Development of Human Lateral Prefrontal Sulcal Morphology and Its Relation to Reasoning Performance.

Previous findings show that the morphology of folds (sulci) of the human cerebral cortex flatten during postnatal development. However, previous studies did not consider the relationship between sulcal morphology and cognitive development in individual participants. Here, we fill this gap in knowledge by leveraging cross-sectional morphologic neuroimaging data in the lateral PFC (LPFC) from individual human participants (6-36 years old, males and females; N = 108; 3672 sulci), as well as longitudinal morphologic and behavioral data from a subset of child and adolescent participants scanned at two time points (6-18 years old; N = 44; 2992 sulci). Manually defining thousands of sulci revealed that LPFC sulcal morphology (depth, surface area, and gray matter thickness) differed between children (6-11 years old)/adolescents (11-18 years old) and young adults (22-36 years old) cross-sectionally, but only cortical thickness showed differences across childhood and adolescence and presented longitudinal changes during childhood and adolescence. Furthermore, a data-driven approach relating morphology and cognition identified that longitudinal changes in cortical thickness of four left-hemisphere LPFC sulci predicted longitudinal changes in reasoning performance, a higher-level cognitive ability that relies on LPFC. Contrary to previous findings, these results suggest that sulci may flatten either after this time frame or over a longer longitudinal period of time than previously presented. Crucially, these results also suggest that longitudinal changes in the cortex within specific LPFC sulci are behaviorally meaningful, providing targeted structures, and areas of the cortex, for future neuroimaging studies examining the development of cognitive abilities.SIGNIFICANCE STATEMENT Recent work has shown that individual differences in neuroanatomical structures (indentations, or sulci) within the lateral PFC are behaviorally meaningful during childhood and adolescence. Here, we describe how specific lateral PFC sulci develop at the level of individual participants for the first time: from both cross-sectional and longitudinal perspectives. Further, we show, also for the first time, that the longitudinal morphologic changes in these structures are behaviorally relevant. These findings lay the foundation for a future avenue to precisely study the development of the cortex and highlight the importance of studying the development of sulci in other cortical expanses and charting how these changes relate to the cognitive abilities those areas support at the level of individual participants.

FMR1 Carriers Report Executive Function Changes Prior to Fragile X-Associated Tremor/Ataxia Syndrome: A Longitudinal Study.

BACKGROUND: Men with fragile X-associated tremor/ataxia syndrome (FXTAS) often develop executive dysfunction, characterized by disinhibition, frontal dyscontrol of movement, and working memory and attention changes. Although cross-sectional studies have suggested that earlier executive function changes may precede FXTAS, the lack of longitudinal studies has made it difficult to address this hypothesis. OBJECTIVE: To determine whether executive function deterioration experienced by premutation carriers (PC) in daily life precedes and predicts FXTAS. METHODS: This study included 66 FMR1 PC ranging from 40 to 78 years (mean, 59.5) and 31 well-matched healthy controls (HC) ages 40 to 75 (mean, 57.7) at baseline. Eighty-four participants returned for 2 to 5 follow up visits over a duration of 1 to 9 years (mean, 4.6); 28 of the PC developed FXTAS. The Behavior Rating Inventory of Executive Function-Adult Version (BRIEF-A) was completed by participants and their spouses/partners at each visit. RESULTS: Longitudinal mixed model regression analyses showed a greater decline with age in PC compared to HC on the Metacognition Index (MI; self-initiation, working memory, organization, task monitoring). Conversion to FXTAS was associated with worsening MI and Behavioral Regulation Index (BRI; inhibition, flexibility, emotion modulation). For spouse/partner report, FXTAS conversion was associated with worsening MI. Finally, increased self-report executive function problems at baseline significantly predicted later development of FXTAS. CONCLUSIONS: Executive function changes experienced by male PC represent a prodrome of the later movement disorder. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Clustering Analysis of Time Series of Affect in Dyadic Interactions.

An important goal when analyzing multivariate time series is the identification of heterogeneity, both within and across individuals over time. This heterogeneity can represent different ways in which psychological processes manifest, either between people or within a person across time. In many instances, those differences can have systematic patterns that can be related to future outcomes. In close relationships, for example, the daily exchange of affect between two individuals in a couple can contain a particular structure that is different across people and can result in varying levels of relationship satisfaction. In this paper we use Louvain, a clustering method, as a tool to characterize heterogeneity in multivariate time series data. Using affect measures from dyadic interactions, we first determine that Louvain is adept at detecting homogeneous patterns that are distinct from one another. Additionally, these homogeneous points are linked, at some level, by time. Thus, we find that clustering via Louvain is useful to find time periods of stable, reoccurring patterns. However, using measures founded on information theory reveals that there is some level of information loss that is inevitable when clustering on levels of variable expression. Finally, we evaluate the predictive validity of the clustering method by examining the relation between the identified clusters of affect and measures outside the time series (i.e., relationship satisfaction and breakup taken one and two years later).

