home and abroad, and explores its advantages and application prospects in bone age assessment. Copyright© by the Editorial Department of Journal of Forensic Medicine.

Hyaluronan functionalizing QDs as turn-on fluorescent probe for targeted recognition CD44 receptor

NASA Astrophysics Data System (ADS)

Zhou, Shang; Huo, Danqun; Hou, Changjun; Yang, Mei; Fa, Huanbao

2017-09-01

The recognition of tumor markers in living cancer cells has attracted increasing interest. In the present study, the turn-on fluorescence probe was designed based on the fluorescence of thiolated chitosan-coated CdTe QDs (CdTe/TCS QDs) quenched by hyaluronan, which could provide the low background signal for sensitive cellular imaging. This system is expected to offer specific recognition of CD44 receptor over other substances owing to the specific affinity of hyaluronan and CD44 receptor ( 8-9 kcal/mol). The probe is stable in aqueous and has little toxicity to living cells; thus, it can be utilized for targeted cancer cell imaging. The living lung cancer cell imaging experiments further demonstrate its value in recognizing cell-surface CD44 receptor with turn-on mode. In addition, the probe can be used to recognize and differentiate the subtypes of lung cancer cells based on the difference of CD44 expression on the surface of lung cancer cells. And, the western blot test further confirmed that the expression level of the CD44 receptor in lung cancer cells is different. Therefore, this probe may be potentially applied in recognizing lung cancer cells with higher contrast and sensitivity and provide new tools for cancer prognosis and therapy. [Figure not available: see fulltext.

Individual differences in the recognition of facial expressions: an event-related potentials study.

PubMed

Tamamiya, Yoshiyuki; Hiraki, Kazuo

2013-01-01

Previous studies have shown that early posterior components of event-related potentials (ERPs) are modulated by facial expressions. The goal of the current study was to investigate individual differences in the recognition of facial expressions by examining the relationship between ERP components and the discrimination of facial expressions. Pictures of 3 facial expressions (angry, happy, and neutral) were presented to 36 young adults during ERP recording. Participants were asked to respond with a button press as soon as they recognized the expression depicted. A multiple regression analysis, where ERP components were set as predictor variables, assessed hits and reaction times in response to the facial expressions as dependent variables. The N170 amplitudes significantly predicted for accuracy of angry and happy expressions, and the N170 latencies were predictive for accuracy of neutral expressions. The P2 amplitudes significantly predicted reaction time. The P2 latencies significantly predicted reaction times only for neutral faces. These results suggest that individual differences in the recognition of facial expressions emerge from early components in visual processing.

Recognition and Posing of Emotional Expressions by Abused Children and Their Mothers.

ERIC Educational Resources Information Center

Camras, Linda A.; And Others

1988-01-01

A total of 20 abused and 20 nonabused pairs of children of three-seven years and their mothers participated in a facial expression posing task and a facial expression recognition task. Findings suggest that abused children may not observe as often as nonabused children do the easily interpreted voluntary displays of emotion by their mothers. (RH)

Positive, but Not Negative, Facial Expressions Facilitate 3-Month-Olds' Recognition of an Individual Face

ERIC Educational Resources Information Center

Brenna, Viola; Proietti, Valentina; Montirosso, Rosario; Turati, Chiara

2013-01-01

The current study examined whether and how the presence of a positive or a negative emotional expression may affect the face recognition process at 3 months of age. Using a familiarization procedure, Experiment 1 demonstrated that positive (i.e., happiness), but not negative (i.e., fear and anger) facial expressions facilitate infants' ability to…

Automatic integration of social information in emotion recognition.

PubMed

Mumenthaler, Christian; Sander, David

2015-04-01

This study investigated the automaticity of the influence of social inference on emotion recognition. Participants were asked to recognize dynamic facial expressions of emotion (fear or anger in Experiment 1 and blends of fear and surprise or of anger and disgust in Experiment 2) in a target face presented at the center of a screen while a subliminal contextual face appearing in the periphery expressed an emotion (fear or anger) or not (neutral) and either looked at the target face or not. Results of Experiment 1 revealed that recognition of the target emotion of fear was improved when a subliminal angry contextual face gazed toward-rather than away from-the fearful face. We replicated this effect in Experiment 2, in which facial expression blends of fear and surprise were more often and more rapidly categorized as expressing fear when the subliminal contextual face expressed anger and gazed toward-rather than away from-the target face. With the contextual face appearing for 30 ms in total, including only 10 ms of emotion expression, and being immediately masked, our data provide the first evidence that social influence on emotion recognition can occur automatically. (c) 2015 APA, all rights reserved).

Effect of Acting Experience on Emotion Expression and Recognition in Voice: Non-Actors Provide Better Stimuli than Expected.

PubMed

Jürgens, Rebecca; Grass, Annika; Drolet, Matthis; Fischer, Julia

Both in the performative arts and in emotion research, professional actors are assumed to be capable of delivering emotions comparable to spontaneous emotional expressions. This study examines the effects of acting training on vocal emotion depiction and recognition. We predicted that professional actors express emotions in a more realistic fashion than non-professional actors. However, professional acting training may lead to a particular speech pattern; this might account for vocal expressions by actors that are less comparable to authentic samples than the ones by non-professional actors. We compared 80 emotional speech tokens from radio interviews with 80 re-enactments by professional and inexperienced actors, respectively. We analyzed recognition accuracies for emotion and authenticity ratings and compared the acoustic structure of the speech tokens. Both play-acted conditions yielded similar recognition accuracies and possessed more variable pitch contours than the spontaneous recordings. However, professional actors exhibited signs of different articulation patterns compared to non-trained speakers. Our results indicate that for emotion research, emotional expressions by professional actors are not better suited than those from non-actors.

Object-Place Recognition Learning Triggers Rapid Induction of Plasticity-Related Immediate Early Genes and Synaptic Proteins in the Rat Dentate Gyrus

PubMed Central

Soulé, Jonathan; Penke, Zsuzsa; Kanhema, Tambudzai; Alme, Maria Nordheim; Laroche, Serge; Bramham, Clive R.

2008-01-01

Long-term recognition memory requires protein synthesis, but little is known about the coordinate regulation of specific genes. Here, we examined expression of the plasticity-associated immediate early genes (Arc, Zif268, and Narp) in the dentate gyrus following long-term object-place recognition learning in rats. RT-PCR analysis from dentate gyrus tissue collected shortly after training did not reveal learning-specific changes in Arc mRNA expression. In situ hybridization and immunohistochemistry were therefore used to assess possible sparse effects on gene expression. Learning about objects increased the density of granule cells expressing Arc, and to a lesser extent Narp, specifically in the dorsal blade of the dentate gyrus, while Zif268 expression was elevated across both blades. Thus, object-place recognition triggers rapid, blade-specific upregulation of plasticity-associated immediate early genes. Furthermore, Western blot analysis of dentate gyrus homogenates demonstrated concomitant upregulation of three postsynaptic density proteins (Arc, PSD-95, and α-CaMKII) with key roles in long-term synaptic plasticity and long-term memory. PMID:19190776

Face recognition via sparse representation of SIFT feature on hexagonal-sampling image

NASA Astrophysics Data System (ADS)

Zhang, Daming; Zhang, Xueyong; Li, Lu; Liu, Huayong

2018-04-01

This paper investigates a face recognition approach based on Scale Invariant Feature Transform (SIFT) feature and sparse representation. The approach takes advantage of SIFT which is local feature other than holistic feature in classical Sparse Representation based Classification (SRC) algorithm and possesses strong robustness to expression, pose and illumination variations. Since hexagonal image has more inherit merits than square image to make recognition process more efficient, we extract SIFT keypoint in hexagonal-sampling image. Instead of matching SIFT feature, firstly the sparse representation of each SIFT keypoint is given according the constructed dictionary; secondly these sparse vectors are quantized according dictionary; finally each face image is represented by a histogram and these so-called Bag-of-Words vectors are classified by SVM. Due to use of local feature, the proposed method achieves better result even when the number of training sample is small. In the experiments, the proposed method gave higher face recognition rather than other methods in ORL and Yale B face databases; also, the effectiveness of the hexagonal-sampling in the proposed method is verified.

Super-resolution method for face recognition using nonlinear mappings on coherent features.

PubMed

Huang, Hua; He, Huiting

2011-01-01

Low-resolution (LR) of face images significantly decreases the performance of face recognition. To address this problem, we present a super-resolution method that uses nonlinear mappings to infer coherent features that favor higher recognition of the nearest neighbor (NN) classifiers for recognition of single LR face image. Canonical correlation analysis is applied to establish the coherent subspaces between the principal component analysis (PCA) based features of high-resolution (HR) and LR face images. Then, a nonlinear mapping between HR/LR features can be built by radial basis functions (RBFs) with lower regression errors in the coherent feature space than in the PCA feature space. Thus, we can compute super-resolved coherent features corresponding to an input LR image according to the trained RBF model efficiently and accurately. And, face identity can be obtained by feeding these super-resolved features to a simple NN classifier. Extensive experiments on the Facial Recognition Technology, University of Manchester Institute of Science and Technology, and Olivetti Research Laboratory databases show that the proposed method outperforms the state-of-the-art face recognition algorithms for single LR image in terms of both recognition rate and robustness to facial variations of pose and expression.

Web Video Event Recognition by Semantic Analysis From Ubiquitous Documents.

PubMed

Yu, Litao; Yang, Yang; Huang, Zi; Wang, Peng; Song, Jingkuan; Shen, Heng Tao

2016-12-01

In recent years, the task of event recognition from videos has attracted increasing interest in multimedia area. While most of the existing research was mainly focused on exploring visual cues to handle relatively small-granular events, it is difficult to directly analyze video content without any prior knowledge. Therefore, synthesizing both the visual and semantic analysis is a natural way for video event understanding. In this paper, we study the problem of Web video event recognition, where Web videos often describe large-granular events and carry limited textual information. Key challenges include how to accurately represent event semantics from incomplete textual information and how to effectively explore the correlation between visual and textual cues for video event understanding. We propose a novel framework to perform complex event recognition from Web videos. In order to compensate the insufficient expressive power of visual cues, we construct an event knowledge base by deeply mining semantic information from ubiquitous Web documents. This event knowledge base is capable of describing each event with comprehensive semantics. By utilizing this base, the textual cues for a video can be significantly enriched. Furthermore, we introduce a two-view adaptive regression model, which explores the intrinsic correlation between the visual and textual cues of the videos to learn reliable classifiers. Extensive experiments on two real-world video data sets show the effectiveness of our proposed framework and prove that the event knowledge base indeed helps improve the performance of Web video event recognition.

Multilevel analysis of facial expressions of emotion and script: self-report (arousal and valence) and psychophysiological correlates.

PubMed

Balconi, Michela; Vanutelli, Maria Elide; Finocchiaro, Roberta

2014-09-26

The paper explored emotion comprehension in children with regard to facial expression of emotion. The effect of valence and arousal evaluation, of context and of psychophysiological measures was monitored. Indeed subjective evaluation of valence (positive vs. negative) and arousal (high vs. low), and contextual (facial expression vs. facial expression and script) variables were supposed to modulate the psychophysiological responses. Self-report measures (in terms of correct recognition, arousal and valence attribution) and psychophysiological correlates (facial electromyography, EMG, skin conductance response, SCR, and heart rate, HR) were observed when children (N = 26; mean age = 8.75 y; range 6-11 y) looked at six facial expressions of emotions (happiness, anger, fear, sadness, surprise, and disgust) and six emotional scripts (contextualized facial expressions). The competencies about the recognition, the evaluation on valence and arousal was tested in concomitance with psychophysiological variations. Specifically, we tested for the congruence of these multiple measures. Log-linear analysis and repeated measure ANOVAs showed different representations across the subjects, as a function of emotion. Specifically, children' recognition and attribution were well developed for some emotions (such as anger, fear, surprise and happiness), whereas some other emotions (mainly disgust and sadness) were less clearly represented. SCR, HR and EMG measures were modulated by the evaluation based on valence and arousal, with increased psychophysiological values mainly in response to anger, fear and happiness. As shown by multiple regression analysis, a significant consonance was found between self-report measures and psychophysiological behavior, mainly for emotions rated as more arousing and negative in valence. The multilevel measures were discussed at light of dimensional attribution model.

Multilevel analysis of facial expressions of emotion and script: self-report (arousal and valence) and psychophysiological correlates

PubMed Central

2014-01-01

Background The paper explored emotion comprehension in children with regard to facial expression of emotion. The effect of valence and arousal evaluation, of context and of psychophysiological measures was monitored. Indeed subjective evaluation of valence (positive vs. negative) and arousal (high vs. low), and contextual (facial expression vs. facial expression and script) variables were supposed to modulate the psychophysiological responses. Methods Self-report measures (in terms of correct recognition, arousal and valence attribution) and psychophysiological correlates (facial electromyography, EMG, skin conductance response, SCR, and heart rate, HR) were observed when children (N = 26; mean age = 8.75 y; range 6-11 y) looked at six facial expressions of emotions (happiness, anger, fear, sadness, surprise, and disgust) and six emotional scripts (contextualized facial expressions). The competencies about the recognition, the evaluation on valence and arousal was tested in concomitance with psychophysiological variations. Specifically, we tested for the congruence of these multiple measures. Results Log-linear analysis and repeated measure ANOVAs showed different representations across the subjects, as a function of emotion. Specifically, children’ recognition and attribution were well developed for some emotions (such as anger, fear, surprise and happiness), whereas some other emotions (mainly disgust and sadness) were less clearly represented. SCR, HR and EMG measures were modulated by the evaluation based on valence and arousal, with increased psychophysiological values mainly in response to anger, fear and happiness. Conclusions As shown by multiple regression analysis, a significant consonance was found between self-report measures and psychophysiological behavior, mainly for emotions rated as more arousing and negative in valence. The multilevel measures were discussed at light of dimensional attribution model. PMID:25261242

Eye-movement assessment of the time course in facial expression recognition: Neurophysiological implications.

PubMed

Calvo, Manuel G; Nummenmaa, Lauri

2009-12-01

Happy, surprised, disgusted, angry, sad, fearful, and neutral faces were presented extrafoveally, with fixations on faces allowed or not. The faces were preceded by a cue word that designated the face to be saccaded in a two-alternative forced-choice discrimination task (2AFC; Experiments 1 and 2), or were followed by a probe word for recognition (Experiment 3). Eye tracking was used to decompose the recognition process into stages. Relative to the other expressions, happy faces (1) were identified faster (as early as 160 msec from stimulus onset) in extrafoveal vision, as revealed by shorter saccade latencies in the 2AFC task; (2) required less encoding effort, as indexed by shorter first fixations and dwell times; and (3) required less decision-making effort, as indicated by fewer refixations on the face after the recognition probe was presented. This reveals a happy-face identification advantage both prior to and during overt attentional processing. The results are discussed in relation to prior neurophysiological findings on latencies in facial expression recognition.

Food-Induced Emotional Resonance Improves Emotion Recognition.

PubMed

Pandolfi, Elisa; Sacripante, Riccardo; Cardini, Flavia

2016-01-01

The effect of food substances on emotional states has been widely investigated, showing, for example, that eating chocolate is able to reduce negative mood. Here, for the first time, we have shown that the consumption of specific food substances is not only able to induce particular emotional states, but more importantly, to facilitate recognition of corresponding emotional facial expressions in others. Participants were asked to perform an emotion recognition task before and after eating either a piece of chocolate or a small amount of fish sauce-which we expected to induce happiness or disgust, respectively. Our results showed that being in a specific emotional state improves recognition of the corresponding emotional facial expression. Indeed, eating chocolate improved recognition of happy faces, while disgusted expressions were more readily recognized after eating fish sauce. In line with the embodied account of emotion understanding, we suggest that people are better at inferring the emotional state of others when their own emotional state resonates with the observed one.

Food-Induced Emotional Resonance Improves Emotion Recognition

PubMed Central

Pandolfi, Elisa; Sacripante, Riccardo; Cardini, Flavia

2016-01-01

The effect of food substances on emotional states has been widely investigated, showing, for example, that eating chocolate is able to reduce negative mood. Here, for the first time, we have shown that the consumption of specific food substances is not only able to induce particular emotional states, but more importantly, to facilitate recognition of corresponding emotional facial expressions in others. Participants were asked to perform an emotion recognition task before and after eating either a piece of chocolate or a small amount of fish sauce—which we expected to induce happiness or disgust, respectively. Our results showed that being in a specific emotional state improves recognition of the corresponding emotional facial expression. Indeed, eating chocolate improved recognition of happy faces, while disgusted expressions were more readily recognized after eating fish sauce. In line with the embodied account of emotion understanding, we suggest that people are better at inferring the emotional state of others when their own emotional state resonates with the observed one. PMID:27973559

Effects of the duration of expressions on the recognition of microexpressions*

PubMed Central

Shen, Xun-bing; Wu, Qi; Fu, Xiao-lan

2012-01-01

Objective: The purpose of this study was to investigate the effects of the duration of expressions on the recognition of microexpressions, which are closely related to deception. Methods: In two experiments, participants were briefly (from 20 to 300 ms) shown one of six basic expressions and then were asked to identify the expression. Results: The results showed that the participants’ performance in recognition of microexpressions increased with the duration of the expressions, reaching a turning point at 200 ms before levelling off. The results also indicated that practice could improve the participants’ performance. Conclusions: The results of this study suggest that the proper upper limit of the duration of microexpressions might be around 1/5 of a second and confirmed that the ability to recognize microexpressions can be enhanced with practice. PMID:22374615

Dynamic texture recognition using local binary patterns with an application to facial expressions.

PubMed

Zhao, Guoying; Pietikäinen, Matti

2007-06-01

Dynamic texture (DT) is an extension of texture to the temporal domain. Description and recognition of DTs have attracted growing attention. In this paper, a novel approach for recognizing DTs is proposed and its simplifications and extensions to facial image analysis are also considered. First, the textures are modeled with volume local binary patterns (VLBP), which are an extension of the LBP operator widely used in ordinary texture analysis, combining motion and appearance. To make the approach computationally simple and easy to extend, only the co-occurrences of the local binary patterns on three orthogonal planes (LBP-TOP) are then considered. A block-based method is also proposed to deal with specific dynamic events such as facial expressions in which local information and its spatial locations should also be taken into account. In experiments with two DT databases, DynTex and Massachusetts Institute of Technology (MIT), both the VLBP and LBP-TOP clearly outperformed the earlier approaches. The proposed block-based method was evaluated with the Cohn-Kanade facial expression database with excellent results. The advantages of our approach include local processing, robustness to monotonic gray-scale changes, and simple computation.

Muecas: A Multi-Sensor Robotic Head for Affective Human Robot Interaction and Imitation

PubMed Central

Cid, Felipe; Moreno, Jose; Bustos, Pablo; Núñez, Pedro

2014-01-01

This paper presents a multi-sensor humanoid robotic head for human robot interaction. The design of the robotic head, Muecas, is based on ongoing research on the mechanisms of perception and imitation of human expressions and emotions. These mechanisms allow direct interaction between the robot and its human companion through the different natural language modalities: speech, body language and facial expressions. The robotic head has 12 degrees of freedom, in a human-like configuration, including eyes, eyebrows, mouth and neck, and has been designed and built entirely by IADeX (Engineering, Automation and Design of Extremadura) and RoboLab. A detailed description of its kinematics is provided along with the design of the most complex controllers. Muecas can be directly controlled by FACS (Facial Action Coding System), the de facto standard for facial expression recognition and synthesis. This feature facilitates its use by third party platforms and encourages the development of imitation and of goal-based systems. Imitation systems learn from the user, while goal-based ones use planning techniques to drive the user towards a final desired state. To show the flexibility and reliability of the robotic head, the paper presents a software architecture that is able to detect, recognize, classify and generate facial expressions in real time using FACS. This system has been implemented using the robotics framework, RoboComp, which provides hardware-independent access to the sensors in the head. Finally, the paper presents experimental results showing the real-time functioning of the whole system, including recognition and imitation of human facial expressions. PMID:24787636

Computerized system for recognition of autism on the basis of gene expression microarray data.

PubMed

Latkowski, Tomasz; Osowski, Stanislaw

2015-01-01

The aim of this paper is to provide a means to recognize a case of autism using gene expression microarrays. The crucial task is to discover the most important genes which are strictly associated with autism. The paper presents an application of different methods of gene selection, to select the most representative input attributes for an ensemble of classifiers. The set of classifiers is responsible for distinguishing autism data from the reference class. Simultaneous application of a few gene selection methods enables analysis of the ill-conditioned gene expression matrix from different points of view. The results of selection combined with a genetic algorithm and SVM classifier have shown increased accuracy of autism recognition. Early recognition of autism is extremely important for treatment of children and increases the probability of their recovery and return to normal social communication. The results of this research can find practical application in early recognition of autism on the basis of gene expression microarray analysis. Copyright © 2014 Elsevier Ltd. All rights reserved.

Brief report: accuracy and response time for the recognition of facial emotions in a large sample of children with autism spectrum disorders.

PubMed

Fink, Elian; de Rosnay, Marc; Wierda, Marlies; Koot, Hans M; Begeer, Sander

2014-09-01

The empirical literature has presented inconsistent evidence for deficits in the recognition of basic emotion expressions in children with autism spectrum disorders (ASD), which may be due to the focus on research with relatively small sample sizes. Additionally, it is proposed that although children with ASD may correctly identify emotion expression they rely on more deliberate, more time-consuming strategies in order to accurately recognize emotion expressions when compared to typically developing children. In the current study, we examine both emotion recognition accuracy and response time in a large sample of children, and explore the moderating influence of verbal ability on these findings. The sample consisted of 86 children with ASD (M age = 10.65) and 114 typically developing children (M age = 10.32) between 7 and 13 years of age. All children completed a pre-test (emotion word-word matching), and test phase consisting of basic emotion recognition, whereby they were required to match a target emotion expression to the correct emotion word; accuracy and response time were recorded. Verbal IQ was controlled for in the analyses. We found no evidence of a systematic deficit in emotion recognition accuracy or response time for children with ASD, controlling for verbal ability. However, when controlling for children's accuracy in word-word matching, children with ASD had significantly lower emotion recognition accuracy when compared to typically developing children. The findings suggest that the social impairments observed in children with ASD are not the result of marked deficits in basic emotion recognition accuracy or longer response times. However, children with ASD may be relying on other perceptual skills (such as advanced word-word matching) to complete emotion recognition tasks at a similar level as typically developing children.

Emotion recognition in frontotemporal dementia and Alzheimer's disease: A new film-based assessment.

PubMed

Goodkind, Madeleine S; Sturm, Virginia E; Ascher, Elizabeth A; Shdo, Suzanne M; Miller, Bruce L; Rankin, Katherine P; Levenson, Robert W

2015-08-01

Deficits in recognizing others' emotions are reported in many psychiatric and neurological disorders, including autism, schizophrenia, behavioral variant frontotemporal dementia (bvFTD) and Alzheimer's disease (AD). Most previous emotion recognition studies have required participants to identify emotional expressions in photographs. This type of assessment differs from real-world emotion recognition in important ways: Images are static rather than dynamic, include only 1 modality of emotional information (i.e., visual information), and are presented absent a social context. Additionally, existing emotion recognition batteries typically include multiple negative emotions, but only 1 positive emotion (i.e., happiness) and no self-conscious emotions (e.g., embarrassment). We present initial results using a new task for assessing emotion recognition that was developed to address these limitations. In this task, respondents view a series of short film clips and are asked to identify the main characters' emotions. The task assesses multiple negative, positive, and self-conscious emotions based on information that is multimodal, dynamic, and socially embedded. We evaluate this approach in a sample of patients with bvFTD, AD, and normal controls. Results indicate that patients with bvFTD have emotion recognition deficits in all 3 categories of emotion compared to the other groups. These deficits were especially pronounced for negative and self-conscious emotions. Emotion recognition in this sample of patients with AD was indistinguishable from controls. These findings underscore the utility of this approach to assessing emotion recognition and suggest that previous findings that recognition of positive emotion was preserved in dementia patients may have resulted from the limited sampling of positive emotion in traditional tests. (c) 2015 APA, all rights reserved).

Bihippocampal damage with emotional dysfunction: impaired auditory recognition of fear.

PubMed

Ghika-Schmid, F; Ghika, J; Vuilleumier, P; Assal, G; Vuadens, P; Scherer, K; Maeder, P; Uske, A; Bogousslavsky, J

1997-01-01

A right-handed man developed a sudden transient, amnestic syndrome associated with bilateral hemorrhage of the hippocampi, probably due to Urbach-Wiethe disease. In the 3rd month, despite significant hippocampal structural damage on imaging, only a milder degree of retrograde and anterograde amnesia persisted on detailed neuropsychological examination. On systematic testing of recognition of facial and vocal expression of emotion, we found an impairment of the vocal perception of fear, but not that of other emotions, such as joy, sadness and anger. Such selective impairment of fear perception was not present in the recognition of facial expression of emotion. Thus emotional perception varies according to the different aspects of emotions and the different modality of presentation (faces versus voices). This is consistent with the idea that there may be multiple emotion systems. The study of emotional perception in this unique case of bilateral involvement of hippocampus suggests that this structure may play a critical role in the recognition of fear in vocal expression, possibly dissociated from that of other emotions and from that of fear in facial expression. In regard of recent data suggesting that the amygdala is playing a role in the recognition of fear in the auditory as well as in the visual modality this could suggest that the hippocampus may be part of the auditory pathway of fear recognition.

Facial recognition: a cognitive study of elderly dementia patients and normal older adults.

PubMed

Zandi, T; Cooper, M; Garrison, L

1992-01-01

Dementia patients' and normal elderlies' recognition of familiar, ordinary emotional and facial expressions was tested. In three conditions subjects were required to name the emotions depicted in pictures and to produce them while presented with the verbal labels of the expressions. The dementia patients' best performance occurred when they had access to the verbal labels while viewing the pictures. The major deficiency in facial recognition was found to be dysnomia related. Findings of this study suggest that the connection between the gnostic units of expression and the gnostic units of verbal labeling is not impaired significantly among the dementia patients.

Influence of emotional expression on memory recognition bias in schizophrenia as revealed by fMRI.

PubMed

Sergerie, Karine; Armony, Jorge L; Menear, Matthew; Sutton, Hazel; Lepage, Martin

2010-07-01

We recently showed that, in healthy individuals, emotional expression influences memory for faces both in terms of accuracy and, critically, in memory response bias (tendency to classify stimuli as previously seen or not, regardless of whether this was the case). Although schizophrenia has been shown to be associated with deficit in episodic memory and emotional processing, the relation between these processes in this population remains unclear. Here, we used our previously validated paradigm to directly investigate the modulation of emotion on memory recognition. Twenty patients with schizophrenia and matched healthy controls completed functional magnetic resonance imaging (fMRI) study of recognition memory of happy, sad, and neutral faces. Brain activity associated with the response bias was obtained by correlating this measure with the contrast subjective old (ie, hits and false alarms) minus subjective new (misses and correct rejections) for sad and happy expressions. Although patients exhibited an overall lower memory performance than controls, they showed the same effects of emotion on memory, both in terms of accuracy and bias. For sad faces, the similar behavioral pattern between groups was mirrored by a largely overlapping neural network, mostly involved in familiarity-based judgments (eg, parahippocampal gyrus). In contrast, controls activated a much larger set of regions for happy faces, including areas thought to underlie recollection-based memory retrieval (eg, superior frontal gyrus and hippocampus) and in novelty detection (eg, amygdala). This study demonstrates that, despite an overall lower memory accuracy, emotional memory is intact in schizophrenia, although emotion-specific differences in brain activation exist, possibly reflecting different strategies.

A Rapid and Quantitative Recombinase Activity Assay

USDA-ARS?s Scientific Manuscript database

We present here a comparison between the recombinase systems FLP-FRT and Cre-loxP. A transient excision based dual luciferase expression assay is used for its rapid and repeatable nature. The detection system was designed within an intron to remove the remaining recombinase recognition site and no...

Effects of GABAB receptors in the insula on recognition memory observed with intellicage.

PubMed

Wu, Nan; Wang, Feng; Jin, Zhe; Zhang, Zhen; Wang, Lian-Kun; Zhang, Chun; Sun, Tao

2017-04-17

Insular function has gradually become a topic of intense study in cognitive research. Recognition memory is a commonly studied type of memory in memory research. GABA B R has been shown to be closely related to memory formation. In the present study, we used intellicage, which is a new intelligent behavioural test system, and a bilateral drug microinjection technique to inject into the bilateral insula, to examine the relationship between GABA B R and recognition memory. Male Sprague-Dawley rats were randomly divided into control, Sham, Nacl, baclofen and CGP35348 groups. Different testing procedures were employed using intellicage to detect changes in rat recognition memory. The expression of GABA B R (GB1, GB2) in the insula of rats was determined by immunofluorescence and western blotting at the protein level. In addition, the expression of GABA B R (GB 1 , GB 2 ) was detected by RT-PCR at the mRNA level. The results of the intellicage test showed that recognition memory was impaired in terms of position learning, punitive learning and punitive reversal learning by using baclofen and CGP35348. In position reversal learning, no significant differences were found in terms of cognitive memory ability between the control groups and the CGP and baclofen groups. Immunofluorescence data showed GABA B R (GB1, GB2) expression in the insula, while data from RT-PCR and western blot analysis demonstrated that the relative expression of GB1 and GB2 was significantly increased in the baclofen group compared with the control groups. In the CGP35348 group, the expression of GB1 and GB2 was significantly decreased, but there was no significant difference in GB1 or GB2 expression in the control groups. GABA B R expression in the insula plays an important role in the formation of recognition memory in rats.

Neutral face classification using personalized appearance models for fast and robust emotion detection.

PubMed

Chiranjeevi, Pojala; Gopalakrishnan, Viswanath; Moogi, Pratibha

2015-09-01

Facial expression recognition is one of the open problems in computer vision. Robust neutral face recognition in real time is a major challenge for various supervised learning-based facial expression recognition methods. This is due to the fact that supervised methods cannot accommodate all appearance variability across the faces with respect to race, pose, lighting, facial biases, and so on, in the limited amount of training data. Moreover, processing each and every frame to classify emotions is not required, as user stays neutral for majority of the time in usual applications like video chat or photo album/web browsing. Detecting neutral state at an early stage, thereby bypassing those frames from emotion classification would save the computational power. In this paper, we propose a light-weight neutral versus emotion classification engine, which acts as a pre-processer to the traditional supervised emotion classification approaches. It dynamically learns neutral appearance at key emotion (KE) points using a statistical texture model, constructed by a set of reference neutral frames for each user. The proposed method is made robust to various types of user head motions by accounting for affine distortions based on a statistical texture model. Robustness to dynamic shift of KE points is achieved by evaluating the similarities on a subset of neighborhood patches around each KE point using the prior information regarding the directionality of specific facial action units acting on the respective KE point. The proposed method, as a result, improves emotion recognition (ER) accuracy and simultaneously reduces computational complexity of the ER system, as validated on multiple databases.

The perception and identification of facial emotions in individuals with autism spectrum disorders using the Let's Face It! Emotion Skills Battery.

PubMed

Tanaka, James W; Wolf, Julie M; Klaiman, Cheryl; Koenig, Kathleen; Cockburn, Jeffrey; Herlihy, Lauren; Brown, Carla; Stahl, Sherin S; South, Mikle; McPartland, James C; Kaiser, Martha D; Schultz, Robert T

2012-12-01

Although impaired social-emotional ability is a hallmark of autism spectrum disorder (ASD), the perceptual skills and mediating strategies contributing to the social deficits of autism are not well understood. A perceptual skill that is fundamental to effective social communication is the ability to accurately perceive and interpret facial emotions. To evaluate the expression processing of participants with ASD, we designed the Let's Face It! Emotion Skills Battery (LFI! Battery), a computer-based assessment composed of three subscales measuring verbal and perceptual skills implicated in the recognition of facial emotions. We administered the LFI! Battery to groups of participants with ASD and typically developing control (TDC) participants that were matched for age and IQ. On the Name Game labeling task, participants with ASD (N = 68) performed on par with TDC individuals (N = 66) in their ability to name the facial emotions of happy, sad, disgust and surprise and were only impaired in their ability to identify the angry expression. On the Matchmaker Expression task that measures the recognition of facial emotions across different facial identities, the ASD participants (N = 66) performed reliably worse than TDC participants (N = 67) on the emotions of happy, sad, disgust, frighten and angry. In the Parts-Wholes test of perceptual strategies of expression, the TDC participants (N = 67) displayed more holistic encoding for the eyes than the mouths in expressive faces whereas ASD participants (N = 66) exhibited the reverse pattern of holistic recognition for the mouth and analytic recognition of the eyes. In summary, findings from the LFI! Battery show that participants with ASD were able to label the basic facial emotions (with the exception of angry expression) on par with age- and IQ-matched TDC participants. However, participants with ASD were impaired in their ability to generalize facial emotions across different identities and showed a tendency to recognize the mouth feature holistically and the eyes as isolated parts. © 2012 The Authors. Journal of Child Psychology and Psychiatry © 2012 Association for Child and Adolescent Mental Health.

Deficits in recognizing disgust facial expressions and Internet addiction: Perceived stress as a mediator.

PubMed

Chen, Zhongting; Poon, Kai-Tak; Cheng, Cecilia

2017-08-01

Studies have examined social maladjustment among individuals with Internet addiction, but little is known about their deficits in specific social skills and the underlying psychological mechanisms. The present study filled these gaps by (a) establishing a relationship between deficits in facial expression recognition and Internet addiction, and (b) examining the mediating role of perceived stress that explains this hypothesized relationship. Ninety-seven participants completed validated questionnaires that assessed their levels of Internet addiction and perceived stress, and performed a computer-based task that measured their facial expression recognition. The results revealed a positive relationship between deficits in recognizing disgust facial expression and Internet addiction, and this relationship was mediated by perceived stress. However, the same findings did not apply to other facial expressions. Ad hoc analyses showed that recognizing disgust was more difficult than recognizing other facial expressions, reflecting that the former task assesses a social skill that requires cognitive astuteness. The present findings contribute to the literature by identifying a specific social skill deficit related to Internet addiction and by unveiling a psychological mechanism that explains this relationship, thus providing more concrete guidelines for practitioners to strengthen specific social skills that mitigate both perceived stress and Internet addiction. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Correlations of recognition memory performance with expression and methylation of brain-derived neurotrophic factor in rats.

PubMed

Muñoz, Pablo C; Aspé, Mauricio A; Contreras, Luis S; Palacios, Adrián G

2010-01-01

Object recognition memory allows discrimination between novel and familiar objects. This kind of memory consists of two components: recollection, which depends on the hippocampus, and familiarity, which depends on the perirhinal cortex (Pcx). The importance of brain-derived neurotrophic factor (BDNF) for recognition memory has already been recognized. Recent evidence suggests that DNA methylation regulates the expression of BDNF and memory. Behavioral and molecular approaches were used to understand the potential contribution of DNA methylation to recognition memory. To that end, rats were tested for their ability to distinguish novel from familiar objects by using a spontaneous object recognition task. Furthermore, the level of DNA methylation was estimated after trials with a methyl-sensitive PCR. We found a significant correlation between performance on the novel object task and the expression of BDNF, negatively in hippocampal slices and positively in perirhinal cortical slices. By contrast, methylation of DNA in CpG island 1 in the promoter of exon 1 in BDNF only correlated in hippocampal slices, but not in the Pxc cortical slices from trained animals. These results suggest that DNA methylation may be involved in the regulation of the BDNF gene during recognition memory, at least in the hippocampus.

Class Energy Image Analysis for Video Sensor-Based Gait Recognition: A Review

PubMed Central

Lv, Zhuowen; Xing, Xianglei; Wang, Kejun; Guan, Donghai

2015-01-01

Gait is a unique perceptible biometric feature at larger distances, and the gait representation approach plays a key role in a video sensor-based gait recognition system. Class Energy Image is one of the most important gait representation methods based on appearance, which has received lots of attentions. In this paper, we reviewed the expressions and meanings of various Class Energy Image approaches, and analyzed the information in the Class Energy Images. Furthermore, the effectiveness and robustness of these approaches were compared on the benchmark gait databases. We outlined the research challenges and provided promising future directions for the field. To the best of our knowledge, this is the first review that focuses on Class Energy Image. It can provide a useful reference in the literature of video sensor-based gait representation approach. PMID:25574935

Deficits in facial affect recognition among antisocial populations: a meta-analysis.

PubMed

Marsh, Abigail A; Blair, R J R

2008-01-01

Individuals with disorders marked by antisocial behavior frequently show deficits in recognizing displays of facial affect. Antisociality may be associated with specific deficits in identifying fearful expressions, which would implicate dysfunction in neural structures that subserve fearful expression processing. A meta-analysis of 20 studies was conducted to assess: (a) if antisocial populations show any consistent deficits in recognizing six emotional expressions; (b) beyond any generalized impairment, whether specific fear recognition deficits are apparent; and (c) if deficits in fear recognition are a function of task difficulty. Results show a robust link between antisocial behavior and specific deficits in recognizing fearful expressions. This impairment cannot be attributed solely to task difficulty. These results suggest dysfunction among antisocial individuals in specified neural substrates, namely the amygdala, involved in processing fearful facial affect.

Development of emotional facial recognition in late childhood and adolescence.

PubMed

Thomas, Laura A; De Bellis, Michael D; Graham, Reiko; LaBar, Kevin S

2007-09-01

The ability to interpret emotions in facial expressions is crucial for social functioning across the lifespan. Facial expression recognition develops rapidly during infancy and improves with age during the preschool years. However, the developmental trajectory from late childhood to adulthood is less clear. We tested older children, adolescents and adults on a two-alternative forced-choice discrimination task using morphed faces that varied in emotional content. Actors appeared to pose expressions that changed incrementally along three progressions: neutral-to-fear, neutral-to-anger, and fear-to-anger. Across all three morph types, adults displayed more sensitivity to subtle changes in emotional expression than children and adolescents. Fear morphs and fear-to-anger blends showed a linear developmental trajectory, whereas anger morphs showed a quadratic trend, increasing sharply from adolescents to adults. The results provide evidence for late developmental changes in emotional expression recognition with some specificity in the time course for distinct emotions.

The Automaticity of Emotional Face-Context Integration

PubMed Central

Aviezer, Hillel; Dudarev, Veronica; Bentin, Shlomo; Hassin, Ran R.

2011-01-01

Recent studies have demonstrated that context can dramatically influence the recognition of basic facial expressions, yet the nature of this phenomenon is largely unknown. In the present paper we begin to characterize the underlying process of face-context integration. Specifically, we examine whether it is a relatively controlled or automatic process. In Experiment 1 participants were motivated and instructed to avoid using the context while categorizing contextualized facial expression, or they were led to believe that the context was irrelevant. Nevertheless, they were unable to disregard the context, which exerted a strong effect on their emotion recognition. In Experiment 2, participants categorized contextualized facial expressions while engaged in a concurrent working memory task. Despite the load, the context exerted a strong influence on their recognition of facial expressions. These results suggest that facial expressions and their body contexts are integrated in an unintentional, uncontrollable, and relatively effortless manner. PMID:21707150

A Genetic Approach to Promoter Recognition during Trans Induction of Viral Gene Expression

NASA Astrophysics Data System (ADS)

Coen, Donald M.; Weinheimer, Steven P.; McKnight, Steven L.

1986-10-01

Viral infection of mammalian cells entails the regulated induction of viral gene expression. The induction of many viral genes, including the herpes simplex virus gene encoding thymidine kinase (tk), depends on viral regulatory proteins that act in trans. Because recognition of the tk promoter by cellular transcription factors is well understood, its trans induction by viral regulatory proteins may serve as a useful model for the regulation of eukaryotic gene expression. A comprehensive set of mutations was therefore introduced into the chromosome of herpes simplex virus at the tk promoter to directly analyze the effects of promoter mutations on tk transcription. The promoter domains required for efficient tk expression under conditions of trans induction corresponded to those important for recognition by cellular transcription factors. Thus, trans induction of tk expression may be catalyzed initially by the interaction of viral regulatory proteins with cellular transcription factors.

Development of Emotional Facial Recognition in Late Childhood and Adolescence

ERIC Educational Resources Information Center

Thomas, Laura A.; De Bellis, Michael D.; Graham, Reiko; Labar, Kevin S.

2007-01-01

The ability to interpret emotions in facial expressions is crucial for social functioning across the lifespan. Facial expression recognition develops rapidly during infancy and improves with age during the preschool years. However, the developmental trajectory from late childhood to adulthood is less clear. We tested older children, adolescents…

Teaching Emotion Recognition Skills to Children with Autism

ERIC Educational Resources Information Center

Ryan, Christian; Charragain, Caitriona Ni

2010-01-01

Autism is associated with difficulty interacting with others and an impaired ability to recognize facial expressions of emotion. Previous teaching programmes have not addressed weak central coherence. Emotion recognition training focused on components of facial expressions. The training was administered in small groups ranging from 4 to 7…

Human and animal sounds influence recognition of body language.

