Rejection of Unfair Offers Can Be Driven by Negative Emotions, Evidence from Modified Ultimatum Games with Anonymity

The rejection of unfair offers can be affected by both negative emotions (e.g. anger and moral disgust) and deliberate cognitive processing of behavioral consequences (e.g. concerns of maintaining social fairness and protecting personal reputation). However, whether negative emotions are sufficient to motivate this behavior is still controversial. With modified ultimatum games, a recent study (Yamagishi T, et al. (2009) Proc Natl Acad Sci USA 106∶11520–11523) found that people reject unfair offers even when this behavior increases inequity, and even when they could not communicate to the proposers. Yamagishi suggested that rejection of unfair offers could occurr without people’s concerning of maintaining social fairness, and could be driven by negative emotions. However, as anonymity was not sufficiently guaranteed in Yamagishi’s study, the rejection rates in their experiments may have been influenced by people’s concerns of protecting personal reputation (reputational concerns) in addition to negative emotions; thus, it was unclear whether the rejection was driven by negative emotions, or by reputational concerns, or both. In the present study, with specific methods to ensure anonymity, the effect of reputational concerns was successfully ruled out. We found that in a private situation in which rejection could not be driven by reputational concerns, the rejection rates of unfair offers were significantly larger than zero, and in public situations in which rejection rates could be influenced by both negative emotions and reputational concerns, rejection rates were significantly higher than that in the private situation. These results, together with Yamagishi’s findings, provided more complete evidence suggesting (a) that the rejection of unfair offers can be driven by negative emotions and (b) that deliberate cognitive processing of the consequences of the behavior can increase the rejection rate, which may benefit social cooperation

Synchronization modulation increases transepithelial potentials in MDCK monolayers through Na/K pumps

Peer reviewedPublisher PD

Sequence Skill Acquisition and Off-Line Learning in Normal Aging

It is well known that certain cognitive abilities decline with age. The ability to form certain new declarative memories, particularly memories for facts and events, has been widely shown to decline with advancing age. In contrast, the effects of aging on the ability to form new procedural memories such as skills are less well known, though it appears that older adults are able to acquire some new procedural skills over practice. The current study examines the effects of normal aging on procedural memory more closely by comparing the effects of aging on the encoding or acquisition stage of procedural learning versus its effects on the consolidation, or between-session stage of procedural learning. Twelve older and 14 young participants completed a sequence-learning task (the Serial Reaction Time Task) over a practice session and at a re-test session 24 hours later. Older participants actually demonstrated more sequence skill during acquisition than the young. However, older participants failed to show skill improvement at re-test as the young participants did. Age thus appears to have a differential effect upon procedural learning stages such that older adults' skill acquisition remains relatively intact, in some cases even superior, compared to that of young adults, while their skill consolidation may be poorer than that of young adults. Although the effect of normal aging on procedural consolidation remains unclear, aging may actually enhance skill acquisition on some procedural tasks

Individual Attachment Style Modulates Human Amygdala and Striatum Activation during Social Appraisal

Adult attachment style refers to individual personality traits that strongly influence emotional bonds and reactions to social partners. Behavioral research has shown that adult attachment style reflects profound differences in sensitivity to social signals of support or conflict, but the neural substrates underlying such differences remain unsettled. Using functional magnetic resonance imaging (fMRI), we examined how the three classic prototypes of attachment style (secure, avoidant, anxious) modulate brain responses to facial expressions conveying either positive or negative feedback about task performance (either supportive or hostile) in a social game context. Activation of striatum and ventral tegmental area was enhanced to positive feedback signaled by a smiling face, but this was reduced in participants with avoidant attachment, indicating relative impassiveness to social reward. Conversely, a left amygdala response was evoked by angry faces associated with negative feedback, and correlated positively with anxious attachment, suggesting an increased sensitivity to social punishment. Secure attachment showed mirror effects in striatum and amygdala, but no other specific correlate. These results reveal a critical role for brain systems implicated in reward and threat processing in the biological underpinnings of adult attachment style, and provide new support to psychological models that have postulated two separate affective dimensions to explain these individual differences, centered on the ventral striatum and amygdala circuits, respectively. These findings also demonstrate that brain responses to face expressions are not driven by facial features alone but determined by the personal significance of expressions in current social context. By linking fundamental psychosocial dimensions of adult attachment with brain function, our results do not only corroborate their biological bases but also help understand their impact on behavior