Detecting Cohort Effects in Accelerated Longitudinal Designs Using Multilevel Models.

Accelerated longitudinal designs allow researchers to efficiently collect longitudinal data covering a time span much longer than the study duration. One important assumption of these designs is that each cohort (a group defined by their age of entry into the study) shares the same longitudinal trajectory. Although previous research has examined the impact of violating this assumption when each cohort is defined by a single age of entry, it is possible that each cohort is instead defined by a range of ages, such as groups that experience a particular historical event. In this paper we examined how including cohort membership in linear and quadratic multilevel models performed in detecting and controlling for cohort effects in this scenario. Using a Monte Carlo simulation study, we assessed the performance of this approach under conditions related to the number of cohorts, the overlap between cohorts, the strength of the cohort effect, the number of affected parameters, and the sample size. Our results indicate that models including a proxy variable for cohort membership based on age at study entry performed comparably to using true cohort membership in detecting cohort effects accurately and returning unbiased parameter estimates. This indicates that researchers can control for cohort effects even when true cohort membership is unknown.

Neural correlates and effect of jealousy on cognitive flexibility in the female titi monkey (Plecturocebus cupreus).

Jealousy is a social emotion that manifests as behavioral reactions from an individual toward a threat to a valuable relationship. Monogamous species exhibit jealousy-type behaviors as an adaptive response to preserve the relationship. Jealousy is also a complex, negatively-valenced emotion which may include fear of loss, anxiety, suspiciousness, and anger. Negative emotion may impair cognitive processes such as cognitive flexibility, an ability important for coping with new situations. However, little is known about how complex social emotions influence cognitive flexibility. To understand the interaction between jealousy and cognitive flexibility, we examined the neural, physiological, and behavioral factors involved in jealousy and cognitive flexibility in female titi monkeys. We presented subjects with a jealousy provoking scenario, followed by a reversal learning task and a PET scan with a glucose-analog radiotracer. We found that female titi monkeys reacted to a jealousy provoking scenario with increased locomotor behavior and higher glucose uptake in the cerebellum; however, hormone measures and were not affected. As only two females demonstrated cognitive flexibility, the effects of jealousy were difficult to interpret. Locomotion behavior was also negatively correlated with glucose uptake in brain areas linked with motivation, sociality, and cognitive flexibility. Surprisingly, glucose uptake in the orbitofrontal cortex (OFC) was significantly decreased during jealousy scenarios, while uptake in the anterior cingulate cortex (ACC) was decreased during reversal tasks. Our findings suggest that the presence of an intruder produces less visible behavioral reactions in female titis than in males, while still reducing activity in the OFC.

Empirically-identified subgroups of children with autism spectrum disorder and their response to two types of cognitive behavioral therapy.

Autism spectrum disorder (ASD) is heterogeneous and likely entails distinct phenotypes with varying etiologies. Identifying these subgroups may contribute to hypotheses about differential treatment responses. The present study aimed to discern subgroups among children with ASD and anxiety in context of the five-factor model of personality (FFM) and evaluate treatment response differences to two cognitive-behavioral therapy treatments. The present study is a secondary data analysis of children with ASD and anxiety (N=202; ages 7-13; 20.8% female) in a cognitive behavioral therapy (CBT) randomized controlled trial (Wood et al., 2020). Subgroups were identified via latent profile analysis of parent-reported FFM data. Treatment groups included standard-of-practice CBT (CC), designed for children with anxiety, and adapted CBT (BIACA), designed for children with ASD and comorbid anxiety. Five subgroups with distinct profiles were extracted. Analysis of covariance revealed CBT response was contingent on subgroup membership. Two subgroups responded better to BIACA on the primary outcome measure and a third responded better to BIACA on a peer-social adaptation measure, while a fourth subgroup responded better to CC on a school-related adaptation measure. These findings suggest that the FFM may be useful in empirically identifying subgroups of children with ASD, which could inform intervention selection decisions for children with ASD and anxiety.

Homogeneity Assumptions in the Analysis of Dynamic Processes.

With the increased use of time series data in human research, ranging from ecological momentary assessments to data passively obtained, researchers can explore dynamic processes more than ever before. An important question researchers must ask themselves is, do I think all individuals have similar processes? If not, how different, and in what ways? Dr. Peter Molenaar's work set the foundation to answer these questions by providing insight into individual-level analysis for processes that are assumed to differ across individuals in at least some aspects. Currently, such assumptions do not have a clear taxonomy regarding the degree of homogeneity in the patterns of relations among variables and the corresponding parameter values. This paper provides the language with which researchers can discuss assumptions inherent in their analyses. We define strict homogeneity as the assumption that all individuals have an identical pattern of relations as well as parameter values; pattern homogeneity assumes the same pattern of relations but parameter values can differ; weak homogeneity assumes there are some (but not all) generalizable aspects of the process; and no homogeneity explicitly assumes no population-level similarities in dynamic processes across individuals. We demonstrate these assumptions with an empirical data set of daily emotions in couples.

