1.Dissecting Social Working Memory: Neural and Behavioral Evidence for Externally and Internally Oriented Components.
Hanxi PAN ; Zefeng CHEN ; Nan XU ; Bolong WANG ; Yuzheng HU ; Hui ZHOU ; Anat PERRY ; Xiang-Zhen KONG ; Mowei SHEN ; Zaifeng GAO
Neuroscience Bulletin 2025;41(11):2049-2062
Social working memory (SWM)-the ability to maintain and manipulate social information in the brain-plays a crucial role in social interactions. However, research on SWM is still in its infancy and is often treated as a unitary construct. In the present study, we propose that SWM can be conceptualized as having two relatively independent components: "externally oriented SWM" (e-SWM) and "internally oriented SWM" (i-SWM). To test this external-internal hypothesis, participants were tasked with memorizing and ranking either facial expressions (e-SWM) or personality traits (i-SWM) associated with images of faces. We then examined the neural correlates of these two SWM components and their functional roles in empathy. The results showed distinct activations as the e-SWM task activated the postcentral and precentral gyri while the i-SWM task activated the precuneus/posterior cingulate cortex and superior frontal gyrus. Distinct multivariate activation patterns were also found within the dorsal medial prefrontal cortex in the two tasks. Moreover, partial least squares analyses combining brain activation and individual differences in empathy showed that e-SWM and i-SWM brain activities were mainly correlated with affective empathy and cognitive empathy, respectively. These findings implicate distinct brain processes as well as functional roles of the two types of SWM, providing support for the internal-external hypothesis of SWM.
Humans
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Memory, Short-Term/physiology*
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Male
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Female
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Empathy/physiology*
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Young Adult
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Magnetic Resonance Imaging
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Adult
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Brain/diagnostic imaging*
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Brain Mapping
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Facial Expression
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Social Behavior
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Facial Recognition/physiology*
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Social Perception
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Personality/physiology*
2.High sensitivity C-reactive protein associated with different health predictors in middle-aged and oldest old Chinese.
Yi ZHAI ; Xiao Ming SHI ; Simon Michael FITZGERALD ; Han Zhu QIAN ; Virginia B KRAUS ; Melanie SERENY ; Perry HU ; Zhao Xue YIN ; Jian Wei XU ; Yi ZENG
Biomedical and Environmental Sciences 2012;25(3):257-266
OBJECTIVETo describe the distribution of plasma high sensitivity C-reactive protein (hsCRP) and explore the relationship between hsCRP and metabolic risk factors among residents living in longevity areas of China.
METHODS268 individuals aged between 40 and 59 years and 506 individuals aged over 90 years were selected from 5 longevity areas of China to participate in a cross section longitudinal cohort study. The participants were interviewed with general health related questionnaire to collect their demographic, behavioral and lifestyle data, as well as their chronic conditions, and meanwhile their physical and biomedical parameters including waist circumference (WC), blood pressure (BP), hsCRP, plasma lipids, and fasting blood glucose (FBG) were measured.
RESULTSThe median of hsCRP was 0.99 mg/L in the middle-aged group and 1.76 mg/L in the oldest old group. No significant gender difference was observed between the above two groups. Among the oldest old individuals, 36.56% had an hsCRP level >3.0 mg/L. The prevalence of high hsCRP was 16.79% in the middle-aged group. The results of stepwise multiple linear regression analyses showed that HDL-C was independently associated with ln (hsCRP) concentration in the middle-aged group, whereas ln (TG), HDL-C and FBG were correlated after adjustment for gender, study site, smoking, drinking, education and BMI in the oldest old group.
CONCLUSIONHDL-C is a stronger predictor of elevated hsCRP than other metabolic factors in the middle-aged population. For the oldest old persons, high TG, low HDL-C, and FBG predict elevated plasma hsCRP.
Adult ; Aged, 80 and over ; Aging ; Asian Continental Ancestry Group ; Biomarkers ; C-Reactive Protein ; metabolism ; China ; Cross-Sectional Studies ; Female ; Humans ; Longevity ; Male ; Middle Aged ; Models, Biological

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