PubMed

Van den Stock, Jan; Grèzes, Julie; de Gelder, Beatrice

2008-11-25

In naturalistic settings emotional events have multiple correlates and are simultaneously perceived by several sensory systems. Recent studies have shown that recognition of facial expressions is biased towards the emotion expressed by a simultaneously presented emotional expression in the voice even if attention is directed to the face only. So far, no study examined whether this phenomenon also applies to whole body expressions, although there is no obvious reason why this crossmodal influence would be specific for faces. Here we investigated whether perception of emotions expressed in whole body movements is influenced by affective information provided by human and by animal vocalizations. Participants were instructed to attend to the action displayed by the body and to categorize the expressed emotion. The results indicate that recognition of body language is biased towards the emotion expressed by the simultaneously presented auditory information, whether it consist of human or of animal sounds. Our results show that a crossmodal influence from auditory to visual emotional information obtains for whole body video images with the facial expression blanked and includes human as well as animal sounds.

Recognition of emotion with temporal lobe epilepsy and asymmetrical amygdala damage.

PubMed

Fowler, Helen L; Baker, Gus A; Tipples, Jason; Hare, Dougal J; Keller, Simon; Chadwick, David W; Young, Andrew W

2006-08-01

Impairments in emotion recognition occur when there is bilateral damage to the amygdala. In this study, ability to recognize auditory and visual expressions of emotion was investigated in people with asymmetrical amygdala damage (AAD) and temporal lobe epilepsy (TLE). Recognition of five emotions was tested across three participant groups: those with right AAD and TLE, those with left AAD and TLE, and a comparison group. Four tasks were administered: recognition of emotion from facial expressions, sentences describing emotion-laden situations, nonverbal sounds, and prosody. Accuracy scores for each task and emotion were analysed, and no consistent overall effect of AAD on emotion recognition was found. However, some individual participants with AAD were significantly impaired at recognizing emotions, in both auditory and visual domains. The findings indicate that a minority of individuals with AAD have impairments in emotion recognition, but no evidence of specific impairments (e.g., visual or auditory) was found.

Memristive Computational Architecture of an Echo State Network for Real-Time Speech Emotion Recognition

DTIC Science & Technology

2015-05-28

recognition is simpler and requires less computational resources compared to other inputs such as facial expressions . The Berlin database of Emotional ...Processing Magazine, IEEE, vol. 18, no. 1, pp. 32– 80, 2001. [15] K. R. Scherer, T. Johnstone, and G. Klasmeyer, “Vocal expression of emotion ...Network for Real-Time Speech- Emotion Recognition 5a. CONTRACT NUMBER IN-HOUSE 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 62788F 6. AUTHOR(S) Q

BDNF Expression in Perirhinal Cortex is Associated with Exercise-Induced Improvement in Object Recognition Memory

PubMed Central

Hopkins, Michael E.; Bucci, David J.

2010-01-01

Physical exercise induces widespread neurobiological adaptations and improves learning and memory. Most research in this field has focused on hippocampus-based spatial tasks and changes in brain-derived neurotrophic factor (BDNF) as a putative substrate underlying exercise-induced cognitive improvements. Chronic exercise can also be anxiolytic and causes adaptive changes in stress reactivity. The present study employed a perirhinal cortex-dependent object recognition task as well as the elevated plus maze to directly test for interactions between the cognitive and anxiolytic effects of exercise in male Long Evans rats. Hippocampal and perirhinal cortex tissue was collected to determine whether the relationship between BDNF and cognitive performance extends to this non-spatial and non-hippocampal-dependent task. We also examined whether the cognitive improvements persisted once the exercise regimen was terminated. Our data indicate that 4 weeks of voluntary exercise every-other-day improved object recognition memory. Importantly, BDNF expression in the perirhinal cortex of exercising rats was strongly correlated with object recognition memory. Exercise also decreased anxiety-like behavior, however there was no evidence to support a relationship between anxiety-like behavior and performance on the novel object recognition task. There was a trend for a negative relationship between anxiety-like behavior and hippocampal BDNF. Neither the cognitive improvements nor the relationship between cognitive function and perirhinal BDNF levels persisted after 2 weeks of inactivity. These are the first data demonstrating that region-specific changes in BDNF protein levels are correlated with exercise-induced improvements in non-spatial memory, mediated by structures outside the hippocampus and are consistent with the theory that, with regard to object recognition, the anxiolytic and cognitive effects of exercise may be mediated through separable mechanisms. PMID:20601027

Model of Emotional Expressions in Movements

ERIC Educational Resources Information Center

Rozaliev, Vladimir L.; Orlova, Yulia A.

2013-01-01

This paper presents a new approach to automated identification of human emotions based on analysis of body movements, a recognition of gestures and poses. Methodology, models and automated system for emotion identification are considered. To characterize the person emotions in the model, body movements are described with linguistic variables and a…

The familial basis of facial emotion recognition deficits in adolescents with conduct disorder and their unaffected relatives.

PubMed

Sully, K; Sonuga-Barke, E J S; Fairchild, G

2015-07-01

There is accumulating evidence of impairments in facial emotion recognition in adolescents with conduct disorder (CD). However, the majority of studies in this area have only been able to demonstrate an association, rather than a causal link, between emotion recognition deficits and CD. To move closer towards understanding the causal pathways linking emotion recognition problems with CD, we studied emotion recognition in the unaffected first-degree relatives of CD probands, as well as those with a diagnosis of CD. Using a family-based design, we investigated facial emotion recognition in probands with CD (n = 43), their unaffected relatives (n = 21), and healthy controls (n = 38). We used the Emotion Hexagon task, an alternative forced-choice task using morphed facial expressions depicting the six primary emotions, to assess facial emotion recognition accuracy. Relative to controls, the CD group showed impaired recognition of anger, fear, happiness, sadness and surprise (all p < 0.005). Similar to probands with CD, unaffected relatives showed deficits in anger and happiness recognition relative to controls (all p < 0.008), with a trend toward a deficit in fear recognition. There were no significant differences in performance between the CD probands and the unaffected relatives following correction for multiple comparisons. These results suggest that facial emotion recognition deficits are present in adolescents who are at increased familial risk for developing antisocial behaviour, as well as those who have already developed CD. Consequently, impaired emotion recognition appears to be a viable familial risk marker or candidate endophenotype for CD.

Impact of severity of drug use on discrete emotions recognition in polysubstance abusers.

PubMed

Fernández-Serrano, María José; Lozano, Oscar; Pérez-García, Miguel; Verdejo-García, Antonio

2010-06-01

Neuropsychological studies support the association between severity of drug intake and alterations in specific cognitive domains and neural systems, but there is disproportionately less research on the neuropsychology of emotional alterations associated with addiction. One of the key aspects of adaptive emotional functioning potentially relevant to addiction progression and treatment is the ability to recognize basic emotions in the faces of others. Therefore, the aims of this study were: (i) to examine facial emotion recognition in abstinent polysubstance abusers, and (ii) to explore the association between patterns of quantity and duration of use of several drugs co-abused (including alcohol, cannabis, cocaine, heroin and MDMA) and the ability to identify discrete facial emotional expressions portraying basic emotions. We compared accuracy of emotion recognition of facial expressions portraying six basic emotions (measured with the Ekman Faces Test) between polysubstance abusers (PSA, n=65) and non-drug using comparison individuals (NDCI, n=30), and used regression models to explore the association between quantity and duration of use of the different drugs co-abused and indices of recognition of each of the six emotions, while controlling for relevant socio-demographic and affect-related confounders. Results showed: (i) that PSA had significantly poorer recognition than NDCI for facial expressions of anger, disgust, fear and sadness; (ii) that measures of quantity and duration of drugs used significantly predicted poorer discrete emotions recognition: quantity of cocaine use predicted poorer anger recognition, and duration of cocaine use predicted both poorer anger and fear recognition. Severity of cocaine use also significantly predicted overall recognition accuracy. Copyright (c) 2010 Elsevier Ireland Ltd. All rights reserved.

Sad people are more accurate at expression identification with a smaller own-ethnicity bias than happy people.

PubMed

Hills, Peter J; Hill, Dominic M

2017-07-12

Sad individuals perform more accurately at face identity recognition (Hills, Werno, & Lewis, 2011), possibly because they scan more of the face during encoding. During expression identification tasks, sad individuals do not fixate on the eyes as much as happier individuals (Wu, Pu, Allen, & Pauli, 2012). Fixating on features other than the eyes leads to a reduced own-ethnicity bias (Hills & Lewis, 2006). This background indicates that sad individuals would not view the eyes as much as happy individuals and this would result in improved expression recognition and a reduced own-ethnicity bias. This prediction was tested using an expression identification task, with eye tracking. We demonstrate that sad-induced participants show enhanced expression recognition and a reduced own-ethnicity bias than happy-induced participants due to scanning more facial features. We conclude that mood affects eye movements and face encoding by causing a wider sampling strategy and deeper encoding of facial features diagnostic for expression identification.

Face recognition system using multiple face model of hybrid Fourier feature under uncontrolled illumination variation.

PubMed

Hwang, Wonjun; Wang, Haitao; Kim, Hyunwoo; Kee, Seok-Cheol; Kim, Junmo

2011-04-01

The authors present a robust face recognition system for large-scale data sets taken under uncontrolled illumination variations. The proposed face recognition system consists of a novel illumination-insensitive preprocessing method, a hybrid Fourier-based facial feature extraction, and a score fusion scheme. First, in the preprocessing stage, a face image is transformed into an illumination-insensitive image, called an "integral normalized gradient image," by normalizing and integrating the smoothed gradients of a facial image. Then, for feature extraction of complementary classifiers, multiple face models based upon hybrid Fourier features are applied. The hybrid Fourier features are extracted from different Fourier domains in different frequency bandwidths, and then each feature is individually classified by linear discriminant analysis. In addition, multiple face models are generated by plural normalized face images that have different eye distances. Finally, to combine scores from multiple complementary classifiers, a log likelihood ratio-based score fusion scheme is applied. The proposed system using the face recognition grand challenge (FRGC) experimental protocols is evaluated; FRGC is a large available data set. Experimental results on the FRGC version 2.0 data sets have shown that the proposed method shows an average of 81.49% verification rate on 2-D face images under various environmental variations such as illumination changes, expression changes, and time elapses.

The within-subjects design in the study of facial expressions.

PubMed

Yik, Michelle; Widen, Sherri C; Russell, James A

2013-01-01

The common within-subjects design of studies on the recognition of emotion from facial expressions allows the judgement of one face to be influenced by previous faces, thus introducing the potential for artefacts. The present study (N=344) showed that the canonical "disgust face" was judged as disgusted, provided that the preceding set of faces included "anger expressions", but was judged as angry when the preceding set of faces excluded anger but instead included persons who looked sad or about to be sick. Chinese observers showed lower recognition of the "disgust face" than did American observers. Chinese observers also showed lower recognition of the "fear face" when responding in Chinese than in English.

Impaired recognition of facial emotions from low-spatial frequencies in Asperger syndrome.

PubMed

Kätsyri, Jari; Saalasti, Satu; Tiippana, Kaisa; von Wendt, Lennart; Sams, Mikko

2008-01-01

The theory of 'weak central coherence' [Happe, F., & Frith, U. (2006). The weak coherence account: Detail-focused cognitive style in autism spectrum disorders. Journal of Autism and Developmental Disorders, 36(1), 5-25] implies that persons with autism spectrum disorders (ASDs) have a perceptual bias for local but not for global stimulus features. The recognition of emotional facial expressions representing various different levels of detail has not been studied previously in ASDs. We analyzed the recognition of four basic emotional facial expressions (anger, disgust, fear and happiness) from low-spatial frequencies (overall global shapes without local features) in adults with an ASD. A group of 20 participants with Asperger syndrome (AS) was compared to a group of non-autistic age- and sex-matched controls. Emotion recognition was tested from static and dynamic facial expressions whose spatial frequency contents had been manipulated by low-pass filtering at two levels. The two groups recognized emotions similarly from non-filtered faces and from dynamic vs. static facial expressions. In contrast, the participants with AS were less accurate than controls in recognizing facial emotions from very low-spatial frequencies. The results suggest intact recognition of basic facial emotions and dynamic facial information, but impaired visual processing of global features in ASDs.

Early visual experience and the recognition of basic facial expressions: involvement of the middle temporal and inferior frontal gyri during haptic identification by the early blind

PubMed Central

Kitada, Ryo; Okamoto, Yuko; Sasaki, Akihiro T.; Kochiyama, Takanori; Miyahara, Motohide; Lederman, Susan J.; Sadato, Norihiro

2012-01-01

Face perception is critical for social communication. Given its fundamental importance in the course of evolution, the innate neural mechanisms can anticipate the computations necessary for representing faces. However, the effect of visual deprivation on the formation of neural mechanisms that underlie face perception is largely unknown. We previously showed that sighted individuals can recognize basic facial expressions by haptics surprisingly well. Moreover, the inferior frontal gyrus (IFG) and posterior superior temporal sulcus (pSTS) in the sighted subjects are involved in haptic and visual recognition of facial expressions. Here, we conducted both psychophysical and functional magnetic-resonance imaging (fMRI) experiments to determine the nature of the neural representation that subserves the recognition of basic facial expressions in early blind individuals. In a psychophysical experiment, both early blind and sighted subjects haptically identified basic facial expressions at levels well above chance. In the subsequent fMRI experiment, both groups haptically identified facial expressions and shoe types (control). The sighted subjects then completed the same task visually. Within brain regions activated by the visual and haptic identification of facial expressions (relative to that of shoes) in the sighted group, corresponding haptic identification in the early blind activated regions in the inferior frontal and middle temporal gyri. These results suggest that the neural system that underlies the recognition of basic facial expressions develops supramodally even in the absence of early visual experience. PMID:23372547

Early visual experience and the recognition of basic facial expressions: involvement of the middle temporal and inferior frontal gyri during haptic identification by the early blind.

PubMed

Kitada, Ryo; Okamoto, Yuko; Sasaki, Akihiro T; Kochiyama, Takanori; Miyahara, Motohide; Lederman, Susan J; Sadato, Norihiro

2013-01-01

Face perception is critical for social communication. Given its fundamental importance in the course of evolution, the innate neural mechanisms can anticipate the computations necessary for representing faces. However, the effect of visual deprivation on the formation of neural mechanisms that underlie face perception is largely unknown. We previously showed that sighted individuals can recognize basic facial expressions by haptics surprisingly well. Moreover, the inferior frontal gyrus (IFG) and posterior superior temporal sulcus (pSTS) in the sighted subjects are involved in haptic and visual recognition of facial expressions. Here, we conducted both psychophysical and functional magnetic-resonance imaging (fMRI) experiments to determine the nature of the neural representation that subserves the recognition of basic facial expressions in early blind individuals. In a psychophysical experiment, both early blind and sighted subjects haptically identified basic facial expressions at levels well above chance. In the subsequent fMRI experiment, both groups haptically identified facial expressions and shoe types (control). The sighted subjects then completed the same task visually. Within brain regions activated by the visual and haptic identification of facial expressions (relative to that of shoes) in the sighted group, corresponding haptic identification in the early blind activated regions in the inferior frontal and middle temporal gyri. These results suggest that the neural system that underlies the recognition of basic facial expressions develops supramodally even in the absence of early visual experience.

Facial Emotion Recognition: A Survey and Real-World User Experiences in Mixed Reality

PubMed Central

Mehta, Dhwani; Siddiqui, Mohammad Faridul Haque

2018-01-01

Extensive possibilities of applications have made emotion recognition ineluctable and challenging in the field of computer science. The use of non-verbal cues such as gestures, body movement, and facial expressions convey the feeling and the feedback to the user. This discipline of Human–Computer Interaction places reliance on the algorithmic robustness and the sensitivity of the sensor to ameliorate the recognition. Sensors play a significant role in accurate detection by providing a very high-quality input, hence increasing the efficiency and the reliability of the system. Automatic recognition of human emotions would help in teaching social intelligence in the machines. This paper presents a brief study of the various approaches and the techniques of emotion recognition. The survey covers a succinct review of the databases that are considered as data sets for algorithms detecting the emotions by facial expressions. Later, mixed reality device Microsoft HoloLens (MHL) is introduced for observing emotion recognition in Augmented Reality (AR). A brief introduction of its sensors, their application in emotion recognition and some preliminary results of emotion recognition using MHL are presented. The paper then concludes by comparing results of emotion recognition by the MHL and a regular webcam. PMID:29389845

Facial Emotion Recognition: A Survey and Real-World User Experiences in Mixed Reality.

PubMed

Mehta, Dhwani; Siddiqui, Mohammad Faridul Haque; Javaid, Ahmad Y

2018-02-01

Extensive possibilities of applications have made emotion recognition ineluctable and challenging in the field of computer science. The use of non-verbal cues such as gestures, body movement, and facial expressions convey the feeling and the feedback to the user. This discipline of Human-Computer Interaction places reliance on the algorithmic robustness and the sensitivity of the sensor to ameliorate the recognition. Sensors play a significant role in accurate detection by providing a very high-quality input, hence increasing the efficiency and the reliability of the system. Automatic recognition of human emotions would help in teaching social intelligence in the machines. This paper presents a brief study of the various approaches and the techniques of emotion recognition. The survey covers a succinct review of the databases that are considered as data sets for algorithms detecting the emotions by facial expressions. Later, mixed reality device Microsoft HoloLens (MHL) is introduced for observing emotion recognition in Augmented Reality (AR). A brief introduction of its sensors, their application in emotion recognition and some preliminary results of emotion recognition using MHL are presented. The paper then concludes by comparing results of emotion recognition by the MHL and a regular webcam.

Early effects of duloxetine on emotion recognition in healthy volunteers

PubMed Central

Bamford, Susan; Penton-Voak, Ian; Pinkney, Verity; Baldwin, David S; Munafò, Marcus R; Garner, Matthew

2015-01-01

The serotonin-noradrenaline reuptake inhibitor (SNRI) duloxetine is an effective treatment for major depression and generalised anxiety disorder. Neuropsychological models of antidepressant drug action suggest therapeutic effects might be mediated by the early correction of maladaptive biases in emotion processing, including the recognition of emotional expressions. Sub-chronic administration of duloxetine (for two weeks) produces adaptive changes in neural circuitry implicated in emotion processing; however, its effects on emotional expression recognition are unknown. Forty healthy participants were randomised to receive either 14 days of duloxetine (60 mg/day, titrated from 30 mg after three days) or matched placebo (with sham titration) in a double-blind, between-groups, repeated-measures design. On day 0 and day 14 participants completed a computerised emotional expression recognition task that measured sensitivity to the six primary emotions. Thirty-eight participants (19 per group) completed their course of tablets and were included in the analysis. Results provide evidence that duloxetine, compared to placebo, may reduce the accurate recognition of sadness. Drug effects were driven by changes in participants’ ability to correctly detect subtle expressions of sadness, with greater change observed in the placebo relative to the duloxetine group. These effects occurred in the absence of changes in mood. Our preliminary findings require replication, but complement recent evidence that sadness recognition is a therapeutic target in major depression, and a mechanism through which SNRIs could resolve negative biases in emotion processing to achieve therapeutic effects. PMID:25759400

Emotion Recognition in Face and Body Motion in Bulimia Nervosa.

PubMed

Dapelo, Marcela Marin; Surguladze, Simon; Morris, Robin; Tchanturia, Kate

2017-11-01

Social cognition has been studied extensively in anorexia nervosa (AN), but there are few studies in bulimia nervosa (BN). This study investigated the ability of people with BN to recognise emotions in ambiguous facial expressions and in body movement. Participants were 26 women with BN, who were compared with 35 with AN, and 42 healthy controls. Participants completed an emotion recognition task by using faces portraying blended emotions, along with a body emotion recognition task by using videos of point-light walkers. The results indicated that BN participants exhibited difficulties recognising disgust in less-ambiguous facial expressions, and a tendency to interpret non-angry faces as anger, compared with healthy controls. These difficulties were similar to those found in AN. There were no significant differences amongst the groups in body motion emotion recognition. The findings suggest that difficulties with disgust and anger recognition in facial expressions may be shared transdiagnostically in people with eating disorders. Copyright © 2017 John Wiley & Sons, Ltd and Eating Disorders Association. Copyright © 2017 John Wiley & Sons, Ltd and Eating Disorders Association.

Loneliness and the social monitoring system: Emotion recognition and eye gaze in a real-life conversation.

PubMed

Lodder, Gerine M A; Scholte, Ron H J; Goossens, Luc; Engels, Rutger C M E; Verhagen, Maaike

2016-02-01

Based on the belongingness regulation theory (Gardner et al., 2005, Pers. Soc. Psychol. Bull., 31, 1549), this study focuses on the relationship between loneliness and social monitoring. Specifically, we examined whether loneliness relates to performance on three emotion recognition tasks and whether lonely individuals show increased gazing towards their conversation partner's faces in a real-life conversation. Study 1 examined 170 college students (Mage = 19.26; SD = 1.21) who completed an emotion recognition task with dynamic stimuli (morph task) and a micro(-emotion) expression recognition task. Study 2 examined 130 college students (Mage = 19.33; SD = 2.00) who completed the Reading the Mind in the Eyes Test and who had a conversation with an unfamiliar peer while their gaze direction was videotaped. In both studies, loneliness was measured using the UCLA Loneliness Scale version 3 (Russell, 1996, J. Pers. Assess., 66, 20). The results showed that loneliness was unrelated to emotion recognition on all emotion recognition tasks, but that it was related to increased gaze towards their conversation partner's faces. Implications for the belongingness regulation system of lonely individuals are discussed. © 2015 The British Psychological Society.

Encoding conditions affect recognition of vocally expressed emotions across cultures.

PubMed

Jürgens, Rebecca; Drolet, Matthis; Pirow, Ralph; Scheiner, Elisabeth; Fischer, Julia

2013-01-01

Although the expression of emotions in humans is considered to be largely universal, cultural effects contribute to both emotion expression and recognition. To disentangle the interplay between these factors, play-acted and authentic (non-instructed) vocal expressions of emotions were used, on the assumption that cultural effects may contribute differentially to the recognition of staged and spontaneous emotions. Speech tokens depicting four emotions (anger, sadness, joy, fear) were obtained from German radio archives and re-enacted by professional actors, and presented to 120 participants from Germany, Romania, and Indonesia. Participants in all three countries were poor at distinguishing between play-acted and spontaneous emotional utterances (58.73% correct on average with only marginal cultural differences). Nevertheless, authenticity influenced emotion recognition: across cultures, anger was recognized more accurately when play-acted (z = 15.06, p < 0.001) and sadness when authentic (z = 6.63, p < 0.001), replicating previous findings from German populations. German subjects revealed a slight advantage in recognizing emotions, indicating a moderate in-group advantage. There was no difference between Romanian and Indonesian subjects in the overall emotion recognition. Differential cultural effects became particularly apparent in terms of differential biases in emotion attribution. While all participants labeled play-acted expressions as anger more frequently than expected, German participants exhibited a further bias toward choosing anger for spontaneous stimuli. In contrast to the German sample, Romanian and Indonesian participants were biased toward choosing sadness. These results support the view that emotion recognition rests on a complex interaction of human universals and cultural specificities. Whether and in which way the observed biases are linked to cultural differences in self-construal remains an issue for further investigation.

Facial affect recognition in symptomatically remitted patients with schizophrenia and bipolar disorder.

PubMed

Yalcin-Siedentopf, Nursen; Hoertnagl, Christine M; Biedermann, Falko; Baumgartner, Susanne; Deisenhammer, Eberhard A; Hausmann, Armand; Kaufmann, Alexandra; Kemmler, Georg; Mühlbacher, Moritz; Rauch, Anna-Sophia; Fleischhacker, W Wolfgang; Hofer, Alex

2014-02-01

Both schizophrenia and bipolar disorder (BD) have consistently been associated with deficits in facial affect recognition (FAR). These impairments have been related to various aspects of social competence and functioning and are relatively stable over time. However, individuals in remission may outperform patients experiencing an acute phase of the disorders. The present study directly contrasted FAR in symptomatically remitted patients with schizophrenia or BD and healthy volunteers and investigated its relationship with patients' outcomes. Compared to healthy control subjects, schizophrenia patients were impaired in the recognition of angry, disgusted, sad and happy facial expressions, while BD patients showed deficits only in the recognition of disgusted and happy facial expressions. When directly comparing the two patient groups individuals suffering from BD outperformed those with schizophrenia in the recognition of expressions depicting anger. There was no significant association between affect recognition abilities and symptomatic or psychosocial outcomes in schizophrenia patients. Among BD patients, relatively higher depression scores were associated with impairments in both the identification of happy faces and psychosocial functioning. Overall, our findings indicate that during periods of symptomatic remission the recognition of facial affect may be less impaired in patients with BD than in those suffering from schizophrenia. However, in the psychosocial context BD patients seem to be more sensitive to residual symptomatology. Copyright © 2013 Elsevier B.V. All rights reserved.

On the evolution of harming and recognition in finite panmictic and infinite structured populations

PubMed Central

Lehmann, Laurent; Feldman, Marcus W.; Rousset, François

2010-01-01

Natural selection may favor two very different types of social behaviors that have costs in vital rates (fecundity and/or survival) to the actor: helping behaviors, which increase the vital rates of recipients, and harming behaviors, which reduce the vital rates of recipients. While social evolutionary theory has mainly dealt with helping behaviors, competition for limited resources creates ecological conditions where an actor may benefit from expressing behaviors that reduce the vital rates of neighbours. This may occur if the reduction in vital rates decreases the intensity of competition experienced by the actor or that experienced by its offspring. Here, we explore the joint evolution of neutral recognition markers and marker-based costly conditional harming whereby actors express harming, conditional on actor and recipient bearing different conspicuous markers. We do so for two complementary demographic scenarios: finite panmictic and infinite structured populations. We find that marker-based conditional harming can evolve under a large range of recombination rates and group sizes under both finite panmictic and infinite structured populations. Direct comparison with results for the evolution of marker-based conditional helping reveals that, if everything else is equal, marker-based conditional harming is often more likely to evolve than marker-based conditional. PMID:19624725

Does Facial Expression Recognition Provide a Toehold for the Development of Emotion Understanding?

ERIC Educational Resources Information Center

Strand, Paul S.; Downs, Andrew; Barbosa-Leiker, Celestina

2016-01-01

The authors explored predictions from basic emotion theory (BET) that facial emotion expression recognition skills are insular with respect to their own development, and yet foundational to the development of emotional perspective-taking skills. Participants included 417 preschool children for whom estimates of these 2 emotion understanding…

Pharmacologic suppression of target cell recognition by engineered T cells expressing chimeric T-cell receptors.

PubMed

Alvarez-Vallina, L; Yañez, R; Blanco, B; Gil, M; Russell, S J

2000-04-01

Adoptive therapy with autologous T cells expressing chimeric T-cell receptors (chTCRs) is of potential interest for the treatment of malignancy. To limit possible T-cell-mediated damage to normal tissues that weakly express the targeted tumor antigen (Ag), we have tested a strategy for the suppression of target cell recognition by engineered T cells. Jurkat T cells were transduced with an anti-hapten chTCR tinder the control of a tetracycline-suppressible promoter and were shown to respond to Ag-positive (hapten-coated) but not to Ag-negative target cells. The engineered T cells were then reacted with hapten-coated target cells at different effector to target cell ratios before and after exposure to tetracycline. When the engineered T cells were treated with tetracycline, expression of the chTCR was greatly decreased and recognition of the hapten-coated target cells was completely suppressed. Tetracycline-mediated suppression of target cell recognition by engineered T cells may be a useful strategy to limit the toxicity of the approach to cancer gene therapy.

Quantifying facial expression recognition across viewing conditions.

PubMed

Goren, Deborah; Wilson, Hugh R

2006-04-01

Facial expressions are key to social interactions and to assessment of potential danger in various situations. Therefore, our brains must be able to recognize facial expressions when they are transformed in biologically plausible ways. We used synthetic happy, sad, angry and fearful faces to determine the amount of geometric change required to recognize these emotions during brief presentations. Five-alternative forced choice conditions involving central viewing, peripheral viewing and inversion were used to study recognition among the four emotions. Two-alternative forced choice was used to study affect discrimination when spatial frequency information in the stimulus was modified. The results show an emotion and task-dependent pattern of detection. Facial expressions presented with low peak frequencies are much harder to discriminate from neutral than faces defined by either mid or high peak frequencies. Peripheral presentation of faces also makes recognition much more difficult, except for happy faces. Differences between fearful detection and recognition tasks are probably due to common confusions with sadness when recognizing fear from among other emotions. These findings further support the idea that these emotions are processed separately from each other.

Facial emotion recognition in Williams syndrome and Down syndrome: A matching and developmental study.

PubMed

Martínez-Castilla, Pastora; Burt, Michael; Borgatti, Renato; Gagliardi, Chiara

2015-01-01

In this study both the matching and developmental trajectories approaches were used to clarify questions that remain open in the literature on facial emotion recognition in Williams syndrome (WS) and Down syndrome (DS). The matching approach showed that individuals with WS or DS exhibit neither proficiency for the expression of happiness nor specific impairments for negative emotions. Instead, they present the same pattern of emotion recognition as typically developing (TD) individuals. Thus, the better performance on the recognition of positive compared to negative emotions usually reported in WS and DS is not specific of these populations but seems to represent a typical pattern. Prior studies based on the matching approach suggested that the development of facial emotion recognition is delayed in WS and atypical in DS. Nevertheless, and even though performance levels were lower in DS than in WS, the developmental trajectories approach used in this study evidenced that not only individuals with DS but also those with WS present atypical development in facial emotion recognition. Unlike in the TD participants, where developmental changes were observed along with age, in the WS and DS groups, the development of facial emotion recognition was static. Both individuals with WS and those with DS reached an early maximum developmental level due to cognitive constraints.

Quest Hierarchy for Hyperspectral Face Recognition

DTIC Science & Technology

2011-03-01

numerous face recognition algorithms available, several very good literature surveys are available that include Abate [29], Samal [110], Kong [18], Zou...Perception, Japan (January 1994). [110] Samal , Ashok and P. Iyengar, Automatic Recognition and Analysis of Human Faces and Facial Expressions: A Survey

Pose-variant facial expression recognition using an embedded image system

NASA Astrophysics Data System (ADS)

Song, Kai-Tai; Han, Meng-Ju; Chang, Shuo-Hung

2008-12-01

In recent years, one of the most attractive research areas in human-robot interaction is automated facial expression recognition. Through recognizing the facial expression, a pet robot can interact with human in a more natural manner. In this study, we focus on the facial pose-variant problem. A novel method is proposed in this paper to recognize pose-variant facial expressions. After locating the face position in an image frame, the active appearance model (AAM) is applied to track facial features. Fourteen feature points are extracted to represent the variation of facial expressions. The distance between feature points are defined as the feature values. These feature values are sent to a support vector machine (SVM) for facial expression determination. The pose-variant facial expression is classified into happiness, neutral, sadness, surprise or anger. Furthermore, in order to evaluate the performance for practical applications, this study also built a low resolution database (160x120 pixels) using a CMOS image sensor. Experimental results show that the recognition rate is 84% with the self-built database.

Actively Paranoid Patients with Schizophrenia Over Attribute Anger to Neutral Faces

PubMed Central

Pinkham, Amy E.; Brensinger, Colleen; Kohler, Christian; Gur, Raquel E.; Gur, Ruben C.

2010-01-01

Previous investigations of the influence of paranoia on facial affect recognition in schizophrenia have been inconclusive as some studies demonstrate better performance for paranoid relative to non-paranoid patients and others show that paranoid patients display greater impairments. These studies have been limited by small sample sizes and inconsistencies in the criteria used to define groups. Here, we utilized an established emotion recognition task and a large sample to examine differential performance in emotion recognition ability between patients who were actively paranoid (AP) and those who were not actively paranoid (NAP). Accuracy and error patterns on the Penn Emotion Recognition test (ER40) were examined in 132 patients (64 NAP and 68 AP). Groups were defined based on the presence of paranoid ideation at the time of testing rather than diagnostic subtype. AP and NAP patients did not differ in overall task accuracy; however, an emotion by group interaction indicated that AP patients were significantly worse than NAP patients at correctly labeling neutral faces. A comparison of error patterns on neutral stimuli revealed that the groups differed only in misattributions of anger expressions, with AP patients being significantly more likely to misidentify a neutral expression as angry. The present findings suggest that paranoia is associated with a tendency to over attribute threat to ambiguous stimuli and also lend support to emerging hypotheses of amygdala hyperactivation as a potential neural mechanism for paranoid ideation. PMID:21112186

Research and Development of Target Recognition and Location Crawling Platform based on Binocular Vision

NASA Astrophysics Data System (ADS)

Xu, Weidong; Lei, Zhu; Yuan, Zhang; Gao, Zhenqing

2018-03-01

The application of visual recognition technology in industrial robot crawling and placing operation is one of the key tasks in the field of robot research. In order to improve the efficiency and intelligence of the material sorting in the production line, especially to realize the sorting of the scattered items, the robot target recognition and positioning crawling platform based on binocular vision is researched and developed. The images were collected by binocular camera, and the images were pretreated. Harris operator was used to identify the corners of the images. The Canny operator was used to identify the images. Hough-chain code recognition was used to identify the images. The target image in the image, obtain the coordinates of each vertex of the image, calculate the spatial position and posture of the target item, and determine the information needed to capture the movement and transmit it to the robot control crawling operation. Finally, In this paper, we use this method to experiment the wrapping problem in the express sorting process The experimental results show that the platform can effectively solve the problem of sorting of loose parts, so as to achieve the purpose of efficient and intelligent sorting.

Infrared and visible fusion face recognition based on NSCT domain

NASA Astrophysics Data System (ADS)

Xie, Zhihua; Zhang, Shuai; Liu, Guodong; Xiong, Jinquan

2018-01-01

Visible face recognition systems, being vulnerable to illumination, expression, and pose, can not achieve robust performance in unconstrained situations. Meanwhile, near infrared face images, being light- independent, can avoid or limit the drawbacks of face recognition in visible light, but its main challenges are low resolution and signal noise ratio (SNR). Therefore, near infrared and visible fusion face recognition has become an important direction in the field of unconstrained face recognition research. In this paper, a novel fusion algorithm in non-subsampled contourlet transform (NSCT) domain is proposed for Infrared and visible face fusion recognition. Firstly, NSCT is used respectively to process the infrared and visible face images, which exploits the image information at multiple scales, orientations, and frequency bands. Then, to exploit the effective discriminant feature and balance the power of high-low frequency band of NSCT coefficients, the local Gabor binary pattern (LGBP) and Local Binary Pattern (LBP) are applied respectively in different frequency parts to obtain the robust representation of infrared and visible face images. Finally, the score-level fusion is used to fuse the all the features for final classification. The visible and near infrared face recognition is tested on HITSZ Lab2 visible and near infrared face database. Experiments results show that the proposed method extracts the complementary features of near-infrared and visible-light images and improves the robustness of unconstrained face recognition.

Facial Emotion Recognition and Expression in Parkinson's Disease: An Emotional Mirror Mechanism?

PubMed

Ricciardi, Lucia; Visco-Comandini, Federica; Erro, Roberto; Morgante, Francesca; Bologna, Matteo; Fasano, Alfonso; Ricciardi, Diego; Edwards, Mark J; Kilner, James

2017-01-01

Parkinson's disease (PD) patients have impairment of facial expressivity (hypomimia) and difficulties in interpreting the emotional facial expressions produced by others, especially for aversive emotions. We aimed to evaluate the ability to produce facial emotional expressions and to recognize facial emotional expressions produced by others in a group of PD patients and a group of healthy participants in order to explore the relationship between these two abilities and any differences between the two groups of participants. Twenty non-demented, non-depressed PD patients and twenty healthy participants (HC) matched for demographic characteristics were studied. The ability of recognizing emotional facial expressions was assessed with the Ekman 60-faces test (Emotion recognition task). Participants were video-recorded while posing facial expressions of 6 primary emotions (happiness, sadness, surprise, disgust, fear and anger). The most expressive pictures for each emotion were derived from the videos. Ten healthy raters were asked to look at the pictures displayed on a computer-screen in pseudo-random fashion and to identify the emotional label in a six-forced-choice response format (Emotion expressivity task). Reaction time (RT) and accuracy of responses were recorded. At the end of each trial the participant was asked to rate his/her confidence in his/her perceived accuracy of response. For emotion recognition, PD reported lower score than HC for Ekman total score (p<0.001), and for single emotions sub-scores happiness, fear, anger, sadness (p<0.01) and surprise (p = 0.02). In the facial emotion expressivity task, PD and HC significantly differed in the total score (p = 0.05) and in the sub-scores for happiness, sadness, anger (all p<0.001). RT and the level of confidence showed significant differences between PD and HC for the same emotions. There was a significant positive correlation between the emotion facial recognition and expressivity in both groups; the correlation was even stronger when ranking emotions from the best recognized to the worst (R = 0.75, p = 0.004). PD patients showed difficulties in recognizing emotional facial expressions produced by others and in posing facial emotional expressions compared to healthy subjects. The linear correlation between recognition and expression in both experimental groups suggests that the two mechanisms share a common system, which could be deteriorated in patients with PD. These results open new clinical and rehabilitation perspectives.

Facial Expression Recognition using Multiclass Ensemble Least-Square Support Vector Machine

NASA Astrophysics Data System (ADS)

Lawi, Armin; Sya'Rani Machrizzandi, M.

2018-03-01

Facial expression is one of behavior characteristics of human-being. The use of biometrics technology system with facial expression characteristics makes it possible to recognize a person’s mood or emotion. The basic components of facial expression analysis system are face detection, face image extraction, facial classification and facial expressions recognition. This paper uses Principal Component Analysis (PCA) algorithm to extract facial features with expression parameters, i.e., happy, sad, neutral, angry, fear, and disgusted. Then Multiclass Ensemble Least-Squares Support Vector Machine (MELS-SVM) is used for the classification process of facial expression. The result of MELS-SVM model obtained from our 185 different expression images of 10 persons showed high accuracy level of 99.998% using RBF kernel.

Facial emotion recognition and borderline personality pathology.

PubMed

Meehan, Kevin B; De Panfilis, Chiara; Cain, Nicole M; Antonucci, Camilla; Soliani, Antonio; Clarkin, John F; Sambataro, Fabio

2017-09-01

The impact of borderline personality pathology on facial emotion recognition has been in dispute; with impaired, comparable, and enhanced accuracy found in high borderline personality groups. Discrepancies are likely driven by variations in facial emotion recognition tasks across studies (stimuli type/intensity) and heterogeneity in borderline personality pathology. This study evaluates facial emotion recognition for neutral and negative emotions (fear/sadness/disgust/anger) presented at varying intensities. Effortful control was evaluated as a moderator of facial emotion recognition in borderline personality. Non-clinical multicultural undergraduates (n = 132) completed a morphed facial emotion recognition task of neutral and negative emotional expressions across different intensities (100% Neutral; 25%/50%/75% Emotion) and self-reported borderline personality features and effortful control. Greater borderline personality features related to decreased accuracy in detecting neutral faces, but increased accuracy in detecting negative emotion faces, particularly at low-intensity thresholds. This pattern was moderated by effortful control; for individuals with low but not high effortful control, greater borderline personality features related to misattributions of emotion to neutral expressions, and enhanced detection of low-intensity emotional expressions. Individuals with high borderline personality features may therefore exhibit a bias toward detecting negative emotions that are not or barely present; however, good self-regulatory skills may protect against this potential social-cognitive vulnerability. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Neurotrophins play differential roles in short and long-term recognition memory.

PubMed

Callaghan, Charlotte K; Kelly, Aine M

2013-09-01

The neurotrophin family of proteins are believed to mediate various forms of synaptic plasticity in the adult brain. Here we have assessed the roles of these proteins in object recognition memory in the rat, using icv infusions of function-blocking antibodies or the tyrosine kinase antagonist, tyrphostin AG879, to block Trk receptors. We report that tyrphostin AG879 impairs both short-term and long-term recognition memory, indicating a requirement for Trk receptor activation in both processes. The effect of inhibition of each of the neurotrophins with activity-blocking neutralising antibodies was also tested. Treatment with anti-BDNF, anti-NGF or anti-NT4 had no effect on short-term memory, but blocked long-term recognition memory. Treatment with anti-NT3 had no effect on either process. We also assessed changes in expression of neurotrophins and their respective receptors in the hippocampus, dentate gyrus and perirhinal cortex over a 24 h period following training in the object recognition task. We observed time-dependent changes in expression of the Trk receptors and their ligands in the dentate gyrus and perirhinal cortex. The data are consistent with a pivotal role for neurotrophic factors in the expression of recognition memory. Copyright © 2013 Elsevier Inc. All rights reserved.

Processing dynamic facial affect in frequent cannabis-users: evidence of deficits in the speed of identifying emotional expressions.

