Relational processing demands and the role of spatial context in the construction of episodic simulations

Reports on differences between remembering the past and imagining the future have led to the hypothesis that constructing future events is a more cognitively demanding process. However, factors that influence these increased demands, such as whether the event has been previously constructed and the types of details comprising the event, have remained relatively unexplored. Across two experiments, we examined how these factors influence the process of constructing event representations by having participants repeatedly construct events and measuring how construction times and a range of phenomenological ratings changed across time points. In Experiment 1, we contrasted the construction of past and future events and found that, relative to past events, the constructive demands associated with future events are particularly heightened when these events are imagined for the first time. Across repeated simulations, future events became increasingly similar to past events in terms of construction times and incorporated detail. In Experiment 2, participants imagined future events involving two memory details (person, location) and then reimagined the event either (a) exactly the same, (b) with a different person, or (c) in a different location. We predicted that if generating spatial information is particularly important for event construction, a change in location will have the greatest impact on constructive demands. Results showed that spatial context contributed to these heightened constructive demands more so than person details, consistent with theories highlighting the central role of spatial processing in episodic simulation. We discuss the findings from both studies in the light of relational processing demands and consider implications for current theoretical frameworks

A many-analysts approach to the relation between religiosity and well-being

The relation between religiosity and well-being is one of the most researched topics in the psychology of religion, yet the directionality and robustness of the effect remains debated. Here, we adopted a many-analysts approach to assess the robustness of this relation based on a new cross-cultural dataset (N=10,535 participants from 24 countries). We recruited 120 analysis teams to investigate (1) whether religious people self-report higher well-being, and (2) whether the relation between religiosity and self-reported well-being depends on perceived cultural norms of religion (i.e., whether it is considered normal and desirable to be religious in a given country). In a two-stage procedure, the teams first created an analysis plan and then executed their planned analysis on the data. For the first research question, all but 3 teams reported positive effect sizes with credible/confidence intervals excluding zero (median reported β=0.120). For the second research question, this was the case for 65% of the teams (median reported β=0.039). While most teams applied (multilevel) linear regression models, there was considerable variability in the choice of items used to construct the independent variables, the dependent variable, and the included covariates

A Many-analysts Approach to the Relation Between Religiosity and Well-being

The relation between religiosity and well-being is one of the most researched topics in the psychology of religion, yet the directionality and robustness of the effect remains debated. Here, we adopted a many-analysts approach to assess the robustness of this relation based on a new cross-cultural dataset (N = 10, 535 participants from 24 countries). We recruited 120 analysis teams to investigate (1) whether religious people self-report higher well-being, and (2) whether the relation between religiosity and self-reported well-being depends on perceived cultural norms of religion (i.e., whether it is considered normal and desirable to be religious in a given country). In a two-stage procedure, the teams first created an analysis plan and then executed their planned analysis on the data. For the first research question, all but 3 teams reported positive effect sizes with credible/confidence intervals excluding zero (median reported β = 0.120). For the second research question, this was the case for 65% of the teams (median reported β = 0.039). While most teams applied (multilevel) linear regression models, there was considerable variability in the choice of items used to construct the independent variables, the dependent variable, and the included covariates

Is space special? The contribution of spatial and non-spatial event components to the construction of episodic simulations

The overall aim of the work presented in this thesis was to provide an analysis of the constructive processes at play during episodic simulation, in terms of behavioural and phenomenological characteristics, as well as underlying neural representations. We focused on two theoretical accounts of episodic simulation: the constructive episodic simulation hypothesis (Schacter & Addis, 2007) and the scene construction theory (Hassabis & Maguire, 2007). These accounts make conflicting predictions about a range of behavioural and neural mechanisms, especially with regard to the importance ascribed to different episodic detail types (spatial vs non-spatial). Studies designed to directly compare these theoretical accounts had been sparse, despite having important implications for episodic memory and episodic simulation, as well as for hippocampal function more generally. Across two behavioural studies—examining event construction times, recall, and a range of phenomenological characteristics, including construction difficulty, and representation vividness—and one fMRI study—focusing on the representational content of the hippocampus during episodic simulation, we find converging evidence for a central role of spatial context in the construction of episodic simulation. While being broadly in line with the scene construction theory, we argue that the results are most consistent with a general relational processing account of episodic simulation. The work presented in this thesis provides novel insight into the behavioural and neural constructive processes involved in episodic simulation, and corroborates previously reported effects highlighting the central role of space. Consistent with general efforts to unify spatial and relational processing accounts, we discuss ways in which our results are coherent within an integrated framework

Grey Matter Volume Anomalies in Schizotypy: A Comparison of Partial Least Squares Correlation and Voxel-Based Morphometry

