Neuroimaging of Individual Differences: A Latent Variable Modeling Perspective

2018 ◽  
Author(s):  
Shelly Renee Cooper ◽  
Joshua James Jackson ◽  
Deanna Barch ◽  
Todd Samuel Braver
Keyword(s):  
Individual Differences ◽  
Individual Difference ◽  
Latent Variable ◽  
Structural Equation ◽  
Behavioral Measure ◽  
Equation Modeling ◽  
Latent Variable Modeling ◽  
Psychometric Theory ◽  
Human Connectome Project ◽  
Neuroimaging Data

Neuroimaging data is being increasingly utilized to address questions of individual difference. When examined with task-related fMRI (t-fMRI), individual differences are typically investigated via correlations between the BOLD activation signal at every voxel and a particular behavioral measure. This can be problematic because: 1) correlational designs require evaluation of t-fMRI psychometric properties, yet these are not well understood; and 2) bivariate correlations are severely limited in modeling the complexities of brain-behavior relationships. Analytic tools from psychometric theory such as latent variable modeling (e.g., structural equation modeling) can help simultaneously address both concerns. This review explores the advantages gained from integrating psychometric theory and methods with cognitive neuroscience for the assessment and interpretation of individual differences. The first section provides background on classic and modern psychometric theories and analytics. The second section details current approaches to t-fMRI individual difference analyses and their psychometric limitations. The last section uses data from the Human Connectome Project to provide illustrative examples of how t-fMRI individual differences research can benefit by utilizing latent variable models.

scholarly journals Individual Differences in Memory and Attention Processes in Prospective Remembering

2021 ◽  
Author(s):  
Hunter Ball ◽  
Elizabeth A. Wiemers ◽  
Gene Brewer
Keyword(s):  
Working Memory ◽  
Individual Differences ◽  
Prospective Memory ◽  
Latent Variable ◽  
Structural Equation ◽  
Large Scale ◽  
Equation Modeling ◽  
Attention And Memory ◽  
Retrospective Memory ◽  
Prospective Remembering

Successful prospective memory (PM) involves not only detecting that an environmental cue requires action (i.e., prospective component), but also retrieval of what is supposed to be done at the appropriate moment (i.e., retrospective component). The current study examined the role of attention and memory during PM tasks that placed distinct demands on detection and retrieval processes. Using a large-scale individual differences design, participants completed three PM tasks that placed high demands on detection (but low demands on retrieval) and three tasks that placed high demands on retrieval (but low demands on detection). Additionally, participants completed three attention control, retrospective memory, and working memory tasks. Latent variable structural equation modeling showed that the prospective and retrospective components of PM were jointly influenced by multiple cognitive abilities. Critically, attention and retrospective memory fully mediated the relation between working memory and prospective memory. Furthermore, only attention uniquely predicted PM detection, whereas only retrospective memory uniquely predicted PM retrieval. These findings highlight the value of independently assessing different PM components and suggest that both attention and memory abilities must be considered to fully understand the dynamic processes underlying prospective remembering.

Individual difference predictors of perceived organizational change fairness

2016 ◽  
Vol 31 (2) ◽  
pp. 420-433 ◽  
Author(s):  
Xiaohong Xu ◽  
Stephanie C. Payne ◽  
Margaret T. Horner ◽  
Allison L. Alexander
Keyword(s):  
Organizational Change ◽  
Individual Differences ◽  
Individual Difference ◽  
Self Efficacy ◽  
Structural Equation ◽  
Resistance To Change ◽  
Equation Modeling ◽  
Perceived Fairness ◽  
Content Type ◽  
The Impact

