Personality traits predict response to novel and familiar stimuli in the hippocampal region

Personality Traits Induce Different Brain Patterns When Processing Social and Valence Information

This paper shows the brain correlates of Cloninger’s personality model during the presentation of social scenarios under positive or negative valence situations. Social scenarios were constructed when participants played the Dictator game with two confederates that had two opposites roles as the cooperator (Coop) and non-cooperator (NoCoop). Later the same day during a fMRI scanning session, participants read negative (Neg) and positive (Pos) situations that happened to confederates in the past. Participants were asked to think “how do you think those people felt during that situation?” A dissimilarity matrix between stimuli were obtained from fMRI results. Results shown that Harm Avoidance trait people make use of right middle frontal gyrus and left superior frontal gyrus to discriminate between Coop and NoCoop. Cooperation as a trait makes use of the right superior temporal gyrus and the right precuneus to discriminate between Coop and NoCoop in positive social scenarios. Finally, Self-directedness trait people make use of the right inferior parietal lobe to discriminate between Coop and NoCoop in negative social scenarios and the right precuneus to discriminate between Coop and Strangers. An intuitive link between discrimination findings and behavioral patterns of those personality traits is proposed.

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.

Uncovering the complex genetics of human temperament

Experimental studies of learning suggest that human temperament may depend on the molecular mechanisms for associative conditioning, which are highly conserved in animals. The main genetic pathways for associative conditioning are known in experimental animals, but have not been identified in prior genome-wide association studies (GWAS) of human temperament. We used a data-driven machine learning method for GWAS to uncover the complex genotypic-phenotypic networks and environmental interactions related to human temperament. In a discovery sample of 2149 healthy Finns, we identified sets of single-nucleotide polymorphisms (SNPs) that cluster within particular individuals (i.e., SNP sets) regardless of phenotype. Second, we identified 3 clusters of people with distinct temperament profiles measured by the Temperament and Character Inventory regardless of genotype. Third, we found 51 SNP sets that identified 736 gene loci and were significantly associated with temperament. The identified genes were enriched in pathways activated by associative conditioning in animals, including the ERK, PI3K, and PKC pathways. 74% of the identified genes were unique to a specific temperament profile. Environmental influences measured in childhood and adulthood had small but significant effects. We confirmed the replicability of the 51 Finnish SNP sets in healthy Korean (90%) and German samples (89%), as well as their associations with temperament. The identified SNPs explained nearly all the heritability expected in each sample (37-53%) despite variable cultures and environments. We conclude that human temperament is strongly influenced by more than 700 genes that modulate associative conditioning by molecular processes for synaptic plasticity and long-term memory.

The complex genetics and biology of human temperament: a review of traditional concepts in relation to new molecular findings

Recent genome-wide association studies (GWAS) have shown that temperament is strongly influenced by more than 700 genes that modulate associative conditioning by molecular processes for synaptic plasticity and long-term learning and memory. The results were replicated in three independent samples despite variable cultures and environments. The identified genes were enriched in pathways activated by behavioral conditioning in animals, including the two major molecular pathways for response to extracellular stimuli, the Ras-MEK-ERK and the PI3K-AKT-mTOR cascades. These pathways are activated by a wide variety of physiological and psychosocial stimuli that vary in positive and negative valence and in consequences for health and survival. Changes in these pathways are orchestrated to maintain cellular homeostasis despite changing conditions by modulating temperament and its circadian and seasonal rhythms. In this review we first consider traditional concepts of temperament in relation to the new genetic findings by examining the partial overlap of alternative measures of temperament. Then we propose a definition of temperament as the disposition of a person to learn how to behave, react emotionally, and form attachments automatically by associative conditioning. This definition provides necessary and sufficient criteria to distinguish temperament from other aspects of personality that become integrated with it across the life span. We describe the effects of specific stimuli on the molecular processes underlying temperament from functional, developmental, and evolutionary perspectives. Our new knowledge can improve communication among investigators, increase the power and efficacy of clinical trials, and improve the effectiveness of treatment of personality and its disorders.

Connectome-based individualized prediction of temperament trait scores

Temperament consists of multi-dimensional traits that affect various domains of human life. Evidence has shown functional connectome-based predictive models are powerful predictors of cognitive abilities. Putatively, individuals' innate temperament traits may be predictable by unique patterns of brain functional connectivity (FC) as well. However, quantitative prediction for multiple temperament traits at the individual level has not yet been studied. Therefore, we were motivated to realize the individualized prediction of four temperament traits (novelty seeking [NS], harm avoidance [HA], reward dependence [RD] and persistence [PS]) using whole-brain FC. Specifically, a multivariate prediction framework integrating feature selection and sparse regression was applied to resting-state fMRI data from 360 college students, resulting in 4 connectome-based predictive models that enabled prediction of temperament scores for unseen subjects in cross-validation. More importantly, predictive models for HA and NS could be successfully generalized to two relevant personality traits for unseen individuals, i.e., neuroticism and extraversion, in an independent dataset. In four temperament trait predictions, brain connectivities that show top contributing power commonly concentrated on the hippocampus, prefrontal cortex, basal ganglia, amygdala, and cingulate gyrus. Finally, across independent datasets and multiple traits, we show person's temperament traits can be reliably predicted using functional connectivity strength within frontal-subcortical circuits, indicating that human social and behavioral performance can be characterized by specific brain connectivity profile.

