Age-related Difference In Risk Preference And Neural Mechanism

The majority of our decisions involve some level of risk in daily life.Decisionmaking under risk is a complex process and both cognitive and emotional factors are involved in the selection of goal-directed responses.Aging is accompanied by a wide range of neurobiological and cognitive decline,such as declines in reward learning,reduced value coding ability,which affects risk preference of older adults in a variety of risky choice tasks.But do different measures converge in showing similar age-related patterns and which underlining neural mechanism contribute to the difference? We conducted behavioral and functional magnetic resonance imaging(fMRI)methods to investigate the risk preference in older adults and neural mechanisms of age differences.In the first study,we employed self-report assessments(i.e.,questionnaire test and pictorial line paradigm)and behavior measurement(i.e.,descriptive decision task)to measure age-related difference in risk preference.In questionnaire test,older adults showed less sensation seeking characteristics and impulsivity than young adults,which indicates that aging is associated with decreased sensation seeking characteristics and impulsivity.In pictorial line paradigm,older people performed less risk seeking preference than young counterparts whereas risk aversion is similar to that of young adults.Gambling task was adopted in behavior measurement and found age-related difference in risk preference.Specifically,in the gain framework,older adults are more inclined to choose certain options than risker options(better benefits),indicating that older adults are less risk seeking than young counterparts.In the loss framework,the risk preference of older adults is similar to young adults'.We computed pearson correlation analysis to address the convergent validity of three measurement and found that impulsivity has nothing to do with risk preference while sensation seeking characteristics can predict individual risk preference performance in pictorial line paradigm and gambling task.Moreover,the results showed that the convergent validity of risk preference under pictorial line paradigm and gambling task is invalid,but the convergent validity under different task conditions of unique measurement method is significant.In the second study,the resting and task state fMRI method are took to explore the neural mechanism of risk preference in older adults.The analysis of resting state showed that the functional connectivities between the dorsolateral prefrontal cortex(dmPFC)and the temporo-parietal junction(TPJ),TPJ and lateral temporal cortex(LTC)were correlated with risk preference in the older adults but not in young adults.Through Z test,it is found that the correlation was significantly different between the older and young adults.Task state activation analysis showed that in the gain framework,the dmPFC,angular gyrus,putamen and other brain regions of older adults were more active than those of the young counterparts.Further individual difference analysis manifested that the activation beta weight of putamen was negatively correlated with risk preference in young but not in older adults,which indicated that the stronger activation of putamen,the lower risk seeking preference of young adults.In the loss framework,older adults showed higher activation in the posterior cingulate gyrus(PCG)and angular gyrus while young adults showed higher activation in the calcarine region.Further individual difference analysis manifested that the activation beta weight of PCG was negatively correlated with risk preference in young but not in older adults,which indicated that the stronger activation of PCG,the lower risk seeking preference of young adults.Based on the results of study 1 and 2,different measurement methods(self-report assessments/ behavior measurement)and dimensions(risk seeking/risk aversion)affect the age-related difference of risk preference.Moreover,under the same measurement,different task frames(gains/losses)also affect the risk preference across older and young adults.This study provides evidence about the effect of measurement methods and task frames on the risk preferences of older adults and underlying neural mechanisms.Further studies are needed to further explore the neural mechanism of older adults' risk preference based on large-scale brain networks.