PubMed

Platt, Bradley; Kamboj, Sunjeev; Morgan, Celia J A; Curran, H Valerie

2010-11-01

While heavy cannabis-users seem to show various cognitive impairments, it remains unclear whether they also experience significant deficits in affective functioning. Evidence of such deficits may contribute to our understanding of the interpersonal difficulties in cannabis-users, and the link between cannabis-use and psychological disorders (Moore et al., 2007). Emotion recognition performance of heavy cannabis-users and non-using controls was compared. A measure of emotion recognition was used in which participants identified facial expressions as they changed from neutral (open-mouth) to gradually more intense expressions of sadness, neutral, anger or happiness (open or closed mouth). Reaction times and accuracy were recorded as the facial expressions changed. Participants also completed measures of 'theory of mind,' depression and impulsivity. Cannabis-users were significantly slower than controls at identifying all three emotional expressions. There was no difference between groups in identifying facial expressions changing from open-mouth neutral expressions to closed-mouth neutral expressions suggesting that differences in emotion recognition were not due to a general slowing of reaction times. Cannabis-users were also significantly more liberal in their response criterion for recognising sadness. Heavy cannabis-use may be associated with affect recognition deficits. In particular, a greater intensity of emotion expression was required before identification of positive and negative emotions. This was found using stimuli which simulated dynamic changes in emotion expression, and in turn, suggests that cannabis-users may experience generalised problems in decoding basic emotions during social interactions. The implications of these findings are discussed for vulnerability to psychological and interpersonal difficulties in cannabis-users. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Identification in a pseudoknot of a U.G motif essential for the regulation of the expression of ribosomal protein S15.

PubMed

Bénard, L; Mathy, N; Grunberg-Manago, M; Ehresmann, B; Ehresmann, C; Portier, C

1998-03-03

The ribosomal protein S15 from Escherichia coli binds to a pseudoknot in its own messenger. This interaction is an essential step in the mechanism of S15 translational autoregulation. In a previous study, a recognition determinant for S15 autoregulation, involving a U.G wobble pair, was located in the center of stem I of the pseudoknot. In this study, an extensive mutagenesis analysis has been conducted in and around this U.G pair by comparing the effects of these mutations on the expression level of S15. The results show that the U.G wobble pair cannot be substituted by A.G, C.A, A.C, G.U, or C.G without loss of the autocontrol. In addition, the base pair C.G, adjacent to the 5' side of U, cannot be flipped or changed to another complementary base pair without also inducing derepression of translation. A unique motif, made of only two adjacent base pairs, U.G/C.G, is essential for S15 autoregulation and is presumably involved in direct recognition by the S15 protein.

Identification in a pseudoknot of a U⋅G motif essential for the regulation of the expression of ribosomal protein S15

PubMed Central

Bénard, Lionel; Mathy, Nathalie; Grunberg-Manago, Marianne; Ehresmann, Bernard; Ehresmann, Chantal; Portier, Claude

1998-01-01

The ribosomal protein S15 from Escherichia coli binds to a pseudoknot in its own messenger. This interaction is an essential step in the mechanism of S15 translational autoregulation. In a previous study, a recognition determinant for S15 autoregulation, involving a U⋅G wobble pair, was located in the center of stem I of the pseudoknot. In this study, an extensive mutagenesis analysis has been conducted in and around this U⋅G pair by comparing the effects of these mutations on the expression level of S15. The results show that the U⋅G wobble pair cannot be substituted by A⋅G, C⋅A, A⋅C, G⋅U, or C⋅G without loss of the autocontrol. In addition, the base pair C⋅G, adjacent to the 5′ side of U, cannot be flipped or changed to another complementary base pair without also inducing derepression of translation. A unique motif, made of only two adjacent base pairs, U⋅G/C⋅G, is essential for S15 autoregulation and is presumably involved in direct recognition by the S15 protein. PMID:9482926

Traffic Behavior Recognition Using the Pachinko Allocation Model

PubMed Central

Huynh-The, Thien; Banos, Oresti; Le, Ba-Vui; Bui, Dinh-Mao; Yoon, Yongik; Lee, Sungyoung

2015-01-01

CCTV-based behavior recognition systems have gained considerable attention in recent years in the transportation surveillance domain for identifying unusual patterns, such as traffic jams, accidents, dangerous driving and other abnormal behaviors. In this paper, a novel approach for traffic behavior modeling is presented for video-based road surveillance. The proposed system combines the pachinko allocation model (PAM) and support vector machine (SVM) for a hierarchical representation and identification of traffic behavior. A background subtraction technique using Gaussian mixture models (GMMs) and an object tracking mechanism based on Kalman filters are utilized to firstly construct the object trajectories. Then, the sparse features comprising the locations and directions of the moving objects are modeled by PAM into traffic topics, namely activities and behaviors. As a key innovation, PAM captures not only the correlation among the activities, but also among the behaviors based on the arbitrary directed acyclic graph (DAG). The SVM classifier is then utilized on top to train and recognize the traffic activity and behavior. The proposed model shows more flexibility and greater expressive power than the commonly-used latent Dirichlet allocation (LDA) approach, leading to a higher recognition accuracy in the behavior classification. PMID:26151213

[Neurological disease and facial recognition].

PubMed

Kawamura, Mitsuru; Sugimoto, Azusa; Kobayakawa, Mutsutaka; Tsuruya, Natsuko

2012-07-01

To discuss the neurological basis of facial recognition, we present our case reports of impaired recognition and a review of previous literature. First, we present a case of infarction and discuss prosopagnosia, which has had a large impact on face recognition research. From a study of patient symptoms, we assume that prosopagnosia may be caused by unilateral right occipitotemporal lesion and right cerebral dominance of facial recognition. Further, circumscribed lesion and degenerative disease may also cause progressive prosopagnosia. Apperceptive prosopagnosia is observed in patients with posterior cortical atrophy (PCA), pathologically considered as Alzheimer's disease, and associative prosopagnosia in frontotemporal lobar degeneration (FTLD). Second, we discuss face recognition as part of communication. Patients with Parkinson disease show social cognitive impairments, such as difficulty in facial expression recognition and deficits in theory of mind as detected by the reading the mind in the eyes test. Pathological and functional imaging studies indicate that social cognitive impairment in Parkinson disease is possibly related to damages in the amygdalae and surrounding limbic system. The social cognitive deficits can be observed in the early stages of Parkinson disease, and even in the prodromal stage, for example, patients with rapid eye movement (REM) sleep behavior disorder (RBD) show impairment in facial expression recognition. Further, patients with myotonic dystrophy type 1 (DM 1), which is a multisystem disease that mainly affects the muscles, show social cognitive impairment similar to that of Parkinson disease. Our previous study showed that facial expression recognition impairment of DM 1 patients is associated with lesion in the amygdalae and insulae. Our study results indicate that behaviors and personality traits in DM 1 patients, which are revealed by social cognitive impairment, are attributable to dysfunction of the limbic system.

Estradiol and luteinizing hormone regulate recognition memory following subchronic phencyclidine: Evidence for hippocampal GABA action.

PubMed

Riordan, Alexander J; Schaler, Ari W; Fried, Jenny; Paine, Tracie A; Thornton, Janice E

2018-05-01

The cognitive symptoms of schizophrenia are poorly understood and difficult to treat. Estrogens may mitigate these symptoms via unknown mechanisms. To examine these mechanisms, we tested whether increasing estradiol (E) or decreasing luteinizing hormone (LH) could mitigate short-term episodic memory loss in a phencyclidine (PCP) model of schizophrenia. We then assessed whether changes in cortical or hippocampal GABA may underlie these effects. Female rats were ovariectomized and injected subchronically with PCP. To modulate E and LH, animals received estradiol capsules or Antide injections. Short-term episodic memory was assessed using the novel object recognition task (NORT). Brain expression of GAD67 was analyzed via western blot, and parvalbumin-containing cells were counted using immunohistochemistry. Some rats received hippocampal infusions of a GABA A agonist, GABA A antagonist, or GAD inhibitor before behavioral testing. We found that PCP reduced hippocampal GAD67 and abolished recognition memory. Antide restored hippocampal GAD67 and rescued recognition memory in PCP-treated animals. Estradiol prevented PCP's amnesic effect in NORT but failed to restore hippocampal GAD67. PCP did not cause significant differences in number of parvalbumin-expressing cells or cortical expression of GAD67. Hippocampal infusions of a GABA A agonist restored recognition memory in PCP-treated rats. Blocking hippocampal GAD or GABA A receptors in ovx animals reproduced recognition memory loss similar to PCP and inhibited estradiol's protection of recognition memory in PCP-treated animals. In summary, decreasing LH or increasing E can lessen short-term episodic memory loss, as measured by novel object recognition, in a PCP model of schizophrenia. Alterations in hippocampal GABA may contribute to both PCP's effects on recognition memory and the hormones' ability to prevent or reverse them. Copyright © 2018 Elsevier Ltd. All rights reserved.

Facial Expression Recognition: Can Preschoolers with Cochlear Implants and Hearing Aids Catch It?

ERIC Educational Resources Information Center

Wang, Yifang; Su, Yanjie; Fang, Ping; Zhou, Qingxia

2011-01-01

Tager-Flusberg and Sullivan (2000) presented a cognitive model of theory of mind (ToM), in which they thought ToM included two components--a social-perceptual component and a social-cognitive component. Facial expression recognition (FER) is an ability tapping the social-perceptual component. Previous findings suggested that normal hearing…

Deficits in Facial Expression Recognition in Male Adolescents with Early-Onset or Adolescence-Onset Conduct Disorder

ERIC Educational Resources Information Center

Fairchild, Graeme; Van Goozen, Stephanie H. M.; Calder, Andrew J.; Stollery, Sarah J.; Goodyer, Ian M.

2009-01-01

Background: We examined whether conduct disorder (CD) is associated with deficits in facial expression recognition and, if so, whether these deficits are specific to the early-onset form of CD, which emerges in childhood. The findings could potentially inform the developmental taxonomic theory of antisocial behaviour, which suggests that…

Emotion Recognition from Congruent and Incongruent Emotional Expressions and Situational Cues in Children with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Tell, Dina; Davidson, Denise

2015-01-01

In this research, the emotion recognition abilities of children with autism spectrum disorder and typically developing children were compared. When facial expressions and situational cues of emotion were congruent, accuracy in recognizing emotions was good for both children with autism spectrum disorder and typically developing children. When…

Orientation and Affective Expression Effects on Face Recognition in Williams Syndrome and Autism

ERIC Educational Resources Information Center

Rose, Fredric E.; Lincoln, Alan J.; Lai, Zona; Ene, Michaela; Searcy, Yvonne M.; Bellugi, Ursula

2007-01-01

We sought to clarify the nature of the face processing strength commonly observed in individuals with Williams syndrome (WS) by comparing the face recognition ability of persons with WS to that of persons with autism and to healthy controls under three conditions: Upright faces with neutral expressions, upright faces with varying affective…

Can gaze avoidance explain why individuals with Asperger's syndrome can't recognise emotions from facial expressions?

PubMed

Sawyer, Alyssa C P; Williamson, Paul; Young, Robyn L

2012-04-01

Research has shown that individuals with Autism Spectrum Disorders (ASD) have difficulties recognising emotions from facial expressions. Since eye contact is important for accurate emotion recognition, and individuals with ASD tend to avoid eye contact, this tendency for gaze aversion has been proposed as an explanation for the emotion recognition deficit. This explanation was investigated using a newly developed emotion and mental state recognition task. Individuals with Asperger's Syndrome were less accurate at recognising emotions and mental states, but did not show evidence of gaze avoidance compared to individuals without Asperger's Syndrome. This suggests that the way individuals with Asperger's Syndrome look at faces cannot account for the difficulty they have recognising expressions.

DNA recognition by synthetic constructs.

PubMed

Pazos, Elena; Mosquera, Jesús; Vázquez, M Eugenio; Mascareñas, José L

2011-09-05

The interaction of transcription factors with specific DNA sites is key for the regulation of gene expression. Despite the availability of a large body of structural data on protein-DNA complexes, we are still far from fully understanding the molecular and biophysical bases underlying such interactions. Therefore, the development of non-natural agents that can reproduce the DNA-recognition properties of natural transcription factors remains a major and challenging goal in chemical biology. In this review we summarize the basics of double-stranded DNA recognition by transcription factors, and describe recent developments in the design and preparation of synthetic DNA binders. We mainly focus on synthetic peptides that have been designed by following the DNA interaction of natural proteins, and we discuss how the tools of organic synthesis can be used to make artificial constructs equipped with functionalities that introduce additional properties to the recognition process, such as sensing and controllability. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

CREMA-D: Crowd-sourced Emotional Multimodal Actors Dataset

PubMed Central

Cao, Houwei; Cooper, David G.; Keutmann, Michael K.; Gur, Ruben C.; Nenkova, Ani; Verma, Ragini

2014-01-01

People convey their emotional state in their face and voice. We present an audio-visual data set uniquely suited for the study of multi-modal emotion expression and perception. The data set consists of facial and vocal emotional expressions in sentences spoken in a range of basic emotional states (happy, sad, anger, fear, disgust, and neutral). 7,442 clips of 91 actors with diverse ethnic backgrounds were rated by multiple raters in three modalities: audio, visual, and audio-visual. Categorical emotion labels and real-value intensity values for the perceived emotion were collected using crowd-sourcing from 2,443 raters. The human recognition of intended emotion for the audio-only, visual-only, and audio-visual data are 40.9%, 58.2% and 63.6% respectively. Recognition rates are highest for neutral, followed by happy, anger, disgust, fear, and sad. Average intensity levels of emotion are rated highest for visual-only perception. The accurate recognition of disgust and fear requires simultaneous audio-visual cues, while anger and happiness can be well recognized based on evidence from a single modality. The large dataset we introduce can be used to probe other questions concerning the audio-visual perception of emotion. PMID:25653738

PHD Finger Recognition of Unmodified Histone H3R2 Links UHRF1 to Regulation of Euchromatic Gene Expression

DOE Office of Scientific and Technical Information (OSTI.GOV)

E Rajakumara; Z Wang; H Ma

2011-12-31

Histone methylation occurs on both lysine and arginine residues, and its dynamic regulation plays a critical role in chromatin biology. Here we identify the UHRF1 PHD finger (PHD{sub UHRF1}), an important regulator of DNA CpG methylation, as a histone H3 unmodified arginine 2 (H3R2) recognition modality. This conclusion is based on binding studies and cocrystal structures of PHD{sub UHRF1} bound to histone H3 peptides, where the guanidinium group of unmodified R2 forms an extensive intermolecular hydrogen bond network, with methylation of H3R2, but not H3K4 or H3K9, disrupting complex formation. We have identified direct target genes of UHRF1 from microarraymore » and ChIP studies. Importantly, we show that UHRF1's ability to repress its direct target gene expression is dependent on PHD{sub UHRF1} binding to unmodified H3R2, thereby demonstrating the functional importance of this recognition event and supporting the potential for crosstalk between histone arginine methylation and UHRF1 function.« less

PHD Finger Recognition of Unmodified Histone H3R2 Links UHRF1 to Regulation of Euchromatic Gene Expression

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rajakumara, Eerappa; Wang, Zhentian; Ma, Honghui

2011-08-29

Histone methylation occurs on both lysine and arginine residues, and its dynamic regulation plays a critical role in chromatin biology. Here we identify the UHRF1 PHD finger (PHD{sub UHRF1}), an important regulator of DNA CpG methylation, as a histone H3 unmodified arginine 2 (H3R2) recognition modality. This conclusion is based on binding studies and cocrystal structures of PHD{sub UHRF1} bound to histone H3 peptides, where the guanidinium group of unmodified R2 forms an extensive intermolecular hydrogen bond network, with methylation of H3R2, but not H3K4 or H3K9, disrupting complex formation. We have identified direct target genes of UHRF1 from microarraymore » and ChIP studies. Importantly, we show that UHRF1's ability to repress its direct target gene expression is dependent on PHD{sub UHRF1} binding to unmodified H3R2, thereby demonstrating the functional importance of this recognition event and supporting the potential for crosstalk between histone arginine methylation and UHRF1 function.« less

Adaptive metric learning with deep neural networks for video-based facial expression recognition

NASA Astrophysics Data System (ADS)

Liu, Xiaofeng; Ge, Yubin; Yang, Chao; Jia, Ping

2018-01-01

Video-based facial expression recognition has become increasingly important for plenty of applications in the real world. Despite that numerous efforts have been made for the single sequence, how to balance the complex distribution of intra- and interclass variations well between sequences has remained a great difficulty in this area. We propose the adaptive (N+M)-tuplet clusters loss function and optimize it with the softmax loss simultaneously in the training phrase. The variations introduced by personal attributes are alleviated using the similarity measurements of multiple samples in the feature space with many fewer comparison times as conventional deep metric learning approaches, which enables the metric calculations for large data applications (e.g., videos). Both the spatial and temporal relations are well explored by a unified framework that consists of an Inception-ResNet network with long short term memory and the two fully connected layer branches structure. Our proposed method has been evaluated with three well-known databases, and the experimental results show that our method outperforms many state-of-the-art approaches.

[The effect of the serotonin transporter 5-HTTLPR polymorphism on the recognition of facial emotions in schizophrenia].

PubMed

Alfimova, M V; Golimbet, V E; Korovaitseva, G I; Lezheiko, T V; Abramova, L I; Aksenova, E V; Bolgov, M I

2014-01-01

The 5-HTTLPR SLC6A4 and catechol-o-methyltransferase (COMT) Val158Met polymorphisms are reported to be associated with processing of facial expressions in general population. Impaired recognition of facial expressions that is characteristic of schizophrenia negatively impacts on the social adaptation of the patients. To search for molecular mechanisms of this deficit, we studied main and epistatic effects of 5-HTTLPR and Val158Met polymorphisms on the facial emotion recognition in patients with schizophrenia (n=299) and healthy controls (n=232). The 5-HTTLPR polymorphism was associated with the emotion recognition in patients. The ll-homozygotes recognized facial emotions significantly better compared to those with an s-allele (F=8.00; p=0.005). Although the recognition of facial emotions was correlated with negative symptoms, verbal learning and trait anxiety, these variables did not significantly modified the association. In both groups, no effect of the COMT on the recognition of facial emotions was found.

Mapping the impairment in decoding static facial expressions of emotion in prosopagnosia.

PubMed

Fiset, Daniel; Blais, Caroline; Royer, Jessica; Richoz, Anne-Raphaëlle; Dugas, Gabrielle; Caldara, Roberto

2017-08-01

Acquired prosopagnosia is characterized by a deficit in face recognition due to diverse brain lesions, but interestingly most prosopagnosic patients suffering from posterior lesions use the mouth instead of the eyes for face identification. Whether this bias is present for the recognition of facial expressions of emotion has not yet been addressed. We tested PS, a pure case of acquired prosopagnosia with bilateral occipitotemporal lesions anatomically sparing the regions dedicated for facial expression recognition. PS used mostly the mouth to recognize facial expressions even when the eye area was the most diagnostic. Moreover, PS directed most of her fixations towards the mouth. Her impairment was still largely present when she was instructed to look at the eyes, or when she was forced to look at them. Control participants showed a performance comparable to PS when only the lower part of the face was available. These observations suggest that the deficits observed in PS with static images are not solely attentional, but are rooted at the level of facial information use. This study corroborates neuroimaging findings suggesting that the Occipital Face Area might play a critical role in extracting facial features that are integrated for both face identification and facial expression recognition in static images. © The Author (2017). Published by Oxford University Press.

Facing the Problem: Impaired Emotion Recognition During Multimodal Social Information Processing in Borderline Personality Disorder.

PubMed

Niedtfeld, Inga; Defiebre, Nadine; Regenbogen, Christina; Mier, Daniela; Fenske, Sabrina; Kirsch, Peter; Lis, Stefanie; Schmahl, Christian

2017-04-01

Previous research has revealed alterations and deficits in facial emotion recognition in patients with borderline personality disorder (BPD). During interpersonal communication in daily life, social signals such as speech content, variation in prosody, and facial expression need to be considered simultaneously. We hypothesized that deficits in higher level integration of social stimuli contribute to difficulties in emotion recognition in BPD, and heightened arousal might explain this effect. Thirty-one patients with BPD and thirty-one healthy controls were asked to identify emotions in short video clips, which were designed to represent different combinations of the three communication channels: facial expression, speech content, and prosody. Skin conductance was recorded as a measure of sympathetic arousal, while controlling for state dissociation. Patients with BPD showed lower mean accuracy scores than healthy control subjects in all conditions comprising emotional facial expressions. This was true for the condition with facial expression only, and for the combination of all three communication channels. Electrodermal responses were enhanced in BPD only in response to auditory stimuli. In line with the major body of facial emotion recognition studies, we conclude that deficits in the interpretation of facial expressions lead to the difficulties observed in multimodal emotion processing in BPD.

Seeing Life through Positive-Tinted Glasses: Color–Meaning Associations

PubMed Central

Gil, Sandrine; Le Bigot, Ludovic

2014-01-01

There is a growing body of literature to show that color can convey information, owing to its emotionally meaningful associations. Most research so far has focused on negative hue–meaning associations (e.g., red) with the exception of the positive aspects associated with green. We therefore set out to investigate the positive associations of two colors (i.e., green and pink), using an emotional facial expression recognition task in which colors provided the emotional contextual information for the face processing. In two experiments, green and pink backgrounds enhanced happy face recognition and impaired sad face recognition, compared with a control color (gray). Our findings therefore suggest that because green and pink both convey positive information, they facilitate the processing of emotionally congruent facial expressions (i.e., faces expressing happiness) and interfere with that of incongruent facial expressions (i.e., faces expressing sadness). Data also revealed a positive association for white. Results are discussed within the theoretical framework of emotional cue processing and color meaning. PMID:25098167

Seeing life through positive-tinted glasses: color-meaning associations.

PubMed

Gil, Sandrine; Le Bigot, Ludovic

2014-01-01

There is a growing body of literature to show that color can convey information, owing to its emotionally meaningful associations. Most research so far has focused on negative hue-meaning associations (e.g., red) with the exception of the positive aspects associated with green. We therefore set out to investigate the positive associations of two colors (i.e., green and pink), using an emotional facial expression recognition task in which colors provided the emotional contextual information for the face processing. In two experiments, green and pink backgrounds enhanced happy face recognition and impaired sad face recognition, compared with a control color (gray). Our findings therefore suggest that because green and pink both convey positive information, they facilitate the processing of emotionally congruent facial expressions (i.e., faces expressing happiness) and interfere with that of incongruent facial expressions (i.e., faces expressing sadness). Data also revealed a positive association for white. Results are discussed within the theoretical framework of emotional cue processing and color meaning.

Codebook-based electrooculography data analysis towards cognitive activity recognition.

PubMed

Lagodzinski, P; Shirahama, K; Grzegorzek, M

2018-04-01

With the advancement in mobile/wearable technology, people started to use a variety of sensing devices to track their daily activities as well as health and fitness conditions in order to improve the quality of life. This work addresses an idea of eye movement analysis, which due to the strong correlation with cognitive tasks can be successfully utilized in activity recognition. Eye movements are recorded using an electrooculographic (EOG) system built into the frames of glasses, which can be worn more unobtrusively and comfortably than other devices. Since the obtained information is low-level sensor data expressed as a sequence representing values in constant intervals (100 Hz), the cognitive activity recognition problem is formulated as sequence classification. However, it is unclear what kind of features are useful for accurate cognitive activity recognition. Thus, a machine learning algorithm like a codebook approach is applied, which instead of focusing on feature engineering is using a distribution of characteristic subsequences (codewords) to describe sequences of recorded EOG data, where the codewords are obtained by clustering a large number of subsequences. Further, statistical analysis of the codeword distribution results in discovering features which are characteristic to a certain activity class. Experimental results demonstrate good accuracy of the codebook-based cognitive activity recognition reflecting the effective usage of the codewords. Copyright © 2017 Elsevier Ltd. All rights reserved.

Emotion recognition deficits associated with ventromedial prefrontal cortex lesions are improved by gaze manipulation.

PubMed

Wolf, Richard C; Pujara, Maia; Baskaya, Mustafa K; Koenigs, Michael

2016-09-01

Facial emotion recognition is a critical aspect of human communication. Since abnormalities in facial emotion recognition are associated with social and affective impairment in a variety of psychiatric and neurological conditions, identifying the neural substrates and psychological processes underlying facial emotion recognition will help advance basic and translational research on social-affective function. Ventromedial prefrontal cortex (vmPFC) has recently been implicated in deploying visual attention to the eyes of emotional faces, although there is mixed evidence regarding the importance of this brain region for recognition accuracy. In the present study of neurological patients with vmPFC damage, we used an emotion recognition task with morphed facial expressions of varying intensities to determine (1) whether vmPFC is essential for emotion recognition accuracy, and (2) whether instructed attention to the eyes of faces would be sufficient to improve any accuracy deficits. We found that vmPFC lesion patients are impaired, relative to neurologically healthy adults, at recognizing moderate intensity expressions of anger and that recognition accuracy can be improved by providing instructions of where to fixate. These results suggest that vmPFC may be important for the recognition of facial emotion through a role in guiding visual attention to emotionally salient regions of faces. Copyright © 2016 Elsevier Ltd. All rights reserved.

Does vigilance to pain make individuals experts in facial recognition of pain?

PubMed

Baum, Corinna; Kappesser, Judith; Schneider, Raphaela; Lautenbacher, Stefan

2013-01-01

It is well known that individual factors are important in the facial recognition of pain. However, it is unclear whether vigilance to pain as a pain-related attentional mechanism is among these relevant factors. Vigilance to pain may have two different effects on the recognition of facial pain expressions: pain-vigilant individuals may detect pain faces better but overinclude other facial displays, misinterpreting them as expressing pain; or they may be true experts in discriminating between pain and other facial expressions. The present study aimed to test these two hypotheses. Furthermore, pain vigilance was assumed to be a distinct predictor, the impact of which on recognition cannot be completely replaced by related concepts such as pain catastrophizing and fear of pain. Photographs of neutral, happy, angry and pain facial expressions were presented to 40 healthy participants, who were asked to classify them into the appropriate emotion categories and provide a confidence rating for each classification. Additionally, potential predictors of the discrimination performance for pain and anger faces - pain vigilance, pain-related catastrophizing, fear of pain--were assessed using self-report questionnaires. Pain-vigilant participants classified pain faces more accurately and did not misclassify anger as pain faces more frequently. However, vigilance to pain was not related to the confidence of recognition ratings. Pain catastrophizing and fear of pain did not account for the recognition performance. Moderate pain vigilance, as assessed in the present study, appears to be associated with appropriate detection of pain-related cues and not necessarily with the overinclusion of other negative cues.

Does vigilance to pain make individuals experts in facial recognition of pain?

PubMed Central

Baum, Corinna; Kappesser, Judith; Schneider, Raphaela; Lautenbacher, Stefan

2013-01-01

BACKGROUND: It is well known that individual factors are important in the facial recognition of pain. However, it is unclear whether vigilance to pain as a pain-related attentional mechanism is among these relevant factors. OBJECTIVES: Vigilance to pain may have two different effects on the recognition of facial pain expressions: pain-vigilant individuals may detect pain faces better but overinclude other facial displays, misinterpreting them as expressing pain; or they may be true experts in discriminating between pain and other facial expressions. The present study aimed to test these two hypotheses. Furthermore, pain vigilance was assumed to be a distinct predictor, the impact of which on recognition cannot be completely replaced by related concepts such as pain catastrophizing and fear of pain. METHODS: Photographs of neutral, happy, angry and pain facial expressions were presented to 40 healthy participants, who were asked to classify them into the appropriate emotion categories and provide a confidence rating for each classification. Additionally, potential predictors of the discrimination performance for pain and anger faces – pain vigilance, pain-related catastrophizing, fear of pain – were assessed using self-report questionnaires. RESULTS: Pain-vigilant participants classified pain faces more accurately and did not misclassify anger as pain faces more frequently. However, vigilance to pain was not related to the confidence of recognition ratings. Pain catastrophizing and fear of pain did not account for the recognition performance. CONCLUSIONS: Moderate pain vigilance, as assessed in the present study, appears to be associated with appropriate detection of pain-related cues and not necessarily with the overinclusion of other negative cues. PMID:23717826

Mapping parahippocampal systems for recognition and recency memory in the absence of the rat hippocampus

PubMed Central

Kinnavane, L; Amin, E; Horne, M; Aggleton, J P

2014-01-01

The present study examined immediate-early gene expression in the perirhinal cortex of rats with hippocampal lesions. The goal was to test those models of recognition memory which assume that the perirhinal cortex can function independently of the hippocampus. The c-fos gene was targeted, as its expression in the perirhinal cortex is strongly associated with recognition memory. Four groups of rats were examined. Rats with hippocampal lesions and their surgical controls were given either a recognition memory task (novel vs. familiar objects) or a relative recency task (objects with differing degrees of familiarity). Perirhinal Fos expression in the hippocampal-lesioned groups correlated with both recognition and recency performance. The hippocampal lesions, however, had no apparent effect on overall levels of perirhinal or entorhinal cortex c-fos expression in response to novel objects, with only restricted effects being seen in the recency condition. Network analyses showed that whereas the patterns of parahippocampal interactions were differentially affected by novel or familiar objects, these correlated networks were not altered by hippocampal lesions. Additional analyses in control rats revealed two modes of correlated medial temporal activation. Novel stimuli recruited the pathway from the lateral entorhinal cortex (cortical layer II or III) to hippocampal field CA3, and thence to CA1. Familiar stimuli recruited the direct pathway from the lateral entorhinal cortex (principally layer III) to CA1. The present findings not only reveal the independence from the hippocampus of some perirhinal systems associated with recognition memory, but also show how novel stimuli engage hippocampal subfields in qualitatively different ways from familiar stimuli. PMID:25264133

Genetic variations in the dopamine system and facial expression recognition in healthy chinese college students.

PubMed

Zhu, Bi; Chen, Chuansheng; Moyzis, Robert K; Dong, Qi; Chen, Chunhui; He, Qinghua; Stern, Hal S; Li, He; Li, Jin; Li, Jun; Lessard, Jared; Lin, Chongde

2012-01-01

This study investigated the relation between genetic variations in the dopamine system and facial expression recognition. A sample of Chinese college students (n = 478) was given a facial expression recognition task. Subjects were genotyped for 98 loci [96 single-nucleotide polymorphisms (SNPs) and 2 variable number tandem repeats] in 16 genes involved in the dopamine neurotransmitter system, including its 4 subsystems: synthesis (TH, DDC, and DBH), degradation/transport (COMT,MAOA,MAOB, and SLC6A3), receptors (DRD1,DRD2,DRD3,DRD4, and DRD5), and modulation (NTS,NTSR1,NTSR2, and NLN). To quantify the total contributions of the dopamine system to emotion recognition, we used a series of multiple regression models. Permutation analyses were performed to assess the posterior probabilities of obtaining such results. Among the 78 loci that were included in the final analyses (after excluding 12 SNPs that were in high linkage disequilibrium and 8 that were not in Hardy-Weinberg equilibrium), 1 (for fear), 3 (for sadness), 5 (for anger), 13 (for surprise), and 15 (for disgust) loci exhibited main effects on the recognition of facial expressions. Genetic variations in the dopamine system accounted for 3% for fear, 6% for sadness, 7% for anger, 10% for surprise, and 18% for disgust, with the latter surviving a stringent permutation test. Genetic variations in the dopamine system (especially the dopamine synthesis and modulation subsystems) made significant contributions to individual differences in the recognition of disgust faces. Copyright © 2012 S. Karger AG, Basel.

Recognition profile of emotions in natural and virtual faces.

PubMed

Dyck, Miriam; Winbeck, Maren; Leiberg, Susanne; Chen, Yuhan; Gur, Ruben C; Gur, Rurben C; Mathiak, Klaus

2008-01-01

Computer-generated virtual faces become increasingly realistic including the simulation of emotional expressions. These faces can be used as well-controlled, realistic and dynamic stimuli in emotion research. However, the validity of virtual facial expressions in comparison to natural emotion displays still needs to be shown for the different emotions and different age groups. Thirty-two healthy volunteers between the age of 20 and 60 rated pictures of natural human faces and faces of virtual characters (avatars) with respect to the expressed emotions: happiness, sadness, anger, fear, disgust, and neutral. Results indicate that virtual emotions were recognized comparable to natural ones. Recognition differences in virtual and natural faces depended on specific emotions: whereas disgust was difficult to convey with the current avatar technology, virtual sadness and fear achieved better recognition results than natural faces. Furthermore, emotion recognition rates decreased for virtual but not natural faces in participants over the age of 40. This specific age effect suggests that media exposure has an influence on emotion recognition. Virtual and natural facial displays of emotion may be equally effective. Improved technology (e.g. better modelling of the naso-labial area) may lead to even better results as compared to trained actors. Due to the ease with which virtual human faces can be animated and manipulated, validated artificial emotional expressions will be of major relevance in future research and therapeutic applications.

Effects of repeated 9 and 30-day exposure to extremely low-frequency electromagnetic fields on social recognition behavior and estrogen receptors expression in olfactory bulb of Wistar female rats.

PubMed

Bernal-Mondragón, C; Arriaga-Avila, V; Martínez-Abundis, E; Barrera-Mera, B; Mercado-Gómez, O; Guevara-Guzmán, R

2017-02-01

We investigated the short- and long-term effects of extremely low-frequency electromagnetic fields (EMF) on social recognition behavior and expression of α- and β-estrogen receptors (ER). Rats were exposed to 60-Hz electromagnetic fields for 9 or 30 days and tested for social recognition behavior. Immunohistochemistry and western blot assays were performed to evaluate α- and β-ER expression in the olfactory bulb of intact, ovariectomized (OVX), and ovariectomized+estradiol (E2) replacement (OVX+E2). Ovariectomization showed impairment of social recognition after 9 days of EMF exposure and a complete recovery after E2 replacement and so did those after 30 days. Short EMF exposure increased expression of β-ER in intact, but not in the others. Longer exposure produced a decrease in intact but an increase in OVX and OVX+E2. Our findings suggest a significant role for β-estrogen receptors and a lack of effect for α-estrogen receptors on a social recognition task. EMF: extremely low frequency electromagnetic fields; ERs: estrogen receptors; OB: olfactory bulb; OVX: ovariectomized; OVX + E 2 : ovariectomized + estradiol replacement; IEI: interexposure interval; β-ER: beta estrogen receptor; E 2 : replacement of estradiol; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; WB: Western blot; PBS: phosphate-buffer saline; PB: phosphate-buffer.

Recognition Profile of Emotions in Natural and Virtual Faces

PubMed Central

Dyck, Miriam; Winbeck, Maren; Leiberg, Susanne; Chen, Yuhan; Gur, Rurben C.; Mathiak, Klaus

2008-01-01

Background Computer-generated virtual faces become increasingly realistic including the simulation of emotional expressions. These faces can be used as well-controlled, realistic and dynamic stimuli in emotion research. However, the validity of virtual facial expressions in comparison to natural emotion displays still needs to be shown for the different emotions and different age groups. Methodology/Principal Findings Thirty-two healthy volunteers between the age of 20 and 60 rated pictures of natural human faces and faces of virtual characters (avatars) with respect to the expressed emotions: happiness, sadness, anger, fear, disgust, and neutral. Results indicate that virtual emotions were recognized comparable to natural ones. Recognition differences in virtual and natural faces depended on specific emotions: whereas disgust was difficult to convey with the current avatar technology, virtual sadness and fear achieved better recognition results than natural faces. Furthermore, emotion recognition rates decreased for virtual but not natural faces in participants over the age of 40. This specific age effect suggests that media exposure has an influence on emotion recognition. Conclusions/Significance Virtual and natural facial displays of emotion may be equally effective. Improved technology (e.g. better modelling of the naso-labial area) may lead to even better results as compared to trained actors. Due to the ease with which virtual human faces can be animated and manipulated, validated artificial emotional expressions will be of major relevance in future research and therapeutic applications. PMID:18985152

Functional architecture of visual emotion recognition ability: A latent variable approach.

PubMed

Lewis, Gary J; Lefevre, Carmen E; Young, Andrew W

2016-05-01

Emotion recognition has been a focus of considerable attention for several decades. However, despite this interest, the underlying structure of individual differences in emotion recognition ability has been largely overlooked and thus is poorly understood. For example, limited knowledge exists concerning whether recognition ability for one emotion (e.g., disgust) generalizes to other emotions (e.g., anger, fear). Furthermore, it is unclear whether emotion recognition ability generalizes across modalities, such that those who are good at recognizing emotions from the face, for example, are also good at identifying emotions from nonfacial cues (such as cues conveyed via the body). The primary goal of the current set of studies was to address these questions through establishing the structure of individual differences in visual emotion recognition ability. In three independent samples (Study 1: n = 640; Study 2: n = 389; Study 3: n = 303), we observed that the ability to recognize visually presented emotions is based on different sources of variation: a supramodal emotion-general factor, supramodal emotion-specific factors, and face- and within-modality emotion-specific factors. In addition, we found evidence that general intelligence and alexithymia were associated with supramodal emotion recognition ability. Autism-like traits, empathic concern, and alexithymia were independently associated with face-specific emotion recognition ability. These results (a) provide a platform for further individual differences research on emotion recognition ability, (b) indicate that differentiating levels within the architecture of emotion recognition ability is of high importance, and (c) show that the capacity to understand expressions of emotion in others is linked to broader affective and cognitive processes. (c) 2016 APA, all rights reserved).

A portable bioluminescence engineered cell-based biosensor for on-site applications.

PubMed

Roda, Aldo; Cevenini, Luca; Michelini, Elisa; Branchini, Bruce R

2011-04-15

We have developed a portable biosensing device based on genetically engineered bioluminescent (BL) cells. Cells were immobilized on a 4 × 3 multiwell cartridge using a new biocompatible matrix that preserved their vitality. Using a fiber optic taper, the cartridge was placed in direct contact with a cooled CCD sensor to image and quantify the BL signals. Yeast and bacterial cells were engineered to express recognition elements, whose interaction with the analyte led to luciferase expression, via reporter gene technology. Three different biosensors were developed. The first detects androgenic compounds using yeast cells carrying a green-emitting P. pyralis luciferase regulated by the human androgen receptor and a red mutant of the same species as internal vitality control. The second biosensor detects two classes of compounds (androgens and estrogens) using yeast strains engineered to express green-or red-emitting mutant firefly luciferases in response to androgens or estrogens, respectively. The third biosensor detects lactose analogue isopropyl β-d-1-thiogalactopyranoside using two E. coli strains. One strain exploits the lac operon as recognition element for the expression of P. pyralis luciferase. The other strain serves as a vitality control expressing Gaussia princeps luciferase, which requires a different luciferin substrate. The immobilized cells were stable for up to 1 month. The analytes could be detected at nanomolar levels with good precision and accuracy when the specific signal was corrected using the internal vitality control. This portable device can be used for on-site multiplexed bioassays for different compound classes. Copyright © 2011 Elsevier B.V. All rights reserved.

The dorsomedial prefrontal cortex plays a causal role in mediating in-group advantage in emotion recognition: A TMS study.

PubMed

Gamond, L; Cattaneo, Z

2016-12-01

Consistent evidence suggests that emotional facial expressions are better recognized when the expresser and the perceiver belong to the same social group (in-group advantage). In this study, we used transcranial magnetic stimulation (TMS) to investigate the possible causal involvement of the dorsomedial prefrontal cortex (dmPFC) and of the right temporo-parietal junction (TPJ), two main nodes of the mentalizing neural network, in mediating the in-group advantage in emotion recognition. Participants performed an emotion discrimination task in a minimal (blue/green) group paradigm. We found that interfering with activity in the dmPFC significantly interfered with the effect of minimal group-membership on emotion recognition, reducing participants' ability to discriminate emotions expressed by in-group members. In turn, rTPJ mainly affected emotion discrimination per se, irrespective of group membership. Overall, our results point to a causal role of the dmPFC in mediating the in-group advantage in emotion recognition, favoring intragroup communication. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Change in Facial Emotion Recognition Ability in Inpatients with Treatment Resistant Schizophrenia After Electroconvulsive Therapy.

PubMed

Dalkıran, Mihriban; Tasdemir, Akif; Salihoglu, Tamer; Emul, Murat; Duran, Alaattin; Ugur, Mufit; Yavuz, Ruhi

2017-09-01

People with schizophrenia have impairments in emotion recognition along with other social cognitive deficits. In the current study, we aimed to investigate the immediate benefits of ECT on facial emotion recognition ability. Thirty-two treatment resistant patients with schizophrenia who have been indicated for ECT enrolled in the study. Facial emotion stimuli were a set of 56 photographs that depicted seven basic emotions: sadness, anger, happiness, disgust, surprise, fear, and neutral faces. The average age of the participants was 33.4 ± 10.5 years. The rate of recognizing the disgusted facial expression increased significantly after ECT (p < 0.05) and no significant changes were found in the rest of the facial expressions (p > 0.05). After the ECT, the time period of responding to the fear and happy facial expressions were significantly shorter (p < 0.05). Facial emotion recognition ability is an important social cognitive skill for social harmony, proper relation and living independently. At least, the ECT sessions do not seem to affect facial emotion recognition ability negatively and seem to improve identifying disgusted facial emotion which is related with dopamine enriched regions in brain.

