Imagination as a facet of Openness/Intellect: A new scale differentiating experiential simulation and conceptual innovation

30 pagesPrevious research has investigated the nature of imagination as a construct related to multiple forms of higher-order cognition. Despite the emergence of various conceptualizations of imagination, few attempts have been made to explore the structure of imagination as a trait in the context of existing hierarchically-nested personality dimensions. We present a scale for measuring trait imagination that distinguishes between experiential simulation and conceptual innovation, aligned with the two major subfactors (aspects) of the Big Five dimension Openness/Intellect. Across two large samples, we provide evidence of a consistent factor structure distinguishing experiential, conceptual, and general descriptions of imagination, as well as validity as measures of facets of Openness and Intellect. Our findings provide a measure of major forms of imagination in line with mainstream models of the hierarchical structure of personality

Imagination as a facet of Openness/Intellect: A new scale differentiating experiential simulation and conceptual innovation

Previous research has investigated the nature of imagination as a construct related to multiple forms of higher-order cognition. Despite the emergence of various conceptualizations of imagination, few attempts have been made to explore the structure of imagination as a trait in the context of existing hierarchically-nested personality dimensions. We present a scale for measuring trait imagination that distinguishes between experiential simulation and conceptual innovation, aligned with the two major subfactors (aspects) of the Big Five dimension Openness/Intellect. Across two large samples, we provide evidence of a consistent factor structure distinguishing experiential, conceptual, and general descriptions of imagination, as well as validity as measures of facets of Openness and Intellect. Our findings provide a measure of major forms of imagination in line with mainstream models of the hierarchical structure of personality

Extraversion but not Depression Predicts Implicit Reward Sensitivity: Revisiting the Measurement of Anhedonic Phenotypes

Recently, increasing efforts have been made to define and measure dimensional phenotypes associated with psychiatric disorders. One example is an implicit reward learning task developed by Pizzagalli et al. (2005) to assess anhedonia, by measuring participants’ responses to a differential reinforcement schedule. This task has been used in many studies, which have connected blunted reward response in the task to depressive symptoms, across clinical groups and in the general population. The current study attempted to replicate these findings in a large community sample and also investigated possible associations with Extraversion, a personality trait linked theoretically and empirically to reward sensitivity. Participants (N = 299) completed the reward-learning task, as well as the Beck Depression Inventory, Personality Inventory for the DSM-5, Big Five Inventory, and Big Five Aspect Scales. Our direct replication attempts used bivariate analyses of observed variables and ANOVA models. Follow-up and extension analyses used structural equation models to assess relations among latent reward sensitivity, depression, Extraversion, and Neuroticism. No significant associations were found between reward sensitivity (i.e., response bias) and depression, thus failing to replicate previous findings. Response bias and change in response bias showed significant positive associations with Extraversion, but not with Neuroticism. Findings suggest reward sensitivity as measured by this implicit reward learning task may be related primarily to Extraversion and its pathological manifestations, rather than to depression per se, consistent with existing models that conceptualize depressive symptoms as combining features of Neuroticism and low Extraversion

Activation of the Default Network During a Theory of Mind Task Predicts Individual Differences in Agreeableness and Social Cognitive Ability

Background: Social cognitive processes such as emotion perception and empathy allow humans to navigate complex social landscapes and are associated with specific neural systems. In particular, theory of mind (ToM), which refers to our ability to decipher the mental states of others, is related to the dorsal medial prefrontal cortex and temporoparietal junction, which include portions of the default network. Both social cognition and the default network have been linked to the personality trait Agreeableness. We hypothesized that default network activity during a ToM task would positively predict social cognitive abilities and Agreeableness. Method: In a 3T fMRI scanner, participants (N = 1050) completed a ToM task in which they observed triangles displaying random or social (i.e., human-like) movement. Participants also completed self-report measures of Agreeableness and tests of intelligence and social cognitive ability. In each participant, average blood oxygen level dependent responses were calculated for default network regions associated with social cognition, and structural equation modeling was used to test associations of personality and task performance with activation in those brain regions. Results: Default network activation in the dorsal medial subsystem was greater for social vs. random animations. Default network activation in response to social animations predicted better performance on social cognition tasks and, to a lesser degree, higher Agreeableness. Conclusions: Neural response to social stimuli in the default network may be associated with effective social processing and could have downstream effects on social interactions. We discuss theoretical and methodological implications of this work for social and personality neuroscience

Conscientiousness associated with efficiency of the salience/ventral attention network: Replication in three samples using individualized parcellation

Previous research in the field of personality neuroscience has identified associations of conscientiousness and related constructs like impulsivity and self-control with structural and functional properties of particular regions in the prefrontal cortex (PFC) and insula. Network-based conceptions of brain function suggest that these regions probably belong to a single large-scale network, labeled the salience/ventral attention network (SVAN). The current study tested associations between conscientiousness and resting-state functional connectivity in this network using two community samples (N = 244 and 239) and data from the Human Connectome Project (N = 1000). Individualized parcellation was used to improve the accuracy of functional localization and to facilitate replication. Functional connectivity was measured using an index of network efficiency, a graph theoretical measure quantifying the capacity for parallel information transfer within a network. Efficiency of a set of parcels in the SVAN was significantly associated with conscientiousness in all samples. Findings are consistent with a theory of conscientiousness as a function of variation in neural networks underlying effective prioritization of goals

Conscientiousness associated with efficiency of the salience/ventral attention network: Replication in three samples using individualized parcellation

Conscientiousness, and related constructs impulsivity and self-control, have been related to structural and functional properties of regions in the prefrontal cortex (PFC) and anterior insula. Network-based conceptions of brain function suggest that these regions belong to a single large-scale network, labeled the salience/ventral attention network (SVAN). The current study tested associations between conscientiousness and resting-state functional connectivity in this network using two community samples (N's = 244 and 239) and data from the Human Connectome Project (N = 1000). Individualized parcellation was used to improve functional localization accuracy and facilitate replication. Functional connectivity was measured using an index of network efficiency, a graph theoretical measure quantifying the capacity for parallel information transfer within a network. Efficiency of a set of parcels in the SVAN was significantly associated with conscientiousness in all samples. Findings are consistent with a theory of conscientiousness as a function of variation in neural networks underlying effective prioritization of goals

Reproducible between-person brain-behavior associations do not always require thousands of individuals

Marek et al. analyzed three very large magnetic resonance imaging (MRI) datasets and concluded that thousands of participants are necessary to ensure replicable results in “brain-wide associations studies,” which they defined as “studies of the associations between common inter-individual variability in human brain structure/function and cognition or psychiatric symptomatology.” This conclusion overgeneralizes the implications of their findings and is likely to have an unwarranted chilling effect on neuroimaging research focused on individual differences, preventing good research with samples in the hundreds from being funded and conducted. To fend off these negative consequences, we explain why their conclusion is not fully justified, discuss methods that can yield larger effects, and suggest practical guidelines for sample size, recognizing the potential utility of samples in the hundreds