A longitudinal study of the relationship between personality traits and the annual rate of volume changes in regional gray matter in healthy adults

Revised Temperament and Character Inventory factors predict neuropsychiatric symptoms and aging-related cognitive decline across 25 years

Introduction

Personality traits and neuropsychiatric symptoms such as neuroticism and depression share genetic overlap and have both been identified as risks factors for development of aging-related neurocognitive decline and Alzheimer's disease (AD). This study aimed to examine revised personality factors derived from the Temperament and Character Inventory, previously shown to be associated with psychiatric disorders, as predictors of neuropsychiatric, cognitive, and brain trajectories of participants from a population-based aging study.

Methods

Mixed-effect linear regression analyses were conducted on data for the full sample (Nmax = 1,286), and a healthy subsample not converting to AD-dementia during 25-year follow-up (Nmax = 1,145), complemented with Cox proportional regression models to determine risk factors for conversion to clinical AD.

Results

Two personality factors, Closeness to Experience (CE: avoidance of new stimuli, high anxiety, pessimistic anticipation, low reward seeking) and Tendence to Liabilities (TL: inability to change, low autonomy, unaware of the value of their existence) were associated with higher levels of depressive symptoms, stress (CE), sleep disturbance (TL), as well as greater decline in memory, vocabulary and verbal fluency in the full sample. Higher CE was additionally associated with greater memory decline across 25 years in the healthy subsample, and faster right hippocampal volume reduction across 8 years in a neuroimaging subsample (N = 216). Most, but not all, personality-cognition associations persisted after controlling for diabetes, hypertension and cardiovascular disease. Concerning risks for conversion to AD, higher age, and APOE-ε4, but none of the personality measures, were significant predictors.

Conclusion

The results indicate that personality traits associated with psychiatric symptoms predict accelerated age-related neurocognitive declines even in the absence of neurodegenerative disease. The attenuation of some personality effects on cognition after adjustment for health indicators suggests that those effects may be partly mediated by somatic health. Taken together, the results further emphasize the importance of personality traits in neurocognitive aging and underscore the need for an integrative (biopsychosocial) perspective of normal and pathological age-related cognitive decline.

Brain volumetrics across the lifespan of the rhesus macaque

The rhesus macaque is a long-lived nonhuman primate (NHP) with a brain structure similar to humans, which may represent a valuable translational animal model in which to study human brain aging. Previous magnetic resonance imaging (MRI) studies of age in rhesus macaque brains have been prone to low statistical power, unbalanced sex ratio and lack of a complete age range. To overcome these problems, the current study surveyed structural T1-weighted magnetic resonance imaging scans of 66 animals, 34 females (aged 6-31 years) and 32 males (aged 5-27 years). Differences observed in older animals, included enlargement of the lateral ventricles and a smaller volume in the frontal cortex, caudate, putamen, hypothalamus, and thalamus. Unexpected, greater volume, were measured in older animals in the hippocampus, amygdala, and globus pallidus. There were also numerous differences between males and females with respect to age in both white and gray matter regions. As an apparent model of normative human aging, the macaque is ideal for studying induction and mitigation of neurodegenerative disease.

Default Mode Network Modulation by Psychedelics: A Systematic Review

Psychedelics are a unique class of drug that commonly produce vivid hallucinations as well as profound psychological and mystical experiences. A grouping of interconnected brain regions characterized by increased temporal coherence at rest have been termed the Default Mode Network (DMN). The DMN has been the focus of numerous studies assessing its role in self-referencing, mind wandering, and autobiographical memories. Altered connectivity in the DMN has been associated with a range of neuropsychiatric conditions such as depression, anxiety, post-traumatic stress disorder, attention deficit hyperactive disorder, schizophrenia, and obsessive-compulsive disorder. To date, several studies have investigated how psychedelics modulate this network, but no comprehensive review, to our knowledge, has critically evaluated how major classical psychedelic agents-lysergic acid diethylamide, psilocybin, and ayahuasca-modulate the DMN. Here we present a systematic review of the knowledge base. Across psychedelics there is consistent acute disruption in resting state connectivity within the DMN and increased functional connectivity between canonical resting-state networks. Various models have been proposed to explain the cognitive mechanisms of psychedelics, and in one model DMN modulation is a central axiom. Although the DMN is consistently implicated in psychedelic studies, it is unclear how central the DMN is to the therapeutic potential of classical psychedelic agents. This article aims to provide the field with a comprehensive overview that can propel future research in such a way as to elucidate the neurocognitive mechanisms of psychedelics.

Functional connectivity of the central autonomic and default mode networks represent neural correlates and predictors of individual personality

There is solid evidence for the prominent involvement of the central autonomic and default mode systems in shaping personality. However, whether functional connectivity of these systems can represent neural correlates and predictors of individual variation in personality traits is largely unknown. Resting-state functional magnetic resonance imaging data of 215 healthy young adults were used to construct the sympathetic (SN), parasympathetic (PN), and default mode (DMN) networks, with intra- and internetwork functional connectivity measured. Personality factors were assessed using the five-factor model. We examined the associations between personality factors and functional network connectivity, followed by performance of personality prediction based on functional connectivity using connectome-based predictive modeling (CPM), a recently developed machine learning approach. All personality factors (neuroticism, extraversion, conscientiousness, and agreeableness) other than openness were significantly correlated with intra- and internetwork functional connectivity of the SN, PN, and DMN. Moreover, the CPM models successfully predicted conscientiousness and agreeableness at the individual level using functional network connectivity. Our findings may expand existing knowledge regarding the neural substrates underlying personality.

