Effects of noise on a person's psychological state under task-loaded condition from the viewpoint of brain function analysis

2016 ◽  
Vol 140 (4) ◽  
pp. 3047-3047
Author(s):  
Takeshi Akita ◽  
Naoko Sano ◽  
Ayako Matsuo
1995 ◽  
Vol 81 (1) ◽  
pp. 275-286 ◽  
Author(s):  
Peter C. Terry ◽  
Andrew Slade

Male Shotokan karate players (karateka) ( N = 208) completed the Competitive State Anxiety Inventory-2 and the Profile of Mood States about 40 minutes before a competition. Single-factor multivariate analysis of variance of preperformance mood and anxiety scores indicated significant differences between winning and losing competitors. Winners scored higher on Vigor, Anger, and Self-confidence, and lower on Tension, Depression, Fatigue, Confusion, Cognitive Anxiety, and Somatic Anxiety. Discriminant function analysis showed that 91.96% of participants could be correctly classified as winners or losers on the basis of preperformance mood scores. This figure rose to 93.47% when scores on the anxiety subscales were also included in the discriminant function analysis. Anxiety scores alone produced 78.89% discrimination. Mood profiles for winning karateka were in line with the “mental health” profile of Morgan except for above-average scores on Anger. This result supports the view of McGowan and Miller that anger may facilitate performance in karate competition. The capacity of measures of psychological state to discriminate performance exceeds previous reports, suggesting that karate performance may be exceptionally mood-dependent. These results suggest that interventions which increase scores on Vigor and Anger and reduce scores on Tension, Depression, Fatigue, and Confusion may be particularly efficacious for Shotokan karate performance.


2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Jie Zhang ◽  
Lingkai Tang ◽  
Bo Liao ◽  
Xiaoshu Zhu ◽  
Fang-Xiang Wu

The brain has the most complex structures and functions in living organisms, and brain networks can provide us an effective way for brain function analysis and brain disease detection. In brain networks, there exist some important neural unit modules, which contain many meaningful biological insights. It is appealing to find the neural unit modules and obtain their affiliations. In this study, we present a novel method by integrating the uniform design into the particle swarm optimization to find community modules of brain networks, abbreviated as UPSO. The difference between UPSO and the existing ones lies in that UPSO is presented first for detecting community modules. Several brain networks generated from functional MRI for studying autism are used to verify the proposed algorithm. Experimental results obtained on these brain networks demonstrate that UPSO can find community modules efficiently and outperforms the other competing methods in terms of modularity and conductance. Additionally, the comparison of UPSO and PSO also shows that the uniform design plays an important role in improving the performance of UPSO.


PLoS ONE ◽  
2013 ◽  
Vol 8 (6) ◽  
pp. e65884 ◽  
Author(s):  
Senhua Zhu ◽  
Zhuo Fang ◽  
Siyuan Hu ◽  
Ze Wang ◽  
Hengyi Rao

1996 ◽  
Vol 82 (2) ◽  
pp. 371-377 ◽  
Author(s):  
Peter C. Terry ◽  
Emma L. Youngs

Field hockey players ( N=128) completed the Competitive State Anxiety Inventory-2 and the Profile of Mood States about 45 min. before a British Universities trial. Single-factor multivariate analysis of variance indicated no significant differences between selected and nonselected players for any preperformance mood or anxiety measure. Discriminant function analysis showed that 74 participants (57.81%) could be correctly classified as selected or nonselected players on the basis of preperformance mood scores. This figure rose to 83 participants (64.84%) when scores on the anxiety subscales were also included in the discriminant function analysis. Anxiety scores alone discriminated 71 participants (55.47%). These results concur with earlier proposals of Terry that psychological state measures decline in predictive effectiveness in long duration, open skill team sports.


2012 ◽  
Vol 52 (11) ◽  
pp. 1174-1177
Author(s):  
Ichiro Miyai ◽  
Masahito Mihara ◽  
Noriaki Hattori ◽  
Megumi Hatakenaka ◽  
Teiji Kawano ◽  
...  

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