Violent media consumption and the recognition of dynamic facial expressions.

PubMed

Kirsh, Steven J; Mounts, Jeffrey R W; Olczak, Paul V

2006-05-01

This study assessed the speed of recognition of facial emotional expressions (happy and angry) as a function of violent media consumption. Color photos of calm facial expressions morphed to either an angry or a happy facial expression. Participants were asked to make a speeded identification of the emotion (happiness or anger) during the morph. Results indicated that, independent of trait aggressiveness, participants high in violent media consumption responded slower to depictions of happiness and faster to depictions of anger than participants low in violent media consumption. Implications of these findings are discussed with respect to current models of aggressive behavior.

Emotion Recognition in Animated Compared to Human Stimuli in Adolescents with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Brosnan, Mark; Johnson, Hilary; Grawmeyer, Beate; Chapman, Emma; Benton, Laura

2015-01-01

There is equivocal evidence as to whether there is a deficit in recognising emotional expressions in Autism spectrum disorder (ASD). This study compared emotion recognition in ASD in three types of emotion expression media (still image, dynamic image, auditory) across human stimuli (e.g. photo of a human face) and animated stimuli (e.g. cartoon…

How does aging affect recognition-based inference? A hierarchical Bayesian modeling approach.

PubMed

Horn, Sebastian S; Pachur, Thorsten; Mata, Rui

2015-01-01

The recognition heuristic (RH) is a simple strategy for probabilistic inference according to which recognized objects are judged to score higher on a criterion than unrecognized objects. In this article, a hierarchical Bayesian extension of the multinomial r-model is applied to measure use of the RH on the individual participant level and to re-evaluate differences between younger and older adults' strategy reliance across environments. Further, it is explored how individual r-model parameters relate to alternative measures of the use of recognition and other knowledge, such as adherence rates and indices from signal-detection theory (SDT). Both younger and older adults used the RH substantially more often in an environment with high than low recognition validity, reflecting adaptivity in strategy use across environments. In extension of previous analyses (based on adherence rates), hierarchical modeling revealed that in an environment with low recognition validity, (a) older adults had a stronger tendency than younger adults to rely on the RH and (b) variability in RH use between individuals was larger than in an environment with high recognition validity; variability did not differ between age groups. Further, the r-model parameters correlated moderately with an SDT measure expressing how well people can discriminate cases where the RH leads to a correct vs. incorrect inference; this suggests that the r-model and the SDT measures may offer complementary insights into the use of recognition in decision making. In conclusion, younger and older adults are largely adaptive in their application of the RH, but cognitive aging may be associated with an increased tendency to rely on this strategy. Copyright © 2014 Elsevier B.V. All rights reserved.

Recognizing Spoken Words: The Neighborhood Activation Model

PubMed Central

Luce, Paul A.; Pisoni, David B.

2012-01-01

Objective A fundamental problem in the study of human spoken word recognition concerns the structural relations among the sound patterns of words in memory and the effects these relations have on spoken word recognition. In the present investigation, computational and experimental methods were employed to address a number of fundamental issues related to the representation and structural organization of spoken words in the mental lexicon and to lay the groundwork for a model of spoken word recognition. Design Using a computerized lexicon consisting of transcriptions of 20,000 words, similarity neighborhoods for each of the transcriptions were computed. Among the variables of interest in the computation of the similarity neighborhoods were: 1) the number of words occurring in a neighborhood, 2) the degree of phonetic similarity among the words, and 3) the frequencies of occurrence of the words in the language. The effects of these variables on auditory word recognition were examined in a series of behavioral experiments employing three experimental paradigms: perceptual identification of words in noise, auditory lexical decision, and auditory word naming. Results The results of each of these experiments demonstrated that the number and nature of words in a similarity neighborhood affect the speed and accuracy of word recognition. A neighborhood probability rule was developed that adequately predicted identification performance. This rule, based on Luce's (1959) choice rule, combines stimulus word intelligibility, neighborhood confusability, and frequency into a single expression. Based on this rule, a model of auditory word recognition, the neighborhood activation model, was proposed. This model describes the effects of similarity neighborhood structure on the process of discriminating among the acoustic-phonetic representations of words in memory. The results of these experiments have important implications for current conceptions of auditory word recognition in normal and hearing impaired populations of children and adults. PMID:9504270

The method for froth floatation condition recognition based on adaptive feature weighted

NASA Astrophysics Data System (ADS)

Wang, Jieran; Zhang, Jun; Tian, Jinwen; Zhang, Daimeng; Liu, Xiaomao

2018-03-01

The fusion of foam characteristics can play a complementary role in expressing the content of foam image. The weight of foam characteristics is the key to make full use of the relationship between the different features. In this paper, an Adaptive Feature Weighted Method For Froth Floatation Condition Recognition is proposed. Foam features without and with weights are both classified by using support vector machine (SVM).The classification accuracy and optimal equaling algorithm under the each ore grade are regarded as the result of the adaptive feature weighting algorithm. At the same time the effectiveness of adaptive weighted method is demonstrated.

Body Emotion Recognition Disproportionately Depends on Vertical Orientations during Childhood

ERIC Educational Resources Information Center

Balas, Benjamin; Auen, Amanda; Saville, Alyson; Schmidt, Jamie

2018-01-01

Children's ability to recognize emotional expressions from faces and bodies develops during childhood. However, the low-level features that support accurate body emotion recognition during development have not been well characterized. This is in marked contrast to facial emotion recognition, which is known to depend upon specific spatial frequency…

Neonatal paternal deprivation impairs social recognition and alters levels of oxytocin and estrogen receptor α mRNA expression in the MeA and NAcc, and serum oxytocin in mandarin voles.

PubMed

Cao, Yan; Wu, Ruiyong; Tai, Fadao; Zhang, Xia; Yu, Peng; An, Xiaolei; Qiao, Xufeng; Hao, Ping

2014-01-01

Paternal care is necessary for the healthy development of social behavior in monogamous rodents and social recognition underpins social behavior in these animals. The effects of paternal care on the development of social recognition and underlying neuroendocrine mechanisms, especially the involvement of oxytocin and estrogen pathways, remain poorly understood. We investigated the effects of paternal deprivation (PD: father was removed from neonatal pups and mother alone raised the offspring) on social recognition in mandarin voles (Microtus mandarinus), a socially monogamous rodent. Paternal deprivation was found to inhibit the development of social recognition in female and male offspring according to a habituation-dishabituation paradigm. Paternal deprivation resulted in increased inactivity and reduced investigation during new encounters with other animals. Paternal deprivation reduced oxytocin receptor (OTR) and estrogen receptor α (ERα) mRNA expression in the medial amygdala and nucleus accumbens. Paternal deprivation reduced serum oxytocin (OT) concentration in females, but had no effect on males. Our results provide substantial evidence that paternal deprivation inhibits the development of social recognition in female and male mandarin voles and alters social behavior later in life. This is possibly the result of altered expression of central OTR and ERα and serum OT levels caused by paternal deprivation. Copyright © 2013 Elsevier Inc. All rights reserved.

The level of cognitive function and recognition of emotions in older adults

PubMed Central

Singh-Manoux, Archana; Batty, G. David; Ebmeier, Klaus P.; Jokela, Markus; Harmer, Catherine J.; Kivimäki, Mika

2017-01-01

Background The association between cognitive decline and the ability to recognise emotions in interpersonal communication is not well understood. We aimed to investigate the association between cognitive function and the ability to recognise emotions in other people’s facial expressions across the full continuum of cognitive capacity. Methods Cross-sectional analysis of 4039 participants (3016 men, 1023 women aged 59 to 82 years) in the Whitehall II study. Cognitive function was assessed using a 30-item Mini-Mental State Examination (MMSE), further classified into 8 groups: 30, 29, 28, 27, 26, 25, 24, and <24 (possible dementia) MMSE points. The Facial Expression Recognition Task (FERT) was used to examine recognition of anger, fear, disgust, sadness, and happiness. Results The multivariable adjusted difference in the percentage of accurate recognition between the highest and lowest MMSE group was 14.9 (95%CI, 11.1–18.7) for anger, 15.5 (11.9–19.2) for fear, 18.5 (15.2–21.8) for disgust, 11.6 (7.3–16.0) for sadness, and 6.3 (3.1–9.4) for happiness. However, recognition of several emotions was reduced already after 1 to 2-point reduction in MMSE and with further points down in MMSE, the recognition worsened at an accelerated rate. Conclusions The ability to recognize emotion in facial expressions is affected at an early stage of cognitive impairment and might decline at an accelerated rate with the deterioration of cognitive function. Accurate recognition of happiness seems to be less affected by a severe decline in cognitive performance than recognition of negatively valued emotions. PMID:28977015

Inconsistent emotion recognition deficits across stimulus modalities in Huntington׳s disease.

PubMed

Rees, Elin M; Farmer, Ruth; Cole, James H; Henley, Susie M D; Sprengelmeyer, Reiner; Frost, Chris; Scahill, Rachael I; Hobbs, Nicola Z; Tabrizi, Sarah J

2014-11-01

Recognition of negative emotions is impaired in Huntington׳s Disease (HD). It is unclear whether these emotion-specific problems are driven by dissociable cognitive deficits, emotion complexity, test cue difficulty, or visuoperceptual impairments. This study set out to further characterise emotion recognition in HD by comparing patterns of deficits across stimulus modalities; notably including for the first time in HD, the more ecologically and clinically relevant modality of film clips portraying dynamic facial expressions. Fifteen early HD and 17 control participants were tested on emotion recognition from static facial photographs, non-verbal vocal expressions and one second dynamic film clips, all depicting different emotions. Statistically significant evidence of impairment of anger, disgust and fear recognition was seen in HD participants compared with healthy controls across multiple stimulus modalities. The extent of the impairment, as measured by the difference in the number of errors made between HD participants and controls, differed according to the combination of emotion and modality (p=0.013, interaction test). The largest between-group difference was seen in the recognition of anger from film clips. Consistent with previous reports, anger, disgust and fear were the most poorly recognised emotions by the HD group. This impairment did not appear to be due to task demands or expression complexity as the pattern of between-group differences did not correspond to the pattern of errors made by either group; implicating emotion-specific cognitive processing pathology. There was however evidence that the extent of emotion recognition deficits significantly differed between stimulus modalities. The implications in terms of designing future tests of emotion recognition and care giving are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

Interactive object recognition assistance: an approach to recognition starting from target objects

NASA Astrophysics Data System (ADS)

Geisler, Juergen; Littfass, Michael

1999-07-01

Recognition of target objects in remotely sensed imagery required detailed knowledge about the target object domain as well as about mapping properties of the sensing system. The art of object recognition is to combine both worlds appropriately and to provide models of target appearance with respect to sensor characteristics. Common approaches to support interactive object recognition are either driven from the sensor point of view and address the problem of displaying images in a manner adequate to the sensing system. Or they focus on target objects and provide exhaustive encyclopedic information about this domain. Our paper discusses an approach to assist interactive object recognition based on knowledge about target objects and taking into account the significance of object features with respect to characteristics of the sensed imagery, e.g. spatial and spectral resolution. An `interactive recognition assistant' takes the image analyst through the interpretation process by indicating step-by-step the respectively most significant features of objects in an actual set of candidates. The significance of object features is expressed by pregenerated trees of significance, and by the dynamic computation of decision relevance for every feature at each step of the recognition process. In the context of this approach we discuss the question of modeling and storing the multisensorial/multispectral appearances of target objects and object classes as well as the problem of an adequate dynamic human-machine-interface that takes into account various mental models of human image interpretation.

Modulation of α power and functional connectivity during facial affect recognition.

PubMed

Popov, Tzvetan; Miller, Gregory A; Rockstroh, Brigitte; Weisz, Nathan

2013-04-03

Research has linked oscillatory activity in the α frequency range, particularly in sensorimotor cortex, to processing of social actions. Results further suggest involvement of sensorimotor α in the processing of facial expressions, including affect. The sensorimotor face area may be critical for perception of emotional face expression, but the role it plays is unclear. The present study sought to clarify how oscillatory brain activity contributes to or reflects processing of facial affect during changes in facial expression. Neuromagnetic oscillatory brain activity was monitored while 30 volunteers viewed videos of human faces that changed their expression from neutral to fearful, neutral, or happy expressions. Induced changes in α power during the different morphs, source analysis, and graph-theoretic metrics served to identify the role of α power modulation and cross-regional coupling by means of phase synchrony during facial affect recognition. Changes from neutral to emotional faces were associated with a 10-15 Hz power increase localized in bilateral sensorimotor areas, together with occipital power decrease, preceding reported emotional expression recognition. Graph-theoretic analysis revealed that, in the course of a trial, the balance between sensorimotor power increase and decrease was associated with decreased and increased transregional connectedness as measured by node degree. Results suggest that modulations in α power facilitate early registration, with sensorimotor cortex including the sensorimotor face area largely functionally decoupled and thereby protected from additional, disruptive input and that subsequent α power decrease together with increased connectedness of sensorimotor areas facilitates successful facial affect recognition.

Understanding amygdala responsiveness to fearful expressions through the lens of psychopathy and altruism.

PubMed

Marsh, Abigail A

2016-06-01

Because the face is the central focus of human social interactions, emotional facial expressions provide a unique window into the emotional lives of others. They play a particularly important role in fostering empathy, which entails understanding and responding to others' emotions, especially distress-related emotions such as fear. This Review considers how fearful facial as well as vocal and postural expressions are interpreted, with an emphasis on the role of the amygdala. The amygdala may be best known for its role in the acquisition and expression of conditioned fear, but it also supports the perception and recognition of others' fear. Various explanations have been supplied for the amygdala's role in interpreting and responding to fearful expressions. They include theories that amygdala responses to fearful expressions 1) reflect heightened vigilance in response to uncertain danger, 2) promote heightened attention to the eye region of faces, 3) represent a response to an unconditioned aversive stimulus, or 4) reflect the generation of an empathic fear response. Among these, only empathic fear explains why amygdala lesions would impair fear recognition across modalities. Supporting the possibility of a link between fundamental empathic processes and amygdala responses to fear is evidence that impaired fear recognition in psychopathic individuals results from amygdala dysfunction, whereas enhanced fear recognition in altruistic individuals results from enhanced amygdala function. Empathic concern and caring behaviors may be fostered by sensitivity to signs of acute distress in others, which relies on intact functioning of the amygdala. © 2015 Wiley Periodicals, Inc.

Antibody recognition of porcine circovirus type 2 capsid protein epitopes after vaccination, infection, and disease

USDA-ARS?s Scientific Manuscript database

Open reading frame 2 (ORF2) of porcine circovirus type 2 (PCV2) codes for the 233-amino-acid capsid protein (CP). Baculovirus-based vaccines that express only ORF2 are protective against clinical disease following experimental challenge or natural infection. The goal of this study was to identify re...

Facial Emotion Recognition and Expression in Parkinson’s Disease: An Emotional Mirror Mechanism?

PubMed Central

Ricciardi, Lucia; Visco-Comandini, Federica; Erro, Roberto; Morgante, Francesca; Bologna, Matteo; Fasano, Alfonso; Ricciardi, Diego; Edwards, Mark J.; Kilner, James

2017-01-01

Background and aim Parkinson’s disease (PD) patients have impairment of facial expressivity (hypomimia) and difficulties in interpreting the emotional facial expressions produced by others, especially for aversive emotions. We aimed to evaluate the ability to produce facial emotional expressions and to recognize facial emotional expressions produced by others in a group of PD patients and a group of healthy participants in order to explore the relationship between these two abilities and any differences between the two groups of participants. Methods Twenty non-demented, non-depressed PD patients and twenty healthy participants (HC) matched for demographic characteristics were studied. The ability of recognizing emotional facial expressions was assessed with the Ekman 60-faces test (Emotion recognition task). Participants were video-recorded while posing facial expressions of 6 primary emotions (happiness, sadness, surprise, disgust, fear and anger). The most expressive pictures for each emotion were derived from the videos. Ten healthy raters were asked to look at the pictures displayed on a computer-screen in pseudo-random fashion and to identify the emotional label in a six-forced-choice response format (Emotion expressivity task). Reaction time (RT) and accuracy of responses were recorded. At the end of each trial the participant was asked to rate his/her confidence in his/her perceived accuracy of response. Results For emotion recognition, PD reported lower score than HC for Ekman total score (p<0.001), and for single emotions sub-scores happiness, fear, anger, sadness (p<0.01) and surprise (p = 0.02). In the facial emotion expressivity task, PD and HC significantly differed in the total score (p = 0.05) and in the sub-scores for happiness, sadness, anger (all p<0.001). RT and the level of confidence showed significant differences between PD and HC for the same emotions. There was a significant positive correlation between the emotion facial recognition and expressivity in both groups; the correlation was even stronger when ranking emotions from the best recognized to the worst (R = 0.75, p = 0.004). Conclusions PD patients showed difficulties in recognizing emotional facial expressions produced by others and in posing facial emotional expressions compared to healthy subjects. The linear correlation between recognition and expression in both experimental groups suggests that the two mechanisms share a common system, which could be deteriorated in patients with PD. These results open new clinical and rehabilitation perspectives. PMID:28068393

Identification of Emotional Facial Expressions: Effects of Expression, Intensity, and Sex on Eye Gaze.

PubMed

Wells, Laura Jean; Gillespie, Steven Mark; Rotshtein, Pia

2016-01-01

The identification of emotional expressions is vital for social interaction, and can be affected by various factors, including the expressed emotion, the intensity of the expression, the sex of the face, and the gender of the observer. This study investigates how these factors affect the speed and accuracy of expression recognition, as well as dwell time on the two most significant areas of the face: the eyes and the mouth. Participants were asked to identify expressions from female and male faces displaying six expressions (anger, disgust, fear, happiness, sadness, and surprise), each with three levels of intensity (low, moderate, and normal). Overall, responses were fastest and most accurate for happy expressions, but slowest and least accurate for fearful expressions. More intense expressions were also classified most accurately. Reaction time showed a different pattern, with slowest response times recorded for expressions of moderate intensity. Overall, responses were slowest, but also most accurate, for female faces. Relative to male observers, women showed greater accuracy and speed when recognizing female expressions. Dwell time analyses revealed that attention to the eyes was about three times greater than on the mouth, with fearful eyes in particular attracting longer dwell times. The mouth region was attended to the most for fearful, angry, and disgusted expressions and least for surprise. These results extend upon previous findings to show important effects of expression, emotion intensity, and sex on expression recognition and gaze behaviour, and may have implications for understanding the ways in which emotion recognition abilities break down.

Identification of Emotional Facial Expressions: Effects of Expression, Intensity, and Sex on Eye Gaze

PubMed Central

Rotshtein, Pia

2016-01-01

The identification of emotional expressions is vital for social interaction, and can be affected by various factors, including the expressed emotion, the intensity of the expression, the sex of the face, and the gender of the observer. This study investigates how these factors affect the speed and accuracy of expression recognition, as well as dwell time on the two most significant areas of the face: the eyes and the mouth. Participants were asked to identify expressions from female and male faces displaying six expressions (anger, disgust, fear, happiness, sadness, and surprise), each with three levels of intensity (low, moderate, and normal). Overall, responses were fastest and most accurate for happy expressions, but slowest and least accurate for fearful expressions. More intense expressions were also classified most accurately. Reaction time showed a different pattern, with slowest response times recorded for expressions of moderate intensity. Overall, responses were slowest, but also most accurate, for female faces. Relative to male observers, women showed greater accuracy and speed when recognizing female expressions. Dwell time analyses revealed that attention to the eyes was about three times greater than on the mouth, with fearful eyes in particular attracting longer dwell times. The mouth region was attended to the most for fearful, angry, and disgusted expressions and least for surprise. These results extend upon previous findings to show important effects of expression, emotion intensity, and sex on expression recognition and gaze behaviour, and may have implications for understanding the ways in which emotion recognition abilities break down. PMID:27942030

Associations between facial emotion recognition and young adolescents’ behaviors in bullying

PubMed Central

Gini, Gianluca; Altoè, Gianmarco

2017-01-01

This study investigated whether different behaviors young adolescents can act during bullying episodes were associated with their ability to recognize morphed facial expressions of the six basic emotions, expressed at high and low intensity. The sample included 117 middle-school students (45.3% girls; mean age = 12.4 years) who filled in a peer nomination questionnaire and individually performed a computerized emotion recognition task. Bayesian generalized mixed-effects models showed a complex picture, in which type and intensity of emotions, students’ behavior and gender interacted in explaining recognition accuracy. Results were discussed with a particular focus on negative emotions and suggesting a “neutral” nature of emotion recognition ability, which does not necessarily lead to moral behavior but can also be used for pursuing immoral goals. PMID:29131871

Actively paranoid patients with schizophrenia over attribute anger to neutral faces.

PubMed

Pinkham, Amy E; Brensinger, Colleen; Kohler, Christian; Gur, Raquel E; Gur, Ruben C

2011-02-01

Previous investigations of the influence of paranoia on facial affect recognition in schizophrenia have been inconclusive as some studies demonstrate better performance for paranoid relative to non-paranoid patients and others show that paranoid patients display greater impairments. These studies have been limited by small sample sizes and inconsistencies in the criteria used to define groups. Here, we utilized an established emotion recognition task and a large sample to examine differential performance in emotion recognition ability between patients who were actively paranoid (AP) and those who were not actively paranoid (NAP). Accuracy and error patterns on the Penn Emotion Recognition test (ER40) were examined in 132 patients (64 NAP and 68 AP). Groups were defined based on the presence of paranoid ideation at the time of testing rather than diagnostic subtype. AP and NAP patients did not differ in overall task accuracy; however, an emotion by group interaction indicated that AP patients were significantly worse than NAP patients at correctly labeling neutral faces. A comparison of error patterns on neutral stimuli revealed that the groups differed only in misattributions of anger expressions, with AP patients being significantly more likely to misidentify a neutral expression as angry. The present findings suggest that paranoia is associated with a tendency to over attribute threat to ambiguous stimuli and also lend support to emerging hypotheses of amygdala hyperactivation as a potential neural mechanism for paranoid ideation. Copyright © 2010 Elsevier B.V. All rights reserved.

Children's understanding of facial expression of emotion: II. Drawing of emotion-faces.

PubMed

Missaghi-Lakshman, M; Whissell, C

1991-06-01

67 children from Grades 2, 4, and 7 drew faces representing the emotional expressions of fear, anger, surprise, disgust, happiness, and sadness. The children themselves and 29 adults later decoded the drawings in an emotion-recognition task. Children were the more accurate decoders, and their accuracy and the accuracy of adults increased significantly for judgments of 7th-grade drawings. The emotions happy and sad were most accurately decoded. There were no significant differences associated with sex. In their drawings, children utilized a symbol system that seems to be based on a highlighting or exaggeration of features of the innately governed facial expression of emotion.

[Face recognition in patients with schizophrenia].

PubMed

Doi, Hirokazu; Shinohara, Kazuyuki

2012-07-01

It is well known that patients with schizophrenia show severe deficiencies in social communication skills. These deficiencies are believed to be partly derived from abnormalities in face recognition. However, the exact nature of these abnormalities exhibited by schizophrenic patients with respect to face recognition has yet to be clarified. In the present paper, we review the main findings on face recognition deficiencies in patients with schizophrenia, particularly focusing on abnormalities in the recognition of facial expression and gaze direction, which are the primary sources of information of others' mental states. The existing studies reveal that the abnormal recognition of facial expression and gaze direction in schizophrenic patients is attributable to impairments in both perceptual processing of visual stimuli, and cognitive-emotional responses to social information. Furthermore, schizophrenic patients show malfunctions in distributed neural regions, ranging from the fusiform gyrus recruited in the structural encoding of facial stimuli, to the amygdala which plays a primary role in the detection of the emotional significance of stimuli. These findings were obtained from research in patient groups with heterogeneous characteristics. Because previous studies have indicated that impairments in face recognition in schizophrenic patients might vary according to the types of symptoms, it is of primary importance to compare the nature of face recognition deficiencies and the impairments of underlying neural functions across sub-groups of patients.

Degraded Impairment of Emotion Recognition in Parkinson's Disease Extends from Negative to Positive Emotions.

PubMed

Lin, Chia-Yao; Tien, Yi-Min; Huang, Jong-Tsun; Tsai, Chon-Haw; Hsu, Li-Chuan

2016-01-01

Because of dopaminergic neurodegeneration, patients with Parkinson's disease (PD) show impairment in the recognition of negative facial expressions. In the present study, we aimed to determine whether PD patients with more advanced motor problems would show a much greater deficit in recognition of emotional facial expressions than a control group and whether impairment of emotion recognition would extend to positive emotions. Twenty-nine PD patients and 29 age-matched healthy controls were recruited. Participants were asked to discriminate emotions in Experiment  1 and identify gender in Experiment  2. In Experiment  1, PD patients demonstrated a recognition deficit for negative (sadness and anger) and positive faces. Further analysis showed that only PD patients with high motor dysfunction performed poorly in recognition of happy faces. In Experiment  2, PD patients showed an intact ability for gender identification, and the results eliminated possible abilities in the functions measured in Experiment  2 as alternative explanations for the results of Experiment  1. We concluded that patients' ability to recognize emotions deteriorated as the disease progressed. Recognition of negative emotions was impaired first, and then the impairment extended to positive emotions.

Degraded Impairment of Emotion Recognition in Parkinson's Disease Extends from Negative to Positive Emotions

PubMed Central

Tien, Yi-Min; Huang, Jong-Tsun

2016-01-01

Because of dopaminergic neurodegeneration, patients with Parkinson's disease (PD) show impairment in the recognition of negative facial expressions. In the present study, we aimed to determine whether PD patients with more advanced motor problems would show a much greater deficit in recognition of emotional facial expressions than a control group and whether impairment of emotion recognition would extend to positive emotions. Twenty-nine PD patients and 29 age-matched healthy controls were recruited. Participants were asked to discriminate emotions in Experiment  1 and identify gender in Experiment  2. In Experiment  1, PD patients demonstrated a recognition deficit for negative (sadness and anger) and positive faces. Further analysis showed that only PD patients with high motor dysfunction performed poorly in recognition of happy faces. In Experiment  2, PD patients showed an intact ability for gender identification, and the results eliminated possible abilities in the functions measured in Experiment  2 as alternative explanations for the results of Experiment  1. We concluded that patients' ability to recognize emotions deteriorated as the disease progressed. Recognition of negative emotions was impaired first, and then the impairment extended to positive emotions. PMID:27555668

Age differences in right-wing authoritarianism and their relation to emotion recognition.

PubMed

Ruffman, Ted; Wilson, Marc; Henry, Julie D; Dawson, Abigail; Chen, Yan; Kladnitski, Natalie; Myftari, Ella; Murray, Janice; Halberstadt, Jamin; Hunter, John A

2016-03-01

This study examined the correlates of right-wing authoritarianism (RWA) in older adults. Participants were given tasks measuring emotion recognition, executive functions and fluid IQ and questionnaires measuring RWA, perceived threat and social dominance orientation. Study 1 established higher age-related RWA across the age span in more than 2,600 New Zealanders. Studies 2 to 4 found that threat, education, social dominance and age all predicted unique variance in older adults' RWA, but the most consistent predictor was emotion recognition, predicting unique variance in older adults' RWA independent of all other variables. We argue that older adults' worse emotion recognition is associated with a more general change in social judgment. Expression of extreme attitudes (right- or left-wing) has the potential to antagonize others, but worse emotion recognition means that subtle signals will not be perceived, making the expression of extreme attitudes more likely. Our findings are consistent with other studies showing that worsening emotion recognition underlies age-related declines in verbosity, understanding of social gaffes, and ability to detect lies. Such results indicate that emotion recognition is a core social insight linked to many aspects of social cognition. (c) 2016 APA, all rights reserved).

Fear recognition impairment in early-stage Alzheimer's disease: when focusing on the eyes region improves performance.

PubMed

Hot, Pascal; Klein-Koerkamp, Yanica; Borg, Céline; Richard-Mornas, Aurélie; Zsoldos, Isabella; Paignon Adeline, Adeline; Thomas Antérion, Catherine; Baciu, Monica

2013-06-01

A decline in the ability to identify fearful expression has been frequently reported in patients with Alzheimer's disease (AD). In patients with severe destruction of the bilateral amygdala, similar difficulties have been reduced by using an explicit visual exploration strategy focusing on gaze. The current study assessed the possibility of applying a similar strategy in AD patients to improve fear recognition. It also assessed the possibility of improving fear recognition when a visual exploration strategy induced AD patients to process the eyes region. Seventeen patients with mild AD and 34 healthy subjects (17 young adults and 17 older adults) performed a classical task of emotional identification of faces expressing happiness, anger, and fear in two conditions: The face appeared progressively from the eyes region to the periphery (eyes region condition) or it appeared as a whole (global condition). Specific impairment in identifying a fearful expression was shown in AD patients compared with older adult controls during the global condition. Fear expression recognition was significantly improved in AD patients during the eyes region condition, in which they performed similarly to older adult controls. Our results suggest that using a different strategy of face exploration, starting first with processing of the eyes region, may compensate for a fear recognition deficit in AD patients. Findings suggest that a part of this deficit could be related to visuo-perceptual impairments. Additionally, these findings suggest that the decline of fearful face recognition reported in both normal aging and in AD may result from impairment of non-amygdalar processing in both groups and impairment of amygdalar-dependent processing in AD. Copyright © 2013 Elsevier Inc. All rights reserved.

Is the emotion recognition deficit associated with frontotemporal dementia caused by selective inattention to diagnostic facial features?

PubMed

Oliver, Lindsay D; Virani, Karim; Finger, Elizabeth C; Mitchell, Derek G V

2014-07-01

Frontotemporal dementia (FTD) is a debilitating neurodegenerative disorder characterized by severely impaired social and emotional behaviour, including emotion recognition deficits. Though fear recognition impairments seen in particular neurological and developmental disorders can be ameliorated by reallocating attention to critical facial features, the possibility that similar benefits can be conferred to patients with FTD has yet to be explored. In the current study, we examined the impact of presenting distinct regions of the face (whole face, eyes-only, and eyes-removed) on the ability to recognize expressions of anger, fear, disgust, and happiness in 24 patients with FTD and 24 healthy controls. A recognition deficit was demonstrated across emotions by patients with FTD relative to controls. Crucially, removal of diagnostic facial features resulted in an appropriate decline in performance for both groups; furthermore, patients with FTD demonstrated a lack of disproportionate improvement in emotion recognition accuracy as a result of isolating critical facial features relative to controls. Thus, unlike some neurological and developmental disorders featuring amygdala dysfunction, the emotion recognition deficit observed in FTD is not likely driven by selective inattention to critical facial features. Patients with FTD also mislabelled negative facial expressions as happy more often than controls, providing further evidence for abnormalities in the representation of positive affect in FTD. This work suggests that the emotional expression recognition deficit associated with FTD is unlikely to be rectified by adjusting selective attention to diagnostic features, as has proven useful in other select disorders. Copyright © 2014 Elsevier Ltd. All rights reserved.

HSP90 inhibitor 17-DMAG enhances EphA2+ tumor cell recognition by specific CD8+ T cells

PubMed Central

Kawabe, Mayumi; Mandic, Maja; Taylor, Jennifer L.; Vasquez, Cecilia A.; Wesa, Amy K.; Neckers, Leonard M.; Storkus, Walter J.

2009-01-01

EphA2, a member of the receptor tyrosine kinase (RTK) family, is commonly expressed by a broad range of cancer types, where its level of (over)expression correlates with poor clinical outcome. Since tumor cell expressed EphA2 is a non-mutated “self” protein, specific CD8+ T cells are subject to self-tolerance mechanisms and typically exhibit only moderate-to-low functional avidity, rendering them marginally competent to recognize EphA2+ tumor cells in vitro or in vivo. We have recently reported that the ability of specific CD8+ T cells to recognize EphA2+ tumor cells can be augmented after the cancer cells are pretreated with EphA2 agonists that promote proteasomal degradation and upregulated expression of EphA2/class I complexes on the tumor cell membrane (Wesa et al., J. Immunol. 2008;181:7721-7). In the current study we show that treatment of EphA2+ tumor cells with the irreversible HSP90 inhibitor, 17-DMAG, similarly enhances their recognition by EphA2-specific CD8+ T cell lines and clones in vitro via a mechanism that is dependent on proteasome and TAP function, as well as, the retrotranslocation of EphA2 into the tumor cytoplasm. When 17-DMAG and agonist anti-EphA2 mAb are co-applied, T cell recognition of tumor cells is further increased over that observed for either agent alone. These studies suggest that EphA2 represents a novel HSP90 client protein and that the treatment of cancer patients with 17-DMAG-based “pulse” therapy may improve the anti-tumor efficacy of CD8+ T effector cells reactive against EphA2-derived epitopes. PMID:19690146

Engineering Translational Activators with CRISPR-Cas System.

PubMed

Du, Pei; Miao, Chensi; Lou, Qiuli; Wang, Zefeng; Lou, Chunbo

2016-01-15

RNA parts often serve as critical components in genetic engineering. Here we report a design of translational activators which is composed of an RNA endoribonuclease (Csy4) and two exchangeable RNA modules. Csy4, a member of Cas endoribonuclease, cleaves at a specific recognition site; this cleavage releases a cis-repressive RNA module (crRNA) from the masked ribosome binding site (RBS), which subsequently allows the downstream translation initiation. Unlike small RNA as a translational activator, the endoribonuclease-based activator is able to efficiently unfold the perfect RBS-crRNA pairing. As an exchangeable module, the crRNA-RBS duplex was forwardly and reversely engineered to modulate the dynamic range of translational activity. We further showed that Csy4 and its recognition site, together as a module, can also be replaced by orthogonal endoribonuclease-recognition site homologues. These modularly structured, high-performance translational activators would endow the programming of gene expression in the translation level with higher feasibility.

Glycan microarray analysis of the carbohydrate-recognition specificity of native and recombinant forms of the lectin ArtinM.

PubMed

Liu, Y; Cecílio, N T; Carvalho, F C; Roque-Barreira, M C; Feizi, T

2015-12-01

This article contains data related to the researc.h article entitled "Yeast-derived ArtinM shares structure, carbohydrate recognition, and biological effects with native ArtinM" by Cecílio et al. (2015) [1]. ArtinM, a D-mannose-binding lectin isolated from the seeds of Artocarpus heterophyllus, exerts immunomodulatory and regenerative activities through its Carbohydrate Recognition Domain (CRD) (Souza et al., 2013; Mariano et al., 2014 [2], [3]). The limited availability of the native lectin (n-ArtinM) led us to characterize a recombinant form of the protein, obtained by expression in Saccharomyces cerevisiae (y-ArtinM). We compared the carbohydrate-binding specificities of y-ArtinM and n-ArtinM by analyzing the binding of biotinylated preparations of the two lectin forms using a neoglycolipid (NGL)-based glycan microarray. Data showed that y-ArtinM mirrored the specificity exhibited by n-ArtinM.

Cooperation between Epstein-Barr Virus Immune Evasion Proteins Spreads Protection from CD8+ T Cell Recognition across All Three Phases of the Lytic Cycle

PubMed Central

Quinn, Laura L.; Zuo, Jianmin; Abbott, Rachel J. M.; Shannon-Lowe, Claire; Tierney, Rosemary J.; Hislop, Andrew D.; Rowe, Martin

2014-01-01

CD8+ T cell responses to Epstein-Barr virus (EBV) lytic cycle expressed antigens display a hierarchy of immunodominance, in which responses to epitopes of immediate-early (IE) and some early (E) antigens are more frequently observed than responses to epitopes of late (L) expressed antigens. It has been proposed that this hierarchy, which correlates with the phase-specific efficiency of antigen presentation, may be due to the influence of viral immune-evasion genes. At least three EBV-encoded genes, BNLF2a, BGLF5 and BILF1, have the potential to inhibit processing and presentation of CD8+ T cell epitopes. Here we examined the relative contribution of these genes to modulation of CD8+ T cell recognition of EBV lytic antigens expressed at different phases of the replication cycle in EBV-transformed B-cells (LCLs) which spontaneously reactivate lytic cycle. Selective shRNA-mediated knockdown of BNLF2a expression led to more efficient recognition of immediate-early (IE)- and early (E)-derived epitopes by CD8+ T cells, while knock down of BILF1 increased recognition of epitopes from E and late (L)-expressed antigens. Contrary to what might have been predicted from previous ectopic expression studies in EBV-negative model cell lines, the shRNA-mediated inhibition of BGLF5 expression in LCLs showed only modest, if any, increase in recognition of epitopes expressed in any phase of lytic cycle. These data indicate that whilst BNLF2a interferes with antigen presentation with diminishing efficiency as lytic cycle progresses (IE>E>>L), interference by BILF1 increases with progression through lytic cycle (IE

Strength Is in Numbers: Can Concordant Artificial Listeners Improve Prediction of Emotion from Speech?

PubMed

Martinelli, Eugenio; Mencattini, Arianna; Daprati, Elena; Di Natale, Corrado

2016-01-01

Humans can communicate their emotions by modulating facial expressions or the tone of their voice. Albeit numerous applications exist that enable machines to read facial emotions and recognize the content of verbal messages, methods for speech emotion recognition are still in their infancy. Yet, fast and reliable applications for emotion recognition are the obvious advancement of present 'intelligent personal assistants', and may have countless applications in diagnostics, rehabilitation and research. Taking inspiration from the dynamics of human group decision-making, we devised a novel speech emotion recognition system that applies, for the first time, a semi-supervised prediction model based on consensus. Three tests were carried out to compare this algorithm with traditional approaches. Labeling performances relative to a public database of spontaneous speeches are reported. The novel system appears to be fast, robust and less computationally demanding than traditional methods, allowing for easier implementation in portable voice-analyzers (as used in rehabilitation, research, industry, etc.) and for applications in the research domain (such as real-time pairing of stimuli to participants' emotional state, selective/differential data collection based on emotional content, etc.).

Age-congruency and contact effects in body expression recognition from point-light displays (PLD)

PubMed Central

Hermens, Frouke; Willmott, Alexander P.

2016-01-01

Recognition of older people’s body expressions is a crucial social skill. We here investigate how age, not just of the observer, but also of the observed individual, affects this skill. Age may influence the ability to recognize other people’s body expressions by changes in one’s own ability to perform certain action over the life-span (i.e., an own-age bias may occur, with best recognition for one’s own age). Whole body point light displays of children, young adults and older adults (>70 years) expressing six different emotions were presented to observers of the same three age-groups. Across two variations of the paradigm, no evidence for the predicted own-age bias (a cross-over interaction between one’s own age and the observed person’s age) was found. Instead, experience effects were found with children better recognizing older actors’ expressions of ‘active emotions,’ such as anger and happiness with greater exposure in daily life. Together, the findings suggest that age-related changes in one own’s mobility only influences body expression categorization in young children who interact frequently with older adults. PMID:27994986

Antennal transcriptome analysis of the Asian longhorned beetle Anoplophora glabripennis

PubMed Central

Hu, Ping; Wang, Jingzhen; Cui, Mingming; Tao, Jing; Luo, Youqing

2016-01-01

Olfactory proteins form the basis of insect olfactory recognition, which is crucial for host identification, mating, and oviposition. Using transcriptome analysis of Anoplophora glabripennis antenna, we identified 42 odorant-binding proteins (OBPs), 12 chemosensory proteins (CSPs), 14 pheromone-degrading enzymes (PDEs), 1 odorant-degrading enzymes (ODE), 37 odorant receptors (ORs), 11 gustatory receptors (GRs), 2 sensory neuron membrane proteins (SNMPs), and 4 ionotropic receptor (IR). All CSPs and PBPs were expressed in antennae, confirming the authenticity of the transcriptome data. CSP expression profiles showed that AglaCSP3, AglaCSP6, and AglaCSP12 were expressed preferentially in maxillary palps and AglaCSP7 and AglaCSP9 were strongly expressed in antennae. The vast majority of CSPs were highly expressed in multiple chemosensory tissues, suggesting their participation in olfactory recognition in almost all olfactory tissues. Intriguingly, the PBP AglaPBP2 was preferentially expressed in antenna, indicating that it is the main protein involved in efficient and sensitive pheromone recognition. Phylogenetic analysis of olfactory proteins indicated AglaGR1 may detect CO2. This study establishes a foundation for determining the chemoreception molecular mechanisms of A. glabripennis, which would provide a new perspective for controlling pest populations, especially those of borers. PMID:27222053

Bidirectional Modulation of Recognition Memory

PubMed Central

Ho, Jonathan W.; Poeta, Devon L.; Jacobson, Tara K.; Zolnik, Timothy A.; Neske, Garrett T.; Connors, Barry W.