Regional gray matter volume mediates the relationship between neuroticism and depressed emotion

The underlying psychological mechanism of the effect of neuroticism on depressed emotion has been widely studied. However, the neural mechanism of this relationship remains unclear. Therefore, the present study aimed to apply voxel-based morphometry (VBM) to explore the neural mechanism of the relationship between depressed emotion and neuroticism in healthy and young participants through longitudinal tracking research. The behavioral results showed that neuroticism was positively related to depressed emotion at T1 and T2 (6 months later). The VBM analysis revealed that neuroticism positively associated with the gray matter volume (GMV) in the dorsal medial prefrontal cortex (dmPFC). Mediation analysis was conducted to investigate the neural basis of the association between depressed emotion and neuroticism. The mediation result revealed that GMV of the dmPFC partially mediates the relationship between neuroticism and depressed emotion at T1 but not T2. Together, these findings suggest that the gray matter volume of dmPFC could may affect the relationship between depressed emotion and neuroticism.

Qualitative and Quantitative Comparison of Hippocampal Volumetric Software Applications: Do All Roads Lead to Rome?

Brain volumetric software is increasingly suggested for clinical routine. The present study quantifies the agreement across different software applications. Ten cases with and ten gender- and age-adjusted healthy controls without hippocampal atrophy (median age: 70; 25–75% range: 64–77 years and 74; 66–78 years) were retrospectively selected from a previously published cohort of Alzheimer’s dementia patients and normal ageing controls. Hippocampal volumes were computed based on 3 Tesla T1-MPRAGE-sequences with FreeSurfer (FS), Statistical-Parametric-Mapping (SPM; Neuromorphometrics and Hammers atlases), Geodesic-Information-Flows (GIF), Similarity-and-Truth-Estimation-for-Propagated-Segmentations (STEPS), and Quantib™. MTA (medial temporal lobe atrophy) scores were manually rated. Volumetric measures of each individual were compared against the mean of all applications with intraclass correlation coefficients (ICC) and Bland–Altman plots. Comparing against the mean of all methods, moderate to low agreement was present considering categorization of hippocampal volumes into quartiles. ICCs ranged noticeably between applications (left hippocampus (LH): from 0.42 (STEPS) to 0.88 (FS); right hippocampus (RH): from 0.36 (Quantib™) to 0.86 (FS). Mean differences between individual methods and the mean of all methods [mm³] were considerable (LH: FS −209, SPM-Neuromorphometrics −820; SPM-Hammers −1474; Quantib™ −680; GIF 891; STEPS 2218; RH: FS −232, SPM-Neuromorphometrics −745; SPM-Hammers −1547; Quantib™ −723; GIF 982; STEPS 2188). In this clinically relevant sample size with large spread in data ranging from normal aging to severe atrophy, hippocampal volumes derived by well-accepted applications were quantitatively different. Thus, interchangeable use is not recommended.

“Nothing to see here”: No structural brain differences as a function of the Big Five personality traits from a systematic review and meta-analysis

Personality reflects social, affective, and cognitive predispositions that emerge from genetic and environmental influences. Contemporary personality theories conceptualize a Big Five Model of personality based on the traits of neuroticism, extraversion, agreeableness, conscientiousness, and openness to experience. Starting around the turn of the millennium, neuroimaging studies began to investigate functional and structural brain features associated with these traits. Here, we present the first study to systematically evaluate the entire published literature of the association between the Big Five traits and three different measures of brain structure. Qualitative results were highly heterogeneous, and a quantitative meta-analysis did not produce any replicable results. The present study provides a comprehensive evaluation of the literature and its limitations, including sample heterogeneity, Big Five personality instruments, structural image data acquisition, processing, and analytic strategies, and the heterogeneous nature of personality and brain structures. We propose to rethink the biological basis of personality traits and identify ways in which the field of personality neuroscience can be strengthened in its methodological rigor and replicability.

Personality Impact on Alzheimer's Disease-Signature and Vascular Imaging Markers: A PET-MRI Study

BACKGROUND

Several studies postulated that personality is an independent determinant of cognitive trajectories in old age.

OBJECTIVE

This study explores the impact of personality on widely used Alzheimer's disease (AD) and vascular imaging markers.

METHODS

We examined the association between personality and three classical AD imaging markers (centiloid-based-amyloid load, MRI volumetry in hippocampus, and media temporal lobe atrophy), and two vascular MRI parameters (Fazekas score and number of cortical microbleeds) assessed at baseline and upon a 54-month-follow-up. Personality was assessed with the Neuroticism Extraversion Openness Personality Inventory-Revised. Regression models were used to identify predictors of imaging markers including sex, personality factors, presence of APOE ɛ4 allele and cognitive evolution over time.

RESULTS

Cortical GM volumes were negatively associated with higher levels of Conscientiousness both at baseline and follow-up. In contrast, higher scores of Openness were related to better preservation of left hippocampal volumes in these two time points and negatively associated with medial temporal atrophy at baseline. Amyloid load was not affected by personality factors. Cases with higher Extraversion scores displayed higher numbers of cortical microbleeds at baseline.

CONCLUSION

Personality impact on brain morphometry is detected only in some among the routinely used imaging markers. The most robust associations concern the positive role of high levels of Conscientiousness and Openness on AD-signature MRI markers. Higher extraversion levels are associated with increased vulnerability to cortical microbleeds pointing to the fact that the socially favorable traits may have a detrimental effect on brain integrity in old age.

