Many emotional experiences such as anxiety and depression are influenced by negative affect (NA). NA has both trait and state features, which play different roles in physiological and mental health. Attending to NA common to various emotional experiences and their trait-state features might help deepen the understanding of the shared foundation of related emotional disorders.

The principal component of five measures was calculated to indicate individuals' NA level. Applying the connectivity-based correlation analysis, we first identified resting-state functional connectives (FCs) relating to NA in sample 1 (n = 367), which were validated through an independent sample (n = 232; sample 2). Next, based on the variability of FCs across large timescale, we further divided the NA-related FCs into high- and low-variability groups. Finally, FCs in different variability groups were separately applied to predict individuals' neuroticism level (which is assumed to be the core trait-related factor underlying NA), and the change of NA level (which represents the state-related fluctuation of NA).

The low-variability FCs were primarily within the default mode network (DMN) and between the DMN and dorsal attention network/sensory system and significantly predicted trait rather than state NA. The high-variability FCs were primarily between the DMN and ventral attention network, the fronto-parietal network and DMN/sensory system, and significantly predicted the change of NA level.

The trait and state NA can be separately predicted by stable and variable spontaneous FCs with different attentional processes and emotion regulatory mechanisms, which could deepen our understanding of NA.

Cognitive decline in advanced age is closely related to dementia. The trajectory of cognitive function in older Chinese is yet to be fully investigated. We aimed to investigate the trajectories of cognitive function in a nationally representative sample of older people living in China and to explore the potential determinants of these trajectories.

This study included 2,038 cognitively healthy persons aged 65–104 years at their first observation in the Chinese Longitudinal Healthy Longevity Survey from 2002 to 2014. Cognitive function was measured using the Chinese version of the Mini-Mental State Examination (MMSE). Group-based trajectory modeling was used to identify potential heterogeneity of longitudinal changes over the 12 years and to investigate associations between baseline predictors of group membership and these trajectories.

Three trajectories were identified according to the following types of changes in MMSE scores: slow decline (14.0%), rapid decline (4.5%), and stable function (81.5%). Older age, female gender, having no schooling, a low frequency of leisure activity, and a low baseline MMSE score were associated with the slow decline trajectory. Older age, body mass index (BMI) less than 18.5 kg/m2, and having more than one cardiovascular disease (CVD) were associated with the rapid decline trajectory.

Three trajectories of cognitive function were identified in the older Chinese population. The identified determinants of these trajectories could be targeted for developing prevention and intervention strategies for dementia.