Neuroanatomical Substrates Underlying Dispositional Optimism

Objective:How to effectively improve personal health and enable people to have a good quality of life has been a long-standing research topic in the fields of psychiatry,psychology and sociology.A great number of studies have shown the importance of character strengths to a spectrum of physical and mental health outcomes.Dispositional optimism(hereinafter,optimism),as a tendency to hold generalized positive expectancies for future outcomes,is one such character strength.Although a large body of research to date has documented many benefits of optimism for personal health and well-being,less attention has been paid to where interindividual differences in optimism come from,especially for those intrinsic neurobiological mechanisms associated with interindividual differences in optimism,which are key to understanding optimism and its relations with health and life outcomes.Therefore,the current study aims to systematically determine the brain structures and structural organization patterns linked to optimism via behavioral measurements and structural magnetic resonance imaging,which may extend previous understandings of the neuroanatomical substrates associated with optimism.Besides,given that optimism has been shown to be associated with basic personality construct(e.g.,big-five personality traits)and with depression and anxiety,the current study also aims to explore the role and pathways of these essential personality traits in optimism acquisition,as well as the role and pathways of optimism in ameliorating negative emotions such as depression and anxiety,which may provide novel insights for the ways to cultivate optimism and alleviate negative emotions through optimism.Methods:Here,we examined these issues via five studies.In the study 1,a voxel-based morphometry(VBM)approach was used to estimate individual’s regional gray matter density(r GMD);and then,whole-brain regression and prediction analyses were employed to identify the brain structures whose r GMD was associated with optimism in a large sample comprising 231 healthy adolescents aged 16 to 20 years.In the study2,a surface-based morphometry(SBM)approach combined with a recent novel structural covariance estimation approach were used to construct individual structural covariance networks based on cortical gyrification;next,topological graph theory was used to estimate global(global efficiency,local efficiency and small-worldness)and regional(betweenness centrality)properties of these constructed networks;and then,partial correlation,as well as partial least squares correlation(PLSC)were employed to determine the patterns of a structural covariance network associated with optimism in the same participants as study 1,in order to bridge the knowledge gap regarding neuroanatomical basis of optimism at the network level.In the study 3,we expanded the study sample [i.e.,adding a new independent sample of healthy adults(N = 151)],and included more morphological metrics(cortical thickness,cortical surface area,volume and cortical gyrification)to further explore the relationships between structural covariances and optimism.A commonly used machine learning method,i.e.,least absolute shrinkage and selection operator(LASSO)regression,combined a fivefold cross-validation approach were used to detect the model/pattern of structural covariance which could predict individual’s optimism score,in order to obtain more comprehensive understandings of the neural structural basis of optimism.In the study4,combining the behavioral results of the big-five personality traits with our previous neuroimaging findings,mediation analyses were used to explore the role and pathways of big-five personality traits in optimism acquisition.In the study 5,combining the behavioral results of depression and anxiety with our previous neuroimaging findings,mediation analyses were used to explore the role and pathways of optimism in ameliorating depression and anxiety.Results:In the study 1,a significant positive correlation between optimism and the r GMD of the bilateral putamen was observed during late adolescence.This result remained significant even after adjusting for age,sex,family socioeconomic status(SES),general intelligence and total gray matter volume(TGMV),suggesting that the bilateral putamen may be a pivotal neuroanatomical site related to optimism.In the study 2,we detected a pattern of cortical-gyrification-based covariance network linked to optimism during late adolescence;that is,optimistic individuals exhibited higher global and local efficiency of the cortical-gyrification-based covariance network,and exhibited a pronounced betweenness centrality pattern,in which nine regions including the left frontopolar cortex(FPo),the right posterior-ventral part of the cingulate gyrus(v PCC),the left subparietal sulcus(Sb PS),the right lingual gyrus(LG),the right posterior transverse collateral sulcus(p Tr Co S),the left paracentral lobule and sulcus(Pa CG/S),the right Heschl’s gyrus(HG),the right orbital gyri(Or G)and the