Representation of social content in dorsomedial prefrontal cortex underlies individual differences in agreeableness trait

Personality traits reflect key aspects of individual variability in different psychological domains. Understanding the mechanisms that give rise to these differences requires an exhaustive investigation of the behaviors associated with such traits, and their underlying neural sources. Here we investigated the mechanisms underlying agreeableness, one of the five major dimensions of personality, which has been linked mainly to socio-cognitive functions. In particular, we examined whether individual differences in the neural representations of social information are related to differences in agreeableness of individuals. To this end, we adopted a multivariate representational similarity approach that captured within single individuals the activation pattern similarity of social and non-social content, and tested its relation to the agreeableness trait in a hypothesis-driven manner. The main result confirmed our prediction: processing social and non-social content led to similar patterns of activation in individuals with low agreeableness, while in more agreeable individuals these patterns were more dissimilar. Critically, this association between agreeableness and encoding similarity of social and random content was significant only in the dorsomedial prefrontal cortex, a brain region consistently involved during attributions of mental states. The present finding reveals the link between neural mechanisms underlying social information processing and agreeableness, a personality trait highly related to socio-cognitive abilities, thereby providing a step forward in characterizing its neural determinants. Furthermore, it emphasizes the advantage of multivariate pattern analysis approaches in capturing and understanding the neural sources of individual variations.

Gray matter structures associated with neuroticism: A meta-analysis of whole-brain voxel-based morphometry studies

Neuroticism is major higher-order personality trait and has been robustly associated with mental and physical health outcomes. Although a growing body of studies have identified neurostructural markers of neuroticism, the results remained highly inconsistent. To characterize robust associations between neuroticism and variations in gray matter (GM) structures, the present meta-analysis investigated the concurrence across voxel-based morphometry (VBM) studies using the anisotropic effect size signed differential mapping (AES-SDM). A total of 13 studies comprising 2,278 healthy subjects (1,275 females, 29.20 ± 14.17 years old) were included. Our analysis revealed that neuroticism was consistently associated with the GM structure of a cluster spanning the bilateral dorsal anterior cingulate cortex and extending to the adjacent medial prefrontal cortex (dACC/mPFC). Meta-regression analyses indicated that the neuroticism-GM associations were not confounded by age and gender. Overall, our study is the first whole-brain meta-analysis exploring the brain structural correlates of neuroticism, and the findings may have implications for the intervention of high-neuroticism individuals, who are at risk of mental disorders, by targeting the dACC/mPFC.

Interactions between Personality, Depression, Anxiety and Cognition to Understand Early Stage of Alzheimer's Disease

The multifaceted nature of Alzheimer's disease (AD) and Mild cognitive impairment (MCI) can lead to wide inter-individual differences in disease manifestation in terms of brain pathology and cognition. The lack of understanding of phenotypic diversity in AD arises from a difficulty in understanding the integration of different levels of network organization (i.e. genes, neurons, synapses, anatomical regions, functions) and in inclusion of other information such as neuropsychiatric characteristics, personal history, information regarding general health or subjective cognitive complaints in a coherent model. Non-cognitive factors, such as personality traits and behavioral and psychiatric symptoms, can be informative markers of early disease stage. It is known that personality can affect cognition and behavioral symptoms. The aim of the paper is to review the different types of interactions existing between personality, depression/anxiety, and cognition and cognitive disorders at behavioral and brain/genetic levels.

The Multilayer Network Approach in the Study of Personality Neuroscience

It has long been understood that a multitude of biological systems, from genetics, to brain networks, to psychological factors, all play a role in personality. Understanding how these systems interact with each other to form both relatively stable patterns of behaviour, cognition and emotion, but also vast individual differences and psychiatric disorders, however, requires new methodological insight. This article explores a way in which to integrate multiple levels of personality simultaneously, with particular focus on its neural and psychological constituents. It does so first by reviewing the current methodology of studies used to relate the two levels, where psychological traits, often defined with a latent variable model are used as higher-level concepts to identify the neural correlates of personality (NCPs). This is known as a top-down approach, which though useful in revealing correlations, is not able to include the fine-grained interactions that occur at both levels. As an alternative, we discuss the use of a novel complex system approach known as a multilayer network, a technique that has recently proved successful in revealing veracious interactions between networks at more than one level. The benefits of the multilayer approach to the study of personality neuroscience follow from its well-founded theoretical basis in network science. Its predictive and descriptive power may surpass that of statistical top-down and latent variable models alone, potentially allowing the discernment of more complete descriptions of individual differences, and psychiatric and neurological changes that accompany disease. Though in its infancy, and subject to a number of methodological unknowns, we argue that the multilayer network approach may contribute to an understanding of personality as a complex system comprised of interrelated psychological and neural features.

Robust prediction of individual personality from brain functional connectome

Neuroimaging studies have linked inter-individual variability in the brain to individualized personality traits. However, only one or several aspects of personality have been effectively predicted based on brain imaging features. The objective of this study was to construct a reliable prediction model of personality in a large sample by using connectome-based predictive modeling (CPM), a recently developed machine learning approach. High-quality resting-state functional magnetic resonance imaging data of 810 healthy young participants from the Human Connectome Project dataset were used to construct large-scale brain networks. Personality traits of the five-factor model (FFM) were assessed by the NEO Five Factor Inventory. We found that CPM successfully and reliably predicted all the FFM personality factors (agreeableness, openness, conscientiousness and neuroticism) other than extraversion in novel individuals. At the neural level, we found that the personality-associated functional networks mainly included brain regions within default mode, frontoparietal executive control, visual and cerebellar systems. Although different feature selection thresholds and parcellation strategies did not significantly influence the prediction results, some findings lost significance after controlling for confounds including age, gender, intelligence and head motion. Our finding of robust personality prediction from an individual's unique functional connectome may help advance the translation of 'brain connectivity fingerprinting' into real-world personality psychological settings.

Neuroticism, conscientiousness, and in vivo Alzheimer pathologies measured by amyloid PET and MRI

AIM

It has been suggested that personality traits, particularly neuroticism and conscientiousness, are risk factors for Alzheimer's disease (AD) and related cognitive decline. However, the underlying pathological links between personality traits and AD-related cognitive impairments remain unclear. Thus, the present study investigated associations of neuroticism and conscientiousness with in vivo cerebral amyloid-beta (Aβ) burden, AD-signature regional neurodegeneration, and white matter hyperintensities (WMH) in non-demented middle- and old-aged adults.