2015-01-01

Perirhinal cortex (PER) has a well established role in the familiarity-based recognition of individual items and objects. For example, animals and humans with perirhinal damage are unable to distinguish familiar from novel objects in recognition memory tasks. In the normal brain, perirhinal neurons respond to novelty and familiarity by increasing or decreasing firing rates. Recent work also implicates oscillatory activity in the low-beta and low-gamma frequency bands in sensory detection, perception, and recognition. Using optogenetic methods in a spontaneous object exploration (SOR) task, we altered recognition memory performance in rats. In the SOR task, normal rats preferentially explore novel images over familiar ones. We modulated exploratory behavior in this task by optically stimulating channelrhodopsin-expressing perirhinal neurons at various frequencies while rats looked at novel or familiar 2D images. Stimulation at 30–40 Hz during looking caused rats to treat a familiar image as if it were novel by increasing time looking at the image. Stimulation at 30–40 Hz was not effective in increasing exploration of novel images. Stimulation at 10–15 Hz caused animals to treat a novel image as familiar by decreasing time looking at the image, but did not affect looking times for images that were already familiar. We conclude that optical stimulation of PER at different frequencies can alter visual recognition memory bidirectionally. SIGNIFICANCE STATEMENT Recognition of novelty and familiarity are important for learning, memory, and decision making. Perirhinal cortex (PER) has a well established role in the familiarity-based recognition of individual items and objects, but how novelty and familiarity are encoded and transmitted in the brain is not known. Perirhinal neurons respond to novelty and familiarity by changing firing rates, but recent work suggests that brain oscillations may also be important for recognition. In this study, we showed that stimulation of the PER could increase or decrease exploration of novel and familiar images depending on the frequency of stimulation. Our findings suggest that optical stimulation of PER at specific frequencies can predictably alter recognition memory. PMID:26424881

Affective theory of mind inferences contextually influence the recognition of emotional facial expressions.

PubMed

Stewart, Suzanne L K; Schepman, Astrid; Haigh, Matthew; McHugh, Rhian; Stewart, Andrew J

2018-03-14

The recognition of emotional facial expressions is often subject to contextual influence, particularly when the face and the context convey similar emotions. We investigated whether spontaneous, incidental affective theory of mind inferences made while reading vignettes describing social situations would produce context effects on the identification of same-valenced emotions (Experiment 1) as well as differently-valenced emotions (Experiment 2) conveyed by subsequently presented faces. Crucially, we found an effect of context on reaction times in both experiments while, in line with previous work, we found evidence for a context effect on accuracy only in Experiment 1. This demonstrates that affective theory of mind inferences made at the pragmatic level of a text can automatically, contextually influence the perceptual processing of emotional facial expressions in a separate task even when those emotions are of a distinctive valence. Thus, our novel findings suggest that language acts as a contextual influence to the recognition of emotional facial expressions for both same and different valences.

A self-organized learning strategy for object recognition by an embedded line of attraction

NASA Astrophysics Data System (ADS)

Seow, Ming-Jung; Alex, Ann T.; Asari, Vijayan K.

2012-04-01

For humans, a picture is worth a thousand words, but to a machine, it is just a seemingly random array of numbers. Although machines are very fast and efficient, they are vastly inferior to humans for everyday information processing. Algorithms that mimic the way the human brain computes and learns may be the solution. In this paper we present a theoretical model based on the observation that images of similar visual perceptions reside in a complex manifold in an image space. The perceived features are often highly structured and hidden in a complex set of relationships or high-dimensional abstractions. To model the pattern manifold, we present a novel learning algorithm using a recurrent neural network. The brain memorizes information using a dynamical system made of interconnected neurons. Retrieval of information is accomplished in an associative sense. It starts from an arbitrary state that might be an encoded representation of a visual image and converges to another state that is stable. The stable state is what the brain remembers. In designing a recurrent neural network, it is usually of prime importance to guarantee the convergence in the dynamics of the network. We propose to modify this picture: if the brain remembers by converging to the state representing familiar patterns, it should also diverge from such states when presented with an unknown encoded representation of a visual image belonging to a different category. That is, the identification of an instability mode is an indication that a presented pattern is far away from any stored pattern and therefore cannot be associated with current memories. These properties can be used to circumvent the plasticity-stability dilemma by using the fluctuating mode as an indicator to create new states. We capture this behavior using a novel neural architecture and learning algorithm, in which the system performs self-organization utilizing a stability mode and an instability mode for the dynamical system. Based on this observation we developed a self- organizing line attractor, which is capable of generating new lines in the feature space to learn unrecognized patterns. Experiments performed on UMIST pose database and CMU face expression variant database for face recognition have shown that the proposed nonlinear line attractor is able to successfully identify the individuals and it provided better recognition rate when compared to the state of the art face recognition techniques. Experiments on FRGC version 2 database has also provided excellent recognition rate in images captured in complex lighting environments. Experiments performed on the Japanese female face expression database and Essex Grimace database using the self organizing line attractor have also shown successful expression invariant face recognition. These results show that the proposed model is able to create nonlinear manifolds in a multidimensional feature space to distinguish complex patterns.

Action recognition in depth video from RGB perspective: A knowledge transfer manner

NASA Astrophysics Data System (ADS)

Chen, Jun; Xiao, Yang; Cao, Zhiguo; Fang, Zhiwen

2018-03-01

Different video modal for human action recognition has becoming a highly promising trend in the video analysis. In this paper, we propose a method for human action recognition from RGB video to Depth video using domain adaptation, where we use learned feature from RGB videos to do action recognition for depth videos. More specifically, we make three steps for solving this problem in this paper. First, different from image, video is more complex as it has both spatial and temporal information, in order to better encode this information, dynamic image method is used to represent each RGB or Depth video to one image, based on this, most methods for extracting feature in image can be used in video. Secondly, as video can be represented as image, so standard CNN model can be used for training and testing for videos, beside, CNN model can be also used for feature extracting as its powerful feature expressing ability. Thirdly, as RGB videos and Depth videos are belong to two different domains, in order to make two different feature domains has more similarity, domain adaptation is firstly used for solving this problem between RGB and Depth video, based on this, the learned feature from RGB video model can be directly used for Depth video classification. We evaluate the proposed method on one complex RGB-D action dataset (NTU RGB-D), and our method can have more than 2% accuracy improvement using domain adaptation from RGB to Depth action recognition.

Emotion recognition based on physiological changes in music listening.

PubMed

Kim, Jonghwa; André, Elisabeth

2008-12-01

Little attention has been paid so far to physiological signals for emotion recognition compared to audiovisual emotion channels such as facial expression or speech. This paper investigates the potential of physiological signals as reliable channels for emotion recognition. All essential stages of an automatic recognition system are discussed, from the recording of a physiological dataset to a feature-based multiclass classification. In order to collect a physiological dataset from multiple subjects over many weeks, we used a musical induction method which spontaneously leads subjects to real emotional states, without any deliberate lab setting. Four-channel biosensors were used to measure electromyogram, electrocardiogram, skin conductivity and respiration changes. A wide range of physiological features from various analysis domains, including time/frequency, entropy, geometric analysis, subband spectra, multiscale entropy, etc., is proposed in order to find the best emotion-relevant features and to correlate them with emotional states. The best features extracted are specified in detail and their effectiveness is proven by classification results. Classification of four musical emotions (positive/high arousal, negative/high arousal, negative/low arousal, positive/low arousal) is performed by using an extended linear discriminant analysis (pLDA). Furthermore, by exploiting a dichotomic property of the 2D emotion model, we develop a novel scheme of emotion-specific multilevel dichotomous classification (EMDC) and compare its performance with direct multiclass classification using the pLDA. Improved recognition accuracy of 95\\% and 70\\% for subject-dependent and subject-independent classification, respectively, is achieved by using the EMDC scheme.

Generating virtual training samples for sparse representation of face images and face recognition

NASA Astrophysics Data System (ADS)

Du, Yong; Wang, Yu

2016-03-01

There are many challenges in face recognition. In real-world scenes, images of the same face vary with changing illuminations, different expressions and poses, multiform ornaments, or even altered mental status. Limited available training samples cannot convey these possible changes in the training phase sufficiently, and this has become one of the restrictions to improve the face recognition accuracy. In this article, we view the multiplication of two images of the face as a virtual face image to expand the training set and devise a representation-based method to perform face recognition. The generated virtual samples really reflect some possible appearance and pose variations of the face. By multiplying a training sample with another sample from the same subject, we can strengthen the facial contour feature and greatly suppress the noise. Thus, more human essential information is retained. Also, uncertainty of the training data is simultaneously reduced with the increase of the training samples, which is beneficial for the training phase. The devised representation-based classifier uses both the original and new generated samples to perform the classification. In the classification phase, we first determine K nearest training samples for the current test sample by calculating the Euclidean distances between the test sample and training samples. Then, a linear combination of these selected training samples is used to represent the test sample, and the representation result is used to classify the test sample. The experimental results show that the proposed method outperforms some state-of-the-art face recognition methods.

[Emotional facial recognition difficulties as primary deficit in children with attention deficit hyperactivity disorder: a systematic review].

PubMed

Rodrigo-Ruiz, D; Perez-Gonzalez, J C; Cejudo, J

2017-08-16

It has recently been warned that children with attention deficit hyperactivity disorder (ADHD) show a deficit in emotional competence and emotional intelligence, specifically in their ability to emotional recognition. A systematic review of the scientific literature in reference to the emotional recognition of facial expressions in children with ADHD is presented in order to establish or rule the existence of emotional deficits as primary dysfunction in this disorder and, where appropriate, the effect size of the differences against normal development or neurotypical children. The results reveal the recent interest in the issue and the lack of information. Although there is no complete agreement, most of the studies show that emotional recognition of facial expressions is affected in children with ADHD, showing them significantly less accurate than children from control groups in recognizing emotions communicated through facial expressions. A part of these studies make comparisons on the recognition of different discrete emotions; having observed that children with ADHD tend to a greater difficulty recognizing negative emotions, especially anger, fear, and disgust. These results have direct implications for the educational and clinical diagnosis of ADHD; and for the educational intervention for children with ADHD, emotional education might entail an advantageous aid.

Gender differences in facial emotion recognition in persons with chronic schizophrenia.

PubMed

Weiss, Elisabeth M; Kohler, Christian G; Brensinger, Colleen M; Bilker, Warren B; Loughead, James; Delazer, Margarete; Nolan, Karen A

2007-03-01

The aim of the present study was to investigate possible sex differences in the recognition of facial expressions of emotion and to investigate the pattern of classification errors in schizophrenic males and females. Such an approach provides an opportunity to inspect the degree to which males and females differ in perceiving and interpreting the different emotions displayed to them and to analyze which emotions are most susceptible to recognition errors. Fifty six chronically hospitalized schizophrenic patients (38 men and 18 women) completed the Penn Emotion Recognition Test (ER40), a computerized emotion discrimination test presenting 40 color photographs of evoked happy, sad, anger, fear expressions and neutral expressions balanced for poser gender and ethnicity. We found a significant sex difference in the patterns of error rates in the Penn Emotion Recognition Test. Neutral faces were more commonly mistaken as angry in schizophrenic men, whereas schizophrenic women misinterpreted neutral faces more frequently as sad. Moreover, female faces were better recognized overall, but fear was better recognized in same gender photographs, whereas anger was better recognized in different gender photographs. The findings of the present study lend support to the notion that sex differences in aggressive behavior could be related to a cognitive style characterized by hostile attributions to neutral faces in schizophrenic men.

Does Facial Amimia Impact the Recognition of Facial Emotions? An EMG Study in Parkinson’s Disease

PubMed Central

Argaud, Soizic; Delplanque, Sylvain; Houvenaghel, Jean-François; Auffret, Manon; Duprez, Joan; Vérin, Marc; Grandjean, Didier; Sauleau, Paul

2016-01-01

According to embodied simulation theory, understanding other people’s emotions is fostered by facial mimicry. However, studies assessing the effect of facial mimicry on the recognition of emotion are still controversial. In Parkinson’s disease (PD), one of the most distinctive clinical features is facial amimia, a reduction in facial expressiveness, but patients also show emotional disturbances. The present study used the pathological model of PD to examine the role of facial mimicry on emotion recognition by investigating EMG responses in PD patients during a facial emotion recognition task (anger, joy, neutral). Our results evidenced a significant decrease in facial mimicry for joy in PD, essentially linked to the absence of reaction of the zygomaticus major and the orbicularis oculi muscles in response to happy avatars, whereas facial mimicry for expressions of anger was relatively preserved. We also confirmed that PD patients were less accurate in recognizing positive and neutral facial expressions and highlighted a beneficial effect of facial mimicry on the recognition of emotion. We thus provide additional arguments for embodied simulation theory suggesting that facial mimicry is a potential lever for therapeutic actions in PD even if it seems not to be necessarily required in recognizing emotion as such. PMID:27467393

Design and Evaluation of a Web-Based Symptom Monitoring Tool for Heart Failure.

PubMed

Wakefield, Bonnie J; Alexander, Gregory; Dohrmann, Mary; Richardson, James

2017-05-01

Heart failure is a chronic condition where symptom recognition and between-visit communication with providers are critical. Patients are encouraged to track disease-specific data, such as weight and shortness of breath. Use of a Web-based tool that facilitates data display in graph form may help patients recognize exacerbations and more easily communicate out-of-range data to clinicians. The purposes of this study were to (1) design a Web-based tool to facilitate symptom monitoring and symptom recognition in patients with chronic heart failure and (2) conduct a usability evaluation of the Web site. Patient participants generally had a positive view of the Web site and indicated it would support recording their health status and communicating with their doctors. Clinician participants generally had a positive view of the Web site and indicated it would be a potentially useful adjunct to electronic health delivery systems. Participants expressed a need to incorporate decision support within the site and wanted to add other data, for example, blood pressure, and have the ability to adjust font size. A few expressed concerns about data privacy and security. Technologies require careful design and testing to ensure they are useful, usable, and safe for patients and do not add to the burden of busy providers.

Astrocytes contribute to gamma oscillations and recognition memory.

PubMed

Lee, Hosuk Sean; Ghetti, Andrea; Pinto-Duarte, António; Wang, Xin; Dziewczapolski, Gustavo; Galimi, Francesco; Huitron-Resendiz, Salvador; Piña-Crespo, Juan C; Roberts, Amanda J; Verma, Inder M; Sejnowski, Terrence J; Heinemann, Stephen F

2014-08-12

Glial cells are an integral part of functional communication in the brain. Here we show that astrocytes contribute to the fast dynamics of neural circuits that underlie normal cognitive behaviors. In particular, we found that the selective expression of tetanus neurotoxin (TeNT) in astrocytes significantly reduced the duration of carbachol-induced gamma oscillations in hippocampal slices. These data prompted us to develop a novel transgenic mouse model, specifically with inducible tetanus toxin expression in astrocytes. In this in vivo model, we found evidence of a marked decrease in electroencephalographic (EEG) power in the gamma frequency range in awake-behaving mice, whereas neuronal synaptic activity remained intact. The reduction in cortical gamma oscillations was accompanied by impaired behavioral performance in the novel object recognition test, whereas other forms of memory, including working memory and fear conditioning, remained unchanged. These results support a key role for gamma oscillations in recognition memory. Both EEG alterations and behavioral deficits in novel object recognition were reversed by suppression of tetanus toxin expression. These data reveal an unexpected role for astrocytes as essential contributors to information processing and cognitive behavior.

Automated Assessment of Child Vocalization Development Using LENA.

PubMed

Richards, Jeffrey A; Xu, Dongxin; Gilkerson, Jill; Yapanel, Umit; Gray, Sharmistha; Paul, Terrance

2017-07-12

To produce a novel, efficient measure of children's expressive vocal development on the basis of automatic vocalization assessment (AVA), child vocalizations were automatically identified and extracted from audio recordings using Language Environment Analysis (LENA) System technology. Assessment was based on full-day audio recordings collected in a child's unrestricted, natural language environment. AVA estimates were derived using automatic speech recognition modeling techniques to categorize and quantify the sounds in child vocalizations (e.g., protophones and phonemes). These were expressed as phone and biphone frequencies, reduced to principal components, and inputted to age-based multiple linear regression models to predict independently collected criterion-expressive language scores. From these models, we generated vocal development AVA estimates as age-standardized scores and development age estimates. AVA estimates demonstrated strong statistical reliability and validity when compared with standard criterion expressive language assessments. Automated analysis of child vocalizations extracted from full-day recordings in natural settings offers a novel and efficient means to assess children's expressive vocal development. More research remains to identify specific mechanisms of operation.

Accurate landmarking of three-dimensional facial data in the presence of facial expressions and occlusions using a three-dimensional statistical facial feature model.

PubMed

Zhao, Xi; Dellandréa, Emmanuel; Chen, Liming; Kakadiaris, Ioannis A

2011-10-01

Three-dimensional face landmarking aims at automatically localizing facial landmarks and has a wide range of applications (e.g., face recognition, face tracking, and facial expression analysis). Existing methods assume neutral facial expressions and unoccluded faces. In this paper, we propose a general learning-based framework for reliable landmark localization on 3-D facial data under challenging conditions (i.e., facial expressions and occlusions). Our approach relies on a statistical model, called 3-D statistical facial feature model, which learns both the global variations in configurational relationships between landmarks and the local variations of texture and geometry around each landmark. Based on this model, we further propose an occlusion classifier and a fitting algorithm. Results from experiments on three publicly available 3-D face databases (FRGC, BU-3-DFE, and Bosphorus) demonstrate the effectiveness of our approach, in terms of landmarking accuracy and robustness, in the presence of expressions and occlusions.

Early pregnancy in the mare: old concepts revisited.

PubMed

Klein, C

2016-07-01

"Maternal recognition of pregnancy" (MRP) is commonly used to describe the ongoing embryo-maternal communication during early pregnancy that culminates in prevention of luteolysis and ensures ongoing progestin support. The conceptus-derived pregnancy recognition signal has not yet been identified in the mare. Although equine conceptuses produce substantial amounts of estrogens, there is a lack of evidence that estrogens are the pregnancy recognition signal in mares. Conceptus mobility is integral to MRP and is driven by conceptus-derived prostaglandin production. Cessation of conceptus mobility, referred to as fixation, is caused by increases in conceptus size and uterine tone and reduction in sialic acid content of the embryonic capsule. Gene expression profiling of equine preimplantation conceptuses revealed expression of neuraminidase 2 (NEU2), an enzyme that cleaves sialic acid from polysaccharide chains. Furthermore, secretion of NEU2 by conceptuses in vitro was functionally active; it appears therefore, that the conceptus itself regulates sialic acid content through expression of NEU2. Based on gene expression profiling, equine conceptuses express increasing amounts of fibrinogen during early development. Western blot analysis confirmed secretion of fibrinogen into culture medium when conceptuses were cultured in vitro and with immunohistochemistry, the acellular glycoprotein capsule of the conceptus had particularly intense staining for fibrinogen. Therefore, we hypothesize that conceptus-derived fibrinogen interacts with endometrial integrins to promote cessation of conceptus mobility and fixation. Indeed, next generation sequencing analysis of conceptus and endometrial samples 16 d after ovulation revealed that the integrin signaling pathway is significantly enriched in both sample types. Real-time reverse transcription polymerase chain reaction (RT-PCR) confirmed ITGAVB1 as the most abundant integrin receptor in endometrium; fibrinogen has the highest affinity for ITGAVB1 among integrins receptors to which it binds. Finally, the equine conceptus expresses increasing quantities of relaxin during preimplantation development, with the endometrium expressing relaxin receptors. In the pig, mouse, and human, relaxin is produced by the corpus luteum and is known to promote angiogenesis during early pregnancy. In summary, substantial advances in understanding MRP in the horse are underway. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

No differences in emotion recognition strategies in children with autism spectrum disorder: evidence from hybrid faces.

PubMed

Evers, Kris; Kerkhof, Inneke; Steyaert, Jean; Noens, Ilse; Wagemans, Johan

2014-01-01

Emotion recognition problems are frequently reported in individuals with an autism spectrum disorder (ASD). However, this research area is characterized by inconsistent findings, with atypical emotion processing strategies possibly contributing to existing contradictions. In addition, an attenuated saliency of the eyes region is often demonstrated in ASD during face identity processing. We wanted to compare reliance on mouth versus eyes information in children with and without ASD, using hybrid facial expressions. A group of six-to-eight-year-old boys with ASD and an age- and intelligence-matched typically developing (TD) group without intellectual disability performed an emotion labelling task with hybrid facial expressions. Five static expressions were used: one neutral expression and four emotional expressions, namely, anger, fear, happiness, and sadness. Hybrid faces were created, consisting of an emotional face half (upper or lower face region) with the other face half showing a neutral expression. Results showed no emotion recognition problem in ASD. Moreover, we provided evidence for the existence of top- and bottom-emotions in children: correct identification of expressions mainly depends on information in the eyes (so-called top-emotions: happiness) or in the mouth region (so-called bottom-emotions: sadness, anger, and fear). No stronger reliance on mouth information was found in children with ASD.

When Early Experiences Build a Wall to Others’ Emotions: An Electrophysiological and Autonomic Study

PubMed Central

Ardizzi, Martina; Martini, Francesca; Umiltà, Maria Alessandra; Sestito, Mariateresa; Ravera, Roberto; Gallese, Vittorio

2013-01-01

Facial expression of emotions is a powerful vehicle for communicating information about others’ emotional states and it normally induces facial mimicry in the observers. The aim of this study was to investigate if early aversive experiences could interfere with emotion recognition, facial mimicry, and with the autonomic regulation of social behaviors. We conducted a facial emotion recognition task in a group of “street-boys” and in an age-matched control group. We recorded facial electromyography (EMG), a marker of facial mimicry, and respiratory sinus arrhythmia (RSA), an index of the recruitment of autonomic system promoting social behaviors and predisposition, in response to the observation of facial expressions of emotions. Results showed an over-attribution of anger, and reduced EMG responses during the observation of both positive and negative expressions only among street-boys. Street-boys also showed lower RSA after observation of facial expressions and ineffective RSA suppression during presentation of non-threatening expressions. Our findings suggest that early aversive experiences alter not only emotion recognition but also facial mimicry of emotions. These deficits affect the autonomic regulation of social behaviors inducing lower social predisposition after the visualization of facial expressions and an ineffective recruitment of defensive behavior in response to non-threatening expressions. PMID:23593374

Heterogeneity of long-history migration predicts emotion recognition accuracy.

PubMed

Wood, Adrienne; Rychlowska, Magdalena; Niedenthal, Paula M

2016-06-01

Recent work (Rychlowska et al., 2015) demonstrated the power of a relatively new cultural dimension, historical heterogeneity, in predicting cultural differences in the endorsement of emotion expression norms. Historical heterogeneity describes the number of source countries that have contributed to a country's present-day population over the last 500 years. People in cultures originating from a large number of source countries may have historically benefited from greater and clearer emotional expressivity, because they lacked a common language and well-established social norms. We therefore hypothesized that in addition to endorsing more expressive display rules, individuals from heterogeneous cultures will also produce facial expressions that are easier to recognize by people from other cultures. By reanalyzing cross-cultural emotion recognition data from 92 papers and 82 cultures, we show that emotion expressions of people from heterogeneous cultures are more easily recognized by observers from other cultures than are the expressions produced in homogeneous cultures. Heterogeneity influences expression recognition rates alongside the individualism-collectivism of the perceivers' culture, as more individualistic cultures were more accurate in emotion judgments than collectivistic cultures. This work reveals the present-day behavioral consequences of long-term historical migration patterns and demonstrates the predictive power of historical heterogeneity. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Impaired holistic coding of facial expression and facial identity in congenital prosopagnosia.

PubMed

Palermo, Romina; Willis, Megan L; Rivolta, Davide; McKone, Elinor; Wilson, C Ellie; Calder, Andrew J

2011-04-01

We test 12 individuals with congenital prosopagnosia (CP), who replicate a common pattern of showing severe difficulty in recognising facial identity in conjunction with normal recognition of facial expressions (both basic and 'social'). Strength of holistic processing was examined using standard expression composite and identity composite tasks. Compared to age- and sex-matched controls, group analyses demonstrated that CPs showed weaker holistic processing, for both expression and identity information. Implications are (a) normal expression recognition in CP can derive from compensatory strategies (e.g., over-reliance on non-holistic cues to expression); (b) the split between processing of expression and identity information may take place after a common stage of holistic processing; and (c) contrary to a recent claim, holistic processing of identity is functionally involved in face identification ability. Copyright © 2011 Elsevier Ltd. All rights reserved.

Impaired holistic coding of facial expression and facial identity in congenital prosopagnosia

PubMed Central

Palermo, Romina; Willis, Megan L.; Rivolta, Davide; McKone, Elinor; Wilson, C. Ellie; Calder, Andrew J.

2011-01-01

We test 12 individuals with congenital prosopagnosia (CP), who replicate a common pattern of showing severe difficulty in recognising facial identity in conjunction with normal recognition of facial expressions (both basic and ‘social’). Strength of holistic processing was examined using standard expression composite and identity composite tasks. Compared to age- and sex-matched controls, group analyses demonstrated that CPs showed weaker holistic processing, for both expression and identity information. Implications are (a) normal expression recognition in CP can derive from compensatory strategies (e.g., over-reliance on non-holistic cues to expression); (b) the split between processing of expression and identity information may take place after a common stage of holistic processing; and (c) contrary to a recent claim, holistic processing of identity is functionally involved in face identification ability. PMID:21333662

Identifying significant environmental features using feature recognition.

DOT National Transportation Integrated Search

2015-10-01

The Department of Environmental Analysis at the Kentucky Transportation Cabinet has expressed an interest in feature-recognition capability because it may help analysts identify environmentally sensitive features in the landscape, : including those r...

Processing of facial affect in social drinkers: a dose-response study of alcohol using dynamic emotion expressions.

PubMed

Kamboj, Sunjeev K; Joye, Alyssa; Bisby, James A; Das, Ravi K; Platt, Bradley; Curran, H Valerie

2013-05-01

Studies of affect recognition can inform our understanding of the interpersonal effects of alcohol and help develop a more complete neuropsychological profile of this drug. The objective of the study was to examine affect recognition in social drinkers using a novel dynamic affect-recognition task, sampling performance across a range of evolutionarily significant target emotions and neutral expressions. Participants received 0, 0.4 or 0.8 g/kg alcohol in a double-blind, independent groups design. Relatively naturalistic changes in facial expression-from neutral (mouth open) to increasing intensities of target emotions, as well as neutral (mouth closed)-were simulated using computer-generated dynamic morphs. Accuracy and reaction time were measured and a two-high-threshold model applied to hits and false-alarm data to determine sensitivity and response bias. While there was no effect on the principal emotion expressions (happiness, sadness, fear, anger and disgust), compared to those receiving 0.8 g/kg of alcohol and placebo, participants administered with 0.4 g/kg alcohol tended to show an enhanced response bias to neutral expressions. Exploration of this effect suggested an accompanying tendency to misattribute neutrality to sad expressions following the 0.4-g/kg dose. The 0.4-g/kg alcohol-but not 0.8 g/kg-produced a limited and specific modification in affect recognition evidenced by a neutral response bias and possibly an accompanying tendency to misclassify sad expressions as neutral. In light of previous findings on involuntary negative memory following the 0.4-g/kg dose, we suggest that moderate-but not high-doses of alcohol have a special relevance to emotional processing in social drinkers.

Proposal of Self-Learning and Recognition System of Facial Expression

NASA Astrophysics Data System (ADS)

Ogawa, Yukihiro; Kato, Kunihito; Yamamoto, Kazuhiko

We describe realization of more complicated function by using the information acquired from some equipped unripe functions. The self-learning and recognition system of the human facial expression, which achieved under the natural relation between human and robot, are proposed. The robot with this system can understand human facial expressions and behave according to their facial expressions after the completion of learning process. The system modelled after the process that a baby learns his/her parents’ facial expressions. Equipping the robot with a camera the system can get face images and equipping the CdS sensors on the robot’s head the robot can get the information of human action. Using the information of these sensors, the robot can get feature of each facial expression. After self-learning is completed, when a person changed his facial expression in front of the robot, the robot operates actions under the relevant facial expression.

Using "The Transporters DVD" as a Learning Tool for Children with Autism Spectrum Disorders (ASD)

ERIC Educational Resources Information Center

Young, Robyn L.; Posselt, Miriam

2012-01-01

Data from two groups of children who were randomly allocated to those groups showed that the ability of children with ASD to identify and label basic and complex facial expressions following a 3-week home based DVD intervention significantly improved when viewing "The Transporters" DVD. Improvements in emotion recognition appear related to the…

Kinect-based sign language recognition of static and dynamic hand movements

NASA Astrophysics Data System (ADS)

Dalawis, Rando C.; Olayao, Kenneth Deniel R.; Ramos, Evan Geoffrey I.; Samonte, Mary Jane C.

2017-02-01

A different approach of sign language recognition of static and dynamic hand movements was developed in this study using normalized correlation algorithm. The goal of this research was to translate fingerspelling sign language into text using MATLAB and Microsoft Kinect. Digital input image captured by Kinect devices are matched from template samples stored in a database. This Human Computer Interaction (HCI) prototype was developed to help people with communication disability to express their thoughts with ease. Frame segmentation and feature extraction was used to give meaning to the captured images. Sequential and random testing was used to test both static and dynamic fingerspelling gestures. The researchers explained some factors they encountered causing some misclassification of signs.

Nuclear factor kappa B-dependent Zif268 expression in hippocampus is required for recognition memory in mice.

PubMed

Zalcman, Gisela; Federman, Noel; de la Fuente, Verónica; Romano, Arturo

2015-03-01

Long-term memory formation requires gene expression after acquisition of new information. The first step in the regulation of gene expression is the participation of transcription factors (TFs) such as nuclear factor kappa B (NF-кB), which are present before the neuronal activity induced by training. It was proposed that the activation of these types of TFs allows a second step in gene regulation by induction of immediate-early genes (IEGs) whose protein products are, in turn, TFs. Between these IEGs, zif268 has been found to play a critical role in long-term memory formation and reprocessing after retrieval. Here we found in mice hippocampus that, on one hand, NF-кB was activated 45 min after training in a novel object recognition (NOR) task and that inhibiting NF-кB immediately after training by intrahippocampal administration of NF-кB Decoy DNA impaired NOR memory consolidation. On the other hand, Zif268 protein expression was induced 45 min after NOR training and the administration of DNA antisense to its mRNA post-training impaired recognition memory. Finally, we found that the inhibition of NF-кB by NF-кB Decoy DNA reduced significantly the training-induced Zif268 increment, indicating that NF-кB is involved in the regulation of Zif268 expression. Thus, the present results support the involvement of NF-кB activity-dependent Zif268 expression in the hippocampus during recognition memory consolidation. Copyright © 2015 Elsevier Inc. All rights reserved.

Integrating conventional and inverse representation for face recognition.

PubMed

Xu, Yong; Li, Xuelong; Yang, Jian; Lai, Zhihui; Zhang, David

2014-10-01

Representation-based classification methods are all constructed on the basis of the conventional representation, which first expresses the test sample as a linear combination of the training samples and then exploits the deviation between the test sample and the expression result of every class to perform classification. However, this deviation does not always well reflect the difference between the test sample and each class. With this paper, we propose a novel representation-based classification method for face recognition. This method integrates conventional and the inverse representation-based classification for better recognizing the face. It first produces conventional representation of the test sample, i.e., uses a linear combination of the training samples to represent the test sample. Then it obtains the inverse representation, i.e., provides an approximation representation of each training sample of a subject by exploiting the test sample and training samples of the other subjects. Finally, the proposed method exploits the conventional and inverse representation to generate two kinds of scores of the test sample with respect to each class and combines them to recognize the face. The paper shows the theoretical foundation and rationale of the proposed method. Moreover, this paper for the first time shows that a basic nature of the human face, i.e., the symmetry of the face can be exploited to generate new training and test samples. As these new samples really reflect some possible appearance of the face, the use of them will enable us to obtain higher accuracy. The experiments show that the proposed conventional and inverse representation-based linear regression classification (CIRLRC), an improvement to linear regression classification (LRC), can obtain very high accuracy and greatly outperforms the naive LRC and other state-of-the-art conventional representation based face recognition methods. The accuracy of CIRLRC can be 10% greater than that of LRC.

Effects of Diesel Engine Exhaust Origin Secondary Organic Aerosols on Novel Object Recognition Ability and Maternal Behavior in BALB/C Mice

PubMed Central

Win-Shwe, Tin-Tin; Fujitani, Yuji; Kyi-Tha-Thu, Chaw; Furuyama, Akiko; Michikawa, Takehiro; Tsukahara, Shinji; Nitta, Hiroshi; Hirano, Seishiro

2014-01-01

Epidemiological studies have reported an increased risk of cardiopulmonary and lung cancer mortality associated with increasing exposure to air pollution. Ambient particulate matter consists of primary particles emitted directly from diesel engine vehicles and secondary organic aerosols (SOAs) are formed by oxidative reaction of the ultrafine particle components of diesel exhaust (DE) in the atmosphere. However, little is known about the relationship between exposure to SOA and central nervous system functions. Recently, we have reported that an acute single intranasal instillation of SOA may induce inflammatory response in lung, but not in brain of adult mice. To clarify the whole body exposure effects of SOA on central nervous system functions, we first created inhalation chambers for diesel exhaust origin secondary organic aerosols (DE-SOAs) produced by oxidation of diesel exhaust particles caused by adding ozone. Male BALB/c mice were exposed to clean air (control), DE and DE-SOA in inhalation chambers for one or three months (5 h/day, 5 days/week) and were examined for memory function using a novel object recognition test and for memory function-related gene expressions in the hippocampus by real-time RT-PCR. Moreover, female mice exposed to DE-SOA for one month were mated and maternal behaviors and the related gene expressions in the hypothalamus examined. Novel object recognition ability and N-methyl-d-aspartate (NMDA) receptor expression in the hippocampus were affected in male mice exposed to DE-SOA. Furthermore, a tendency to decrease maternal performance and significantly decreased expression levels of estrogen receptor (ER)-α, and oxytocin receptor were found in DE-SOA exposed dams compared with the control. This is the first study of this type and our results suggest that the constituents of DE-SOA may be associated with memory function and maternal performance based on the impaired gene expressions in the hippocampus and hypothalamus, respectively. PMID:25361045

Updating schematic emotional facial expressions in working memory: Response bias and sensitivity.

PubMed

Tamm, Gerly; Kreegipuu, Kairi; Harro, Jaanus; Cowan, Nelson

2017-01-01

It is unclear if positive, negative, or neutral emotional expressions have an advantage in short-term recognition. Moreover, it is unclear from previous studies of working memory for emotional faces whether effects of emotions comprise response bias or sensitivity. The aim of this study was to compare how schematic emotional expressions (sad, angry, scheming, happy, and neutral) are discriminated and recognized in an updating task (2-back recognition) in a representative sample of birth cohort of young adults. Schematic facial expressions allow control of identity processing, which is separate from expression processing, and have been used extensively in attention research but not much, until now, in working memory research. We found that expressions with a U-curved mouth (i.e., upwardly curved), namely happy and scheming expressions, favoured a bias towards recognition (i.e., towards indicating that the probe and the stimulus in working memory are the same). Other effects of emotional expression were considerably smaller (1-2% of the variance explained)) compared to a large proportion of variance that was explained by the physical similarity of items being compared. We suggest that the nature of the stimuli plays a role in this. The present application of signal detection methodology with emotional, schematic faces in a working memory procedure requiring fast comparisons helps to resolve important contradictions that have emerged in the emotional perception literature. Copyright © 2016 Elsevier B.V. All rights reserved.

Electrophoretic mobility shift assay reveals a novel recognition sequence for Setaria italica NAC protein.

PubMed

Puranik, Swati; Kumar, Karunesh; Srivastava, Prem S; Prasad, Manoj

2011-10-01

The NAC (NAM/ATAF1,2/CUC2) proteins are among the largest family of plant transcription factors. Its members have been associated with diverse plant processes and intricately regulate the expression of several genes. Inspite of this immense progress, knowledge of their DNA-binding properties are still limited. In our recent publication,1 we reported isolation of a membrane-associated NAC domain protein from Setaria italica (SiNAC). Transactivation analysis revealed that it was a functionally active transcription factor as it could stimulate expression of reporter genes in vivo. Truncations of the transmembrane region of the protein lead to its nuclear localization. Here we describe expression and purification of SiNAC DNA-binding domain. We further report identification of a novel DNA-binding site, [C/G][A/T][T/A][G/C]TC[C/G][A/T][C/G][G/C] for SiNAC by electrophoretic mobility shift assay. The SiNAC-GST protein could bind to the NAC recognition sequence in vitro as well as to sequences where some bases had been reshuffled. The results presented here contribute to our understanding of the DNA-binding specificity of SiNAC protein.

Electrophoretic mobility shift assay reveals a novel recognition sequence for Setaria italica NAC protein

PubMed Central

Puranik, Swati; Kumar, Karunesh; Srivastava, Prem S

2011-01-01

The NAC (NAM/ATAF1,2/CUC2) proteins are among the largest family of plant transcription factors. Its members have been associated with diverse plant processes and intricately regulate the expression of several genes. Inspite of this immense progress, knowledge of their DNA-binding properties are still limited. In our recent publication,1 we reported isolation of a membrane-associated NAC domain protein from Setaria italica (SiNAC). Transactivation analysis revealed that it was a functionally active transcription factor as it could stimulate expression of reporter genes in vivo. Truncation of the transmembrane region of the protein lead to its nuclear localization. Here we describe expression and purification of SiNAC DNA-binding domain. We further report identification of a novel DNA-binding site, [C/G][A/T] [T/A][G/C]TC[C/G][A/T][C/G][G/C] for SiNAC by electrophoretic mobility shift assay. The SiNAC-GST protein could bind to the NAC recognition sequence in vitro as well as to sequences where some bases had been reshuffled. The results presented here contribute to our understanding of the DNA-binding specificity of SiNAC protein. PMID:21918373

Progesterone Impairs Social Recognition in Male Rats

PubMed Central

Auger, Catherine J.

2012-01-01

The influence of progesterone in the brain and on the behavior of females is fairly well understood. However, less is known about the effect of progesterone in the male system. In male rats, receptors for progesterone are present in virtually all vasopressin (AVP) immunoreactive cells in the bed nucleus of the stria terminalis (BST) and the medial amygdala (MeA). This colocalization functions to regulate AVP expression, as progesterone and/or progestin receptors (PR)s suppresses AVP expression in these same extrahypothalamic regions in the brain. These data suggest that progesterone may influence AVP-dependant behavior. While AVP is implicated in numerous behavioral and physiological functions in rodents, AVP appears essential for social recognition of conspecifics. Therefore, we examined the effects of progesterone on social recognition. We report that progesterone plays an important role in modulating social recognition in the male brain, as progesterone treatment lead to a significant impairment of social recognition in male rats. Moreover, progesterone appears to act on PRs to impair social recognition, as progesterone impairment of social recognition is blocked by a PR antagonist, RU-486. Social recognition is also impaired by a specific progestin agonist, R5020. Interestingly, we show that progesterone does not interfere with either general memory or olfactory processes, suggesting that progesterone seems critically important to social recognition memory. These data provide strong evidence that physiological levels of progesterone can have an important impact on social behavior in male rats. PMID:22366506

Does cortisol modulate emotion recognition and empathy?

PubMed

Duesenberg, Moritz; Weber, Juliane; Schulze, Lars; Schaeuffele, Carmen; Roepke, Stefan; Hellmann-Regen, Julian; Otte, Christian; Wingenfeld, Katja

2016-04-01

Emotion recognition and empathy are important aspects in the interaction and understanding of other people's behaviors and feelings. The Human environment comprises of stressful situations that impact social interactions on a daily basis. Aim of the study was to examine the effects of the stress hormone cortisol on emotion recognition and empathy. In this placebo-controlled study, 40 healthy men and 40 healthy women (mean age 24.5 years) received either 10mg of hydrocortisone or placebo. We used the Multifaceted Empathy Test to measure emotional and cognitive empathy. Furthermore, we examined emotion recognition from facial expressions, which contained two emotions (anger and sadness) and two emotion intensities (40% and 80%). We did not find a main effect for treatment or sex on either empathy or emotion recognition but a sex × emotion interaction on emotion recognition. The main result was a four-way-interaction on emotion recognition including treatment, sex, emotion and task difficulty. At 40% task difficulty, women recognized angry faces better than men in the placebo condition. Furthermore, in the placebo condition, men recognized sadness better than anger. At 80% task difficulty, men and women performed equally well in recognizing sad faces but men performed worse compared to women with regard to angry faces. Apparently, our results did not support the hypothesis that increases in cortisol concentration alone influence empathy and emotion recognition in healthy young individuals. However, sex and task difficulty appear to be important variables in emotion recognition from facial expressions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Progesterone impairs social recognition in male rats.

