Final Synthesis

Personality Neuroscience: A Synthesis of Extraversion and Neuroticism 

Broad personality traits have been described as stable patterns of thinking, feeling and behaving that can differ between individuals. Although personality is broadly measured through behavioural studies, researchers have been using biological processes to examine what mechanisms contribute to the development of personality traits. This Final Synthesis paper will cover Extraversion and Neuroticism. The characterization of Extraversion can be condensed to reward-seeking, approach motivation, positive emotions whereas Neuroticism can be considered emotional instability, sensitivity to stress and vulnerability to anxiety or negative emotions. This synthesis examines how different research methods converge to explain the neural mechanisms associated with Extraversion and Neuroticism.

Extraversion p 1

Wacker et al. (2012) examined whether variation in the COMT Val158Met gene was associated with intelligence and extraversion. The COMT gene helps regulate how quickly dopamine is broken down in the prefrontal cortex, a brain region involved in planning, decision-making, and goal-directed behaviour. The researchers recruited 201 healthy young men, collected DNA samples to determine each participant's genotype, and administered standardized intelligence tests alongside 17 personality scales.

Instead of treating extraversion as a single personality trait, the researchers used factor analysis to divide it into three components: agency, affiliation, and impulsive sensation seeking. They then statistically controlled for overlap between these components so that each could be examined independently. This approach revealed an important finding. There was no significant relationship between overall extraversion and COMT genotype. However, when the individual components were examined separately, participants with the Val/Val genotype scored significantly higher on agency than Val/Met carriers, with a similar trend compared with Met/Met carriers. No significant differences were found for affiliation or impulsive sensation seeking.

These findings suggest that dopamine-related genetic variation is linked specifically to the goal-directed and achievement-oriented aspects of extraversion rather than sociability itself. Individuals with greater dopamine regulation through the COMT gene may be more motivated to pursue goals, show leadership, and display confidence, rather than simply enjoying social interactions.A major strength of this study was its approach to measuring personality. By separating extraversion into smaller dimensions, the researchers identified genetic associations that would have been missed if only overall extraversion had been analysed. This demonstrates that broad personality traits can hide important biological differences. However, the study also has important limitations. Because it was correlational, it cannot show that COMT directly causes differences in agency. In addition, although COMT influences dopamine metabolism, it also indirectly affects serotonin and norepinephrine, meaning the observed relationship cannot be attributed solely to dopamine. There is also striatal regions of the brain that have other pathways of dopamine regulation (dopamine transporter) and there are numerous possibilities that could be influencing the dopaminergic pathway, making it unlikely that the comt gene variation alone would explain the broad individual differences in extraversion.

Extraversion p 2

Wacker et al. (2013) addressed this limitation by examining dopamine more directly using a pharmacological approach. Participants were randomly assigned in a double-blind experiment to receive either 200 mg of sulpiride, a dopamine D2 receptor blocker, or a placebo. Brain activity was then measured using frontal EEG alpha asymmetry, which compares activity between the left and right frontal cortex. Greater left frontal activity has consistently been associated with approach motivation and reward seeking, which are core features of extraversion as described earlier. Participants also completed the Behavioural Approach System (BAS) questionnaire, which measures an individual's tendency to pursue rewarding experiences.

The results provided stronger evidence that dopamine plays a causal role in approach motivation. In the placebo group, individuals with higher BAS scores showed greater left frontal activity, indicating stronger approach-related brain activation. However, this relationship completely reversed after dopamine D2 receptors were blocked with sulpiride. This suggests that dopamine directly influences the neural systems involved in reward motivation.

Interestingly, this effect was only observed when participants interacted with female experimenters who were rated as more attractive than dominant. This finding suggests that dopamine-related brain activity is influenced not only by biology but also by the surrounding environment. Reward-related neural processes appear to become most active in situations that are personally motivating or rewarding.

One of the greatest strengths of this study is its experimental design. Unlike correlational genetic research, pharmacological manipulation allows researchers to make stronger conclusions about causation because dopamine activity is directly altered. However, the findings should still be interpreted cautiously because the sample consisted entirely of healthy young men, limiting the ability to generalize the results to women or older adults.