METHODS

A total of 397 non-demented participants underwent comprehensive clinical and neuropsychological assessments, ¹¹ C-labeled Pittsburgh Compound B positron emission tomography, and magnetic resonance imaging. Additionally, the NEO Five-Factor Inventory was administered to both the participants and their informants to measure neuroticism and conscientiousness.

RESULTS

Neither neuroticism nor conscientiousness was associated with cerebral Aβ deposition or WMH. In contrast, higher neuroticism and lower conscientiousness, reported by informants in particular, were significantly associated with reduced AD-signature region cortical thickness. In regards to the direct and indirect effect of each personality on AD-signature region cortical thickness, only the direct effects were found, whereas indirect effects via Aβ deposition or WMH were not.

CONCLUSION

The present findings suggest that amyloid-independent regional neurodegeneration might underlie relations of neuroticism and conscientiousness with AD.

Personality factors and cerebral glucose metabolism in community-dwelling older adults

Personality factors have been associated with Alzheimer's disease (AD) and dementia, but they have not been examined against markers of regional brain glucose metabolism (a primary measure of brain functioning) in older adults without clinically diagnosed cognitive impairment. The relationship between personality factors derived from the five-factor model and cerebral glucose metabolism determined using positron emission tomography (PET) with [18F]-2-fluoro-2-deoxy-D-glucose (18F-FDG-PET) was examined in a cohort of 237 non-demented, community-dwelling older adults aged 60-89 years (M ± SD = 73.76 ± 6.73). Higher neuroticism and lower scores on extraversion and conscientiousness were significantly associated with decreased glucose metabolism in brain regions typically affected by AD neuropathological processes, including the hippocampus and entorhinal cortex. Furthermore, while there were significant differences between apolipoprotein E (APOE) ε4 allele carriers and non-carriers on ¹⁸F-FDG-PET results in the neocortex and other brain regions (p < 0.05), there was no significant difference between carriers and non-carriers on personality factors and no significant interactions were found between APOE ε4 carriage and personality factors on brain glucose metabolism. In conclusion, we found significant relationships between personality factors and glucose metabolism in neural regions more susceptible to AD neuropathology in older adults without clinically significant cognitive impairment. These findings support the need for longitudinal research into the potential mechanisms underlying the relationship between personality and dementia risk, including measurement of change in other AD biomarkers (amyloid and tau imaging) and how they correspond to change in personality factors. Future research is also warranted to determine whether timely psychological interventions aimed at personality facets (specific aspects or characteristics of personality factors) can affect imaging or other biomarkers of AD resulting in delay or ideally preventing the onset of the cognitive impairment.

Less agreeable, better preserved? A PET amyloid and MRI study in a community-based cohort

The relationship between personality profiles and brain integrity in old age is still a matter of debate. We examined the association between Big Five factor and facet scores and MRI brain volume changes on a 54-month follow-up in 65 elderly controls with 3 neurocognitive assessments (baseline, 18 months, and 54 months), structural brain MRI (baseline and 54 months), brain amyloid PET during follow-up, and APOE genotyping. Personality was assessed with the Neuroticism Extraversion Openness Personality Inventory-Revised. Regression models were used to identify predictors of volume loss including time, age, sex, personality, amyloid load, presence of APOE ε4 allele, and cognitive evolution. Lower agreeableness factor scores (and 4 of its facets) were associated with lower volume loss in the hippocampus, entorhinal cortex, amygdala, mesial temporal lobe, and precuneus bilaterally. Higher openness factor scores (and 2 of its facets) were also associated with lower volume loss in the left hippocampus. Our findings persisted when adjusting for confounders in multivariable models. These data suggest that the combination of low agreeableness and high openness is an independent predictor of better preservation of brain volume in areas vulnerable to neurodegeneration.

Associations between personality and whole-brain functional connectivity at rest: Evidence across the adult lifespan

INTRODUCTION

Personality is associated with cognitive, emotional, and social functioning, and can play a role in age-related cognitive decline and dementia risk; however, little is known about the brain dynamics underlying personality characteristics, and whether they are moderated by age.

METHODS

We investigated the associations between personality and resting-state functional MRI data from 365 individuals across the adult lifespan (20-80 years). Participants completed the 50-item International Personality Item Pool and a resting-state imaging protocol on a 3T MRI scanner. Within-network connectivity values were computed based on predefined networks. Regression analyzes were conducted in order to investigate personality-connectivity associations, as well as moderation by age. All models controlled for potential confounders (such as age, sex, education, IQ, and the other personality traits).

RESULTS

We found that openness was positively associated with connectivity in the default-mode network, neuroticism was negatively associated with both the ventral and dorsal attention networks, and agreeableness was negatively associated with the dorsal attention network. In addition, age moderated the association between conscientiousness and the frontoparietal network, indicating that this association become stronger in older age.

CONCLUSIONS

Our findings demonstrate that personality is associated with brain connectivity, which may contribute to identifying personality profiles that play a role in protection against or risk for age-related brain changes and dementia.

Creativity in the Advertisement Domain: The Role of Experience on Creative Achievement

The creativity of an advertisement campaign is one of the most relevant predictors of its success. Past research has highlighted the relevance of domain-specific experience in enhancing creativity, but the results are controversial. We explored the role of work experience, in terms of number of years spent in the advertisement domain, in various forms of creativity expressed within this specific working domain. We hypothesized a mediator role of experience in the relationship between the individual’s creative potential, as measured through a series of divergent thinking tasks, and creative achievement in the advertisement domain. Moreover, considering the importance of personality in creative achievement, we also explored the influence of the openness-to-experience on advertisers’ creative achievement. A range of measures assessing creative achievement, openness, and divergent thinking abilities in terms of fluency and originality were administered to a group of professionals in the advertisement domain. The results demonstrate a crucial role for experience in the connection between originality and creative achievement. Moreover, our findings extend previous studies by showing that fluency and openness are significant predictors of creative achievement in the advertisement environment. These results emphasize the importance of canalizing the advertiser’s divergent thinking abilities through appropriate routes provided by working experience, raising important implications for future explorations of domain-specific creative achievement within an individual differences framework. Final indications for future developments are provided, with a special emphasis on the replication of these findings in various work domains and in various cultural contexts.