Full text is available to authenticated members of The University of Auckland only.Background: Schizophrenia is characterised by altered grey matter volume in several structures across the brain; however, the temporal emergence and progression of these alterations remains unknown. Schizotypy denotes a continuum of personality traits that, in their extreme, represent a liability for schizophrenia. Because of the dimensional relationship between schizotypy and schizophrenia, schizotypy enables researchers to examine how schizophrenia characteristics might arise and how they might be related to causative mechanisms of the disorder. To date, there has been little agreement on whether or not grey matter volume anomalies similar to those observed in schizophrenia already occur in individuals with high levels of schizotypy. Six studies so far have investigated brain structure in schizotypy, but results have been heterogeneous and only one brain structure has been implicated in more than one study thus far. This thesis aimed to resolve this debate. Methods: We used magnetic resonance imaging (MRI) to investigate changes in global brain volumes and local grey matter volumes in a sample of 49 healthy individuals between the ages of 18 and 38. Levels of positive, negative, disorganised, and impulsive schizotypal traits were assessed with the Oxford-Liverpool Inventory of Feelings and Experiences. Behavioural and MRI data were corrected for the effects of potentially confounding variables and analysed using partial least squares correlation (PLS) and voxel-based morphometry (VBM). The two analysis techniques were compared with regards to statistical sensitivity to regional differences. Results: We did not find any associations between whole brain volume, total intracranial volume, total grey matter volume, or total white matter volume and high levels of schizotypy. With regards to local changes, PLS identified a pattern of brain changes consisting of decreased grey matter volume, as well as increased grey matter volume that was associated with high levels of positive schizotypy. Decreased volume was found in frontal, temporal, parietal, and insular lobes; increased volume was found in putamen, cerebellum, and limbic-paralimbic regions. VBM detected no regions where volume was altered when a correction for multiple comparisons (FWE) was applied. An uncorrected VBM analysis at p < .001 identified a subset of the regions detected by PLS. No structures were uniquely identified by this VBM analysis. Conclusions: We confirmed and extended earlier findings on an association between schizotypy and alterations in grey matter volume. The identified structures in high levels of schizotypy are amongst the core grey matter changes that characterise first-episode and chronic schizophrenia. Smaller volumes in right medial frontal gyri, left superior temporal gyrus, and left insula appear to occur in schizotypy, as well as in first-episode and chronic schizophrenia. Volumes in left posterior cingulate cortex/precuneus and cerebellum appear to undergo transient changes during the pathogenesis of schizophrenia, with larger volumes in schizotypy and smaller volumes in schizophrenia. Volume changes in these areas might play a direct role in processes related to the development of schizophrenia, which raises the possibility of using changes in these structures as liability markers to aid prediction of the disorder. With regards to our methodological comparison, PLS appears to be more sensitive to regional alterations than VBM, and is therefore a valuable statistical alternative to VBM, especially in schizotypy research, where smaller effect sizes are expected than those observed in clinical conditions. Keywords: schizotypy; MRI; grey matter volume; partial least squares correlation; voxel-based morphometry

Dynamic Data Visualizations to Enhance Insight and Communication Across the Lifecycle of a Scientific Project

In scientific communication, figures are typically rendered as static displays. This often prevents active exploration of the underlying data, for example to gauge the influence of particular data points or of particular analytic choices. Yet modern data visualization tools, from animated plots to interactive notebooks and reactive web applications, allow psychologists to share and present their findings in dynamic and transparent ways. In this tutorial, we present a number of recent developments to build interactivity and animations into scientific communication and publications, using examples and illustrations in the R language (basic knowledge of R is assumed). In particular, we discuss when and how to build dynamic figures, with step-by-step reproducible code that can easily be extended to the reader’s own projects. We illustrate how interactivity and animations can facilitate insight and communication across a project lifecycle—from initial exchanges and discussions within a team to peer-review and final publication—and provide a number of recommendations to use dynamic visualizations effectively. We close with a reflection on how the scientific publishing model is currently evolving, and consider the challenges and opportunities this shift might bring along for data visualization

Psychological Constructs as Local Optima

Psychological constructs are necessary abstractions to operationalize otherwise intractable entities. However, the way constructs are defined and refined over time introduces notable bias into models of behavior, which prevents effective knowledge building within and across subfields

Leveraging Containers for Reproducible Psychological Research

Containers have become increasingly popular in computing and software engineering, and are gaining traction in scientific research. They allow packaging up all code and dependencies to ensure that analyses run reliably across a range of operating systems and software versions. Despite being a crucial component for reproducible science, containerization has yet to become mainstream in psychology. In this tutorial, we describe the logic behind containers, what they are, and the practical problems they can solve. We walk the reader through the implementation of containerization within a research workflow, with examples using Docker and R. Specifically, we describe how to use existing containers, build personalized containers, and share containers alongside publications. We provide a worked example that includes all steps required to set up a container for a research project and can easily be adapted and extended. We conclude with a discussion of the possibilities afforded by the large-scale adoption of containerization, especially in the context of cumulative, open science, toward a more efficient and inclusive research ecosystem.</p

Assessing Change in Intervention Research: The Benefits of Composite Outcomes

Intervention research is often time- and resource-intensive, with numerous participants involved over extended periods of time. In order to maximize the value of intervention studies, multiple outcome measures are often included, either to ensure a diverse set of outcomes is being assessed or to refine assessments of specific outcomes. In the paper, we advocate for combining assessments, rather than relying on individual measures assessed separately, to better evaluate the effectiveness of interventions. Specifically, we argue that by pooling information from individual measures into a single outcome, composite scores can provide finer estimates of the underlying theoretical construct of interest, while retaining important properties more sophisticated methods often forego, such as transparency and interpretability. Shiny app: https://kwiebels.shinyapps.io/Multiple_outcomes_in_interventions