Principal component analysis of the P600 waveform: RF and gender effects

2010 ◽  
Vol 478 (1) ◽  
pp. 19-23 ◽  
Author(s):  
Argiro E. Maganioti ◽  
Chrissanthi D. Hountala ◽  
Charalambos C. Papageorgiou ◽  
Miltiades A. Kyprianou ◽  
Andreas D. Rabavilas ◽  
...  
2020 ◽  
Author(s):  
Xin Di ◽  
Bharat B. Biswal

AbstractFunctional MRI (fMRI) study of naturalistic conditions, e.g. movie watching, usually focuses on shared responses across subjects. However, individual differences in the responses have been attracting increasing attention in search of group differences or associations with behavioral outcomes. The individual differences have been studied by directly modeling the cross-subject correlation matrix or projecting the relations into a 1-D space. We contend that it is critical to examine whether there are single or multiple consistent components of responses underlying the whole population, because multiple components may undermine the individual relations using the previous methods. We use principal component analysis (PCA) to examine the heterogeneity of brain responses across subjects in terms of the eigenvalues of the covariance matrix, and utilize this approach to study developmental trajectories and gender effects in a movie watching dataset. We identified several brain networks in the parietal cortex that showed a significant second principal component (PC) of regional responses, which were mainly represented the younger children. The second PCs in some networks, i.e. the supramarginal network, resembled a delayed version of the first PCs for 4 seconds (2 TR), indicating delayed responses in the younger children than the older children and adults. However, no apparent gender effects were found in the first and second PCs. The analyses highlight the importance of identifying multiple consistent responses underlying individual differences in responses to naturalistic stimuli. And the PCA-based approach could be complementary to the commonly used intersubject correlation analysis.HighlightsThere may be multiple consistent responses among subjects during movie watchingPrincipal component analysis can be used to identify the multiple consistent responsesMany brain regions showed two principal components that were separated by ageYounger children showed delayed response in the supramarginal gyrus and precuneus


Perception ◽  
10.1068/p5811 ◽  
2008 ◽  
Vol 37 (11) ◽  
pp. 1637-1648 ◽  
Author(s):  
Satoru Kawamura ◽  
Masashi Komori ◽  
Yusuke Miyamoto

We examined the effect of facial expression on the assignment of gender to facial images. A computational analysis of the facial images was applied to examine whether physical aspects of the face itself induced this effect. Thirty-six observers rated the degree of masculinity of the faces of 48 men, and the degree of femininity of the faces of 48 women. Half of the faces had a neutral facial expression, and the other half was smiling. Smiling significantly reduced the perceived masculinity of men's faces, especially for male observers, whereas no effect of smiling on femininity ratings was obtained for women's faces. A principal component analysis was conducted on the matrix of pixel luminance values for each facial image × all the images. The third principle component explained a relatively high proportion of the variance of both facial expressions and gender of face. These results suggest that the effect of smiling on the assignment of gender is caused, at least in part, by the physical relationship between facial expression and face gender.


Author(s):  
Putri Nurmala ◽  
Wikaria Gazali ◽  
Widodo Budiharto

Face recognition and gender information is a computer application for automatically identifying or verifying a person's face from a camera to capture a person's face. It is usually used in access control systemsand it can be compared to other biometrics such as finger print identification system or iris. Many of face recognition algorithms have been developed in recent years. Face recognition system and gender information inthis system based on the Principal Component Analysis method (PCA). Computational method has a simple and fast compared with the use of the method requires a lot of learning, such as artificial neural network. In thisaccess control system, relay used and Arduino controller. In this essay focuses on face recognition and gender - based information in real time using the method of Principal Component Analysis ( PCA ). The result achievedfrom the application design is the identification of a person’s face with gender using PCA. The results achieved by the application is face recognition system using PCA can obtain good results the 85 % success rate in face recognition with face images that have been tested by a few people and a fairly high degree of accuracy.


2021 ◽  
Vol 2021 (0) ◽  
pp. 1-20
Author(s):  
Flor Micaela Ramírez Leyva ◽  
◽  
José Luis Terrón Blanco ◽  
Remberto Castro Castañeda ◽  
◽  
...  

Based on contributions where communication, health and gender converge, an attempt is made to clarify how news and health frames are characterized on television, mainly addressing actors and actions. The objective is to observe the institutional presence, visibility and gender parity and perspective. Through the content analysis of 510 pieces from TV Azteca, Televisa and C7 –using Principal Component Analysis in SPSS as a tool– a major presence of political actors or the health system was found, a lesser presence of women and the absence of gender perspective in the information.


VASA ◽  
2012 ◽  
Vol 41 (5) ◽  
pp. 333-342 ◽  
Author(s):  
Kirchberger ◽  
Finger ◽  
Müller-Bühl

Background: The Intermittent Claudication Questionnaire (ICQ) is a short questionnaire for the assessment of health-related quality of life (HRQOL) in patients with intermittent claudication (IC). The objective of this study was to translate the ICQ into German and to investigate the psychometric properties of the German ICQ version in patients with IC. Patients and methods: The original English version was translated using a forward-backward method. The resulting German version was reviewed by the author of the original version and an experienced clinician. Finally, it was tested for clarity with 5 German patients with IC. A sample of 81 patients were administered the German ICQ. The sample consisted of 58.0 % male patients with a median age of 71 years and a median IC duration of 36 months. Test of feasibility included completeness of questionnaires, completion time, and ratings of clarity, length and relevance. Reliability was assessed through a retest in 13 patients at 14 days, and analysis of Cronbach’s alpha for internal consistency. Construct validity was investigated using principal component analysis. Concurrent validity was assessed by correlating the ICQ scores with the Short Form 36 Health Survey (SF-36) as well as clinical measures. Results: The ICQ was completely filled in by 73 subjects (90.1 %) with an average completion time of 6.3 minutes. Cronbach’s alpha coefficient reached 0.75. Intra-class correlation for test-retest reliability was r = 0.88. Principal component analysis resulted in a 3 factor solution. The first factor explained 51.5 of the total variation and all items had loadings of at least 0.65 on it. The ICQ was significantly associated with the SF-36 and treadmill-walking distances whereas no association was found for resting ABPI. Conclusions: The German version of the ICQ demonstrated good feasibility, satisfactory reliability and good validity. Responsiveness should be investigated in further validation studies.


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