Brain gray matter correlates of extraversion: A systematic review and meta-analysis of voxel-based morphometry studies

Extraversion is a fundamental personality dimension closely related to an individual's life outcomes and mental health. Although an increasing number of studies have attempted to identify the neurostructural markers of extraversion, the results have been highly inconsistent. The current study aimed to achieve a comprehensive understanding of brain gray matter (GM) correlates of extraversion with a systematic review and meta-analysis approach. Our review showed relatively high interstudy heterogeneity among previous findings. Our meta-analysis of whole-brain voxel-based morphometry studies revealed that extraversion was stably associated with six core brain regions. Additionally, meta-regression analyses identified brain regions where the associations of extraversion with GM volume were modulated by gender and age. The relationships between extraversion and GM structures were discussed based on three extraversion-related functional systems. Furthermore, we explained the gender and age effects. Overall, our study is the first to reveal a comprehensive picture of brain GM correlates of extraversion, and the findings may be useful for the selection of targeted brain areas for extraversion interventions.

Testing Trait-State Isomorphism in a New Domain: An Exploratory Manipulation of Openness to Experience

The trait-state isomorphism hypothesis holds that personality traits and states (i.e., trait-related behavior) are characterized by similar outcomes (Fleeson, 2001). Openness is associated with creative thinking, personal growth, and positive affect. Engaging in behavior associated with openness has also been found to covary with feelings of authenticity. In the present experiment, participants (N = 210) completed a pre-test assessment, five daily exercises designed to either be inert (control condition) or engage the behaviors and cognitions associated with openness (experimental condition), a post-test assessment, and a 2 week follow up assessment. Results supported the isomorphism hypothesis for positive affect but not creative thinking ability or personal growth. Furthermore, open behavior was only associated with authenticity for individuals high on trait openness.

The Neuroanatomical Basis of Two Subcomponents of Rumination: A VBM Study

Rumination is a trait that includes two subcomponents, namely brooding and reflective pondering, respectively construed as maladaptive and adaptive response styles to negative experiences. Existing evidence indicates that rumination in general is associated with structural and functional differences in the anterior cingulate cortex (ACC) and the dorsal lateral prefrontal cortex (DLPFC). However, conclusive evidence on the specific neural structural basis of each of the two subcomponents is lacking. In this voxel-based morphometry study, we investigated the independent and specific neural structural basis of brooding and reflective pondering in 30 healthy young adults, who belonged to high or low brooding or reflective pondering groups. Consistent with past research, modest but significant positive correlation was found between brooding and reflective pondering. When controlling for reflective pondering, high-brooding group showed increased gray matter volumes in the left DLPFC and ACC. Further analysis on extracted gray matter values showed that gray matter of the same DLPFC and ACC regions also showed significant negative effects of reflective pondering. Taken together, our findings indicate that the two subcomponents of rumination might share some common processes yet also have distinct neural basis. In view of the significant roles of the left DLPFC and ACC in attention and self-related emotional processing/regulation, our findings provide insight into how the potentially shared and distinct cognitive, affective and neural processes of brooding and reflective pondering can be extended to clinical populations to further elucidate the neurobehavioral relationships between rumination and prefrontal abnormality.

Resting-state functional brain connectivity best predicts the personality dimension of openness to experience

Personality neuroscience aims to find associations between brain measures and personality traits. Findings to date have been severely limited by a number of factors, including small sample size and omission of out-of-sample prediction. We capitalized on the recent availability of a large database, together with the emergence of specific criteria for best practices in neuroimaging studies of individual differences. We analyzed resting-state functional magnetic resonance imaging data from 884 young healthy adults in the Human Connectome Project (HCP) database. We attempted to predict personality traits from the "Big Five", as assessed with the NEO-FFI test, using individual functional connectivity matrices. After regressing out potential confounds (such as age, sex, handedness and fluid intelligence), we used a cross-validated framework, together with test-retest replication (across two sessions of resting-state fMRI for each subject), to quantify how well the neuroimaging data could predict each of the five personality factors. We tested three different (published) denoising strategies for the fMRI data, two inter-subject alignment and brain parcellation schemes, and three different linear models for prediction. As measurement noise is known to moderate statistical relationships, we performed final prediction analyses using average connectivity across both imaging sessions (1 h of data), with the analysis pipeline that yielded the highest predictability overall. Across all results (test/retest; 3 denoising strategies; 2 alignment schemes; 3 models), Openness to experience emerged as the only reliably predicted personality factor. Using the full hour of resting-state data and the best pipeline, we could predict Openness to experience (NEOFAC_O: r=0.24, R2=0.024) almost as well as we could predict the score on a 24-item intelligence test (PMAT24_A_CR: r=0.26, R2=0.044). Other factors (Extraversion, Neuroticism, Agreeableness and Conscientiousness) yielded weaker predictions across results that were not statistically significant under permutation testing. We also derived two superordinate personality factors ("α" and "β") from a principal components analysis of the NEO-FFI factor scores, thereby reducing noise and enhancing the precision of these measures of personality. We could account for 5% of the variance in the β superordinate factor (r=0.27, R2=0.050), which loads highly on Openness to experience. We conclude with a discussion of the potential for predicting personality from neuroimaging data and make specific recommendations for the field.

