How personality psychology and cognitive neuroscience can enrich one another: Insights from information seeking to machine learning

Abstract

© 2021 Hayley Kristina JachPersonality psychology investigates individual differences in emotion, behaviour, cognition, and motivation, whereas cognitive neuroscience investigates the neurobiological bases of these phenomena. This substantial content overlap suggests that these areas are well placed to integrate knowledge. Accordingly, I present results from two empirical research programs that demonstrate how combining theories and methods from personality psychology and cognitive neuroscience can provide a new perspective on outstanding research questions and spur novel research programs. Part 1 (Studies 1-5) assessed how theory from personality psychology can address a current question in cognitive neuroscience: why people seek information that provides no extrinsic reward. One explanation is that uncertainty is aversive, and information reduces this uncertainty. This would suggest that the personality trait uncertainty intolerance would relate to information seeking. However, this conflicts with a theory from personality psychology whereby openness/intellect (describing tendencies toward imagination and intellect; thought to relate to greater tolerance for uncertainty) is grounded in increased information seeking. Because no explicit confirmatory study has assessed the putative negative relation between uncertainty intolerance and openness/intellect, Study 1 (N = 308) investigated—and confirmed—these relations. Next, Studies 2 (N = 151) and 3 (N = 301) assessed personality trait correlates of information seeking to gauge relative evidence for either conflicting theory. Openness/intellect did not predict information seeking; however, joyous exploration (a facet of curiosity positively related to openness/intellect) predicted information seeking across both studies, and uncertainty intolerance predicted information seeking in Study 3. These results informed a conceptual model featuring two motivations to seek information—either to explore (related to joyous exploration and openness/intellect) or to feel safe (related to uncertainty intolerance and neuroticism)—each differentially elicited depending on how the situation is perceived. To evaluate this model, Study 4 (N = 436) assessed personality and situation perception predictors of information seeking across four stimulus sets. Study 5 (N = 316) provided a partial replication and extension. Results provided consistent evidence for the exploration pathway, but more tentative evidence for the safety pathway. These findings suggest that an incorporation of person and situation factors can assist theory-development for information seeking. Part 2 provided a complementary approach to interdisciplinary dialogue by investigating how methods from cognitive neuroscience could be applied to explore possible neural bases of personality. Specifically, the machine learning technique multivariate pattern analysis was used to explore, then confirm, relations between personality and spectral power derived from electroencephalography. Study 6 (N = 174) found that agreeableness and neuroticism could be consistently decoded in particular frequencies across four testing conditions. Study 7 (N = 197) failed to replicate Study 6 in the full testing sample, but when subsequent analyses were stratified by country, agreeableness could be decoded in participants from Australia and neuroticism from participants from Germany. Caution is warranted for these latter findings given their unexpected nature and the smaller sample size of individual groups. The advantages of employing new methods are counterbalanced by a need to accept some measure of uncertainty in our inferences. However, open documentation of this complexity can spur new investigations to gain future insight into the neural bases of personality. Together, these studies emphasise the challenges, but also substantial benefits, from combining knowledge and methods from personality psychology and cognitive neuroscience to constrain existing theory, form links between research domains, and propose new avenues for research