Fitting Bayesian Stochastic Differential Equation Models with Mixed Effects through a Filtering Approach.

Recent advances in technology contribute to a fast-growing number of studies utilizing intensive longitudinal data, and call for more flexible methods to address the demands that come with them. One issue that arises from collecting longitudinal data from multiple units in time is nested data, where the variability observed in such data is a mixture of within-unit changes and between-unit differences. This article aims to provide a model-fitting approach that simultaneously models the within-unit changes with differential equation models and accounts for between-unit differences with mixed effects. This approach combines a variant of the Kalman filter, the continuous-discrete extended Kalman filter (CDEKF), and the Markov chain Monte Carlo method often employed in the Bayesian framework through the platform Stan. At the same time, it utilizes Stan's functionality of numerical solvers for the implementation of CDEKF. For an empirical illustration, we applied this method in the context of differential equation models to an empirical dataset to explore the physiological dynamics and co-regulation between couples.

Model Selection and Model Averaging for Mixed-Effects Models with Crossed Random Effects for Subjects and Items.

A good deal of experimental research is characterized by the presence of random effects on subjects and items. A standard modeling approach that includes such sources of variability is the mixed-effects models (MEMs) with crossed random effects. However, under-parameterizing or over-parameterizing the random structure of MEMs bias the estimations of the Standard Errors (SEs) of fixed effects. In this simulation study, we examined two different but complementary perspectives: model selection with likelihood-ratio tests, AIC, and BIC; and model averaging with Akaike weights. Results showed that true model selection was constant across the different strategies examined (including ML and REML estimators). However, sample size and variance of random slopes were found to explain true model selection and SE bias of fixed effects. No relevant differences in SE bias were found for model selection and model averaging. Sample size and variance of random slopes interacted with the estimator to explain SE bias. Only the within-subjects effect showed significant underestimation of SEs with smaller number of items and larger item random slopes. SE bias was higher for ML than REML, but the variability of SE bias was the opposite. Such variability can be translated into high rates of unacceptable bias in many replications.

Use of Composites in Analysis of Individual Time Series: Implications for Person-Specific Dynamic Parameters.

Psychology has seen an increase in the study of intra-individual processes through time series. Although timely and relevant, modeling variance from unique sources in time series may lead to model non-convergence, making it tempting to reduce the number of parameters in the model. The purpose of this paper was to investigate use of composite scores in analysis of individual time series. To meet this goal, we compared the dynamic factor analysis (DFA) model using multiple indicators with the autoregressive (AR) and autoregressive + white noise (AR + WN) models using composites. We conducted a Monte Carlo study in which a DFA(1,1) model was used to generate the data with varying conditions of size of factor loadings, number of indicators, size of AR parameters, and time series length. We also conducted analysis of empirical data from six individuals' daily self-reports of mood. Findings indicated that the DFA(1,1) and AR(1) + WN models performed comparably in their recovery of AR parameters, while the AR(1) model underestimated the parameter under nearly all conditions. However, variability of estimates may make the AR(1) + WN model less viable for researchers conducting individual-level analyses when the true data-generating mechanism is the DFA(1, 1) model.

Dynamic Mixture Modeling with dynr.

Mixture modeling is commonly used to model sample heterogeneity by identifying unobserved classes of individuals with similar characteristics. Despite abundance of evidence in the literature suggesting that individuals are often characterized by different dynamic processes underlying their physiological, cognitive, psychological, and behavioral states, applications of dynamic mixture modeling are surprisingly lacking. We present here a proof-of-concept example of dynamic mixture modeling, where latent groups of individuals were identified based on different dynamic patterns in their time series. Our sample consists of 192 men who were in a heterosexual relationship. They were asked to complete a daily questionnaire involving emotions related to their relationship. Two latent groups were identified based on the strength of association between positive (e.g., loving) and negative (e.g., doubtful) affect. Men in the group characterized by a strong negative association (ß=-.67) tended to be younger and had higher levels of anxiety toward their relationship than men in the other group, which was characterized by a weaker negative association (ß=-.31). We illustrate the specification and estimation of dynamic mixture model using "dynr," an R package capable of handling a broad class of linear and nonlinear discrete- and continuous-time models with regime-switching properties.

Estimating Age-Based Developmental Trajectories Using Latent Change Score Models Based on Measurement Occasion.