Learning facts during aging: the benefits of curiosity

Background/study context: Recent studies have shown that young adults better remember factual information they are curious about. It is not entirely clear, however, whether this effect is retained during aging. Here, the authors investigated curiosity-driven memory benefits in young and elderly individuals.

METHODS

In two experiments, young (age range 18-26) and older (age range 65-89) adults read trivia questions and rated their curiosity to find out the answer. They also attended to task-irrelevant faces presented between the trivia question and the answer. The authors then administered a surprise memory test to assess recall accuracy for trivia answers and recognition memory performance for the incidentally learned faces.

RESULTS

In both young and elderly adults, recall performance was higher for answers to questions that elicited high levels of curiosity. In Experiment 1, the authors also found that faces presented in temporal proximity to curiosity-eliciting trivia questions were better recognized, indicating that the beneficial effects of curiosity extended to the encoding of task-irrelevant material.

CONCLUSIONS

These findings show that elderly individuals benefit from the memory-enhancing effects of curiosity. This may lead to the implementation of learning strategies that target and stimulate curiosity in aging.

Surface-based morphometry reveals the neuroanatomical basis of the five-factor model of personality

The five-factor model (FFM) is a widely used taxonomy of human personality; yet its neuro anatomical basis remains unclear. This is partly because past associations between gray-matter volume and FFM were driven by different surface-based morphometry (SBM) indices (i.e. cortical thickness, surface area, cortical folding or any combination of them). To overcome this limitation, we used Free-Surfer to study how variability in SBM measures was related to the FFM in n = 507 participants from the Human Connectome Project.

Neuroticism was associated with thicker cortex and smaller area and folding in prefrontal–temporal regions. Extraversion was linked to thicker pre-cuneus and smaller superior temporal cortex area. Openness was linked to thinner cortex and greater area and folding in prefrontal–parietal regions. Agreeableness was correlated to thinner prefrontal cortex and smaller fusiform gyrus area. Conscientiousness was associated with thicker cortex and smaller area and folding in prefrontal regions. These findings demonstrate that anatomical variability in prefrontal cortices is linked to individual differences in the socio-cognitive dispositions described by the FFM. Cortical thickness and surface area/folding were inversely related each others as a function of different FFM traits (neuroticism, extraversion and consciousness vs openness), which may reflect brain maturational effects that predispose or protect against psychiatric disorders.

Greater cerebellar gray matter volume in car drivers: an exploratory voxel-based morphometry study

Previous functional neuroimaging studies have identified multiple brain areas associated with distinct aspects of car driving in simulated traffic environments. Few studies, however, have examined brain morphology associated with everyday car-driving experience in real traffic. Thus, the aim of the current study was to identify gray matter volume differences between drivers and non-drivers. We collected T1-weighted structural brain images from 73 healthy young adults (36 drivers and 37 non-drivers). We performed a whole-brain voxel-based morphometry analysis to examine between-group differences in regional gray matter volume. Compared with non-drivers, drivers showed significantly greater gray matter volume in the left cerebellar hemisphere, which has been associated with cognitive rather than motor functioning. In contrast, we found no brain areas with significantly greater gray matter volume in non-drivers compared with drivers. Our findings indicate that experience with everyday car driving in real traffic is associated with greater gray matter volume in the left cerebellar hemisphere. This brain area may be involved in abilities that are critical for driving a car, but are not commonly or frequently used during other daily activities.

Estimating Intracranial Volume in Brain Research: An Evaluation of Methods

Intracranial volume (ICV) is a standard measure often used in morphometric analyses to correct for head size in brain studies. Inaccurate ICV estimation could introduce bias in the outcome. The current study provides a decision aid in defining protocols for ICV estimation across different subject groups in terms of sampling frequencies that can be optimally used on the volumetric MRI data, and type of software most suitable for use in estimating the ICV measure. Four groups of 53 subjects are considered, including adult controls (AC, adults with Alzheimer's disease (AD), pediatric controls (PC) and group of pediatric epilepsy subjects (PE). Reference measurements were calculated for each subject by manually tracing intracranial cavity without sub-sampling. The reliability of reference measurements were assured through intra- and inter- variation analyses. Three publicly well-known software packages (FreeSurfer Ver. 5.3.0, FSL Ver. 5.0, SPM8 and SPM12) were examined in their ability to automatically estimate ICV across the groups. Results on sub-sampling studies with a 95 % confidence showed that in order to keep the accuracy of the inter-leaved slice sampling protocol above 99 %, sampling period cannot exceed 20 mm for AC, 25 mm for PC, 15 mm for AD and 17 mm for the PE groups. The study assumes a priori knowledge about the population under study into the automated ICV estimation. Tuning of the parameters in FSL and the use of proper atlas in SPM showed significant reduction in the systematic bias and the error in ICV estimation via these automated tools. SPM12 with the use of pediatric template is found to be a more suitable candidate for PE group. SPM12 and FSL subjected to tuning are the more appropriate tools for the PC group. The random error is minimized for FS in AD group and SPM8 showed less systematic bias. Across the AC group, both SPM12 and FS performed well but SPM12 reported lesser amount of systematic bias.

Impact of Personality on Cognitive Aging: A Prospective Cohort Study

OBJECTIVES

The aim of this study was to assess the association between personality factors and age-related longitudinal cognitive performance, and explore interactions of stress-proneness with apolipoprotein E (APOE) ɛ4, a prevalent risk factor for Alzheimer's disease (AD).

METHODS

A total of 510 neuropsychiatrically healthy residents of Maricopa County recruited through media ads (mean age 57.6±10.6 years; 70% women; mean education 15.8±2.4 years; 213 APOE ɛ4 carriers) had neuropsychological testing every 2 years (mean duration follow-up 9.1±4.4 years), and the complete Neuroticism Extraversion Openness Personality Inventory-Revised. Several tests were administered within each of the following cognitive domains: memory, executive skills, language, visuospatial skills, and general cognition. Primary effects on cognitive trajectories and APOE ɛ4 interactions were ascertained with quadratic models.