PubMed

Bychowski, Meaghan E; Auger, Catherine J

2012-04-01

The influence of progesterone in the brain and on the behavior of females is fairly well understood. However, less is known about the effect of progesterone in the male system. In male rats, receptors for progesterone are present in virtually all vasopressin (AVP) immunoreactive cells in the bed nucleus of the stria terminalis (BST) and the medial amygdala (MeA). This colocalization functions to regulate AVP expression, as progesterone and/or progestin receptors (PR)s suppress AVP expression in these same extrahypothalamic regions in the brain. These data suggest that progesterone may influence AVP-dependent behavior. While AVP is implicated in numerous behavioral and physiological functions in rodents, AVP appears essential for social recognition of conspecifics. Therefore, we examined the effects of progesterone on social recognition. We report that progesterone plays an important role in modulating social recognition in the male brain, as progesterone treatment leads to a significant impairment of social recognition in male rats. Moreover, progesterone appears to act on PRs to impair social recognition, as progesterone impairment of social recognition is blocked by a PR antagonist, RU-486. Social recognition is also impaired by a specific progestin agonist, R5020. Interestingly, we show that progesterone does not interfere with either general memory or olfactory processes, suggesting that progesterone seems critically important to social recognition memory. These data provide strong evidence that physiological levels of progesterone can have an important impact on social behavior in male rats. Copyright © 2012 Elsevier Inc. All rights reserved.

Evaluation of the usability of a serious game aiming to teach facial expressions to schizophrenic patients.

PubMed

Isleyen, Filiz; Gulkesen, K Hakan; Cinemre, Buket; Samur, M Kemal; Zayim, Nese; Sen Kaya, Semiha

2014-01-01

In some psychological disorders such as autism and schizophrenia, loss of facial expression recognition skill may complicate patient's daily life. Information technology may help to develop facial expression recognition skill by educational software and games. We designed and developed an interactive web-based educational program with which we performed a usability study before investigating its effectiveness on the schizophrenia patients' ability of emotion perception. The purpose of this study is to describe the usability evaluation for a web-based game set that has been designed to teach facial expressions to schizophrenic patients. The usability study was done at two steps; first, we applied heuristic evaluation and the violations were rated in a scale from most to least severe and the major problems were solved. In the second step, think-aloud method was used and the web site was assessed by five schizophrenic patients. Eight experts participated in the heuristic evaluation, in which a total of 60 violations were identified with a mean severity of 2.77 (range: 0-4). All of the major problems (severity over 2.5) were listed and the usability problems were solved by the development team. After solving the problems, five users with a diagnosis of schizophrenia used the web site with the same scenario. They reported to have experienced minor, but different problems. In conclusion, we suggest that a combination of heuristic evaluation and think-aloud method may be an effective and efficient way for usability evaluations for the serious games that have been designed for special patient groups.

Using computerized games to teach face recognition skills to children with autism spectrum disorder: the Let's Face It! program.

PubMed

Tanaka, James W; Wolf, Julie M; Klaiman, Cheryl; Koenig, Kathleen; Cockburn, Jeffrey; Herlihy, Lauren; Brown, Carla; Stahl, Sherin; Kaiser, Martha D; Schultz, Robert T

2010-08-01

An emerging body of evidence indicates that relative to typically developing children, children with autism are selectively impaired in their ability to recognize facial identity. A critical question is whether face recognition skills can be enhanced through a direct training intervention. In a randomized clinical trial, children diagnosed with autism spectrum disorder were pre-screened with a battery of subtests (the Let's Face It! Skills battery) examining face and object processing abilities. Participants who were significantly impaired in their face processing abilities were assigned to either a treatment or a waitlist group. Children in the treatment group (N = 42) received 20 hours of face training with the Let's Face It! (LFI!) computer-based intervention. The LFI! program is comprised of seven interactive computer games that target the specific face impairments associated with autism, including the recognition of identity across image changes in expression, viewpoint and features, analytic and holistic face processing strategies and attention to information in the eye region. Time 1 and Time 2 performance for the treatment and waitlist groups was assessed with the Let's Face It! Skills battery. The main finding was that relative to the control group (N = 37), children in the face training group demonstrated reliable improvements in their analytic recognition of mouth features and holistic recognition of a face based on its eyes features. These results indicate that a relatively short-term intervention program can produce measurable improvements in the face recognition skills of children with autism. As a treatment for face processing deficits, the Let's Face It! program has advantages of being cost-free, adaptable to the specific learning needs of the individual child and suitable for home and school applications.

Reconstructing 3D Face Model with Associated Expression Deformation from a Single Face Image via Constructing a Low-Dimensional Expression Deformation Manifold.

PubMed

Wang, Shu-Fan; Lai, Shang-Hong

2011-10-01

Facial expression modeling is central to facial expression recognition and expression synthesis for facial animation. In this work, we propose a manifold-based 3D face reconstruction approach to estimating the 3D face model and the associated expression deformation from a single face image. With the proposed robust weighted feature map (RWF), we can obtain the dense correspondences between 3D face models and build a nonlinear 3D expression manifold from a large set of 3D facial expression models. Then a Gaussian mixture model in this manifold is learned to represent the distribution of expression deformation. By combining the merits of morphable neutral face model and the low-dimensional expression manifold, a novel algorithm is developed to reconstruct the 3D face geometry as well as the facial deformation from a single face image in an energy minimization framework. Experimental results on simulated and real images are shown to validate the effectiveness and accuracy of the proposed algorithm.

From The Cover: Induction of antiviral immunity requires Toll-like receptor signaling in both stromal and dendritic cell compartments

NASA Astrophysics Data System (ADS)

Sato, Ayuko; Iwasaki, Akiko

2004-11-01

Pattern recognition by Toll-like receptors (TLRs) is known to be important for the induction of dendritic cell (DC) maturation. DCs, in turn, are critically important in the initiation of T cell responses. However, most viruses do not infect DCs. This recognition system poses a biological problem in ensuring that most viral infections be detected by pattern recognition receptors. Furthermore, it is unknown what, if any, is the contribution of TLRs expressed by cells that are infected by a virus, versus TLRs expressed by DCs, in the initiation of antiviral adaptive immunity. Here we address these issues using a physiologically relevant model of mucosal infection with herpes simplex virus type 2. We demonstrate that innate immune recognition of viral infection occurs in two distinct stages, one at the level of the infected epithelial cells and the other at the level of the noninfected DCs. Importantly, both TLR-mediated recognition events are required for the induction of effector T cells. Our results demonstrate that virally infected tissues instruct DCs to initiate the appropriate class of effector T cell responses and reveal the critical importance of the stromal cells in detecting infectious agents through their own pattern recognition receptors. mucosal immunity | pattern recognition | viral infection

Brain correlates of musical and facial emotion recognition: evidence from the dementias.

PubMed

Hsieh, S; Hornberger, M; Piguet, O; Hodges, J R

2012-07-01

The recognition of facial expressions of emotion is impaired in semantic dementia (SD) and is associated with right-sided brain atrophy in areas known to be involved in emotion processing, notably the amygdala. Whether patients with SD also experience difficulty recognizing emotions conveyed by other media, such as music, is unclear. Prior studies have used excerpts of known music from classical or film repertoire but not unfamiliar melodies designed to convey distinct emotions. Patients with SD (n = 11), Alzheimer's disease (n = 12) and healthy control participants (n = 20) underwent tests of emotion recognition in two modalities: unfamiliar musical tunes and unknown faces as well as volumetric MRI. Patients with SD were most impaired with the recognition of facial and musical emotions, particularly for negative emotions. Voxel-based morphometry showed that the labelling of emotions, regardless of modality, correlated with the degree of atrophy in the right temporal pole, amygdala and insula. The recognition of musical (but not facial) emotions was also associated with atrophy of the left anterior and inferior temporal lobe, which overlapped with regions correlating with standardized measures of verbal semantic memory. These findings highlight the common neural substrates supporting the processing of emotions by facial and musical stimuli but also indicate that the recognition of emotions from music draws upon brain regions that are associated with semantics in language. Copyright © 2012 Elsevier Ltd. All rights reserved.

Face shape and face identity processing in behavioral variant fronto-temporal dementia: A specific deficit for familiarity and name recognition of famous faces.

PubMed

De Winter, François-Laurent; Timmers, Dorien; de Gelder, Beatrice; Van Orshoven, Marc; Vieren, Marleen; Bouckaert, Miriam; Cypers, Gert; Caekebeke, Jo; Van de Vliet, Laura; Goffin, Karolien; Van Laere, Koen; Sunaert, Stefan; Vandenberghe, Rik; Vandenbulcke, Mathieu; Van den Stock, Jan

2016-01-01

Deficits in face processing have been described in the behavioral variant of fronto-temporal dementia (bvFTD), primarily regarding the recognition of facial expressions. Less is known about face shape and face identity processing. Here we used a hierarchical strategy targeting face shape and face identity recognition in bvFTD and matched healthy controls. Participants performed 3 psychophysical experiments targeting face shape detection (Experiment 1), unfamiliar face identity matching (Experiment 2), familiarity categorization and famous face-name matching (Experiment 3). The results revealed group differences only in Experiment 3, with a deficit in the bvFTD group for both familiarity categorization and famous face-name matching. Voxel-based morphometry regression analyses in the bvFTD group revealed an association between grey matter volume of the left ventral anterior temporal lobe and familiarity recognition, while face-name matching correlated with grey matter volume of the bilateral ventral anterior temporal lobes. Subsequently, we quantified familiarity-specific and name-specific recognition deficits as the sum of the celebrities of which respectively only the name or only the familiarity was accurately recognized. Both indices were associated with grey matter volume of the bilateral anterior temporal cortices. These findings extent previous results by documenting the involvement of the left anterior temporal lobe (ATL) in familiarity detection and the right ATL in name recognition deficits in fronto-temporal lobar degeneration.

Neural network face recognition using wavelets

NASA Astrophysics Data System (ADS)

Karunaratne, Passant V.; Jouny, Ismail I.

1997-04-01

The recognition of human faces is a phenomenon that has been mastered by the human visual system and that has been researched extensively in the domain of computer neural networks and image processing. This research is involved in the study of neural networks and wavelet image processing techniques in the application of human face recognition. The objective of the system is to acquire a digitized still image of a human face, carry out pre-processing on the image as required, an then, given a prior database of images of possible individuals, be able to recognize the individual in the image. The pre-processing segment of the system includes several procedures, namely image compression, denoising, and feature extraction. The image processing is carried out using Daubechies wavelets. Once the images have been passed through the wavelet-based image processor they can be efficiently analyzed by means of a neural network. A back- propagation neural network is used for the recognition segment of the system. The main constraints of the system is with regard to the characteristics of the images being processed. The system should be able to carry out effective recognition of the human faces irrespective of the individual's facial-expression, presence of extraneous objects such as head-gear or spectacles, and face/head orientation. A potential application of this face recognition system would be as a secondary verification method in an automated teller machine.

Recognition of DHN-melanin by a C-type lectin receptor is required for immunity to Aspergillus.

PubMed

Stappers, Mark H T; Clark, Alexandra E; Aimanianda, Vishukumar; Bidula, Stefan; Reid, Delyth M; Asamaphan, Patawee; Hardison, Sarah E; Dambuza, Ivy M; Valsecchi, Isabel; Kerscher, Bernhard; Plato, Anthony; Wallace, Carol A; Yuecel, Raif; Hebecker, Betty; da Glória Teixeira Sousa, Maria; Cunha, Cristina; Liu, Yan; Feizi, Ten; Brakhage, Axel A; Kwon-Chung, Kyung J; Gow, Neil A R; Zanda, Matteo; Piras, Monica; Zanato, Chiara; Jaeger, Martin; Netea, Mihai G; van de Veerdonk, Frank L; Lacerda, João F; Campos, António; Carvalho, Agostinho; Willment, Janet A; Latgé, Jean-Paul; Brown, Gordon D

2018-03-15

Resistance to infection is critically dependent on the ability of pattern recognition receptors to recognize microbial invasion and induce protective immune responses. One such family of receptors are the C-type lectins, which are central to antifungal immunity. These receptors activate key effector mechanisms upon recognition of conserved fungal cell-wall carbohydrates. However, several other immunologically active fungal ligands have been described; these include melanin, for which the mechanism of recognition is hitherto undefined. Here we identify a C-type lectin receptor, melanin-sensing C-type lectin receptor (MelLec), that has an essential role in antifungal immunity through recognition of the naphthalene-diol unit of 1,8-dihydroxynaphthalene (DHN)-melanin. MelLec recognizes melanin in conidial spores of Aspergillus fumigatus as well as in other DHN-melanized fungi. MelLec is ubiquitously expressed by CD31 + endothelial cells in mice, and is also expressed by a sub-population of these cells that co-express epithelial cell adhesion molecule and are detected only in the lung and the liver. In mouse models, MelLec was required for protection against disseminated infection with A. fumigatus. In humans, MelLec is also expressed by myeloid cells, and we identified a single nucleotide polymorphism of this receptor that negatively affected myeloid inflammatory responses and significantly increased the susceptibility of stem-cell transplant recipients to disseminated Aspergillus infections. MelLec therefore recognizes an immunologically active component commonly found on fungi and has an essential role in protective antifungal immunity in both mice and humans.

Facial emotion recognition ability: psychiatry nurses versus nurses from other departments.

PubMed

Gultekin, Gozde; Kincir, Zeliha; Kurt, Merve; Catal, Yasir; Acil, Asli; Aydin, Aybike; Özcan, Mualla; Delikkaya, Busra N; Kacar, Selma; Emul, Murat

2016-12-01

Facial emotion recognition is a basic element in non-verbal communication. Although some researchers have shown that recognizing facial expressions may be important in the interaction between doctors and patients, there are no studies concerning facial emotion recognition in nurses. Here, we aimed to investigate facial emotion recognition ability in nurses and compare the abilities between nurses from psychiatry and other departments. In this cross-sectional study, sixty seven nurses were divided into two groups according to their departments: psychiatry (n=31); and, other departments (n=36). A Facial Emotion Recognition Test, constructed from a set of photographs from Ekman and Friesen's book "Pictures of Facial Affect", was administered to all participants. In whole group, the highest mean accuracy rate of recognizing facial emotion was the happy (99.14%) while the lowest accurately recognized facial expression was fear (47.71%). There were no significant differences between two groups among mean accuracy rates in recognizing happy, sad, fear, angry, surprised facial emotion expressions (for all, p>0.05). The ability of recognizing disgusted and neutral facial emotions tended to be better in other nurses than psychiatry nurses (p=0.052 and p=0.053, respectively) Conclusion: This study was the first that revealed indifference in the ability of FER between psychiatry nurses and non-psychiatry nurses. In medical education curricula throughout the world, no specific training program is scheduled for recognizing emotional cues of patients. We considered that improving the ability of recognizing facial emotion expression in medical stuff might be beneficial in reducing inappropriate patient-medical stuff interaction.

The integration of visual context information in facial emotion recognition in 5- to 15-year-olds.

PubMed

Theurel, Anne; Witt, Arnaud; Malsert, Jennifer; Lejeune, Fleur; Fiorentini, Chiara; Barisnikov, Koviljka; Gentaz, Edouard

2016-10-01

The current study investigated the role of congruent visual context information in the recognition of facial emotional expression in 190 participants from 5 to 15years of age. Children performed a matching task that presented pictures with different facial emotional expressions (anger, disgust, happiness, fear, and sadness) in two conditions: with and without a visual context. The results showed that emotions presented with visual context information were recognized more accurately than those presented in the absence of visual context. The context effect remained steady with age but varied according to the emotion presented and the gender of participants. The findings demonstrated for the first time that children from the age of 5years are able to integrate facial expression and visual context information, and this integration improves facial emotion recognition. Copyright © 2016 Elsevier Inc. All rights reserved.

Test battery for measuring the perception and recognition of facial expressions of emotion

PubMed Central

Wilhelm, Oliver; Hildebrandt, Andrea; Manske, Karsten; Schacht, Annekathrin; Sommer, Werner

2014-01-01

Despite the importance of perceiving and recognizing facial expressions in everyday life, there is no comprehensive test battery for the multivariate assessment of these abilities. As a first step toward such a compilation, we present 16 tasks that measure the perception and recognition of facial emotion expressions, and data illustrating each task's difficulty and reliability. The scoring of these tasks focuses on either the speed or accuracy of performance. A sample of 269 healthy young adults completed all tasks. In general, accuracy and reaction time measures for emotion-general scores showed acceptable and high estimates of internal consistency and factor reliability. Emotion-specific scores yielded lower reliabilities, yet high enough to encourage further studies with such measures. Analyses of task difficulty revealed that all tasks are suitable for measuring emotion perception and emotion recognition related abilities in normal populations. PMID:24860528

Enhancement of cell recognition in vitro by dual-ligand cancer targeting gold naoparticles

PubMed Central

Li, Xi; Zhou, Hongyu; Yang, Lei; Du, Guoqing; Pai-Panandiker, Atmaram; Huang, Xuefei; Yan, Bing

2011-01-01

A dual-ligand gold nanoparticle (DLGNP) was designed and synthesized to explore the therapeutic benefits of multivalent interactions between gold nanoparticles (GNPs) and cancer cells. DLGNP was tested on human epidermal cancer cells (KB), which had high expression of folate receptor. The cellular uptake of DLGNP was increased by 3.9 and 12.7 folds compared with GNP-folate or GNP-glucose. The enhanced cell recognition was due to multivalent interactions between both ligands on GNPs and cancer cells as shown by the ligand competition experiments. Furthermore, the multivalent interactions increased contrast between cells with high and low expression of folate receptors. The enhanced cell recognition enabled DLGNP to kill KB cells under X-ray irradiation at a dose that was safe to folate receptor low-expression (such as normal) cells. Thus DLGP has the potential to be a cancer-specific nano-theranostic agent. PMID:21232787

Characterization and recognition of mixed emotional expressions in thermal face image

NASA Astrophysics Data System (ADS)

Saha, Priya; Bhattacharjee, Debotosh; De, Barin K.; Nasipuri, Mita

2016-05-01

Facial expressions in infrared imaging have been introduced to solve the problem of illumination, which is an integral constituent of visual imagery. The paper investigates facial skin temperature distribution on mixed thermal facial expressions of our created face database where six are basic expressions and rest 12 are a mixture of those basic expressions. Temperature analysis has been performed on three facial regions of interest (ROIs); periorbital, supraorbital and mouth. Temperature variability of the ROIs in different expressions has been measured using statistical parameters. The temperature variation measurement in ROIs of a particular expression corresponds to a vector, which is later used in recognition of mixed facial expressions. Investigations show that facial features in mixed facial expressions can be characterized by positive emotion induced facial features and negative emotion induced facial features. Supraorbital is a useful facial region that can differentiate basic expressions from mixed expressions. Analysis and interpretation of mixed expressions have been conducted with the help of box and whisker plot. Facial region containing mixture of two expressions is generally less temperature inducing than corresponding facial region containing basic expressions.

Altering sensorimotor feedback disrupts visual discrimination of facial expressions.

PubMed

Wood, Adrienne; Lupyan, Gary; Sherrin, Steven; Niedenthal, Paula

2016-08-01

Looking at another person's facial expression of emotion can trigger the same neural processes involved in producing the expression, and such responses play a functional role in emotion recognition. Disrupting individuals' facial action, for example, interferes with verbal emotion recognition tasks. We tested the hypothesis that facial responses also play a functional role in the perceptual processing of emotional expressions. We altered the facial action of participants with a gel facemask while they performed a task that involved distinguishing target expressions from highly similar distractors. Relative to control participants, participants in the facemask condition demonstrated inferior perceptual discrimination of facial expressions, but not of nonface stimuli. The findings suggest that somatosensory/motor processes involving the face contribute to the visual perceptual-and not just conceptual-processing of facial expressions. More broadly, our study contributes to growing evidence for the fundamentally interactive nature of the perceptual inputs from different sensory modalities.

Emotion Recognition in Faces and the Use of Visual Context in Young People with High-Functioning Autism Spectrum Disorders

ERIC Educational Resources Information Center

Wright, Barry; Clarke, Natalie; Jordan, Jo; Young, Andrew W.; Clarke, Paula; Miles, Jeremy; Nation, Kate; Clarke, Leesa; Williams, Christine

2008-01-01

We compared young people with high-functioning autism spectrum disorders (ASDs) with age, sex and IQ matched controls on emotion recognition of faces and pictorial context. Each participant completed two tests of emotion recognition. The first used Ekman series faces. The second used facial expressions in visual context. A control task involved…

Using Automatic Speech Recognition to Dictate Mathematical Expressions: The Development of the "TalkMaths" Application at Kingston University

ERIC Educational Resources Information Center

Wigmore, Angela; Hunter, Gordon; Pflugel, Eckhard; Denholm-Price, James; Binelli, Vincent

2009-01-01

Speech technology--especially automatic speech recognition--has now advanced to a level where it can be of great benefit both to able-bodied people and those with various disabilities. In this paper we describe an application "TalkMaths" which, using the output from a commonly-used conventional automatic speech recognition system,…

Pathogen recognition in the innate immune response.

PubMed

Kumar, Himanshu; Kawai, Taro; Akira, Shizuo

2009-04-28

Immunity against microbial pathogens primarily depends on the recognition of pathogen components by innate receptors expressed on immune and non-immune cells. Innate receptors are evolutionarily conserved germ-line-encoded proteins and include TLRs (Toll-like receptors), RLRs [RIG-I (retinoic acid-inducible gene-I)-like receptors] and NLRs (Nod-like receptors). These receptors recognize pathogens or pathogen-derived products in different cellular compartments, such as the plasma membrane, the endosomes or the cytoplasm, and induce the expression of cytokines, chemokines and co-stimulatory molecules to eliminate pathogens and instruct pathogen-specific adaptive immune responses. In the present review, we will discuss the recent progress in the study of pathogen recognition by TLRs, RLRs and NLRs and their signalling pathways.

Bringing an Ecological Perspective to the Study of Aging and Recognition of Emotional Facial Expressions: Past, Current, and Future Methods

PubMed Central

Isaacowitz, Derek M.; Stanley, Jennifer Tehan

2011-01-01

Older adults perform worse on traditional tests of emotion recognition accuracy than do young adults. In this paper, we review descriptive research to date on age differences in emotion recognition from facial expressions, as well as the primary theoretical frameworks that have been offered to explain these patterns. We propose that this is an area of inquiry that would benefit from an ecological approach in which contextual elements are more explicitly considered and reflected in experimental methods. Use of dynamic displays and examination of specific cues to accuracy, for example, may reveal more nuanced age-related patterns and may suggest heretofore unexplored underlying mechanisms. PMID:22125354

Identities of P2 and P3 Residues of H-2Kb-Bound Peptides Determine Mouse Ly49C Recognition

PubMed Central

Marquez, Elsa A.; Kane, Kevin P.

2015-01-01

Ly49 receptors can be peptide selective in their recognition of MHC-I-peptide complexes, affording them a level of discrimination beyond detecting the presence or absence of specific MHC-I allele products. Despite this ability, little is understood regarding the properties that enable some peptides, when bound to MHC-I molecules, to support Ly49 recognition, but not others. Using RMA-S target cells expressing MHC-I molecules loaded with individual peptides and effector cells expressing the ectodomain of the inhibitory Ly49C receptor, we found that two adjacent amino acid residues, P2 and P3, both buried in the peptide binding groove of H-2Kb, determine mouse Ly49C specificity. If both are aliphatic residues, this is supportive. Whereas, small amino acids at P2 and aromatic amino acids at the P3 auxiliary anchor residue are detrimental to Ly49C recognition. These results resemble those with a rat Ly49 where the identity of a peptide anchor residue determines recognition, suggesting that dependence on specific peptide residues buried in the MHC-I peptide-binding groove may be fundamental to Ly49 peptide selectivity and recognition. PMID:26147851

Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications.

PubMed

Corneanu, Ciprian Adrian; Simon, Marc Oliu; Cohn, Jeffrey F; Guerrero, Sergio Escalera

2016-08-01

Facial expressions are an important way through which humans interact socially. Building a system capable of automatically recognizing facial expressions from images and video has been an intense field of study in recent years. Interpreting such expressions remains challenging and much research is needed about the way they relate to human affect. This paper presents a general overview of automatic RGB, 3D, thermal and multimodal facial expression analysis. We define a new taxonomy for the field, encompassing all steps from face detection to facial expression recognition, and describe and classify the state of the art methods accordingly. We also present the important datasets and the bench-marking of most influential methods. We conclude with a general discussion about trends, important questions and future lines of research.

Emotion processing in chimeric faces: hemispheric asymmetries in expression and recognition of emotions.

PubMed

Indersmitten, Tim; Gur, Ruben C

2003-05-01

Since the discovery of facial asymmetries in emotional expressions of humans and other primates, hypotheses have related the greater left-hemiface intensity to right-hemispheric dominance in emotion processing. However, the difficulty of creating true frontal views of facial expressions in two-dimensional photographs has confounded efforts to better understand the phenomenon. We have recently described a method for obtaining three-dimensional photographs of posed and evoked emotional expressions and used these stimuli to investigate both intensity of expression and accuracy of recognizing emotion in chimeric faces constructed from only left- or right-side composites. The participant population included 38 (19 male, 19 female) African-American, Caucasian, and Asian adults. They were presented with chimeric composites generated from faces of eight actors and eight actresses showing four emotions: happiness, sadness, anger, and fear, each in posed and evoked conditions. We replicated the finding that emotions are expressed more intensely in the left hemiface for all emotions and conditions, with the exception of evoked anger, which was expressed more intensely in the right hemiface. In contrast, the results indicated that emotional expressions are recognized more efficiently in the right hemiface, indicating that the right hemiface expresses emotions more accurately. The double dissociation between the laterality of expression intensity and that of recognition efficiency supports the notion that the two kinds of processes may have distinct neural substrates. Evoked anger is uniquely expressed more intensely and accurately on the side of the face that projects to the viewer's right hemisphere, dominant in emotion recognition.

Biometric identification based on novel frequency domain facial asymmetry measures

NASA Astrophysics Data System (ADS)

Mitra, Sinjini; Savvides, Marios; Vijaya Kumar, B. V. K.

2005-03-01

In the modern world, the ever-growing need to ensure a system's security has spurred the growth of the newly emerging technology of biometric identification. The present paper introduces a novel set of facial biometrics based on quantified facial asymmetry measures in the frequency domain. In particular, we show that these biometrics work well for face images showing expression variations and have the potential to do so in presence of illumination variations as well. A comparison of the recognition rates with those obtained from spatial domain asymmetry measures based on raw intensity values suggests that the frequency domain representation is more robust to intra-personal distortions and is a novel approach for performing biometric identification. In addition, some feature analysis based on statistical methods comparing the asymmetry measures across different individuals and across different expressions is presented.

Recognition Of Complex Three Dimensional Objects Using Three Dimensional Moment Invariants

NASA Astrophysics Data System (ADS)

Sadjadi, Firooz A.

1985-01-01

A technique for the recognition of complex three dimensional objects is presented. The complex 3-D objects are represented in terms of their 3-D moment invariants, algebraic expressions that remain invariant independent of the 3-D objects' orientations and locations in the field of view. The technique of 3-D moment invariants has been used successfully for simple 3-D object recognition in the past. In this work we have extended this method for the representation of more complex objects. Two complex objects are represented digitally; their 3-D moment invariants have been calculated, and then the invariancy of these 3-D invariant moment expressions is verified by changing the orientation and the location of the objects in the field of view. The results of this study have significant impact on 3-D robotic vision, 3-D target recognition, scene analysis and artificial intelligence.

Gender affects body language reading.

PubMed

Sokolov, Arseny A; Krüger, Samuel; Enck, Paul; Krägeloh-Mann, Ingeborg; Pavlova, Marina A

2011-01-01

Body motion is a rich source of information for social cognition. However, gender effects in body language reading are largely unknown. Here we investigated whether, and, if so, how recognition of emotional expressions revealed by body motion is gender dependent. To this end, females and males were presented with point-light displays portraying knocking at a door performed with different emotional expressions. The findings show that gender affects accuracy rather than speed of body language reading. This effect, however, is modulated by emotional content of actions: males surpass in recognition accuracy of happy actions, whereas females tend to excel in recognition of hostile angry knocking. Advantage of women in recognition accuracy of neutral actions suggests that females are better tuned to the lack of emotional content in body actions. The study provides novel insights into understanding of gender effects in body language reading, and helps to shed light on gender vulnerability to neuropsychiatric and neurodevelopmental impairments in visual social cognition.

How Mood and Task Complexity Affect Children's Recognition of Others’ Emotions

PubMed Central

Cummings, Andrew J.; Rennels, Jennifer L.

2013-01-01

Previous studies examined how mood affects children's accuracy in matching emotional expressions and labels (label-based tasks). This study was the first to assess how induced mood (positive, neutral, or negative) influenced 5- to 8-year-olds’ accuracy and reaction time using both context-based tasks, which required inferring a character's emotion from a vignette, and label-based tasks. Both tasks required choosing one of four facial expressions to respond. Children responded more accurately to label-based questions relative to context-based questions at 5 to 7 years of age, but showed no differences at 8 years of age, and when the emotional expression being identified was happiness, sadness, or surprise, but not disgust. For the context-based questions, children were more accurate at inferring sad and disgusted emotions compared to happy and surprised emotions. Induced positive mood facilitated 5-year-olds’ processing (decreased reaction time) in both tasks compared to induced negative and neutral moods. Results demonstrate how task type and children's mood influence children's emotion processing at different ages. PMID:24489442

Reading the lines in the face: The contribution of angularity and roundness to perceptions of facial anger and joy.

PubMed

Franklin, Robert G; Adams, Reginald B; Steiner, Troy G; Zebrowitz, Leslie A

2018-05-14

Through 3 studies, we investigated whether angularity and roundness present in faces contributes to the perception of anger and joyful expressions, respectively. First, in Study 1 we found that angry expressions naturally contain more inward-pointing lines, whereas joyful expressions contain more outward-pointing lines. Then, using image-processing techniques in Studies 2 and 3, we filtered images to contain only inward-pointing or outward-pointing lines as a way to approximate angularity and roundness. We found that filtering images to be more angular increased how threatening and angry a neutral face was rated, increased how intense angry expressions were rated, and enhanced the recognition of anger. Conversely, filtering images to be rounder increased how warm and joyful a neutral face was rated, increased the intensity of joyful expressions, and enhanced recognition of joy. Together these findings show that angularity and roundness play a direct role in the recognition of angry and joyful expressions. Given evidence that angularity and roundness may play a biological role in indicating threat and safety in the environment, this suggests that angularity and roundness represent primitive facial cues used to signal threat-anger and warmth-joy pairings. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Nonintrusive Finger-Vein Recognition System Using NIR Image Sensor and Accuracy Analyses According to Various Factors

PubMed Central

Pham, Tuyen Danh; Park, Young Ho; Nguyen, Dat Tien; Kwon, Seung Yong; Park, Kang Ryoung

2015-01-01

Biometrics is a technology that enables an individual person to be identified based on human physiological and behavioral characteristics. Among biometrics technologies, face recognition has been widely used because of its advantages in terms of convenience and non-contact operation. However, its performance is affected by factors such as variation in the illumination, facial expression, and head pose. Therefore, fingerprint and iris recognitions are preferred alternatives. However, the performance of the former can be adversely affected by the skin condition, including scarring and dryness. In addition, the latter has the disadvantages of high cost, large system size, and inconvenience to the user, who has to align their eyes with the iris camera. In an attempt to overcome these problems, finger-vein recognition has been vigorously researched, but an analysis of its accuracies according to various factors has not received much attention. Therefore, we propose a nonintrusive finger-vein recognition system using a near infrared (NIR) image sensor and analyze its accuracies considering various factors. The experimental results obtained with three databases showed that our system can be operated in real applications with high accuracy; and the dissimilarity of the finger-veins of different people is larger than that of the finger types and hands. PMID:26184214

Nonintrusive Finger-Vein Recognition System Using NIR Image Sensor and Accuracy Analyses According to Various Factors.

PubMed

Pham, Tuyen Danh; Park, Young Ho; Nguyen, Dat Tien; Kwon, Seung Yong; Park, Kang Ryoung

2015-07-13

Biometrics is a technology that enables an individual person to be identified based on human physiological and behavioral characteristics. Among biometrics technologies, face recognition has been widely used because of its advantages in terms of convenience and non-contact operation. However, its performance is affected by factors such as variation in the illumination, facial expression, and head pose. Therefore, fingerprint and iris recognitions are preferred alternatives. However, the performance of the former can be adversely affected by the skin condition, including scarring and dryness. In addition, the latter has the disadvantages of high cost, large system size, and inconvenience to the user, who has to align their eyes with the iris camera. In an attempt to overcome these problems, finger-vein recognition has been vigorously researched, but an analysis of its accuracies according to various factors has not received much attention. Therefore, we propose a nonintrusive finger-vein recognition system using a near infrared (NIR) image sensor and analyze its accuracies considering various factors. The experimental results obtained with three databases showed that our system can be operated in real applications with high accuracy; and the dissimilarity of the finger-veins of different people is larger than that of the finger types and hands.

Basic and complex emotion recognition in children with autism: cross-cultural findings.

PubMed

Fridenson-Hayo, Shimrit; Berggren, Steve; Lassalle, Amandine; Tal, Shahar; Pigat, Delia; Bölte, Sven; Baron-Cohen, Simon; Golan, Ofer

2016-01-01

Children with autism spectrum conditions (ASC) have emotion recognition deficits when tested in different expression modalities (face, voice, body). However, these findings usually focus on basic emotions, using one or two expression modalities. In addition, cultural similarities and differences in emotion recognition patterns in children with ASC have not been explored before. The current study examined the similarities and differences in the recognition of basic and complex emotions by children with ASC and typically developing (TD) controls across three cultures: Israel, Britain, and Sweden. Fifty-five children with high-functioning ASC, aged 5-9, were compared to 58 TD children. On each site, groups were matched on age, sex, and IQ. Children were tested using four tasks, examining recognition of basic and complex emotions from voice recordings, videos of facial and bodily expressions, and emotional video scenarios including all modalities in context. Compared to their TD peers, children with ASC showed emotion recognition deficits in both basic and complex emotions on all three modalities and their integration in context. Complex emotions were harder to recognize, compared to basic emotions for the entire sample. Cross-cultural agreement was found for all major findings, with minor deviations on the face and body tasks. Our findings highlight the multimodal nature of ER deficits in ASC, which exist for basic as well as complex emotions and are relatively stable cross-culturally. Cross-cultural research has the potential to reveal both autism-specific universal deficits and the role that specific cultures play in the way empathy operates in different countries.

Gender Differences in the Recognition of Vocal Emotions

PubMed Central

Lausen, Adi; Schacht, Annekathrin

2018-01-01

The conflicting findings from the few studies conducted with regard to gender differences in the recognition of vocal expressions of emotion have left the exact nature of these differences unclear. Several investigators have argued that a comprehensive understanding of gender differences in vocal emotion recognition can only be achieved by replicating these studies while accounting for influential factors such as stimulus type, gender-balanced samples, number of encoders, decoders, and emotional categories. This study aimed to account for these factors by investigating whether emotion recognition from vocal expressions differs as a function of both listeners' and speakers' gender. A total of N = 290 participants were randomly and equally allocated to two groups. One group listened to words and pseudo-words, while the other group listened to sentences and affect bursts. Participants were asked to categorize the stimuli with respect to the expressed emotions in a fixed-choice response format. Overall, females were more accurate than males when decoding vocal emotions, however, when testing for specific emotions these differences were small in magnitude. Speakers' gender had a significant impact on how listeners' judged emotions from the voice. The group listening to words and pseudo-words had higher identification rates for emotions spoken by male than by female actors, whereas in the group listening to sentences and affect bursts the identification rates were higher when emotions were uttered by female than male actors. The mixed pattern for emotion-specific effects, however, indicates that, in the vocal channel, the reliability of emotion judgments is not systematically influenced by speakers' gender and the related stereotypes of emotional expressivity. Together, these results extend previous findings by showing effects of listeners' and speakers' gender on the recognition of vocal emotions. They stress the importance of distinguishing these factors to explain recognition ability in the processing of emotional prosody. PMID:29922202

Identifying differences in biased affective information processing in major depression.

PubMed

Gollan, Jackie K; Pane, Heather T; McCloskey, Michael S; Coccaro, Emil F

2008-05-30

This study investigates the extent to which participants with major depression differ from healthy comparison participants in the irregularities in affective information processing, characterized by deficits in facial expression recognition, intensity categorization, and reaction time to identifying emotionally salient and neutral information. Data on diagnoses, symptom severity, and affective information processing using a facial recognition task were collected from 66 participants, male and female between ages 18 and 54 years, grouped by major depressive disorder (N=37) or healthy non-psychiatric (N=29) status. Findings from MANCOVAs revealed that major depression was associated with a significantly longer reaction time to sad facial expressions compared with healthy status. Also, depressed participants demonstrated a negative bias towards interpreting neutral facial expressions as sad significantly more often than healthy participants. In turn, healthy participants interpreted neutral faces as happy significantly more often than depressed participants. No group differences were observed for facial expression recognition and intensity categorization. The observed effects suggest that depression has significant effects on the perception of the intensity of negative affective stimuli, delayed speed of processing sad affective information, and biases towards interpreting neutral faces as sad.

Efficient Spatio-Temporal Local Binary Patterns for Spontaneous Facial Micro-Expression Recognition

PubMed Central

Wang, Yandan; See, John; Phan, Raphael C.-W.; Oh, Yee-Hui

2015-01-01

Micro-expression recognition is still in the preliminary stage, owing much to the numerous difficulties faced in the development of datasets. Since micro-expression is an important affective clue for clinical diagnosis and deceit analysis, much effort has gone into the creation of these datasets for research purposes. There are currently two publicly available spontaneous micro-expression datasets—SMIC and CASME II, both with baseline results released using the widely used dynamic texture descriptor LBP-TOP for feature extraction. Although LBP-TOP is popular and widely used, it is still not compact enough. In this paper, we draw further inspiration from the concept of LBP-TOP that considers three orthogonal planes by proposing two efficient approaches for feature extraction. The compact robust form described by the proposed LBP-Six Intersection Points (SIP) and a super-compact LBP-Three Mean Orthogonal Planes (MOP) not only preserves the essential patterns, but also reduces the redundancy that affects the discriminality of the encoded features. Through a comprehensive set of experiments, we demonstrate the strengths of our approaches in terms of recognition accuracy and efficiency. PMID:25993498

Helix Unwinding and Base Flipping Enable Human MTERF1 to Terminate Mitochondrial Transcription

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yakubovskaya, E.; Mejia, E; Byrnes, J

2010-01-01

Defects in mitochondrial gene expression are associated with aging and disease. Mterf proteins have been implicated in modulating transcription, replication and protein synthesis. We have solved the structure of a member of this family, the human mitochondrial transcriptional terminator MTERF1, bound to dsDNA containing the termination sequence. The structure indicates that upon sequence recognition MTERF1 unwinds the DNA molecule, promoting eversion of three nucleotides. Base flipping is critical for stable binding and transcriptional termination. Additional structural and biochemical results provide insight into the DNA binding mechanism and explain how MTERF1 recognizes its target sequence. Finally, we have demonstrated that themore » mitochondrial pathogenic G3249A and G3244A mutations interfere with key interactions for sequence recognition, eliminating termination. Our results provide insight into the role of mterf proteins and suggest a link between mitochondrial disease and the regulation of mitochondrial transcription.« less

On Utilizing Optimal and Information Theoretic Syntactic Modeling for Peptide Classification

NASA Astrophysics Data System (ADS)

Aygün, Eser; Oommen, B. John; Cataltepe, Zehra

Syntactic methods in pattern recognition have been used extensively in bioinformatics, and in particular, in the analysis of gene and protein expressions, and in the recognition and classification of bio-sequences. These methods are almost universally distance-based. This paper concerns the use of an Optimal and Information Theoretic (OIT) probabilistic model [11] to achieve peptide classification using the information residing in their syntactic representations. The latter has traditionally been achieved using the edit distances required in the respective peptide comparisons. We advocate that one can model the differences between compared strings as a mutation model consisting of random Substitutions, Insertions and Deletions (SID) obeying the OIT model. Thus, in this paper, we show that the probability measure obtained from the OIT model can be perceived as a sequence similarity metric, using which a Support Vector Machine (SVM)-based peptide classifier, referred to as OIT_SVM, can be devised.

Comparative analysis of cell wall surface glycan expression in Candida albicans and Saccharomyces cerevisiae yeasts by flow cytometry.

PubMed

Martínez-Esparza, M; Sarazin, A; Jouy, N; Poulain, D; Jouault, T

2006-07-31

The yeast Candida albicans is an opportunistic pathogen, part of the normal human microbial flora that causes infections in immunocompromised individuals with a high morbidity and mortality levels. Recognition of yeasts by host cells is based on components of the yeast cell wall, which are considered part of its virulence attributes. Cell wall glycans play an important role in the continuous interchange that regulates the balance between saprophytism and parasitism, and also between resistance and infection. Some of these molecular entities are expressed both by the pathogenic yeast C. albicans and by Saccharomyces cerevisiae, a related non-pathogenic yeast, involving similar molecular mechanisms and receptors for recognition. In this work we have exploited flow cytometry methods for probing surface glycans of the yeasts. We compared glycan expression by C. albicans and by S. cerevisiae, and studied the effect of culture conditions. Our results show that the expression levels of alpha- and beta-linked mannosides as well as beta-glucans can be successfully evaluated by flow cytometry methods using different antibodies independent of agglutination reactions. We also found that the surface expression pattern of beta-mannosides detected by monoclonal or polyclonal antibodies are differently modulated during the growth course. These data indicate that the yeast beta-mannosides exposed on mannoproteins and/or phospholipomannan are increased in stationary phase, whereas those linked to mannan are not affected by the yeast growth phase. The cytometric method described here represents a useful tool to investigate to what extent C. albicans is able to regulate its glycan surface expression and therefore modify its virulence properties.