right circular sulcus of the insula(s INS)had robust positive contributions,while other three regions,the left opercular part of the inferior frontal gyrus(IFG),the left triangular part of the IFG,and the right postcentral sulcus(Pos CS)had robust negative contributions.These results remained significant even after adjusting for age,sex and estimated total intracranial volume(e TIV),and showed significant correlations with optimism scores from 2.5 years before,suggesting that this organization pattern of cortical-gyrification-based covariance network may indeed be associated with optimism,and those regions which have robust contributions to the betweenness centrality pattern may also be the key regions linked to optimism.In the study 3,in addition to cortical gyrification,structural covariance patterns based on other morphological metrics(cortical thickness,cortical surface area and volume)were also found to be the key features linked to optimism;especially after adjusting for age,sex and e TIV,an effective LASSO regression model for predicting optimism was obtained only relying on inter-regional covariance in cortical thickness,cortical surface area,volume and cortical gyrification,which performed well in both training set and an unseen testing set.The resultant LASSO regression model included a total of 54 covariance features based on cortical thickness,cortical surface area,volume or cortical gyrification,which mainly located among the frontal lobe(e.g.,the IFG,the middle frontal gyrus,the superior frontal gyrus,the Or G,the precentral gyrus and the central sulcus),the insular lobe(e.g.,the s INS,the short insular gyri and the long insular gyrus),the limbic system(e.g,the anterior cingulate cortex,the v PCC,the parahippocampal gyrus and the pericallosal sulcus),the temporal lobe(e.g.,the HG,the transverse temporal sulcus,the middle temporal gyrus,the superior temporal gyrus and the temporal pole),the parietal lobe(e.g.,the Sb PS,the Pa CG/S,the precuneus,the angular gyrus,the supramarginal gyrus and the postcentral gyrus)and the occipital lobe(e.g.,the Tr Co S,the fusiform gyrus,the cuneus,the superior occipital gyrus and the middle occipital gyrus),suggesting that the structural covariance patterns among these brain regions may as the key features to predicting optimism,and these brain regions may also as the key regions linked to optimism.In the study 4,although other big-five personality traits(neuroticism,openness and agreeableness)were found to be significantly correlated with optimism,only extraversion can independently explain the variance in optimism.Mediation analyses further showed that extraversion may account for the associations between previously identified brain structures / structural covariance patterns and optimism,i.e.,mediating the association between putamen density and optimism;mediating the association between global efficiency of the cortical-gyrification-based covariance network and optimism;mediating the association between betweenness centrality pattern of the cortical-gyrification-based covariance network and optimism;and mediating the association between structural covariance patterns and optimism.These results remained significant even after adjusting for age,sex and e TIV,suggesting that extraversion may be an essential personal resource for acquiring optimism.In the study 5,we confirmed significant negative relationships between optimism and depression and anxiety.Mediation analyses further showed that the abovementioned betweenness centrality pattern of the cortical-gyrification-based covariance network could alleviate depression and anxiety through affecting optimism,and the abovementioned structural covariance patterns linked to optimism could also alleviate depression and anxiety through affecting optimism.These results remained significant even after adjusting for age,sex and e TIV,suggesting that optimism may indeed play an important role in alleviating depression and anxiety,and may ameliorate these negative emotions through abovementioned potential neural pathways.Conclusion:The current findings bridge the knowledge gap of neuroanatomical substrates underlying optimism during late adolescence,and for the first time,provide preliminary evidence of structural covariance patterns associated with optimism,extending previous neurobiological understandings of optimism.Our findings suggest that optimism may be a psychological construct formed from complex interactions among multiple brain regions subserving cognition,emotion and motivation,and the interactions of these brain regions may promote one’s optimism acquisition through improving his/her extraversion,and the interactions of these brain regions may also alleviate one’s depression and anxiety through enhancing his/her optimism.These findings are important,as they may be helpful for understanding the nature of optimism and its relationship to health and may have implications for neurobiologically based interventions aimed at raising optimism to ameliorate health problems and increase well-being and quality of life.