RESULTS

With personality factors treated as continuous variables, Neuroticism was associated with greater decline, and Conscientiousness associated with reduced decline consistently across tests in memory and executive domains. With personality factors trichotomized, the associations of Neuroticism and Conscientiousness were again highly consistent across tests within memory and to a lesser degree executive domains. While age-related memory decline was greater in APOE ɛ4 carriers as a group than ɛ4 noncarriers, verbal memory decline was mitigated in ɛ4 carriers with higher Conscientiousness, and visuospatial perception and memory decline was mitigated in ɛ4 carriers with higher Openness.

CONCLUSIONS

Neuroticism and Conscientiousness were associated with changes in longitudinal performances on tests sensitive to memory and executive skills. APOE interactions were less consistent. Our findings are consistent with previous studies that have suggested that personality factors, particularly Neuroticism and Conscientiousness are associated with cognitive aging patterns. (JINS, 2016, 22, 765-776).

Developmentally Sensitive Interaction Effects of Genes and the Social Environment on Total and Subcortical Brain Volumes

Smaller total brain and subcortical volumes have been linked to psychopathology including attention-deficit/hyperactivity disorder (ADHD). Identifying mechanisms underlying these alterations, therefore, is of great importance. We investigated the role of gene-environment interactions (GxE) in interindividual variability of total gray matter (GM), caudate, and putamen volumes. Brain volumes were derived from structural magnetic resonance imaging scans in participants with (N = 312) and without ADHD (N = 437) from N = 402 families (age M = 17.00, SD = 3.60). GxE effects between DAT1, 5-HTT, and DRD4 and social environments (maternal expressed warmth and criticism; positive and deviant peer affiliation) as well as the possible moderating effect of age were examined using linear mixed modeling. We also tested whether findings depended on ADHD severity. Deviant peer affiliation was associated with lower caudate volume. Participants with low deviant peer affiliations had larger total GM volumes with increasing age. Likewise, developmentally sensitive GxE effects were found on total GM and putamen volume. For total GM, differential age effects were found for DAT1 9-repeat and HTTLPR L/L genotypes, depending on the amount of positive peer affiliation. For putamen volume, DRD4 7-repeat carriers and DAT1 10/10 homozygotes showed opposite age relations depending on positive peer affiliation and maternal criticism, respectively. All results were independent of ADHD severity. The presence of differential age-dependent GxE effects might explain the diverse and sometimes opposing results of environmental and genetic effects on brain volumes observed so far.

Effects of parental emotional warmth on the relationship between regional gray matter volume and depression-related personality traits

The depression-related personality trait is associated with the severity of patients' current depressive symptoms and with the vulnerability to depression within the nonclinical groups. However, little is known about the anatomical structure associated with the depression-related personality traits within the nonclinical sample. Parenting behavior is associated with the depression symptoms; however, whether or not parenting behavior influence the neural basis of the depression-related personality traits is unclear. Thus in current study, first, we used voxel-based morphometry to identify the brain regions underlying individual differences in depression-related personality traits, as measured by the revised Neuroticism-Extraversion-Openness Personality Inventory, in a large sample of young healthy adults. Second, we use mediation analysis to investigate the relationship between parenting behavior and neural basis of depression-related personality traits. The results revealed that depression-related personality traits were positively correlated with gray matter volume mainly in medial frontal gyrus (MFG) that is implicated in the self-referential processing and emotional regulation. Furthermore, parental emotional warmth acted as a mediational mechanism underlying the association between the MFG volume and the depression-related personality trait. Together, our findings suggested that the family environment might play an important role in the acquisition and process of the depression-related personality traits.

A structural model of age, grey matter volumes, education, and personality traits

BACKGROUND

When the relationship between ageing and changes in personality traits is considered, it is important to know how they are influenced by biological and environmental factors. The present study examined the relationships between various factors associated with the effect of ageing on personality traits, including structural changes of the brain and environmental factors such as education.

METHODS

We recruited 41 healthy subjects. We administered the NEO Five-Factor Inventory to assess personality factors. Magnetic resonance imaging was performed, and regional grey matter (GM) volumes were obtained. We identified associations in the correlation analysis of age, cerebral GM volume, years of education, and the personality trait of openness. Path analysis was used to estimate the relationships among these factors.

RESULTS

The path analysis model of age, GM volume, years of education, and the personality trait of openness revealed that age has an indirect negative association with openness through GM volume and years of education. Ageing was related to a decrease in GM volume, which was in turn related to a decrease in the openness score. Older subjects generally had fewer years of education, which was related to a lower openness score.

CONCLUSIONS

Maintaining openness against the effects of ageing is desirable, and our results imply that interventions against age-related cerebral atrophy and the promotion of opportunities for higher education may contribute to the development and stability of a healthy personality during the adult life course.

Estimating anatomical trajectories with Bayesian mixed-effects modeling

We introduce a mass-univariate framework for the analysis of whole-brain structural trajectories using longitudinal Voxel-Based Morphometry data and Bayesian inference. Our approach to developmental and aging longitudinal studies characterizes heterogeneous structural growth/decline between and within groups. In particular, we propose a probabilistic generative model that parameterizes individual and ensemble average changes in brain structure using linear mixed-effects models of age and subject-specific covariates. Model inversion uses Expectation Maximization (EM), while voxelwise (empirical) priors on the size of individual differences are estimated from the data. Bayesian inference on individual and group trajectories is realized using Posterior Probability Maps (PPM). In addition to parameter inference, the framework affords comparisons of models with varying combinations of model order for fixed and random effects using model evidence. We validate the model in simulations and real MRI data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) project. We further demonstrate how subject specific characteristics contribute to individual differences in longitudinal volume changes in healthy subjects, Mild Cognitive Impairment (MCI), and Alzheimer's Disease (AD).