Novelty seeking is related to individual risk preference and brain activation associated with risk prediction during decision making

Novelty seeking (NS) is a personality trait reflecting excitement in response to novel stimuli. High NS is usually a predictor of risky behaviour such as drug abuse. However, the relationships between NS and risk-related cognitive processes, including individual risk preference and the brain activation associated with risk prediction, remain elusive. In this fMRI study, participants completed the Tridimensional Personality Questionnaire to measure NS and performed a probabilistic decision making task. Using a mathematical model, we estimated individual risk preference. Brain regions associated with risk prediction were determined via fMRI. The NS score showed a positive correlation with risk preference and a negative correlation with the activation elicited by risk prediction in the right posterior insula (r-PI), left anterior insula (l-AI), right striatum (r-striatum) and supplementary motor area (SMA). Within these brain regions, only the activation associated with risk prediction in the r-PI showed a correlation with NS after controlling for the effect of risk preference. Resting-state functional connectivity between the r-PI and r-striatum/l-AI was negatively correlated with NS. Our results suggest that high NS may be associated with less aversion to risk and that the r-PI plays an important role in relating risk prediction to NS.

Behavioral endophenotypes of drug addiction: Etiological insights from neuroimaging studies

This article reviews recent advances in the elucidation of neurobehavioral endophenotypes associated with drug addiction made possible by the translational neuroimaging techniques magnetic resonance imaging (MRI) and positron emission tomography (PET). Increasingly, these non-invasive imaging approaches have been the catalyst for advancing our understanding of the etiology of drug addiction as a brain disorder involving complex interactions between pre-disposing behavioral traits, environmental influences and neural perturbations arising from the chronic abuse of licit and illicit drugs. In this article we discuss the causal role of trait markers associated with impulsivity and novelty-/sensation-seeking in speeding the development of compulsive drug administration and in facilitating relapse. We also discuss the striking convergence of imaging findings from these behavioural traits and addiction in rats, monkeys and humans with a focus on biomarkers of dopamine neurotransmission, and highlight areas where further research is needed to disambiguate underlying causal mechanisms. This article is part of a Special Issue entitled 'NIDA 40th Anniversary Issue'.

Neural correlates of personality: an integrative review

This review examines the neural correlates of Gray's model (Gray and McNaughton, 2000; McNaughton and Corr, 2004), supplemented by a fourth dimension: constraint (Carver, 2005). The purpose of this review is to summarize findings from fMRI studies that tap on neural correlates of personality aspects in healthy subjects, in order to provide insight into the neural activity underlying human temperament. BAS-related personality traits were consistently reported to correlate positively to activity of the ventral and dorsal striatum and ventral PFC in response to positive stimuli. FFFS and BIS-related personality traits are positively correlated to activity in the amygdala in response to negative stimuli. There is limited evidence that constraint is associated with PFC and ACC activity. In conclusion, functional MRI research sheds some light on the specific neural networks underlying personality. It is clear that more sophisticated task paradigms are required, as well as personality questionnaires that effectively differentiate between BAS, FFFS, BIS, and constraint. Further research is proposed to potentially reveal new insight in the neural subsystems governing basic human behavior.

Specific frequency bands of amplitude low-frequency oscillation encodes personality

The biological model of extraversion and neuroticism identified by Eysenck has stimulated increasing interest in uncovering neurobiological substrate of the two fundamental dimensions. Here we aim to explore brain disturbances underlying extraversion and neuroticism in 87 healthy individuals using fractional amplitude of low-frequency fluctuations (LFF) on resting-state functional magnetic resonance imaging. Two different frequency bands, Slow-5 (0.01-0.027 Hz) exhibiting higher power and involving larger brain regions, and Slow-4 (0.027-0.073 Hz) exhibiting less power and emerging locally, were analyzed. Our results showed a positive correlation between LFF amplitude at Slow-5 and extraversion in medial prefrontal cortex and precuneus, important portions of the default mode network, thus suggesting a link between default network activity and personality traits. LFF amplitude at Slow-5 was correlated positively with neuroticism in right posterior portion of the frontal lobe, further validating neuroticism with frontal lateralization. In addition, LFF amplitude at Slow-4 was negatively associated with extraversion and neuroticism in left hippocampus (HIP) and bilateral superior temporal cortex (STC) respectively, supporting the hypothesized (inverse) relationship between extraversion and resting arousal, also implying neural circuit underlying emotional process influencing on personality. Overall, these findings suggest the important relationships, between personality and LFF amplitude dynamic, depend on specific frequency bands.

Negative affectivity, self-referential processing and the cortical midline structures

The neural bases of the association between negative affectivity and self-focus remain unknown in healthy subjects. Building on the role of the cortical midline structures (CMS) in self-referential processing, we hypothesized that negative affectivity in healthy subjects would be associated with an increased activation of the CMS during self-referential processing. We presented positive and negative pictures to 45 healthy subjects during fMRI and asked them to judge whether the pictures were related to themselves or not (self condition), or whether the pictures were positive or negative (general condition). Negative affectivity was measured by the level of harm avoidance (HA) with the Temperament and Character Inventory. Self-referential processing activated the CMS, including the dorsal and ventral medial prefrontal cortex (MPFC) and the posterior cingulate cortex (PCC). A higher HA score was associated with a greater activation of the dorsal MPFC and PCC during self-referential processing, this greater activation being more pronounced for negative pictures in the dorsal MPFC. This increased activation of the CMS may embody the association between negative affectivity and self-focus in healthy subjects, as previously observed in major depression. Within the CMS, the dorsal MPFC may play a key role in negative affectivity, integrating an increased attention to negative stimuli with an increased attention to the self.