Happiness refers to people's cognitive and affective evaluation of their life. Why are some people happier than others? One reason might be that unhappy people are prone to ruminate more than happy people. The default mode network (DMN) is normally active during rest and is implicated in rumination. We hypothesized that unhappiness may be associated with increased default-mode functional connectivity during rest, including the medial prefrontal cortex (MPFC), posterior cingulate cortex (PCC) and inferior parietal lobule (IPL). The hyperconnectivity of these areas may be associated with higher levels of rumination. One hundred forty-eight healthy participants underwent a resting-state fMRI scan. A group-independent component analysis identified the DMNs. Results indicated increased functional connectivity in the DMN was associated with lower levels of happiness. Specifically, relative to happy people, unhappy people exhibited greater functional connectivity in the anterior medial cortex (bilateral MPFC), posterior medial cortex regions (bilateral PCC) and posterior parietal cortex (left IPL). Moreover, the increased functional connectivity of the MPFC, PCC and IPL, correlated positively with the inclination to ruminate. These results highlight the important role of the DMN in the neural correlates of happiness, and suggest that rumination may play an important role in people's perceived happiness.

BackgroundWhy are some people happier than others? This question has intrigued many researchers. However, limited work has addressed this question within a neuroscientific framework.MethodsThe present study investigated the neural correlates of trait happiness using the resting-state functional magnetic resonance imaging (rs-fMRI) approach. Specifically, regional homogeneity (ReHo) was examined on two groups of young adults: happy and unhappy individuals (N = 25 per group).ResultsDecreased ReHo in unhappy relative to happy individuals was observed within prefrontal cortex, medial temporal lobe, superior temporal lobe, and retrosplenial cortex. In contrast, increased ReHo in unhappy relative to happy individuals was observed within the dorsolateral prefrontal cortex, middle cingulate gyrus, putamen, and thalamus. In addition, the ReHo within the left thalamus was negatively correlated with Chinese Happiness Inventory (CHI) score within the happy group.LimitationsAs an exploratory study, we examined how general trait happiness is reflected in the regional homogeneity of intrinsic brain activity in a relatively small sample. Examining other types of happiness in a larger sample using a multitude of intrinsic brain activity indices are warranted for future work.ConclusionsThe local synchronization of BOLD signal is altered in unhappy individuals. The regions implicated in this alteration partly overlapped with previously identified default mode network, emotional circuitry, and rewarding system, suggesting that these systems may be involved in happiness.

Flexible and stretchable strain sensors are vital for emerging fields of wearable and personal electronics, but it is a huge challenge for them to possess both wide-range measurement capability and good sensitivity. In this study, a highly stretchable strain sensor with a wide strain range and a good sensitivity is fabricated based on smart composites of carbon black (CB)/wrinkled Ecoflex. The sensor exhibits a maximum recoverable strain up to 500% and a high gauge factor of 67.7. It has a low hysteresis, a fast signal response (as short as 120 ms) and a high reproducibility (up to 5000 cycles with a strain of 150%). The sensor is capable of detecting and capturing wide-range human activities, from speech recognition, pulse monitoring, to vigorous motions. It is also applicable for real-time monitoring of robot movements and vehicle security crash in an anthropomorphic field. More importantly, the sensor is successfully used to send signals of a volunteer's breathing data to a local hospital in real time through a big-data cloud platform. This research provides the feasibility using strain sensor for wearable internet of things and demonstrates its exciting prospect for healthcare applications.