Purpose – The purpose of this paper is to examine how individual differences influence employees’ attitude toward organizational change. Specifically, the present study examined how and why proactive personality, dispositional resistance to change, and change self-efficacy influence employees’ perceived fairness about the organizational change. Design/methodology/approach – Structural equation modeling was utilized to analyze the survey data obtained from a sample of 140 food service employees after some organizational changes in leadership, menu offerings, and facilities. Findings – The results revealed support for two micromediational chains predicting change fairness: first, change self-efficacy leads to less uncertainty and second, dispositional resistance to change leads to less communication regarding change resulting in employees perceiving they have fewer opportunities to voice concerns about the changes. Research limitations/implications – The cross-sectional design prevents causal inferences and the generalizability of the present findings beyond similar samples experiencing similar changes is unknown. However, the predictions were based on theories that apply to all employees regardless of the changes or the employees’ occupations or workplace. Social implications – Employees with particular personality traits are more receptive to change, suggesting that organizations should consider the impact of individual differences when facing large-scale change. To ensure the success of organizational change, organizations should communicate with employees and encourage employee input before implementing change which in turn improves the chances that employees will have favorable reactions to the change. Originality/value – This is the first study to examine how and why individual difference variables influence employees’ perceptions about organizational change fairness.

scholarly journals Individual Differences in Memory and Attention Processes in Prospective Remembering

2021 ◽  
Author(s):  
Hunter Ball ◽  
Elizabeth A. Wiemers ◽  
Gene Arnold Brewer
Keyword(s):  
Working Memory ◽  
Individual Differences ◽  
Prospective Memory ◽  
Latent Variable ◽  
Structural Equation ◽  
Large Scale ◽  
Equation Modeling ◽  
Attention And Memory ◽  
Retrospective Memory ◽  
Prospective Remembering

Successful prospective memory (PM) involves not only detecting that an environmental cue requires action (i.e., prospective component), but also retrieval of what is supposed to be done at the appropriate moment (i.e., retrospective component). The current study examined the role of attention and memory during PM tasks that placed distinct demands on detection and retrieval processes. Using a large-scale individual differences design, participants completed three PM tasks that placed high demands on detection (but low demands on retrieval) and three tasks that placed high demands on retrieval (but low demands on detection). Additionally, participants completed three attention control, retrospective memory, and working memory tasks. Latent variable structural equation modeling showed that the prospective and retrospective components of PM were jointly influenced by multiple cognitive abilities. Critically, attention and retrospective memory fully mediated the relation between working memory and prospective memory. Furthermore, only attention uniquely predicted PM detection, whereas only retrospective memory uniquely predicted PM retrieval. These findings highlight the value of independently assessing different PM components and suggest that both attention and memory abilities must be considered to fully understand the dynamic processes underlying prospective remembering.

Psychology in Outerspace

2010 ◽  
Vol 15 (3) ◽  
pp. 220-228 ◽  
Author(s):  
Viren Swami ◽  
Tomas Chamorro-Premuzic ◽  
Manal Shafi
Keyword(s):  
Individual Difference ◽  
Sensation Seeking ◽  
Structural Equation ◽  
Political Orientation ◽  
Equation Modeling ◽  
Big Five Personality ◽  
Social Conformity ◽  
Extraterrestrial Life ◽  
Paranormal Beliefs ◽  
Future Work

Previous work has shown that is important to consider the disjunction between paranormal and nonparanormal beliefs about extraterrestrial life. The current study examined the association between both such beliefs and individual difference and demographic variables. A total of 555 British participants completed the Extraterrestrial Beliefs Scale, as well as measures of their Big Five personality scores, social conformity, sensation seeking, and demographics. Results showed no sex differences in ratings of paranormal and nonparanormal extraterrestrial beliefs, but participants rated nonparanormal beliefs more positively than paranormal beliefs. Results of structural equation modeling showed that individual difference factors (specifically, Openness, Conscientiousness, and social conformity) explained 21% of the variance in extraterrestrial beliefs, whereas demographic factors (specifically, education level, political orientation, and religiosity) explained 16% of the variance. Limitations and directions for future work are considered.

