While the aging process is a universal phenomenon, people perceive and experience one’s aging considerably differently. Subjective age (SA), referring to how individuals experience themselves as younger or older than their actual age, has been highlighted as an important predictor of late-life health outcomes. However, it is unclear whether and how SA is associated with the neurobiological process of aging. In this study, 68 healthy older adults underwent a SA survey and magnetic resonance imaging (MRI) scans. T1-weighted brain images of open-access datasets were utilized to construct a model for age prediction. We utilized both voxel-based morphometry (VBM) and age-prediction modeling techniques to explore whether the three groups of SA (i.e., feels younger, same, or older than actual age) differed in their regional gray matter (GM) volumes, and predicted brain age. The results showed that elderly individuals who perceived themselves as younger than their real age showed not only larger GM volume in the inferior frontal gyrus and the superior temporal gyrus, but also younger predicted brain age. Our findings suggest that subjective experience of aging is closely related to the process of brain aging and underscores the neurobiological mechanisms of SA as an important marker of late-life neurocognitive health.

The social brain hypothesis proposes that large neocortex size evolved to support cognitively demanding social interactions. Accordingly, previous studies have observed that larger orbitofrontal and amygdala structures predict the size of an individual's social network. However, it remains uncertain how an individual's social connectedness reported by other people is associated with the social brain volume. In this study, we found that a greater in-degree network size, a measure of social ties identified by a subject's social connections rather than by the subject, significantly correlated with a larger regional volume of the orbitofrontal cortex, dorsomedial prefrontal cortex and lingual gyrus. By contrast, out-degree size, which is based on an individual's self-perceived connectedness, showed no associations. Meta-analytic reverse inference further revealed that regional volume pattern of in-degree size was specifically involved in social inference ability. These findings were possible because our dataset contained the social networks of an entire village, i.e. a global network. The results suggest that the in-degree aspect of social network size not only confirms the previously reported brain correlates of the social network but also shows an association in brain regions involved in the ability to infer other people's minds. This study provides insight into understanding how the social brain is uniquely associated with sociocentric measures derived from a global network.

Significance: In what ways are we similar to our friends? Here, we characterized the social network of residents of a remote village, a subset of whom contributed personality and neuroimaging data. We demonstrate that similarity in individuals’ resting-state functional connectomes predicts individuals’ proximity in their real-world social network, even when controlling for demographic characteristics and self-reported personality traits. Our results suggest that patterns of functional brain activity during rest encode latent similarities (e.g., in terms of how people think and behave) that are associated with friendship. Taken together, integrating neuroimaging and social network analysis can offer novel insights into how the brain shapes or is shaped by the social networks that it inhabits.

The Clock Drawing Test (CDT) has been recognized as an effective tool for dementia detection. This study investigated the clock drawing performance of 240 non-demented elderly Korean people with a wide-range of educational levels and 28 patients with mild dementia of the Alzheimer’s type (DAT). We examined the effects of demographic factors, including education, and established norms for the elderly population. We found that the educational attainment and literacy status of older people influenced performance on the CDT significantly (p < .001). Furthermore, qualitative error analysis revealed that normal participants with low educational background committed errors similar to errors of the DAT patients. The DAT patients performed significantly worse than the non-demented participants in the CDT Total score (p < .001). However, the CDT has better criterion validity in participants with more than 6 years of education. In conclusion, the CDT performance in older people who are either illiterate or with 6 or less years of education should be interpreted with caution. Conceptual errors in the CDT can be the result of not only dementia but also lack of education. (JINS, 2010, 16, 1138–1146.)

The aim of this study was to investigate the changes in cognitive functions and brain activation after multicomponent training of cognitive control in non-demented older adults, utilizing neuropsychological tests and fMRI. We developed and implemented a computerized Multicomponent Training of Cognitive Control (MTCC), characterized by task variability and adaptive procedures, in order to maximize training effects in cognitive control and transfer to other cognitive domains. Twenty-seven community-dwelling adults, aged 64-77 years, without any history of neurological or psychiatric problems, participated in this study (14 in the training group and 13 in the control group). The MTCC was administered to the participants assigned to the training group for 8 weeks, while those in the control group received no training. Neuropsychological tests and fMRI were administered prior to and after the training. Trained participants showed improvements in cognitive control, recognition memory and general cognitive functioning. Furthermore, the MTCC led to an increased brain activation of the regions adjacent to the baseline cognitive control-related areas in the frontoparietal network. Future studies are necessary to confirm our hypothesis that MTCC improves cognitive functioning of healthy elderly individuals by expanding their frontoparietal network that is involved in cognitive control.