Extraversion p 3

Smillie et al. (2019) addressed several remaining limitations of the previous studies by examining how extraverts respond during an actual reward-learning task. Rather than inferring dopamine function from genetics or experimentally manipulating dopamine receptors, the researchers measured participants' neural responses to unexpected rewards. They also assessed extraversion using three different personality questionnaires, improving confidence that the findings reflected the broader trait rather than one specific measure.

Participants completed a passive associative learning task while EEG recorded a brain response known as Reward Positivity (RewP). Reward Positivity reflects a reward prediction error, or the difference between an expected outcome and the outcome that actually occurs. When rewards are unexpected, the brain generates a larger RewP because it must update its expectations. Using this task allowed the researchers to examine reward sensitivity directly, a core characteristic of extraversion.

The study first confirmed that the task successfully produced reward prediction errors, with participants responding differently to expected and unexpected outcomes. More importantly, individuals with higher levels of extraversion showed significantly larger Reward Positivity responses than those with lower levels of extraversion. Bayesian analyses supported this relationship, and regression analyses demonstrated that extraversion was the only Big Five personality trait that uniquely predicted Reward Positivity.

These findings suggest that extraverts are more sensitive to rewarding experiences and may learn more effectively from unexpected positive outcomes. Rather than simply enjoying rewards more, extraverts appear to show a stronger neural response when positive events occur unexpectedly. This finding is consistent with theories proposing that dopamine plays an important role in reward learning and approach motivation.

A major strength of this study is that it replicated previous findings using a larger sample while measuring extraversion with three different personality questionnaires. This increases confidence that the relationship between extraversion and Reward processing is reliable rather than depending on one specific measure of personality. However, EEG has limited spatial resolution. Although it measures brain activity with excellent timing, it cannot precisely identify which brain structures generate the observed electrical signals.

Extraversion p 4

Overall, Extraversion is a complex personality trait, and the evidence suggests that dopamine contributes specifically to its reward-processing and approach-motivation components, rather than fully explaining the trait as a whole. Rather than being explained by one neurotransmitter or one biological pathway, extraversion appears to reflect multiple underlying processes. Dopamine plays a key role in reward sensitivity and approach motivation, but it is unlikely to account for all aspects of extraverted behaviour. Instead, this research represents an important stepping stone toward understanding the biological mechanisms that contribute to personality, while highlighting the need for future studies

Neuroticism p 1

Unlike extraversion, which is closely linked to dopamine and reward processing, neuroticism appears to be associated with how different brain regions communicate during emotional processing and regulation. Rather than reflecting overactivity in a single brain region, neuroticism is better understood as differences in the networks responsible for processing emotional information, regulating negative emotions, and directing attention. The three studies reviewed here examine these networks using different fMRI approaches. Kim et al. (2025) investigated emotional conflict during a cognitive task, Creamers et al. (2010) examined responses to emotional facial expressions, and Hsu et al. (2018) explored resting-state functional connectivity. Together, these studies suggest that neuroticism reflects widespread differences in communication across the brain rather than abnormalities within one isolated structure.

Neuroticism p 2

Kim et al. (2025) investigated how neuroticism influences communication between brain regions during emotional conflict. The researchers first screened more than 3,000 young adults before selecting participants with low, medium, and high neuroticism scores. The final sample consisted of 65 participants who completed a modified word-face Stroop task while undergoing functional magnetic resonance imaging (fMRI).

During the task, participants identified the emotional meaning of a word while ignoring the emotional expression displayed on a face behind it. Some trials were emotionally congruent, whereas others were incongruent, forcing participants to ignore distracting emotional information. Instead of examining which brain regions became more active, the researchers focused on functional connectivity, or how different brain regions communicated with one another while completing the task. They specifically examined communication between the anterior midcingulate cortex (aMCC), which monitors conflict, the dorsolateral prefrontal cortex (dlPFC), which supports cognitive control, and the amygdala, which processes emotionally important information.

Behaviourally, participants responded more slowly during emotionally incongruent trials, confirming that the task successfully created emotional conflict. However, neuroticism was not associated with poorer task performance, suggesting that participants with higher neuroticism were just as accurate as those with lower neuroticism. The differences instead appeared in the brain imaging data.