Toward a Neural Model of the Openness-Psychoticism Dimension: Functional Connectivity in the Default and Frontoparietal Control Networks

2019 ◽  
Author(s):  
Scott D. Blain ◽  
Rachael Grazioplene ◽  
Yizhou Ma ◽  
Colin G. DeYoung
Keyword(s):  
Functional Connectivity ◽  
Structural Equation ◽  
Psychotic Disorders ◽  
Neural Model ◽  
Equation Modeling ◽  
Control Networks ◽  
Psychosis Proneness ◽  
Human Connectome Project ◽  
Intrinsic Connectivity Networks ◽  
Personality Psychopathology

Psychosis proneness has been linked to heightened Openness to Experience and to cognitive deficits. Openness and psychotic disorders are associated with the default and frontoparietal networks, and the latter network is also robustly associated with intelligence. We tested the hypothesis that functional connectivity of the default and frontoparietal networks is a neural correlate of the openness-psychoticism dimension. Participants in the Human Connectome Project (N = 1003) completed measures of psychoticism, openness, and intelligence. Resting state functional magnetic resonance imaging was used to identify intrinsic connectivity networks. Structural equation modeling revealed relations among personality, intelligence, and network coherence. Psychoticism, openness, and especially their shared variance, were related positively to default network coherence and negatively to frontoparietal coherence. These associations remained after controlling for intelligence. Intelligence was positively related to frontoparietal coherence. Research suggests psychoticism and openness are linked in part through their association with connectivity in networks involving experiential simulation and cognitive control. We propose a model of psychosis risk that highlights roles of the default and frontoparietal networks. Findings echo research on functional connectivity in psychosis patients, suggesting shared mechanisms across the personality-psychopathology continuum.

The Affiliative Role of Empathy in Everyday Interpersonal Interactions

2019 ◽  
Author(s):  
Whitney R. Ringwald ◽  
Aidan G.C. Wright
Keyword(s):  
Individual Differences ◽  
Structural Equation ◽  
Community Sample ◽  
Empirical Support ◽  
Interpersonal Behavior ◽  
Equation Modeling ◽  
Experimental Conditions ◽  
Student Sample ◽  
Ecological Momentary

Empathy theoretically serves an affiliative interpersonal function by satisfying motives for intimacy and union with others. Accordingly, empathy is expected to vary depending on the situation. Inconsistent empirical support for empathy’s affiliative role may be due to methodology focused on individual differences in empathy or differences between controlled experimental conditions, which fail to capture its dynamic and interpersonal nature. To address these shortcomings, we used ecological momentary assessment to establish typical patterns of empathy across everyday interactions. Associations among empathy, affect, and interpersonal behavior of self and interaction partner were examined in a student sample (N=330), then replicated in a pre-registered community sample (N=279). Multi-level structural equation modeling was used to distinguish individual differences in empathy from interaction-level effects. Results show people are more empathetic during positively-valanced interactions with others perceived as warm and when expressing warmth. By confirming the typically affiliative role of empathy, existing research to the contrary can be best understood as exceptions to the norm.

scholarly journals Postpartum depression symptoms in survey-based research: a structural equation analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Che Wan Jasimah Bt Wan Mohamed Radzi ◽  
Hashem Salarzadeh Jenatabadi ◽  
Nadia Samsudin
Keyword(s):  
Postpartum Depression ◽  
Latent Variable ◽  
Structural Equation ◽  
Depression Scale ◽  
Public Health Problem ◽  
Equation Modeling ◽  
Depression Symptoms ◽  
Postpartum Women ◽  
Unhealthy Food ◽  
High Level

Abstract Background Since the last decade, postpartum depression (PPD) has been recognized as a significant public health problem, and several factors have been linked to PPD. Mothers at risk are rarely undetected and underdiagnosed. Our study aims to determine the factors leading to symptoms of depression using Structural Equation Modeling (SEM) analysis. In this research, we introduced a new framework for postpartum depression modeling for women. Methods We structured the model of this research to take into consideration the Malaysian culture in particular. A total of 387 postpartum women have completed the questionnaire. The symptoms of postpartum depression were examined using the Edinburgh Postnatal Depression Scale (EPDS), and they act as a dependent variable in this research model. Results Four hundred fifty mothers were invited to participate in this research. 86% of the total distributed questionnaire received feedback. The majority of 79.6% of respondents were having depression symptoms. The highest coefficients of factor loading analysis obtained in every latent variable indicator were income (β = 0.77), screen time (β = 0.83), chips (β = 0.85), and anxiety (β = 0.88). Lifestyle, unhealthy food, and BMI variables were directly affected by the dependent variable. Based on the output, respondents with a high level of depression symptoms tended to consume more unhealthy food and had a high level of body mass indexes (BMI). The highest significant impact on depression level among postpartum women was unhealthy food consumption. Based on our model, the findings indicated that 76% of the variances stemmed from a variety of factors: socio-demographics, lifestyle, healthy food, unhealthy food, and BMI. The strength of the exogenous and endogenous variables in this research framework is strong. Conclusion The prevalence of postpartum women with depression symptoms in this study is considerably high. It is, therefore, imperative that postpartum women seek medical help to prevent postpartum depressive symptoms from worsening.