Automatic 2.5-D Facial Landmarking and Emotion Annotation for Social Interaction Assistance.

PubMed

Zhao, Xi; Zou, Jianhua; Li, Huibin; Dellandrea, Emmanuel; Kakadiaris, Ioannis A; Chen, Liming

2016-09-01

People with low vision, Alzheimer's disease, and autism spectrum disorder experience difficulties in perceiving or interpreting facial expression of emotion in their social lives. Though automatic facial expression recognition (FER) methods on 2-D videos have been extensively investigated, their performance was constrained by challenges in head pose and lighting conditions. The shape information in 3-D facial data can reduce or even overcome these challenges. However, high expenses of 3-D cameras prevent their widespread use. Fortunately, 2.5-D facial data from emerging portable RGB-D cameras provide a good balance for this dilemma. In this paper, we propose an automatic emotion annotation solution on 2.5-D facial data collected from RGB-D cameras. The solution consists of a facial landmarking method and a FER method. Specifically, we propose building a deformable partial face model and fit the model to a 2.5-D face for localizing facial landmarks automatically. In FER, a novel action unit (AU) space-based FER method has been proposed. Facial features are extracted using landmarks and further represented as coordinates in the AU space, which are classified into facial expressions. Evaluated on three publicly accessible facial databases, namely EURECOM, FRGC, and Bosphorus databases, the proposed facial landmarking and expression recognition methods have achieved satisfactory results. Possible real-world applications using our algorithms have also been discussed.

Horror Image Recognition Based on Context-Aware Multi-Instance Learning.

PubMed

Li, Bing; Xiong, Weihua; Wu, Ou; Hu, Weiming; Maybank, Stephen; Yan, Shuicheng

2015-12-01

Horror content sharing on the Web is a growing phenomenon that can interfere with our daily life and affect the mental health of those involved. As an important form of expression, horror images have their own characteristics that can evoke extreme emotions. In this paper, we present a novel context-aware multi-instance learning (CMIL) algorithm for horror image recognition. The CMIL algorithm identifies horror images and picks out the regions that cause the sensation of horror in these horror images. It obtains contextual cues among adjacent regions in an image using a random walk on a contextual graph. Borrowing the strength of the fuzzy support vector machine (FSVM), we define a heuristic optimization procedure based on the FSVM to search for the optimal classifier for the CMIL. To improve the initialization of the CMIL, we propose a novel visual saliency model based on the tensor analysis. The average saliency value of each segmented region is set as its initial fuzzy membership in the CMIL. The advantage of the tensor-based visual saliency model is that it not only adaptively selects features, but also dynamically determines fusion weights for saliency value combination from different feature subspaces. The effectiveness of the proposed CMIL model is demonstrated by its use in horror image recognition on two large-scale image sets collected from the Internet.

Mobile Diagnostics Based on Motion? A Close Look at Motility Patterns in the Schistosome Life Cycle

PubMed Central

Linder, Ewert; Varjo, Sami; Thors, Cecilia

2016-01-01

Imaging at high resolution and subsequent image analysis with modified mobile phones have the potential to solve problems related to microscopy-based diagnostics of parasitic infections in many endemic regions. Diagnostics using the computing power of “smartphones” is not restricted by limited expertise or limitations set by visual perception of a microscopist. Thus diagnostics currently almost exclusively dependent on recognition of morphological features of pathogenic organisms could be based on additional properties, such as motility characteristics recognizable by computer vision. Of special interest are infectious larval stages and “micro swimmers” of e.g., the schistosome life cycle, which infect the intermediate and definitive hosts, respectively. The ciliated miracidium, emerges from the excreted egg upon its contact with water. This means that for diagnostics, recognition of a swimming miracidium is equivalent to recognition of an egg. The motility pattern of miracidia could be defined by computer vision and used as a diagnostic criterion. To develop motility pattern-based diagnostics of schistosomiasis using simple imaging devices, we analyzed Paramecium as a model for the schistosome miracidium. As a model for invasive nematodes, such as strongyloids and filaria, we examined a different type of motility in the apathogenic nematode Turbatrix, the “vinegar eel.” The results of motion time and frequency analysis suggest that target motility may be expressed as specific spectrograms serving as “diagnostic fingerprints.” PMID:27322330

Oxytocin Reduces Face Processing Time but Leaves Recognition Accuracy and Eye-Gaze Unaffected.

PubMed

Hubble, Kelly; Daughters, Katie; Manstead, Antony S R; Rees, Aled; Thapar, Anita; van Goozen, Stephanie H M

2017-01-01

Previous studies have found that oxytocin (OXT) can improve the recognition of emotional facial expressions; it has been proposed that this effect is mediated by an increase in attention to the eye-region of faces. Nevertheless, evidence in support of this claim is inconsistent, and few studies have directly tested the effect of oxytocin on emotion recognition via altered eye-gaze Methods: In a double-blind, within-subjects, randomized control experiment, 40 healthy male participants received 24 IU intranasal OXT and placebo in two identical experimental sessions separated by a 2-week interval. Visual attention to the eye-region was assessed on both occasions while participants completed a static facial emotion recognition task using medium intensity facial expressions. Although OXT had no effect on emotion recognition accuracy, recognition performance was improved because face processing was faster across emotions under the influence of OXT. This effect was marginally significant (p<.06). Consistent with a previous study using dynamic stimuli, OXT had no effect on eye-gaze patterns when viewing static emotional faces and this was not related to recognition accuracy or face processing time. These findings suggest that OXT-induced enhanced facial emotion recognition is not necessarily mediated by an increase in attention to the eye-region of faces, as previously assumed. We discuss several methodological issues which may explain discrepant findings and suggest the effect of OXT on visual attention may differ depending on task requirements. (JINS, 2017, 23, 23-33).

Evidence for cultural dialects in vocal emotion expression: acoustic classification within and across five nations.

PubMed

Laukka, Petri; Neiberg, Daniel; Elfenbein, Hillary Anger

2014-06-01

The possibility of cultural differences in the fundamental acoustic patterns used to express emotion through the voice is an unanswered question central to the larger debate about the universality versus cultural specificity of emotion. This study used emotionally inflected standard-content speech segments expressing 11 emotions produced by 100 professional actors from 5 English-speaking cultures. Machine learning simulations were employed to classify expressions based on their acoustic features, using conditions where training and testing were conducted on stimuli coming from either the same or different cultures. A wide range of emotions were classified with above-chance accuracy in cross-cultural conditions, suggesting vocal expressions share important characteristics across cultures. However, classification showed an in-group advantage with higher accuracy in within- versus cross-cultural conditions. This finding demonstrates cultural differences in expressive vocal style, and supports the dialect theory of emotions according to which greater recognition of expressions from in-group members results from greater familiarity with culturally specific expressive styles.

Fractal Clustering and Knowledge-driven Validation Assessment for Gene Expression Profiling.

PubMed

Wang, Lu-Yong; Balasubramanian, Ammaiappan; Chakraborty, Amit; Comaniciu, Dorin

2005-01-01

DNA microarray experiments generate a substantial amount of information about the global gene expression. Gene expression profiles can be represented as points in multi-dimensional space. It is essential to identify relevant groups of genes in biomedical research. Clustering is helpful in pattern recognition in gene expression profiles. A number of clustering techniques have been introduced. However, these traditional methods mainly utilize shape-based assumption or some distance metric to cluster the points in multi-dimension linear Euclidean space. Their results shows poor consistence with the functional annotation of genes in previous validation study. From a novel different perspective, we propose fractal clustering method to cluster genes using intrinsic (fractal) dimension from modern geometry. This method clusters points in such a way that points in the same clusters are more self-affine among themselves than to the points in other clusters. We assess this method using annotation-based validation assessment for gene clusters. It shows that this method is superior in identifying functional related gene groups than other traditional methods.

The Role of Progesterone in the Feto-Maternal Immunological Crosstalk.

PubMed

Szekeres-Bartho, Julia

2018-06-27

This review aims to provide a brief historical overview of the feto-maternal immunological relationship, which profoundly influences the outcome of pregnancy. The initial question posed in the nineteen fifties by Medawar, was based on the assumption that the maternal immune system recognizes the fetus as an allograft. Indeed, based on the association between HLA-matching and spontaneous miscarriage, it became obvious that immunological recognition of pregnancy is required for a successful gestation. The restricted expression of polymorphic HLA antigens on the trophoblast, together with the presence of non-polymorphic MHC products excludes recognition by both T and NK cells of trophoblast presented antigens, however, T cells, which constitute the majority of decidual T cells are likely candidates. Indeed, a high number of activated, progesterone receptor-expressing T cells are present in peripheral blood of healthy pregnant women, and in the presence of progesterone, these cells secrete an immunomodulatory protein called Progesterone-induced Blocking Factor or PIBF. As early as in the peri-implantation period, the embryo communicates with the maternal immune system via PIBF containing extracellular vesicles. PIBF contributes to the dominance of Th2-type reactivity characterising normal pregnancy, by inducing increased production of Th2 cytokines. The high expression of this molecule in the decidua might be one of the reasons for the low cytotoxic activity of decidual NK cells. ©2018The Author(s). Published by S. Karger AG, Basel.

Analysis of miRNA expression profile based on SVM algorithm

NASA Astrophysics Data System (ADS)

Ting-ting, Dai; Chang-ji, Shan; Yan-shou, Dong; Yi-duo, Bian

2018-05-01

Based on mirna expression spectrum data set, a new data mining algorithm - tSVM - KNN (t statistic with support vector machine - k nearest neighbor) is proposed. the idea of the algorithm is: firstly, the feature selection of the data set is carried out by the unified measurement method; Secondly, SVM - KNN algorithm, which combines support vector machine (SVM) and k - nearest neighbor (k - nearest neighbor) is used as classifier. Simulation results show that SVM - KNN algorithm has better classification ability than SVM and KNN alone. Tsvm - KNN algorithm only needs 5 mirnas to obtain 96.08 % classification accuracy in terms of the number of mirna " tags" and recognition accuracy. compared with similar algorithms, tsvm - KNN algorithm has obvious advantages.

Refractive index inversion based on Mueller matrix method

NASA Astrophysics Data System (ADS)

Fan, Huaxi; Wu, Wenyuan; Huang, Yanhua; Li, Zhaozhao

2016-03-01

Based on Stokes vector and Jones vector, the correlation between Mueller matrix elements and refractive index was studied with the result simplified, and through Mueller matrix way, the expression of refractive index inversion was deduced. The Mueller matrix elements, under different incident angle, are simulated through the expression of specular reflection so as to analyze the influence of the angle of incidence and refractive index on it, which is verified through the measure of the Mueller matrix elements of polished metal surface. Research shows that, under the condition of specular reflection, the result of Mueller matrix inversion is consistent with the experiment and can be used as an index of refraction of inversion method, and it provides a new way for target detection and recognition technology.

Introduction of statistical information in a syntactic analyzer for document image recognition

NASA Astrophysics Data System (ADS)

Maroneze, André O.; Coüasnon, Bertrand; Lemaitre, Aurélie

2011-01-01

This paper presents an improvement to document layout analysis systems, offering a possible solution to Sayre's paradox (which states that an element "must be recognized before it can be segmented; and it must be segmented before it can be recognized"). This improvement, based on stochastic parsing, allows integration of statistical information, obtained from recognizers, during syntactic layout analysis. We present how this fusion of numeric and symbolic information in a feedback loop can be applied to syntactic methods to improve document description expressiveness. To limit combinatorial explosion during exploration of solutions, we devised an operator that allows optional activation of the stochastic parsing mechanism. Our evaluation on 1250 handwritten business letters shows this method allows the improvement of global recognition scores.

Interfacial polymerization for colorimetric labeling of protein expression in cells.

PubMed

Lilly, Jacob L; Sheldon, Phillip R; Hoversten, Liv J; Romero, Gabriela; Balasubramaniam, Vivek; Berron, Brad J

2014-01-01

Determining the location of rare proteins in cells typically requires the use of on-sample amplification. Antibody based recognition and enzymatic amplification is used to produce large amounts of visible label at the site of protein expression, but these techniques suffer from the presence of nonspecific reactivity in the biological sample and from poor spatial control over the label. Polymerization based amplification is a recently developed alternative means of creating an on-sample amplification for fluorescence applications, while not suffering from endogenous labels or loss of signal localization. This manuscript builds upon polymerization based amplification by developing a stable, archivable, and colorimetric mode of amplification termed Polymer Dye Labeling. The basic concept involves an interfacial polymer grown at the site of protein expression and subsequent staining of this polymer with an appropriate dye. The dyes Evans Blue and eosin were initially investigated for colorimetric response in a microarray setting, where both specifically stained polymer films on glass. The process was translated to the staining of protein expression in human dermal fibroblast cells, and Polymer Dye Labeling was specific to regions consistent with desired protein expression. The labeling is stable for over 200 days in ambient conditions and is also compatible with modern mounting medium.

Cerebellum and processing of negative facial emotions: cerebellar transcranial DC stimulation specifically enhances the emotional recognition of facial anger and sadness.

PubMed

Ferrucci, Roberta; Giannicola, Gaia; Rosa, Manuela; Fumagalli, Manuela; Boggio, Paulo Sergio; Hallett, Mark; Zago, Stefano; Priori, Alberto

2012-01-01

Some evidence suggests that the cerebellum participates in the complex network processing emotional facial expression. To evaluate the role of the cerebellum in recognising facial expressions we delivered transcranial direct current stimulation (tDCS) over the cerebellum and prefrontal cortex. A facial emotion recognition task was administered to 21 healthy subjects before and after cerebellar tDCS; we also tested subjects with a visual attention task and a visual analogue scale (VAS) for mood. Anodal and cathodal cerebellar tDCS both significantly enhanced sensory processing in response to negative facial expressions (anodal tDCS, p=.0021; cathodal tDCS, p=.018), but left positive emotion and neutral facial expressions unchanged (p>.05). tDCS over the right prefrontal cortex left facial expressions of both negative and positive emotion unchanged. These findings suggest that the cerebellum is specifically involved in processing facial expressions of negative emotion.

Measuring facial expression of emotion.

PubMed

Wolf, Karsten

2015-12-01

Research into emotions has increased in recent decades, especially on the subject of recognition of emotions. However, studies of the facial expressions of emotion were compromised by technical problems with visible video analysis and electromyography in experimental settings. These have only recently been overcome. There have been new developments in the field of automated computerized facial recognition; allowing real-time identification of facial expression in social environments. This review addresses three approaches to measuring facial expression of emotion and describes their specific contributions to understanding emotion in the healthy population and in persons with mental illness. Despite recent progress, studies on human emotions have been hindered by the lack of consensus on an emotion theory suited to examining the dynamic aspects of emotion and its expression. Studying expression of emotion in patients with mental health conditions for diagnostic and therapeutic purposes will profit from theoretical and methodological progress.

Strength Is in Numbers: Can Concordant Artificial Listeners Improve Prediction of Emotion from Speech?

PubMed Central

Martinelli, Eugenio; Mencattini, Arianna; Di Natale, Corrado

2016-01-01

Humans can communicate their emotions by modulating facial expressions or the tone of their voice. Albeit numerous applications exist that enable machines to read facial emotions and recognize the content of verbal messages, methods for speech emotion recognition are still in their infancy. Yet, fast and reliable applications for emotion recognition are the obvious advancement of present ‘intelligent personal assistants’, and may have countless applications in diagnostics, rehabilitation and research. Taking inspiration from the dynamics of human group decision-making, we devised a novel speech emotion recognition system that applies, for the first time, a semi-supervised prediction model based on consensus. Three tests were carried out to compare this algorithm with traditional approaches. Labeling performances relative to a public database of spontaneous speeches are reported. The novel system appears to be fast, robust and less computationally demanding than traditional methods, allowing for easier implementation in portable voice-analyzers (as used in rehabilitation, research, industry, etc.) and for applications in the research domain (such as real-time pairing of stimuli to participants’ emotional state, selective/differential data collection based on emotional content, etc.). PMID:27563724

Human phoneme recognition depending on speech-intrinsic variability.

PubMed

Meyer, Bernd T; Jürgens, Tim; Wesker, Thorsten; Brand, Thomas; Kollmeier, Birger

2010-11-01

The influence of different sources of speech-intrinsic variation (speaking rate, effort, style and dialect or accent) on human speech perception was investigated. In listening experiments with 16 listeners, confusions of consonant-vowel-consonant (CVC) and vowel-consonant-vowel (VCV) sounds in speech-weighted noise were analyzed. Experiments were based on the OLLO logatome speech database, which was designed for a man-machine comparison. It contains utterances spoken by 50 speakers from five dialect/accent regions and covers several intrinsic variations. By comparing results depending on intrinsic and extrinsic variations (i.e., different levels of masking noise), the degradation induced by variabilities can be expressed in terms of the SNR. The spectral level distance between the respective speech segment and the long-term spectrum of the masking noise was found to be a good predictor for recognition rates, while phoneme confusions were influenced by the distance to spectrally close phonemes. An analysis based on transmitted information of articulatory features showed that voicing and manner of articulation are comparatively robust cues in the presence of intrinsic variations, whereas the coding of place is more degraded. The database and detailed results have been made available for comparisons between human speech recognition (HSR) and automatic speech recognizers (ASR).

Still-to-video face recognition in unconstrained environments

NASA Astrophysics Data System (ADS)

Wang, Haoyu; Liu, Changsong; Ding, Xiaoqing

2015-02-01

Face images from video sequences captured in unconstrained environments usually contain several kinds of variations, e.g. pose, facial expression, illumination, image resolution and occlusion. Motion blur and compression artifacts also deteriorate recognition performance. Besides, in various practical systems such as law enforcement, video surveillance and e-passport identification, only a single still image per person is enrolled as the gallery set. Many existing methods may fail to work due to variations in face appearances and the limit of available gallery samples. In this paper, we propose a novel approach for still-to-video face recognition in unconstrained environments. By assuming that faces from still images and video frames share the same identity space, a regularized least squares regression method is utilized to tackle the multi-modality problem. Regularization terms based on heuristic assumptions are enrolled to avoid overfitting. In order to deal with the single image per person problem, we exploit face variations learned from training sets to synthesize virtual samples for gallery samples. We adopt a learning algorithm combining both affine/convex hull-based approach and regularizations to match image sets. Experimental results on a real-world dataset consisting of unconstrained video sequences demonstrate that our method outperforms the state-of-the-art methods impressively.

Traffic sign recognition based on deep convolutional neural network

NASA Astrophysics Data System (ADS)

Yin, Shi-hao; Deng, Ji-cai; Zhang, Da-wei; Du, Jing-yuan

2017-11-01

Traffic sign recognition (TSR) is an important component of automated driving systems. It is a rather challenging task to design a high-performance classifier for the TSR system. In this paper, we propose a new method for TSR system based on deep convolutional neural network. In order to enhance the expression of the network, a novel structure (dubbed block-layer below) which combines network-in-network and residual connection is designed. Our network has 10 layers with parameters (block-layer seen as a single layer): the first seven are alternate convolutional layers and block-layers, and the remaining three are fully-connected layers. We train our TSR network on the German traffic sign recognition benchmark (GTSRB) dataset. To reduce overfitting, we perform data augmentation on the training images and employ a regularization method named "dropout". The activation function we employ in our network adopts scaled exponential linear units (SELUs), which can induce self-normalizing properties. To speed up the training, we use an efficient GPU to accelerate the convolutional operation. On the test dataset of GTSRB, we achieve the accuracy rate of 99.67%, exceeding the state-of-the-art results.

Tryptophan depletion decreases the recognition of fear in female volunteers.

PubMed

Harmer, C J; Rogers, R D; Tunbridge, E; Cowen, P J; Goodwin, G M

2003-06-01

Serotonergic processes have been implicated in the modulation of fear conditioning in humans, postulated to occur at the level of the amygdala. The processing of other fear-relevant cues, such as facial expressions, has also been associated with amygdala function, but an effect of serotonin depletion on these processes has not been assessed. The present study investigated the effects of reducing serotonin function, using acute tryptophan depletion, on the recognition of basic facial expressions of emotions in healthy male and female volunteers. A double-blind between-groups design was used, with volunteers being randomly allocated to receive an amino acid drink specifically lacking tryptophan or a control mixture containing a balanced mixture of these amino acids. Participants were given a facial expression recognition task 5 h after drink administration. This task featured examples of six basic emotions (fear, anger, disgust, surprise, sadness and happiness) that had been morphed between each full emotion and neutral in 10% steps. As a control, volunteers were given a famous face classification task matched in terms of response selection and difficulty level. Tryptophan depletion significantly impaired the recognition of fearful facial expressions in female, but not male, volunteers. This was specific since recognition of other basic emotions was comparable in the two groups. There was also no effect of tryptophan depletion on the classification of famous faces or on subjective state ratings of mood or anxiety. These results confirm a role for serotonin in the processing of fear related cues, and in line with previous findings also suggest greater effects of tryptophan depletion in female volunteers. Although acute tryptophan depletion does not typically affect mood in healthy subjects, the present results suggest that subtle changes in the processing of emotional material may occur with this manipulation of serotonin function.

Culture but not gender modulates amygdala activation during explicit emotion recognition.

PubMed

Derntl, Birgit; Habel, Ute; Robinson, Simon; Windischberger, Christian; Kryspin-Exner, Ilse; Gur, Ruben C; Moser, Ewald

2012-05-29

Mounting evidence indicates that humans have significant difficulties in understanding emotional expressions from individuals of different ethnic backgrounds, leading to reduced recognition accuracy and stronger amygdala activation. However, the impact of gender on the behavioral and neural reactions during the initial phase of cultural assimilation has not been addressed. Therefore, we investigated 24 Asians students (12 females) and 24 age-matched European students (12 females) during an explicit emotion recognition task, using Caucasian facial expressions only, on a high-field MRI scanner. Analysis of functional data revealed bilateral amygdala activation to emotional expressions in Asian and European subjects. However, in the Asian sample, a stronger response of the amygdala emerged and was paralleled by reduced recognition accuracy, particularly for angry male faces. Moreover, no significant gender difference emerged. We also observed a significant inverse correlation between duration of stay and amygdala activation. In this study we investigated the "alien-effect" as an initial problem during cultural assimilation and examined this effect on a behavioral and neural level. This study has revealed bilateral amygdala activation to emotional expressions in Asian and European females and males. In the Asian sample, a stronger response of the amygdala bilaterally was observed and this was paralleled by reduced performance, especially for anger and disgust depicted by male expressions. However, no gender difference occurred. Taken together, while gender exerts only a subtle effect, culture and duration of stay as well as gender of poser are shown to be relevant factors for emotion processing, influencing not only behavioral but also neural responses in female and male immigrants.

Culture but not gender modulates amygdala activation during explicit emotion recognition

PubMed Central

2012-01-01

Background Mounting evidence indicates that humans have significant difficulties in understanding emotional expressions from individuals of different ethnic backgrounds, leading to reduced recognition accuracy and stronger amygdala activation. However, the impact of gender on the behavioral and neural reactions during the initial phase of cultural assimilation has not been addressed. Therefore, we investigated 24 Asians students (12 females) and 24 age-matched European students (12 females) during an explicit emotion recognition task, using Caucasian facial expressions only, on a high-field MRI scanner. Results Analysis of functional data revealed bilateral amygdala activation to emotional expressions in Asian and European subjects. However, in the Asian sample, a stronger response of the amygdala emerged and was paralleled by reduced recognition accuracy, particularly for angry male faces. Moreover, no significant gender difference emerged. We also observed a significant inverse correlation between duration of stay and amygdala activation. Conclusion In this study we investigated the “alien-effect” as an initial problem during cultural assimilation and examined this effect on a behavioral and neural level. This study has revealed bilateral amygdala activation to emotional expressions in Asian and European females and males. In the Asian sample, a stronger response of the amygdala bilaterally was observed and this was paralleled by reduced performance, especially for anger and disgust depicted by male expressions. However, no gender difference occurred. Taken together, while gender exerts only a subtle effect, culture and duration of stay as well as gender of poser are shown to be relevant factors for emotion processing, influencing not only behavioral but also neural responses in female and male immigrants. PMID:22642400

A multiplexable TALE-based binary expression system for in vivo cellular interaction studies.

PubMed

Toegel, Markus; Azzam, Ghows; Lee, Eunice Y; Knapp, David J H F; Tan, Ying; Fa, Ming; Fulga, Tudor A

2017-11-21

Binary expression systems have revolutionised genetic research by enabling delivery of loss-of-function and gain-of-function transgenes with precise spatial-temporal resolution in vivo. However, at present, each existing platform relies on a defined exogenous transcription activator capable of binding a unique recognition sequence. Consequently, none of these technologies alone can be used to simultaneously target different tissues or cell types in the same organism. Here, we report a modular system based on programmable transcription activator-like effector (TALE) proteins, which enables parallel expression of multiple transgenes in spatially distinct tissues in vivo. Using endogenous enhancers coupled to TALE drivers, we demonstrate multiplexed orthogonal activation of several transgenes carrying cognate variable activating sequences (VAS) in distinct neighbouring cell types of the Drosophila central nervous system. Since the number of combinatorial TALE-VAS pairs is virtually unlimited, this platform provides an experimental framework for highly complex genetic manipulation studies in vivo.

The expression and recognition of emotions in the voice across five nations: A lens model analysis based on acoustic features.

PubMed

Laukka, Petri; Elfenbein, Hillary Anger; Thingujam, Nutankumar S; Rockstuhl, Thomas; Iraki, Frederick K; Chui, Wanda; Althoff, Jean

2016-11-01

This study extends previous work on emotion communication across cultures with a large-scale investigation of the physical expression cues in vocal tone. In doing so, it provides the first direct test of a key proposition of dialect theory, namely that greater accuracy of detecting emotions from one's own cultural group-known as in-group advantage-results from a match between culturally specific schemas in emotional expression style and culturally specific schemas in emotion recognition. Study 1 used stimuli from 100 professional actors from five English-speaking nations vocally conveying 11 emotional states (anger, contempt, fear, happiness, interest, lust, neutral, pride, relief, sadness, and shame) using standard-content sentences. Detailed acoustic analyses showed many similarities across groups, and yet also systematic group differences. This provides evidence for cultural accents in expressive style at the level of acoustic cues. In Study 2, listeners evaluated these expressions in a 5 × 5 design balanced across groups. Cross-cultural accuracy was greater than expected by chance. However, there was also in-group advantage, which varied across emotions. A lens model analysis of fundamental acoustic properties examined patterns in emotional expression and perception within and across groups. Acoustic cues were used relatively similarly across groups both to produce and judge emotions, and yet there were also subtle cultural differences. Speakers appear to have a culturally nuanced schema for enacting vocal tones via acoustic cues, and perceivers have a culturally nuanced schema in judging them. Consistent with dialect theory's prediction, in-group judgments showed a greater match between these schemas used for emotional expression and perception. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Two antibacterial C-type lectins from crustacean, Eriocheir sinensis, stimulated cellular encapsulation in vitro.

PubMed

Jin, Xing-Kun; Li, Shuang; Guo, Xiao-Nv; Cheng, Lin; Wu, Min-Hao; Tan, Shang-Jian; Zhu, You-Ting; Yu, Ai-Qing; Li, Wei-Wei; Wang, Qun

2013-12-01

The first step of host fighting against pathogens is that pattern recognition receptors recognized pathogen-associated molecular patterns. However, the specificity of recognition within the innate immune molecular of invertebrates remains largely unknown. In the present study, we investigated how invertebrate pattern recognition receptor (PRR) C-type lectins might be involved in the antimicrobial response in crustacean. Based on our previously obtained completed coding regions of EsLecA and EsLecG in Eriocheir sinensis, the recombinant EsLectin proteins were produced via prokaryotic expression system and affinity chromatography. Subsequently, both rEsLecA and rEsLecG were discovered to have wide spectrum binding activities towards microorganisms, and their microbial-binding was calcium-independent. Moreover, the binding activities of both rEsLecA and rEsLecG induced the aggregation against microbial pathogens. Both microorganism growth inhibitory activities assays and antibacterial activities assays revealed their capabilities of suppressing microorganisms growth and directly killing microorganisms respectively. Furthermore, the encapsulation assays signified that both rEsLecA and rEsLecG could stimulate the cellular encapsulation in vitro. Collectively, data presented here demonstrated the successful expression and purification of two C-type lectins proteins in the Chinese mitten crab, and their critical role in the innate immune system of an invertebrate. Copyright © 2013 Elsevier Ltd. All rights reserved.

The telltale face: possible mechanisms behind defector and cooperator recognition revealed by emotional facial expression metrics.

PubMed

Kovács-Bálint, Zsófia; Bereczkei, Tamás; Hernádi, István

2013-11-01

In this study, we investigated the role of facial cues in cooperator and defector recognition. First, a face image database was constructed from pairs of full face portraits of target subjects taken at the moment of decision-making in a prisoner's dilemma game (PDG) and in a preceding neutral task. Image pairs with no deficiencies (n = 67) were standardized for orientation and luminance. Then, confidence in defector and cooperator recognition was tested with image rating in a different group of lay judges (n = 62). Results indicate that (1) defectors were better recognized (58% vs. 47%), (2) they looked different from cooperators (p < .01), (3) males but not females evaluated the images with a relative bias towards the cooperator category (p < .01), and (4) females were more confident in detecting defectors (p < .05). According to facial microexpression analysis, defection was strongly linked with depressed lower lips and less opened eyes. Significant correlation was found between the intensity of micromimics and the rating of images in the cooperator-defector dimension. In summary, facial expressions can be considered as reliable indicators of momentary social dispositions in the PDG. Females may exhibit an evolutionary-based overestimation bias to detecting social visual cues of the defector face. © 2012 The British Psychological Society.

Circadian Clearance of a Fungal Pathogen from the Lung Is Not Based on Cell-intrinsic Macrophage Rhythms.

PubMed

Chen, Shan; Fuller, Kevin K; Dunlap, Jay C; Loros, Jennifer J

2018-02-01

Circadian rhythms govern immune cell function, giving rise to time-of-day variation in the recognition and clearance of bacterial or viral pathogens; to date, however, no such regulation of the host-fungal interaction has been described. In this report, we use murine models to explore circadian control of either fungal-macrophage interactions in vitro or pathogen clearance from the lung in vivo. First, we show that expression of the important fungal pattern recognition receptor Dectin-1 ( clec7a), from either bone marrow-derived or peritoneum-derived macrophages, is not under circadian regulation at either the level of transcript or cell surface protein expression. Consistent with this finding, the phagocytic activity of macrophages in culture against spores of the pathogen Aspergillus fumigatus also did not vary over time. To account for the multiple cell types and processes that may be coordinated in a circadian fashion in vivo, we examined the clearance of A. fumigatus from the lungs of immunocompetent mice. Interestingly, animals inoculated at night demonstrated a 2-fold enhancement in clearance compared with animals inoculated in the morning. Taken together, our data suggest that while molecular recognition of fungi by immune cells may not be circadian, other processes in vivo may still allow for time-of-day differences in fungal clearance from the lung.

The Molecular Chaperone HSPA2 Plays a Key Role in Regulating the Expression of Sperm Surface Receptors That Mediate Sperm-Egg Recognition

PubMed Central

Redgrove, Kate A.; Nixon, Brett; Baker, Mark A.; Hetherington, Louise; Baker, Gordon; Liu, De-Yi; Aitken, R. John

2012-01-01

A common defect encountered in the spermatozoa of male infertility patients is an idiopathic failure of sperm–egg recognition. In order to resolve the molecular basis of this condition we have compared the proteomic profiles of spermatozoa exhibiting an impaired capacity for sperm-egg recognition with normal cells using label free mass spectrometry (MS)-based quantification. This analysis indicated that impaired sperm–zona binding was associated with reduced expression of the molecular chaperone, heat shock 70 kDa protein 2 (HSPA2), from the sperm proteome. Western blot analysis confirmed this observation in independent patients and demonstrated that the defect did not extend to other members of the HSP70 family. HSPA2 was present in the acrosomal domain of human spermatozoa as a major component of 5 large molecular mass complexes, the most dominant of which was found to contain HSPA2 in close association with just two other proteins, sperm adhesion molecule 1 (SPAM1) and arylsulfatase A (ARSA), both of which that have previously been implicated in sperm-egg interaction. The interaction between SPAM1, ARSA and HSPA2 in a multimeric complex mediating sperm-egg interaction, coupled with the complete failure of this process when HSPA2 is depleted in infertile patients, provides new insights into the mechanisms by which sperm function is impaired in cases of male infertility. PMID:23209833

Branch length similarity entropy-based descriptors for shape representation

NASA Astrophysics Data System (ADS)

Kwon, Ohsung; Lee, Sang-Hee

2017-11-01

In previous studies, we showed that the branch length similarity (BLS) entropy profile could be successfully used for the shape recognition such as battle tanks, facial expressions, and butterflies. In the present study, we proposed new descriptors, roundness, symmetry, and surface roughness, for the recognition, which are more accurate and fast in the computation than the previous descriptors. The roundness represents how closely a shape resembles to a circle, the symmetry characterizes how much one shape is similar with another when the shape is moved in flip, and the surface roughness quantifies the degree of vertical deviations of a shape boundary. To evaluate the performance of the descriptors, we used the database of leaf images with 12 species. Each species consisted of 10 - 20 leaf images and the total number of images were 160. The evaluation showed that the new descriptors successfully discriminated the leaf species. We believe that the descriptors can be a useful tool in the field of pattern recognition.

Local gradient Gabor pattern (LGGP) with applications in face recognition, cross-spectral matching, and soft biometrics

NASA Astrophysics Data System (ADS)

Chen, Cunjian; Ross, Arun

2013-05-01

Researchers in face recognition have been using Gabor filters for image representation due to their robustness to complex variations in expression and illumination. Numerous methods have been proposed to model the output of filter responses by employing either local or global descriptors. In this work, we propose a novel but simple approach for encoding Gradient information on Gabor-transformed images to represent the face, which can be used for identity, gender and ethnicity assessment. Extensive experiments on the standard face benchmark FERET (Visible versus Visible), as well as the heterogeneous face dataset HFB (Near-infrared versus Visible), suggest that the matching performance due to the proposed descriptor is comparable against state-of-the-art descriptor-based approaches in face recognition applications. Furthermore, the same feature set is used in the framework of a Collaborative Representation Classification (CRC) scheme for deducing soft biometric traits such as gender and ethnicity from face images in the AR, Morph and CAS-PEAL databases.

Mapping the emotional face. How individual face parts contribute to successful emotion recognition.

PubMed

Wegrzyn, Martin; Vogt, Maria; Kireclioglu, Berna; Schneider, Julia; Kissler, Johanna

2017-01-01

Which facial features allow human observers to successfully recognize expressions of emotion? While the eyes and mouth have been frequently shown to be of high importance, research on facial action units has made more precise predictions about the areas involved in displaying each emotion. The present research investigated on a fine-grained level, which physical features are most relied on when decoding facial expressions. In the experiment, individual faces expressing the basic emotions according to Ekman were hidden behind a mask of 48 tiles, which was sequentially uncovered. Participants were instructed to stop the sequence as soon as they recognized the facial expression and assign it the correct label. For each part of the face, its contribution to successful recognition was computed, allowing to visualize the importance of different face areas for each expression. Overall, observers were mostly relying on the eye and mouth regions when successfully recognizing an emotion. Furthermore, the difference in the importance of eyes and mouth allowed to group the expressions in a continuous space, ranging from sadness and fear (reliance on the eyes) to disgust and happiness (mouth). The face parts with highest diagnostic value for expression identification were typically located in areas corresponding to action units from the facial action coding system. A similarity analysis of the usefulness of different face parts for expression recognition demonstrated that faces cluster according to the emotion they express, rather than by low-level physical features. Also, expressions relying more on the eyes or mouth region were in close proximity in the constructed similarity space. These analyses help to better understand how human observers process expressions of emotion, by delineating the mapping from facial features to psychological representation.

Mapping the emotional face. How individual face parts contribute to successful emotion recognition

PubMed Central

Wegrzyn, Martin; Vogt, Maria; Kireclioglu, Berna; Schneider, Julia; Kissler, Johanna

2017-01-01

Which facial features allow human observers to successfully recognize expressions of emotion? While the eyes and mouth have been frequently shown to be of high importance, research on facial action units has made more precise predictions about the areas involved in displaying each emotion. The present research investigated on a fine-grained level, which physical features are most relied on when decoding facial expressions. In the experiment, individual faces expressing the basic emotions according to Ekman were hidden behind a mask of 48 tiles, which was sequentially uncovered. Participants were instructed to stop the sequence as soon as they recognized the facial expression and assign it the correct label. For each part of the face, its contribution to successful recognition was computed, allowing to visualize the importance of different face areas for each expression. Overall, observers were mostly relying on the eye and mouth regions when successfully recognizing an emotion. Furthermore, the difference in the importance of eyes and mouth allowed to group the expressions in a continuous space, ranging from sadness and fear (reliance on the eyes) to disgust and happiness (mouth). The face parts with highest diagnostic value for expression identification were typically located in areas corresponding to action units from the facial action coding system. A similarity analysis of the usefulness of different face parts for expression recognition demonstrated that faces cluster according to the emotion they express, rather than by low-level physical features. Also, expressions relying more on the eyes or mouth region were in close proximity in the constructed similarity space. These analyses help to better understand how human observers process expressions of emotion, by delineating the mapping from facial features to psychological representation. PMID:28493921

Empathy, but not mimicry restriction, influences the recognition of change in emotional facial expressions.

PubMed

Kosonogov, Vladimir; Titova, Alisa; Vorobyeva, Elena

2015-01-01

The current study addressed the hypothesis that empathy and the restriction of facial muscles of observers can influence recognition of emotional facial expressions. A sample of 74 participants recognized the subjective onset of emotional facial expressions (anger, disgust, fear, happiness, sadness, surprise, and neutral) in a series of morphed face photographs showing a gradual change (frame by frame) from one expression to another. The high-empathy (as measured by the Empathy Quotient) participants recognized emotional facial expressions at earlier photographs from the series than did low-empathy ones, but there was no difference in the exploration time. Restriction of facial muscles of observers (with plasters and a stick in mouth) did not influence the responses. We discuss these findings in the context of the embodied simulation theory and previous data on empathy.

Online Feature Transformation Learning for Cross-Domain Object Category Recognition.

PubMed

Zhang, Xuesong; Zhuang, Yan; Wang, Wei; Pedrycz, Witold

2017-06-09

In this paper, we introduce a new research problem termed online feature transformation learning in the context of multiclass object category recognition. The learning of a feature transformation is viewed as learning a global similarity metric function in an online manner. We first consider the problem of online learning a feature transformation matrix expressed in the original feature space and propose an online passive aggressive feature transformation algorithm. Then these original features are mapped to kernel space and an online single kernel feature transformation (OSKFT) algorithm is developed to learn a nonlinear feature transformation. Based on the OSKFT and the existing Hedge algorithm, a novel online multiple kernel feature transformation algorithm is also proposed, which can further improve the performance of online feature transformation learning in large-scale application. The classifier is trained with k nearest neighbor algorithm together with the learned similarity metric function. Finally, we experimentally examined the effect of setting different parameter values in the proposed algorithms and evaluate the model performance on several multiclass object recognition data sets. The experimental results demonstrate the validity and good performance of our methods on cross-domain and multiclass object recognition application.

Psychometric properties of the NEPSY-II affect recognition subtest in a preschool sample: a Rasch modeling approach.

PubMed

Yao, Shih-Ying; Bull, Rebecca; Khng, Kiat Hui; Rahim, Anisa

2018-01-01

Understanding a child's ability to decode emotion expressions is important to allow early interventions for potential difficulties in social and emotional functioning. This study applied the Rasch model to investigate the psychometric properties of the NEPSY-II Affect Recognition subtest, a U.S. normed measure for 3-16 year olds which assesses the ability to recognize facial expressions of emotion. Data were collected from 1222 children attending preschools in Singapore. We first performed the Rasch analysis with the raw item data, and examined the technical qualities and difficulty pattern of the studied items. We subsequently investigated the relation of the estimated affect recognition ability from the Rasch analysis to a teacher-reported measure of a child's behaviors, emotions, and relationships. Potential gender differences were also examined. The Rasch model fits our data well. Also, the NEPSY-II Affect Recognition subtest was found to have reasonable technical qualities, expected item difficulty pattern, and desired association with the external measure of children's behaviors, emotions, and relationships for both boys and girls. Overall, findings from this study suggest that the NEPSY-II Affect Recognition subtest is a promising measure of young children's affect recognition ability. Suggestions for future test improvement and research were discussed.

Impaired perception of facial emotion in developmental prosopagnosia.

