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Functional activation of the parahippocampal cortex and amygdala during social statistical information processing

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机构: [a]The International WIC Institute, Beijing University of Technology, Beijing, China [b]The School of Computer and Communication Engineering, Liaoning ShiHua University, Liaoning, China [c]Department of Life Science and Informatics, Maebashi Institute of Technology, Maebashi-City, Japan [d]Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China
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关键词: fMRI Social statistical information Sociality Associations Parahippocampal cortex (PHC) Amygdala

摘要:
Social statistical information can be used to quantitatively describe external events or facts, such as statistics on products, incomes, or sales, which consist of two basic features: associations and sociality. Previous studies in cognitive psychology have investigated statistical graph comprehension, but the neural basis of social statistical information processing has not been examined. In our study, 36 subjects were scanned using functional magnetic resonance imaging (fMRI) while reading statistical information visually presented in one of three basic forms: as text, as statistical graphs, and as both graphs and text. All three forms consistently activated the right posterior tip of the parahippocampal cortex (PHC) and the left amygdala, suggesting that both regions contribute to social statistical information processing, regardless of the presentation form. Previous studies have implicated the posterior tip of the PHC in contextual associations and the amygdala in processing emotion-related events and social cognition. Taken together with previous studies, we proposed that the posterior tip of the PHC is more involved in establishing associations during social statistical information processing, while the amygdala is more related to the social component. This study provides neuroimaging evidence for commonly processing of the two basic features of social statistical information by the PHC and amygdala. (C) 2011 Elsevier B.V. All rights reserved.

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出版当年[2011]版:
大类 | 4 区 工程技术
小类 | 4 区 计算机:人工智能 4 区 神经科学
最新[2023]版:
大类 | 3 区 心理学
小类 | 3 区 神经科学 4 区 计算机:人工智能 4 区 心理学:实验
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出版当年[2010]版:
Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Q4 NEUROSCIENCES Q4 PSYCHOLOGY, EXPERIMENTAL
最新[2023]版:
Q2 PSYCHOLOGY, EXPERIMENTAL Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Q3 NEUROSCIENCES

影响因子: 最新[2023版] 最新五年平均 出版当年[2010版] 出版当年五年平均 出版前一年[2009版] 出版后一年[2011版]

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第一作者机构: [a]The International WIC Institute, Beijing University of Technology, Beijing, China [b]The School of Computer and Communication Engineering, Liaoning ShiHua University, Liaoning, China
通讯作者:
通讯机构: [a]The International WIC Institute, Beijing University of Technology, Beijing, China [*1]The International WIC Institute, Beijing University of Technology, Beijing, China
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