Participants with higher neuroticism showed weaker functional connectivity between the aMCC and both the left dlPFC and the left amygdala. In other words, the brain regions responsible for cognitive control and emotional processing communicated less effectively when participants had to manage emotional conflict. These findings suggest that highly neurotic individuals may have greater difficulty coordinating emotional and regulatory brain systems, even when their behavioural performance appears normal.

One of the major strengths of this study is that it examined communication between brain regions rather than focusing only on which regions became active. This provides a more complete understanding of how emotional regulation occurs across large-scale brain networks. However, because the study was correlational, it cannot determine whether weaker connectivity causes higher neuroticism or develops as a consequence of it.

Neuroticism p 3

Creamers et al. (2010) built on Kim et al. (2025) by examining functional connectivity during a different type of emotional task. Participants completed an emotional face gender-decision task while undergoing fMRI. Rather than identifying emotions, participants simply judged whether each face was male or female while viewing angry, fearful, sad, and neutral facial expressions. This allowed emotional processing to occur automatically without directing participants' attention toward the emotions themselves.

The researchers focused on three brain regions. The amygdala detects emotionally significant information, the anterior cingulate cortex (ACC) contributes to emotion regulation, and the dorsomedial prefrontal cortex (dmPFC) is involved in self-referential thinking, or processing information in relation to oneself.

The results showed that individuals with higher neuroticism displayed greater activity in the dmPFC when viewing fearful faces. This suggests that highly neurotic individuals may process threatening social information in a more self-focused manner. The connectivity analyses provided even stronger evidence. Higher neuroticism was associated with weaker connectivity between the left amygdala and the ACC, suggesting reduced communication between emotional processing and emotion regulation systems. At the same time, participants with higher neuroticism showed stronger connectivity between the right amygdala and the dmPFC, indicating that emotional information may become more personally meaningful or self-relevant.

Together, these findings indicate that neuroticism is associated with both reduced communication between brain regions involved in emotion regulation and increased processing of emotionally relevant information.

A major strength of this study is that it examined both brain activation and functional connectivity. Looking at communication between brain regions provided a more complete picture than studying activation alone. However, the task required participants to view emotional facial expressions in a laboratory setting, which may not fully reflect the complexity of emotional experiences encountered in everyday life. As a result, the ecological validity of the findings is somewhat limited.

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Whereas the first two studies examined brain activity during emotional tasks, Hsu et al. (2018) investigated whether neuroticism could be predicted from resting-state functional connectivity. Instead of completing a task, participants simply rested quietly while undergoing fMRI. This allowed researchers to measure spontaneous communication between brain regions without the influence of specific emotional or cognitive demands.

The researchers used Connectome-Based Predictive Modelling (CPM), a machine-learning approach that examines patterns of communication across the entire brain. Rather than focusing on one or two regions, CPM determines whether large-scale connectivity patterns can predict individual differences in personality.

The results showed that resting-state connectivity significantly predicted neuroticism, although the relationship was modest. Importantly, prediction depended on communication across multiple large-scale brain networks, including the cerebellum, motor network, and several distributed functional networks, rather than activity within a single brain region. These findings suggest that neuroticism reflects stable patterns of communication throughout the brain, even when individuals are not actively processing emotional information.

One of the greatest strengths of this study is its use of machine learning and cross-validation. These methods improve confidence that the findings are reliable and not simply due to chance. In addition, studying resting-state connectivity demonstrates that personality differences can be detected even when participants are not performing a specific task. However, resting-state fMRI cannot identify the exact psychological processes responsible for these connectivity patterns. Although it reveals which brain regions communicate, it cannot explain what participants are thinking or feeling during the scan. Together, these findings suggest that neuroticism is not linked to one specific brain region, but rather to differences in how emotion-related brain networks communicate. Across different experimental tasks and even during rest, individuals with higher neuroticism consistently show altered patterns of connectivity between regions involved in emotion processing, cognitive control, and self-referential thinking. This suggests that neuroticism reflects widespread differences in brain network organization rather than dysfunction in a single area.