Phenotypic Signatures Arising from Unbalanced Bacterial Growth

Fluctuations in the growth rate of a bacterial culture during unbalanced growth are generally considered undesirable in quantitative studies of bacterial physiology. Under well-controlled experimental conditions, however, these fluctuations are not random but instead reflect the interplay between intra-cellular networks underlying bacterial growth and the growth environment. Therefore, these fluctuations could be considered quantitative phenotypes of the bacteria under a specific growth condition. Here, we present a method to identify “phenotypic signatures” by time-frequency analysis of unbalanced growth curves measured with high temporal resolution. The signatures are then applied to differentiate amongst different bacterial strains or the same strain under different growth conditions, and to identify the essential architecture of the gene network underlying the observed growth dynamics. Our method has implications for both basic understanding of bacterial physiology and for the classification of bacterial strains

A Combination of Dopamine Genes Predicts Success by Professional Wall Street Traders

What determines success on Wall Street? This study examined if genes affecting dopamine levels of professional traders were associated with their career tenure. Sixty professional Wall Street traders were genotyped and compared to a control group who did not trade stocks. We found that distinct alleles of the dopamine receptor 4 promoter (DRD4P) and catecholamine-O-methyltransferase (COMT) that affect synaptic dopamine were predominant in traders. These alleles are associated with moderate, rather than very high or very low, levels of synaptic dopamine. The activity of these alleles correlated positively with years spent trading stocks on Wall Street. Differences in personality and trading behavior were also correlated with allelic variants. This evidence suggests there may be a genetic basis for the traits that make one a successful trader

Combination of searches for heavy spin-1 resonances using 139 fb−1 of proton-proton collision data at s = 13 TeV with the ATLAS detector

A combination of searches for new heavy spin-1 resonances decaying into different pairings of W, Z, or Higgs bosons, as well as directly into leptons or quarks, is presented. The data sample used corresponds to 139 fb−1 of proton-proton collisions at = 13 TeV collected during 2015–2018 with the ATLAS detector at the CERN Large Hadron Collider. Analyses selecting quark pairs (qq, bb, , and tb) or third-generation leptons (τν and ττ) are included in this kind of combination for the first time. A simplified model predicting a spin-1 heavy vector-boson triplet is used. Cross-section limits are set at the 95% confidence level and are compared with predictions for the benchmark model. These limits are also expressed in terms of constraints on couplings of the heavy vector-boson triplet to quarks, leptons, and the Higgs boson. The complementarity of the various analyses increases the sensitivity to new physics, and the resulting constraints are stronger than those from any individual analysis considered. The data exclude a heavy vector-boson triplet with mass below 5.8 TeV in a weakly coupled scenario, below 4.4 TeV in a strongly coupled scenario, and up to 1.5 TeV in the case of production via vector-boson fusion

Search for resonant production of dark quarks in the dijet final state with the ATLAS detector

This paper presents a search for a new Z′ resonance decaying into a pair of dark quarks which hadronise into dark hadrons before promptly decaying back as Standard Model particles. This analysis is based on proton-proton collision data recorded at $$\sqrt{s}$$ s = 13 TeV with the ATLAS detector at the Large Hadron Collider between 2015 and 2018, corresponding to an integrated luminosity of 139 fb−1. After selecting events containing large-radius jets with high track multiplicity, the invariant mass distribution of the two highest-transverse-momentum jets is scanned to look for an excess above a data-driven estimate of the Standard Model multijet background. No significant excess of events is observed and the results are thus used to set 95% confidence-level upper limits on the production cross-section times branching ratio of the Z′ to dark quarks as a function of the Z′ mass for various dark-quark scenarios