A practical guideline for intracranial volume estimation in patients with Alzheimer's disease

Background

Intracranial volume (ICV) is an important normalization measure used in morphometric analyses to correct for head size in studies of Alzheimer Disease (AD). Inaccurate ICV estimation could introduce bias in the outcome. The current study provides a decision aid in defining protocols for ICV estimation in patients with Alzheimer disease in terms of sampling frequencies that can be optimally used on the volumetric MRI data, and the type of software most suitable for use in estimating the ICV measure.

Methods

Two groups of 22 subjects are considered, including adult controls (AC) and patients with Alzheimer Disease (AD). Reference measurements were calculated for each subject by manually tracing intracranial cavity by the means of visual inspection. The reliability of reference measurements were assured through intra- and inter- variation analyses. Three publicly well-known software packages (Freesurfer, FSL, and SPM) were examined in their ability to automatically estimate ICV across the groups.

Results

Analysis of the results supported the significant effect of estimation method, gender, cognitive condition of the subject and the interaction among method and cognitive condition factors in the measured ICV. Results on sub-sampling studies with a 95% confidence showed that in order to keep the accuracy of the interleaved slice sampling protocol above 99%, the sampling period cannot exceed 20 millimeters for AC and 15 millimeters for AD. Freesurfer showed promising estimates for both adult groups. However SPM showed more consistency in its ICV estimation over the different phases of the study.

Conclusions

This study emphasized the importance in selecting the appropriate protocol, the choice of the sampling period in the manual estimation of ICV and selection of suitable software for the automated estimation of ICV. The current study serves as an initial framework for establishing an appropriate protocol in both manual and automatic ICV estimations with different subject populations.

Increased functional connectivity within mesocortical networks in open people

Openness is a personality trait reflecting absorption in sensory experience, preference for novelty, and creativity, and is thus considered a driving force of human evolution. At the brain level, a relation between openness and dopaminergic circuits has been proposed, although evidence to support this hypothesis is lacking. Recent behavioral research has also found that people with mania, a psychopathological condition linked to dopaminergic dysfunctions, may display high levels of openness. However, whether openness is related to dopaminergic circuits has not been determined thus far. We addressed this issue via three functional magnetic resonance imaging (fMRI) experiments in n=46 healthy volunteers. In the first experiment participants lied at rest in the scanner while in the other two experiments they performed active tasks that included the presentation of pleasant odors and pictures of food. Individual differences in openness and other personality traits were assessed via the NEO-PI-R questionnaire (NEO-Personality Inventory-Revised), a widely employed measure of the five-factor model personality traits. Correlation between fMRI and personality data was analyzed via state-of-art methods assessing resting-state and task-related functional connectivity within specific brain networks. Openness was positively associated with the functional connectivity between the right substantia nigra/ventral tegmental area, the major source of dopaminergic inputs in the brain, and the ipsilateral dorsolateral prefrontal cortex (DLPFC), a key region in encoding, maintaining, and updating information that is relevant for adaptive behaviors. Of note, the same connectivity pattern was consistently found across all of the three fMRI experiments. Given the critical role of dopaminergic signal in gating information in DLPFC, the increased functional connectivity within mesocortical networks in open people may explain why these individuals display a wide "mental permeability" to salient stimuli and an increased absorption in sensory experience.

Brain structure links trait creativity to openness to experience

Creativity is crucial to the progression of human civilization and has led to important scientific discoveries. Especially, individuals are more likely to have scientific discoveries if they possess certain personality traits of creativity (trait creativity), including imagination, curiosity, challenge and risk-taking. This study used voxel-based morphometry to identify the brain regions underlying individual differences in trait creativity, as measured by the Williams creativity aptitude test, in a large sample (n = 246). We found that creative individuals had higher gray matter volume in the right posterior middle temporal gyrus (pMTG), which might be related to semantic processing during novelty seeking (e.g. novel association, conceptual integration and metaphor understanding). More importantly, although basic personality factors such as openness to experience, extroversion, conscientiousness and agreeableness (as measured by the NEO Personality Inventory) all contributed to trait creativity, only openness to experience mediated the association between the right pMTG volume and trait creativity. Taken together, our results suggest that the basic personality trait of openness might play an important role in shaping an individual's trait creativity.

A longitudinal study of structural brain network changes with normal aging

The aim of this study was to investigate age-related changes in the topological organization of structural brain networks by applying a longitudinal design over 6 years. Structural brain networks were derived from measurements of regional gray matter volume and were constructed in age-specific groups from baseline and follow-up scans. The structural brain networks showed economical small-world properties, providing high global and local efficiency for parallel information processing at low connection costs. In the analysis of the global network properties, the local and global efficiency of the baseline scan were significantly lower compared to the follow-up scan. Moreover, the annual rate of change in local and global efficiency showed a positive and negative quadratic correlation with the baseline age, respectively; both curvilinear correlations peaked at approximately the age of 50. In the analysis of the regional nodal properties, significant negative correlations between the annual rate of change in nodal strength and the baseline age were found in the brain regions primarily involved in the visual and motor/control systems, whereas significant positive quadratic correlations were found in the brain regions predominately associated with the default-mode, attention, and memory systems. The results of the longitudinal study are consistent with the findings of our previous cross-sectional study: the structural brain networks develop into a fast distribution from young to middle age (approximately 50 years old) and eventually became a fast localization in the old age. Our findings elucidate the network topology of structural brain networks and its longitudinal changes, thus enhancing the understanding of the underlying physiology of normal aging in the human brain.