PubMed

Biotti, Federica; Cook, Richard

2016-08-01

Developmental prosopagnosia (DP) is a neurodevelopmental condition characterised by difficulties recognising faces. Despite severe difficulties recognising facial identity, expression recognition is typically thought to be intact in DP; case studies have described individuals who are able to correctly label photographic displays of facial emotion, and no group differences have been reported. This pattern of deficits suggests a locus of impairment relatively late in the face processing stream, after the divergence of expression and identity analysis pathways. To date, however, there has been little attempt to investigate emotion recognition systematically in a large sample of developmental prosopagnosics using sensitive tests. In the present study, we describe three complementary experiments that examine emotion recognition in a sample of 17 developmental prosopagnosics. In Experiment 1, we investigated observers' ability to make binary classifications of whole-face expression stimuli drawn from morph continua. In Experiment 2, observers judged facial emotion using only the eye-region (the rest of the face was occluded). Analyses of both experiments revealed diminished ability to classify facial expressions in our sample of developmental prosopagnosics, relative to typical observers. Imprecise expression categorisation was particularly evident in those individuals exhibiting apperceptive profiles, associated with problems encoding facial shape accurately. Having split the sample of prosopagnosics into apperceptive and non-apperceptive subgroups, only the apperceptive prosopagnosics were impaired relative to typical observers. In our third experiment, we examined the ability of observers' to classify the emotion present within segments of vocal affect. Despite difficulties judging facial emotion, the prosopagnosics exhibited excellent recognition of vocal affect. Contrary to the prevailing view, our results suggest that many prosopagnosics do experience difficulties classifying expressions, particularly those with apperceptive profiles. These individuals may have difficulties forming view-invariant structural descriptions at an early stage in the face processing stream, before identity and expression pathways diverge. Copyright © 2016 Elsevier Ltd. All rights reserved.

Effects of training set selection on pain recognition via facial expressions

NASA Astrophysics Data System (ADS)

Shier, Warren A.; Yanushkevich, Svetlana N.

2016-07-01

This paper presents an approach to pain expression classification based on Gabor energy filters with Support Vector Machines (SVMs), followed by analyzing the effects of training set variations on the systems classification rate. This approach is tested on the UNBC-McMaster Shoulder Pain Archive, which consists of spontaneous pain images, hand labelled using the Prkachin and Solomon Pain Intensity scale. In this paper, the subjects pain intensity level has been quantized into three disjoint groups: no pain, weak pain and strong pain. The results of experiments show that Gabor energy filters with SVMs provide comparable or better results to previous filter- based pain recognition methods, with precision rates of 74%, 30% and 78% for no pain, weak pain and strong pain, respectively. The study of effects of intra-class skew, or changing the number of images per subject, show that both completely removing and over-representing poor quality subjects in the training set has little effect on the overall accuracy of the system. This result suggests that poor quality subjects could be removed from the training set to save offline training time and that SVM is robust not only to outliers in training data, but also to significant amounts of poor quality data mixed into the training sets.

Pathways for smiling, disgust and fear recognition in blindsight patients.

PubMed

Gerbella, Marzio; Caruana, Fausto; Rizzolatti, Giacomo

2017-08-31

The aim of the present review is to discuss the localization of circuits that allow recognition of emotional facial expressions in blindsight patients. Because recognition of facial expressions is function of different centers, and their localization is not always clear, we decided to discuss here three emotional facial expression - smiling, disgust, and fear - whose anatomical localization in the pregenual sector of the anterior cingulate cortex (pACC), anterior insula (AI), and amygdala, respectively, is well established. We examined, then, the possible pathways that may convey affective visual information to these centers following lesions of V1. We concluded that the pathway leading to pACC, AI, and amygdala involves the deep layers of the superior colliculus, the medial pulvinar, and the superior temporal sulcus region. We suggest that this visual pathway provides an image of the observed affective faces, which, although deteriorated, is sufficient to determine some overt behavior, but not to provide conscious experience of the presented stimuli. Copyright © 2017 Elsevier Ltd. All rights reserved.

Emotion through locomotion: gender impact.

PubMed

Krüger, Samuel; Sokolov, Alexander N; Enck, Paul; Krägeloh-Mann, Ingeborg; Pavlova, Marina A

2013-01-01

Body language reading is of significance for daily life social cognition and successful social interaction, and constitutes a core component of social competence. Yet it is unclear whether our ability for body language reading is gender specific. In the present work, female and male observers had to visually recognize emotions through point-light human locomotion performed by female and male actors with different emotional expressions. For subtle emotional expressions only, males surpass females in recognition accuracy and readiness to respond to happy walking portrayed by female actors, whereas females exhibit a tendency to be better in recognition of hostile angry locomotion expressed by male actors. In contrast to widespread beliefs about female superiority in social cognition, the findings suggest that gender effects in recognition of emotions from human locomotion are modulated by emotional content of actions and opposite actor gender. In a nutshell, the study makes a further step in elucidation of gender impact on body language reading and on neurodevelopmental and psychiatric deficits in visual social cognition.

Reduced fear-recognition sensitivity following acute buprenorphine administration in healthy volunteers.

PubMed

Ipser, Jonathan C; Terburg, David; Syal, Supriya; Phillips, Nicole; Solms, Mark; Panksepp, Jaak; Malcolm-Smith, Susan; Thomas, Kevin; Stein, Dan J; van Honk, Jack

2013-01-01

In rodents, the endogenous opioid system has been implicated in emotion regulation, and in the reduction of fear in particular. In humans, while there is evidence that the opioid antagonist naloxone acutely enhances the acquisition of conditioned fear, there are no corresponding data on the effect of opioid agonists in moderating responses to fear. We investigated whether a single 0.2mg administration of the mu-opioid agonist buprenorphine would decrease fear sensitivity with an emotion-recognition paradigm. Healthy human subjects participated in a randomized placebo-controlled within-subject design, in which they performed a dynamic emotion recognition task 120min after administration of buprenorphine and placebo. In the recognition task, basic emotional expressions were morphed between their full expression and neutral in 2% steps, and presented as dynamic video-clips with final frames of different emotional intensity for each trial, which allows for a fine-grained measurement of emotion sensitivity. Additionally, visual analog scales were used to investigate acute effects of buprenorphine on mood. Compared to placebo, buprenorphine resulted in a significant reduction in the sensitivity for recognizing fearful facial expressions exclusively. Our data demonstrate, for the first time in humans, that acute up-regulation of the opioid system reduces fear recognition sensitivity. Moreover, the absence of an effect of buprenorphine on mood provides evidence of a direct influence of opioids upon the core fear system in the human brain. Copyright © 2012 Elsevier Ltd. All rights reserved.

Analysis of facial expressions in parkinson's disease through video-based automatic methods.

PubMed

Bandini, Andrea; Orlandi, Silvia; Escalante, Hugo Jair; Giovannelli, Fabio; Cincotta, Massimo; Reyes-Garcia, Carlos A; Vanni, Paola; Zaccara, Gaetano; Manfredi, Claudia

2017-04-01

The automatic analysis of facial expressions is an evolving field that finds several clinical applications. One of these applications is the study of facial bradykinesia in Parkinson's disease (PD), which is a major motor sign of this neurodegenerative illness. Facial bradykinesia consists in the reduction/loss of facial movements and emotional facial expressions called hypomimia. In this work we propose an automatic method for studying facial expressions in PD patients relying on video-based METHODS: 17 Parkinsonian patients and 17 healthy control subjects were asked to show basic facial expressions, upon request of the clinician and after the imitation of a visual cue on a screen. Through an existing face tracker, the Euclidean distance of the facial model from a neutral baseline was computed in order to quantify the changes in facial expressivity during the tasks. Moreover, an automatic facial expressions recognition algorithm was trained in order to study how PD expressions differed from the standard expressions. Results show that control subjects reported on average higher distances than PD patients along the tasks. This confirms that control subjects show larger movements during both posed and imitated facial expressions. Moreover, our results demonstrate that anger and disgust are the two most impaired expressions in PD patients. Contactless video-based systems can be important techniques for analyzing facial expressions also in rehabilitation, in particular speech therapy, where patients could get a definite advantage from a real-time feedback about the proper facial expressions/movements to perform. Copyright © 2017 Elsevier B.V. All rights reserved.

Prenatal exposure to phencyclidine produces abnormal behaviour and NMDA receptor expression in postpubertal mice.

PubMed

Lu, Lingling; Mamiya, Takayoshi; Lu, Ping; Toriumi, Kazuya; Mouri, Akihiro; Hiramatsu, Masayuki; Kim, Hyoung-Chun; Zou, Li-Bo; Nagai, Taku; Nabeshima, Toshitaka

2010-08-01

Several studies have shown the disruptive effects of non-competitive N-methyl-d-aspartate (NMDA) receptor antagonists on neurobehavioural development. Based on the neurodevelopment hypothesis of schizophrenia, there is growing interest in animal models treated with NMDA antagonists at developing stages to investigate the pathogenesis of psychological disturbances in humans. Previous studies have reported that perinatal treatment with phencyclidine (PCP) impairs the development of neuronal systems and induces schizophrenia-like behaviour. However, the adverse effects of prenatal exposure to PCP on behaviour and the function of NMDA receptors are not well understood. This study investigated the long-term effects of prenatal exposure to PCP in mice. The prenatal PCP-treated mice showed hypersensitivity to a low dose of PCP in locomotor activity and impairment of recognition memory in the novel object recognition test at age 7 wk. Meanwhile, the prenatal exposure reduced the phosphorylation of NR1, although it increased the expression of NR1 itself. Furthermore, these behavioural changes were attenuated by atypical antipsychotic treatment. Taken together, prenatal exposure to PCP produced long-lasting behavioural deficits, accompanied by the abnormal expression and dysfunction of NMDA receptors in postpubertal mice. It is worth investigating the influences of disrupted NMDA receptors during the prenatal period on behaviour in later life.

A galectin from Eriocheir sinensis functions as pattern recognition receptor enhancing microbe agglutination and haemocytes encapsulation.

PubMed

Wang, Mengqiang; Wang, Lingling; Huang, Mengmeng; Yi, Qilin; Guo, Ying; Gai, Yunchao; Wang, Hao; Zhang, Huan; Song, Linsheng

2016-08-01

Galectins are a family of β-galactoside binding lectins that function as pattern recognition receptors (PRRs) in innate immune system of both vertebrates and invertebrates. The cDNA of Chinese mitten crab Eriocheir sinensis galectin (designated as EsGal) was cloned via rapid amplification of cDNA ends (RACE) technique based on expressed sequence tags (ESTs) analysis. The full-length cDNA of EsGal was 999 bp. Its open reading frame encoded a polypeptide of 218 amino acids containing a GLECT/Gal-bind_lectin domain and a proline/glycine rich low complexity region. The deduced amino acid sequence and domain organization of EsGal were highly similar to those of crustacean galectins. The mRNA transcripts of EsGal were found to be constitutively expressed in a wide range of tissues and mainly in hepatopancreas, gill and haemocytes. The mRNA expression level of EsGal increased rapidly and significantly after crabs were stimulated by different microbes. The recombinant EsGal (rEsGal) could bind various pathogen-associated molecular patterns (PAMPs), including lipopolysaccharide (LPS), peptidoglycan (PGN) and glucan (GLU), and exhibited strong activity to agglutinate Escherichia coli, Vibrio anguillarum, Bacillus subtilis, Micrococcus luteus, Staphylococcus aureus and Pichia pastoris, and such agglutinating activity could be inhibited by both d-galactose and α-lactose. The in vitro encapsulation assay revealed that rEsGal could enhance the encapsulation of haemocytes towards agarose beads. These results collectively suggested that EsGal played crucial roles in the immune recognition and elimination of pathogens and contributed to the innate immune response against various microbes in crabs. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparison of a preQ1 riboswitch aptamer in metabolite-bound and free states with implications for gene regulation.

PubMed

Jenkins, Jermaine L; Krucinska, Jolanta; McCarty, Reid M; Bandarian, Vahe; Wedekind, Joseph E

2011-07-15

Riboswitches are RNA regulatory elements that govern gene expression by recognition of small molecule ligands via a high affinity aptamer domain. Molecular recognition can lead to active or attenuated gene expression states by controlling accessibility to mRNA signals necessary for transcription or translation. Key areas of inquiry focus on how an aptamer attains specificity for its effector, the extent to which the aptamer folds prior to encountering its ligand, and how ligand binding alters expression signal accessibility. Here we present crystal structures of the preQ(1) riboswitch from Thermoanaerobacter tengcongensis in the preQ(1)-bound and free states. Although the mode of preQ(1) recognition is similar to that observed for preQ(0), surface plasmon resonance revealed an apparent K(D) of 2.1 ± 0.3 nm for preQ(1) but a value of 35.1 ± 6.1 nm for preQ(0). This difference can be accounted for by interactions between the preQ(1) methylamine and base G5 of the aptamer. To explore conformational states in the absence of metabolite, the free-state aptamer structure was determined. A14 from the ceiling of the ligand pocket shifts into the preQ(1)-binding site, resulting in "closed" access to the metabolite while simultaneously increasing exposure of the ribosome-binding site. Solution scattering data suggest that the free-state aptamer is compact, but the "closed" free-state crystal structure is inadequate to describe the solution scattering data. These observations are distinct from transcriptional preQ(1) riboswitches of the same class that exhibit strictly ligand-dependent folding. Implications for gene regulation are discussed.

Learning the spherical harmonic features for 3-D face recognition.

PubMed

Liu, Peijiang; Wang, Yunhong; Huang, Di; Zhang, Zhaoxiang; Chen, Liming

2013-03-01

In this paper, a competitive method for 3-D face recognition (FR) using spherical harmonic features (SHF) is proposed. With this solution, 3-D face models are characterized by the energies contained in spherical harmonics with different frequencies, thereby enabling the capture of both gross shape and fine surface details of a 3-D facial surface. This is in clear contrast to most 3-D FR techniques which are either holistic or feature based, using local features extracted from distinctive points. First, 3-D face models are represented in a canonical representation, namely, spherical depth map, by which SHF can be calculated. Then, considering the predictive contribution of each SHF feature, especially in the presence of facial expression and occlusion, feature selection methods are used to improve the predictive performance and provide faster and more cost-effective predictors. Experiments have been carried out on three public 3-D face datasets, SHREC2007, FRGC v2.0, and Bosphorus, with increasing difficulties in terms of facial expression, pose, and occlusion, and which demonstrate the effectiveness of the proposed method.

[Patients' autonomy and doctors' duties according to the Andalusian bill of "dignified dead"].

PubMed

Díez Fernández, José Antonio

2010-01-01

The provisions of the andalusian Law on rights and guarantees of the dignity of persons in the process of death, also known as "act of dignified death", are based on two pillars: the right to the autonomy of the patient, supported, if it be, in a will expressed in instructions given in advance and the duties of doctors and health centers to give satisfaction, to the extent of their potential and respecting the law, those demands. the core of the question is to find the point of necessary balance between the wishes of the patient and the freedom and responsibility of the doctor. Together with positive aspects, such as the recognition of the right and the implementation of the palliative care, there are other questionable proposals, affecting the rights of doctors: a lack of understanding of freedom and professional responsibility, recognition of the objection of conscience and certain ethics duties, etc. As expressed by the law, remain committed substantial rights of doctors and might favor, in the care activity, introducing practices of defensive medicine.

Multiple mechanisms underlie defective recognition of melanoma cells cultured in three-dimensional architectures by antigen-specific cytotoxic T lymphocytes.

PubMed

Feder-Mengus, C; Ghosh, S; Weber, W P; Wyler, S; Zajac, P; Terracciano, L; Oertli, D; Heberer, M; Martin, I; Spagnoli, G C; Reschner, A

2007-04-10

Cancer cells' growth in three-dimensional (3D) architectures promotes resistance to drugs, cytokines, or irradiation. We investigated effects of 3D culture as compared to monolayers (2D) on melanoma cells' recognition by tumour-associated antigen (TAA)-specific HLA-A(*)0201-restricted cytotoxic T-lymphocytes (CTL). Culture of HBL, D10 (both HLA-A(*)0201+, TAA+) and NA8 (HLA-A(*)0201+, TAA-) melanoma cells on polyHEMA-coated plates, resulted in generation of 3D multicellular tumour spheroids (MCTS). Interferon-gamma (IFN-gamma) production by HLA-A(*)0201-restricted Melan-A/MART-1(27-35) or gp 100(280-288)-specific CTL clones served as immunorecognition marker. Co-culture with melanoma MCTS, resulted in defective TAA recognition by CTL as compared to 2D as witnessed by decreased IFN-gamma production and decreased Fas Ligand, perforin and granzyme B gene expression. A multiplicity of mechanisms were potentially involved. First, MCTS per se limit CTL capacity of recognising HLA class I restricted antigens by reducing exposed cell surfaces. Second, expression of melanoma differentiation antigens is downregulated in MCTS. Third, expression of HLA class I molecules can be downregulated in melanoma MCTS, possibly due to decreased interferon-regulating factor-1 gene expression. Fourth, lactic acid production is increased in MCTS, as compared to 2D. These data suggest that melanoma cells growing in 3D, even in the absence of immune selection, feature characteristics capable of dramatically inhibiting TAA recognition by specific CTL.

Versatile aptasensor for electrochemical quantification of cell surface glycan and naked-eye tracking glycolytic inhibition in living cells.

PubMed

Zhang, Jing-Jing; Cheng, Fang-Fang; Zheng, Ting-Ting; Zhu, Jun-Jie

2017-03-15

Quantifying the glycan expression status on cell surfaces is of vital importance for insight into the glycan function in biological processes and related diseases. Here we developed a versatile aptasensor for electrochemical quantification of cell surface glycan by taking advantage of the cell-specific aptamer, and the lectin-functionalized gold nanoparticles acting as both a glycan recognition unit and a signal amplification probe. To construct the aptasensor, amine-functionalized mucin 1 protein (MUC1) aptamer was first covalently conjugated to carboxylated-magnetic beads (MBs) using the succinimide coupling (EDC-NHS) method. On the basis of the specific recognition between aptamer and MUC1 protein that overexpressed on the surface of MCF-7 cells, the aptamer conjugated MBs showed a predominant capability for cell capture with high selectivity. Moreover, a lectin-based nanoprobe was designed by noncovalent assembly of concanavalin A (ConA) on gold nanoparticles (AuNPs). This nanoprobe incorporated the abilities of both the specific carbohydrate recognition and the signal amplification based on the gold-promoted reduction of silver ions. By coupling with electrochemical stripping analysis, the proposed sandwich-type cytosensor showed an excellent analytical performance for the ultrasensitive detection of MCF-7 cells and quantification of cell surface glycan. More importantly, taking advantage of Con A-gold nanoprobe catalyzed silver enhancement, the proposed method was further used for naked-eye tracking glycolytic inhibition in living cells. This aptasensor holds great promise as a new point-of-care diagnostic tool for analyzing glycan expression on living cells and further helps cancer diagnosis and treatment. Copyright © 2016 Elsevier B.V. All rights reserved.

Activation of Supraoptic Oxytocin Neurons by Secretin Facilitates Social Recognition.

PubMed

Takayanagi, Yuki; Yoshida, Masahide; Takashima, Akihide; Takanami, Keiko; Yoshida, Shoma; Nishimori, Katsuhiko; Nishijima, Ichiko; Sakamoto, Hirotaka; Yamagata, Takanori; Onaka, Tatsushi

2017-02-01

Social recognition underlies social behavior in animals, and patients with psychiatric disorders associated with social deficits show abnormalities in social recognition. Oxytocin is implicated in social behavior and has received attention as an effective treatment for sociobehavioral deficits. Secretin receptor-deficient mice show deficits in social behavior. The relationship between oxytocin and secretin concerning social behavior remains to be determined. Expression of c-Fos in oxytocin neurons and release of oxytocin from their dendrites after secretin application were investigated. Social recognition was examined after intracerebroventricular or local injection of secretin, oxytocin, or an oxytocin receptor antagonist in rats, oxytocin receptor-deficient mice, and secretin receptor-deficient mice. Electron and light microscopic immunohistochemical analysis was also performed to determine whether oxytocin neurons extend their dendrites into the medial amygdala. Supraoptic oxytocin neurons expressed the secretin receptor. Secretin activated supraoptic oxytocin neurons and facilitated oxytocin release from dendrites. Secretin increased acquisition of social recognition in an oxytocin receptor-dependent manner. Local application of secretin into the supraoptic nucleus facilitated social recognition, and this facilitation was blocked by an oxytocin receptor antagonist injected into, but not outside of, the medial amygdala. In the medial amygdala, dendrite-like thick oxytocin processes were found to extend from the supraoptic nucleus. Furthermore, oxytocin treatment restored deficits of social recognition in secretin receptor-deficient mice. The results of our study demonstrate that secretin-induced dendritic oxytocin release from supraoptic neurons enhances social recognition. The newly defined secretin-oxytocin system may lead to a possible treatment for social deficits. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Design method of ARM based embedded iris recognition system

NASA Astrophysics Data System (ADS)

Wang, Yuanbo; He, Yuqing; Hou, Yushi; Liu, Ting

2008-03-01

With the advantages of non-invasiveness, uniqueness, stability and low false recognition rate, iris recognition has been successfully applied in many fields. Up to now, most of the iris recognition systems are based on PC. However, a PC is not portable and it needs more power. In this paper, we proposed an embedded iris recognition system based on ARM. Considering the requirements of iris image acquisition and recognition algorithm, we analyzed the design method of the iris image acquisition module, designed the ARM processing module and its peripherals, studied the Linux platform and the recognition algorithm based on this platform, finally actualized the design method of ARM-based iris imaging and recognition system. Experimental results show that the ARM platform we used is fast enough to run the iris recognition algorithm, and the data stream can flow smoothly between the camera and the ARM chip based on the embedded Linux system. It's an effective method of using ARM to actualize portable embedded iris recognition system.

Identification of Id4 as a regulator of BRCA1 expression by using a ribozyme-library-based inverse genomics approach

PubMed Central

Beger, Carmela; Pierce, Leigh N.; Krüger, Martin; Marcusson, Eric G.; Robbins, Joan M.; Welcsh, Piri; Welch, Peter J.; Welte, Karl; King, Mary-Claire; Barber, Jack R.; Wong-Staal, Flossie

2001-01-01

Expression of the breast and ovarian cancer susceptibility gene BRCA1 is down-regulated in sporadic breast and ovarian cancer cases. Therefore, the identification of genes involved in the regulation of BRCA1 expression might lead to new insights into the pathogenesis and treatment of these tumors. In the present study, an “inverse genomics” approach based on a randomized ribozyme gene library was applied to identify cellular genes regulating BRCA1 expression. A ribozyme gene library with randomized target recognition sequences was introduced into human ovarian cancer-derived cells stably expressing a selectable marker [enhanced green fluorescence protein (EGFP)] under the control of the BRCA1 promoter. Cells in which BRCA1 expression was upregulated by particular ribozymes were selected through their concomitant increase in EGFP expression. The cellular target gene of one ribozyme was identified to be the dominant negative transcriptional regulator Id4. Modulation of Id4 expression resulted in inversely regulated expression of BRCA1. In addition, increase in Id4 expression was associated with the ability of cells to exhibit anchorage-independent growth, demonstrating the biological relevance of this gene. Our data suggest that Id4 is a crucial gene regulating BRCA1 expression and might therefore be important for the BRCA1 regulatory pathway involved in the pathogenesis of sporadic breast and ovarian cancer. PMID:11136250

Facial emotion recognition in adolescents with psychotic-like experiences: a school-based sample from the general population.

PubMed

Roddy, S; Tiedt, L; Kelleher, I; Clarke, M C; Murphy, J; Rawdon, C; Roche, R A P; Calkins, M E; Richard, J A; Kohler, C G; Cannon, M

2012-10-01

Psychotic symptoms, also termed psychotic-like experiences (PLEs) in the absence of psychotic disorder, are common in adolescents and are associated with increased risk of schizophrenia-spectrum illness in adulthood. At the same time, schizophrenia is associated with deficits in social cognition, with deficits particularly documented in facial emotion recognition (FER). However, little is known about the relationship between PLEs and FER abilities, with only one previous prospective study examining the association between these abilities in childhood and reported PLEs in adolescence. The current study was a cross-sectional investigation of the association between PLEs and FER in a sample of Irish adolescents. The Adolescent Psychotic-Like Symptom Screener (APSS), a self-report measure of PLEs, and the Penn Emotion Recognition-40 Test (Penn ER-40), a measure of facial emotion recognition, were completed by 793 children aged 10-13 years. Children who reported PLEs performed significantly more poorly on FER (β=-0.03, p=0.035). Recognition of sad faces was the major driver of effects, with children performing particularly poorly when identifying this expression (β=-0.08, p=0.032). The current findings show that PLEs are associated with poorer FER. Further work is needed to elucidate causal relationships with implications for the design of future interventions for those at risk of developing psychosis.

Face photo-sketch synthesis and recognition.

PubMed

Wang, Xiaogang; Tang, Xiaoou

2009-11-01

In this paper, we propose a novel face photo-sketch synthesis and recognition method using a multiscale Markov Random Fields (MRF) model. Our system has three components: 1) given a face photo, synthesizing a sketch drawing; 2) given a face sketch drawing, synthesizing a photo; and 3) searching for face photos in the database based on a query sketch drawn by an artist. It has useful applications for both digital entertainment and law enforcement. We assume that faces to be studied are in a frontal pose, with normal lighting and neutral expression, and have no occlusions. To synthesize sketch/photo images, the face region is divided into overlapping patches for learning. The size of the patches decides the scale of local face structures to be learned. From a training set which contains photo-sketch pairs, the joint photo-sketch model is learned at multiple scales using a multiscale MRF model. By transforming a face photo to a sketch (or transforming a sketch to a photo), the difference between photos and sketches is significantly reduced, thus allowing effective matching between the two in face sketch recognition. After the photo-sketch transformation, in principle, most of the proposed face photo recognition approaches can be applied to face sketch recognition in a straightforward way. Extensive experiments are conducted on a face sketch database including 606 faces, which can be downloaded from our Web site (http://mmlab.ie.cuhk.edu.hk/facesketch.html).

Micro-Controllable, Multi-Functional Interface Module for Digital MP: A Wearable Computer Security Application

DTIC Science & Technology

2004-05-01

Army Soldier System Command: http://www.natick.armv.mil Role Name Facial Recognition Program Manager, Army Technical Lead Mark Chandler...security force with a facial recognition system. Mike Holloran, technology officer with the 6 Fleet, directed LCDR Hoa Ho and CAPT(s) Todd Morgan to...USN 6th Fleet was accomplished with the admiral expressing his support for continuing the evaluation of the a facial recognition system. This went

Recognition, Expression, and Understanding Facial Expressions of Emotion in Adolescents with Nonverbal and General Learning Disabilities

ERIC Educational Resources Information Center

Bloom, Elana; Heath, Nancy

2010-01-01

Children with nonverbal learning disabilities (NVLD) have been found to be worse at recognizing facial expressions than children with verbal learning disabilities (LD) and without LD. However, little research has been done with adolescents. In addition, expressing and understanding facial expressions is yet to be studied among adolescents with LD…

Peptidoglycan Recognition Protein S2 From Silkworm Integument: Characterization, Microbe-Induced Expression, and Involvement in the Immune-Deficiency Pathway

PubMed Central

Yang, Jie; Wang, Xiaonan; Tang, Shunming; Shen, Zhongyuan; Wu, Jinmei

2015-01-01

Peptidoglycan recognition protein (PGRP) binds specifically to peptidoglycan and plays an important role as a pattern recognition receptor in the innate immunity of insects. The cDNA of a short-type PGRP, an open reading frame of 588 bp encoding a polypeptide of 196 amino acids, was cloned from Bombyx mori. A phylogenetic tree was constructed, and the results showed that BmPGRP-S2 was most similar to Drosophila melanogaster PGRP (DmPGRP-SA). The induced expression profile of BmPGRP-S2 in healthy Escherichia coli- and Bacillus subtilis-challenged B. mori was measured using semiquantitative reverse transcriptase polymerase chain reaction analysis. The expression of BmPGRP-S2 was upregulated at 24 h by E. coli and Ba. subtilis challenge. In addition, in the integument of B. mori, RNAi knockdown of BmPGRP-S2 caused an obvious reduction in the transcription expression of the transcription factor Relish and in antibacterial effector genes Attacin, Gloverin, and Moricin. The results indicated that BmPGRP-S2 participates in the signal transduction pathway of B. mori. PMID:25797797

Anatomically constrained neural network models for the categorization of facial expression

NASA Astrophysics Data System (ADS)

McMenamin, Brenton W.; Assadi, Amir H.

2004-12-01

The ability to recognize facial expression in humans is performed with the amygdala which uses parallel processing streams to identify the expressions quickly and accurately. Additionally, it is possible that a feedback mechanism may play a role in this process as well. Implementing a model with similar parallel structure and feedback mechanisms could be used to improve current facial recognition algorithms for which varied expressions are a source for error. An anatomically constrained artificial neural-network model was created that uses this parallel processing architecture and feedback to categorize facial expressions. The presence of a feedback mechanism was not found to significantly improve performance for models with parallel architecture. However the use of parallel processing streams significantly improved accuracy over a similar network that did not have parallel architecture. Further investigation is necessary to determine the benefits of using parallel streams and feedback mechanisms in more advanced object recognition tasks.

Anatomically constrained neural network models for the categorization of facial expression

NASA Astrophysics Data System (ADS)

McMenamin, Brenton W.; Assadi, Amir H.

2005-01-01

The ability to recognize facial expression in humans is performed with the amygdala which uses parallel processing streams to identify the expressions quickly and accurately. Additionally, it is possible that a feedback mechanism may play a role in this process as well. Implementing a model with similar parallel structure and feedback mechanisms could be used to improve current facial recognition algorithms for which varied expressions are a source for error. An anatomically constrained artificial neural-network model was created that uses this parallel processing architecture and feedback to categorize facial expressions. The presence of a feedback mechanism was not found to significantly improve performance for models with parallel architecture. However the use of parallel processing streams significantly improved accuracy over a similar network that did not have parallel architecture. Further investigation is necessary to determine the benefits of using parallel streams and feedback mechanisms in more advanced object recognition tasks.

Somatosensory Representations Link the Perception of Emotional Expressions and Sensory Experience.

PubMed

Kragel, Philip A; LaBar, Kevin S

2016-01-01

Studies of human emotion perception have linked a distributed set of brain regions to the recognition of emotion in facial, vocal, and body expressions. In particular, lesions to somatosensory cortex in the right hemisphere have been shown to impair recognition of facial and vocal expressions of emotion. Although these findings suggest that somatosensory cortex represents body states associated with distinct emotions, such as a furrowed brow or gaping jaw, functional evidence directly linking somatosensory activity and subjective experience during emotion perception is critically lacking. Using functional magnetic resonance imaging and multivariate decoding techniques, we show that perceiving vocal and facial expressions of emotion yields hemodynamic activity in right somatosensory cortex that discriminates among emotion categories, exhibits somatotopic organization, and tracks self-reported sensory experience. The findings both support embodied accounts of emotion and provide mechanistic insight into how emotional expressions are capable of biasing subjective experience in those who perceive them.

Somatosensory Representations Link the Perception of Emotional Expressions and Sensory Experience123

PubMed Central

2016-01-01

Abstract Studies of human emotion perception have linked a distributed set of brain regions to the recognition of emotion in facial, vocal, and body expressions. In particular, lesions to somatosensory cortex in the right hemisphere have been shown to impair recognition of facial and vocal expressions of emotion. Although these findings suggest that somatosensory cortex represents body states associated with distinct emotions, such as a furrowed brow or gaping jaw, functional evidence directly linking somatosensory activity and subjective experience during emotion perception is critically lacking. Using functional magnetic resonance imaging and multivariate decoding techniques, we show that perceiving vocal and facial expressions of emotion yields hemodynamic activity in right somatosensory cortex that discriminates among emotion categories, exhibits somatotopic organization, and tracks self-reported sensory experience. The findings both support embodied accounts of emotion and provide mechanistic insight into how emotional expressions are capable of biasing subjective experience in those who perceive them. PMID:27280154

A functional glycoprotein competitive recognition and signal amplification strategy for carbohydrate-protein interaction profiling and cell surface carbohydrate expression evaluation

NASA Astrophysics Data System (ADS)

Wang, Yangzhong; Chen, Zhuhai; Liu, Yang; Li, Jinghong

2013-07-01

A simple and sensitive carbohydrate biosensor has been suggested as a potential tool for accurate analysis of cell surface carbohydrate expression as well as carbohydrate-based therapeutics for a variety of diseases and infections. In this work, a sensitive biosensor for carbohydrate-lectin profiling and in situ cell surface carbohydrate expression was designed by taking advantage of a functional glycoprotein of glucose oxidase acting as both a multivalent recognition unit and a signal amplification probe. Combining the gold nanoparticle catalyzed luminol electrogenerated chemiluminescence and nanocarrier for active biomolecules, the number of cell surface carbohydrate groups could be conveniently read out. The apparent dissociation constant between GOx@Au probes and Con A was detected to be 1.64 nM and was approximately 5 orders of magnitude smaller than that of mannose and Con A, which would arise from the multivalent effect between the probe and Con A. Both glycoproteins and gold nanoparticles contribute to the high affinity between carbohydrates and lectin. The as-proposed biosensor exhibits excellent analytical performance towards the cytosensing of K562 cells with a detection limit of 18 cells, and the mannose moieties on a single K562 cell were determined to be 1.8 × 1010. The biosensor can also act as a useful tool for antibacterial drug screening and mechanism investigation. This strategy integrates the excellent biocompatibility and multivalent recognition of glycoproteins as well as the significant enzymatic catalysis and gold nanoparticle signal amplification, and avoids the cell pretreatment and labelling process. This would contribute to the glycomic analysis and the understanding of complex native glycan-related biological processes.A simple and sensitive carbohydrate biosensor has been suggested as a potential tool for accurate analysis of cell surface carbohydrate expression as well as carbohydrate-based therapeutics for a variety of diseases and infections. In this work, a sensitive biosensor for carbohydrate-lectin profiling and in situ cell surface carbohydrate expression was designed by taking advantage of a functional glycoprotein of glucose oxidase acting as both a multivalent recognition unit and a signal amplification probe. Combining the gold nanoparticle catalyzed luminol electrogenerated chemiluminescence and nanocarrier for active biomolecules, the number of cell surface carbohydrate groups could be conveniently read out. The apparent dissociation constant between GOx@Au probes and Con A was detected to be 1.64 nM and was approximately 5 orders of magnitude smaller than that of mannose and Con A, which would arise from the multivalent effect between the probe and Con A. Both glycoproteins and gold nanoparticles contribute to the high affinity between carbohydrates and lectin. The as-proposed biosensor exhibits excellent analytical performance towards the cytosensing of K562 cells with a detection limit of 18 cells, and the mannose moieties on a single K562 cell were determined to be 1.8 × 1010. The biosensor can also act as a useful tool for antibacterial drug screening and mechanism investigation. This strategy integrates the excellent biocompatibility and multivalent recognition of glycoproteins as well as the significant enzymatic catalysis and gold nanoparticle signal amplification, and avoids the cell pretreatment and labelling process. This would contribute to the glycomic analysis and the understanding of complex native glycan-related biological processes. Electronic supplementary information (ESI) available: Experimental details; characterization of probes; the influence of electrolyte pH; probe concentration and glucose concentration on the electrode ECL effect. See DOI: 10.1039/c3nr01598j

Heat Shock Protein-90 Inhibitors Enhance Antigen Expression on Melanomas and Increase T Cell Recognition of Tumor Cells

PubMed Central

Haggerty, Timothy J.; Dunn, Ian S.; Rose, Lenora B.; Newton, Estelle E.; Pandolfi, Franco; Kurnick, James T.

2014-01-01

In an effort to enhance antigen-specific T cell recognition of cancer cells, we have examined numerous modulators of antigen-expression. In this report we demonstrate that twelve different Hsp90 inhibitors (iHsp90) share the ability to increase the expression of differentiation antigens and MHC Class I antigens. These iHsp90 are active in several molecular and cellular assays on a series of tumor cell lines, including eleven human melanomas, a murine B16 melanoma, and two human glioma-derived cell lines. Intra-cytoplasmic antibody staining showed that all of the tested iHsp90 increased expression of the melanocyte differentiation antigens Melan-A/MART-1, gp100, and TRP-2, as well as MHC Class I. The gliomas showed enhanced gp100 and MHC staining. Quantitative analysis of mRNA levels showed a parallel increase in message transcription, and a reporter assay shows induction of promoter activity for Melan-A/MART-1 gene. In addition, iHsp90 increased recognition of tumor cells by T cells specific for Melan-A/MART-1. In contrast to direct Hsp90 client proteins, the increased levels of full-length differentiation antigens that result from iHsp90 treatment are most likely the result of transcriptional activation of their encoding genes. In combination, these results suggest that iHsp90 improve recognition of tumor cells by T cells specific for a melanoma-associated antigen as a result of increasing the expressed intracellular antigen pool available for processing and presentation by MHC Class I, along with increased levels of MHC Class I itself. As these Hsp90 inhibitors do not interfere with T cell function, they could have potential for use in immunotherapy of cancer. PMID:25503774

Altered brain mechanisms of emotion processing in pre-manifest Huntington's disease.

PubMed

Novak, Marianne J U; Warren, Jason D; Henley, Susie M D; Draganski, Bogdan; Frackowiak, Richard S; Tabrizi, Sarah J

2012-04-01

Huntington's disease is an inherited neurodegenerative disease that causes motor, cognitive and psychiatric impairment, including an early decline in ability to recognize emotional states in others. The pathophysiology underlying the earliest manifestations of the disease is not fully understood; the objective of our study was to clarify this. We used functional magnetic resonance imaging to investigate changes in brain mechanisms of emotion recognition in pre-manifest carriers of the abnormal Huntington's disease gene (subjects with pre-manifest Huntington's disease): 16 subjects with pre-manifest Huntington's disease and 14 control subjects underwent 1.5 tesla magnetic resonance scanning while viewing pictures of facial expressions from the Ekman and Friesen series. Disgust, anger and happiness were chosen as emotions of interest. Disgust is the emotion in which recognition deficits have most commonly been detected in Huntington's disease; anger is the emotion in which impaired recognition was detected in the largest behavioural study of emotion recognition in pre-manifest Huntington's disease to date; and happiness is a positive emotion to contrast with disgust and anger. Ekman facial expressions were also used to quantify emotion recognition accuracy outside the scanner and structural magnetic resonance imaging with voxel-based morphometry was used to assess the relationship between emotion recognition accuracy and regional grey matter volume. Emotion processing in pre-manifest Huntington's disease was associated with reduced neural activity for all three emotions in partially separable functional networks. Furthermore, the Huntington's disease-associated modulation of disgust and happiness processing was negatively correlated with genetic markers of pre-manifest disease progression in distributed, largely extrastriatal networks. The modulated disgust network included insulae, cingulate cortices, pre- and postcentral gyri, precunei, cunei, bilateral putamena, right pallidum, right thalamus, cerebellum, middle frontal, middle occipital, right superior and left inferior temporal gyri, and left superior parietal lobule. The modulated happiness network included postcentral gyri, left caudate, right cingulate cortex, right superior and inferior parietal lobules, and right superior frontal, middle temporal, middle occipital and precentral gyri. These effects were not driven merely by striatal dysfunction. We did not find equivalent associations between brain structure and emotion recognition, and the pre-manifest Huntington's disease cohort did not have a behavioural deficit in out-of-scanner emotion recognition relative to controls. In addition, we found increased neural activity in the pre-manifest subjects in response to all three emotions in frontal regions, predominantly in the middle frontal gyri. Overall, these findings suggest that pathophysiological effects of Huntington's disease may precede the development of overt clinical symptoms and detectable cerebral atrophy.

Anomalous subjective experience and psychosis risk in young depressed patients.

PubMed

Szily, Erika; Kéri, Szabolcs

2009-01-01

Help-seeking young people often display depressive symptoms. In some patients, these symptoms may co-exist with clinically high-risk mental states for psychosis. The aim of this study was to determine differences in subjective experience and social perception in young depressed patients with and without psychosis risk. Participants were 68 young persons with major depressive disorder. Twenty-six patients also met the criteria of attenuated or brief limited intermittent psychotic symptoms according to the Comprehensive Assessment of At Risk Mental States (CAARMS) criteria. Subjective experiences were assessed with the Bonn Scale for the Assessment of Basic Symptoms (BSABS). Recognition of complex social emotions and mental states was assessed using the 'Reading the Mind in the Eyes' test. Perplexity, self-disorder, and diminished affectivity significantly predicted psychosis risk. Depressed patients without psychosis risk displayed impaired recognition performance for negative social emotions, whereas patients with psychosis risk were also impaired in the recognition of cognitive expressions. In the high-risk group, self-disorder was associated with impaired recognition of facial expressions. These results suggest that anomalous subjective experience and impaired recognition of complex emotions may differentiate between young depressed patients with and without psychosis risk. 2009 S. Karger AG, Basel.