scholarly journals Insights Into the Correspondence Between Land Use Pattern and Spatial Distribution of Rail Transit Services

2021 ◽  
Author(s):  
Zhongqi Wang ◽  
Qi Han ◽  
Bauke de Vries ◽  
Li Dai
Keyword(s):  
Land Use ◽  
Spatial Distribution ◽  
Operations Management ◽  
Latent Variable ◽  
Structural Equation ◽  
Equation Modeling ◽  
Rail Transit ◽  
Land Use Patterns ◽  
Transit Services ◽  
The Relationship

AbstractThe identification of the relationship between land use and transport lays the foundation for integrated land use and transport planning and management. This work aims to investigate how rail transit is linked to land use. The research on the relationship between land use and rail-based transport is dominated by the impacts of rail projects on land use, without an in-depth understanding of the reverse. However, it is important to note that issues of operation management rather than new constructions deserve greater attention for regions with established rail networks. Given that there is a correspondence between land use patterns and spatial distribution of heavy railway transit (HRT) services at such regions, the study area (i.e., the Netherlands) is partitioned by the Voronoi diagram of HRT stations and the causal relationship between land use and HRT services is examined by structural equation modeling (SEM). The case study of Helmond (a Dutch city) shows the potential of the SEM model for discussing the rail station selection problem in a multiple transit station region (MTSR). Furthermore, in this study, the node place model is adapted with the derivatives of the SEM model (i.e., the latent variable scores for rail service levels and land use characteristics), which are assigned as node and place indexes respectively, to analyze and differentiate the integration of land use and HRT services at the regional level. The answer to whether and how land use affects rail transit services from this study strengthens the scientific basis for rail transit operations management. The SEM model and the modified node place model are complementary to be used as analytical and decision-making tools for rail transit-oriented regional development.

Attributional Style as a Predictor of Hopelessness Depression

2006 ◽  
Vol 20 (4) ◽  
pp. 447-458 ◽  
Author(s):  
Edward D. Sturman ◽  
Myriam Mongrain ◽  
Paul M. Kohn
Keyword(s):  
Attributional Style ◽  
Latent Variable ◽  
Structural Equation ◽  
Depression Scale ◽  
Epidemiological Studies ◽  
Psychomotor Retardation ◽  
Equation Modeling ◽  
Depression Symptoms ◽  
Negative Events ◽  
Hopelessness Depression

Stable and global attributions for negative events were tested as predictors of hopelessness depression symptoms, obtained from a diagnostic interview for a past depressive episode in a sample of 102 graduate students. All participants were administered the Structured Clinical Interview for DSM–IV, Center for Epidemiological Studies Depression Scale, Personal Style Inventory, and a modified version of the Extended Attributional Style Questionnaire. A stable and global attributional style for negative events was significantly associated with a composite of hopelessness depression symptoms. A regression analysis revealed that attributional style significantly postdicted hopelessness depression symptoms when controlling for both sociotropy and autonomy. Structural equation modeling supported a model in which stable and global attributions predicted a latent variable, which we refer to as a motivational deficit, involving psychomotor retardation and fatigue as indicators. Therefore, this study obtained some support for the hopelessness model and highlights the vulnerability posed by attributional style ( Abramson, Metalsky, & Alloy, 1989 ).

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