Accelerated longitudinal designs (ALDs) are designs in which participants from different cohorts provide repeated measures covering a fraction of the time range of the study. ALDs allow researchers to study developmental processes spanning long periods within a relatively shorter time framework. The common trajectory is studied by aggregating the information provided by the different cohorts. Latent change score (LCS) models provide a powerful analytical framework to analyze data from ALDs. With developmental data, LCS models can be specified using measurement occasion as the time metric. This provides a number of benefits, but has an important limitation: It makes it not possible to characterize the longitudinal changes as a function of a developmental process such as age or biological maturation. To overcome this limitation, we propose an extension of an occasion-based LCS model that includes age differences at the first measurement occasion. We conducted a Monte Carlo study and compared the results of including different transformations of the age variable. Our results indicate that some of the proposed transformations resulted in accurate expectations for the studied process across all the ages in the study, and excellent model fit. We discuss these results and provide the R code for our analysis.

Tuning of brain-autonomic coupling by prior threat exposure: Implications for internalizing problems in Mexican-origin adolescents.

Exposure to threat increases the risk for internalizing problems in adolescence. Deficits in integrating bodily cues into representations of emotion are thought to contribute to internalizing problems. Given the role of the medial prefrontal cortex in regulating bodily responses and integrating them into representations of emotional states, coordination between activity in the medial prefrontal cortex and autonomic nervous system responses may be influenced by past threat exposure with consequences for the emergence of internalizing problems. A sample of 179 Mexican-origin adolescents (88 female) reported on neighborhood and school crime, peer victimization, and discrimination when they were 10-16 years old. At age 17, participants underwent a functional neuroimaging scan during which they viewed pictures of emotional faces while respiratory sinus arrhythmia (RSA) and skin conductance responses were measured. Adolescents also reported symptoms of internalizing problems. Greater exposure to threats across adolescence was associated with more internalizing problems. Threat exposure was also associated with stronger negative coupling between the ventromedial prefrontal cortex and RSA. Stronger negative ventromedial prefrontal cortex-RSA coupling was associated with fewer internalizing problems. These results suggest the degree of coordinated activity between the brain and parasympathetic nervous system is both enhanced by threat experiences and decreased in adolescents with more internalizing problems.

Frontoparietal Structural Connectivity in Childhood Predicts Development of Functional Connectivity and Reasoning Ability: A Large-Scale Longitudinal Investigation.

Prior research points to a positive concurrent relationship between reasoning ability and both frontoparietal structural connectivity (SC) as measured by diffusion tensor imaging (Tamnes et al., 2010) and frontoparietal functional connectivity (FC) as measured by fMRI (Cocchi et al., 2014). Further, recent research demonstrates a link between reasoning ability and FC of two brain regions in particular: rostrolateral prefrontal cortex (RLPFC) and the inferior parietal lobe (IPL) (Wendelken et al., 2016). Here, we sought to investigate the concurrent and dynamic, lead-lag relationships among frontoparietal SC, FC, and reasoning ability in humans. To this end, we combined three longitudinal developmental datasets with behavioral and neuroimaging data from 523 male and female participants between 6 and 22 years of age. Cross-sectionally, reasoning ability was most strongly related to FC between RLPFC and IPL in adolescents and adults, but to frontoparietal SC in children. Longitudinal analysis revealed that RLPFC-IPL SC, but not FC, was a positive predictor of future changes in reasoning ability. Moreover, we found that RLPFC-IPL SC at one time point positively predicted future changes in RLPFC-IPL FC, whereas, in contrast, FC did not predict future changes in SC. Our results demonstrate the importance of strong white matter connectivity between RLPFC and IPL during middle childhood for the subsequent development of both robust FC and good reasoning ability.SIGNIFICANCE STATEMENT The human capacity for reasoning develops substantially during childhood and has a profound impact on achievement in school and in cognitively challenging careers. Reasoning ability depends on communication between lateral prefrontal and parietal cortices. Therefore, to understand how this capacity develops, we examined the dynamic relationships over time among white matter tracts connecting frontoparietal cortices (i.e., structural connectivity, SC), coordinated frontoparietal activation (functional connectivity, FC), and reasoning ability in a large longitudinal sample of subjects 6-22 years of age. We found that greater frontoparietal SC in childhood predicts future increases in both FC and reasoning ability, demonstrating the importance of white matter development during childhood for subsequent brain and cognitive functioning.

Adolescents' brain-autonomic coupling during emotion processing.

Autonomic nervous system (ANS) activity is a core component of emotion processing. The limbic system and medial prefrontal cortex play important roles in the regulation of ANS activity. However, the integration of brain activity and ANS activity has yet to be investigated in adolescents despite independent evidence of adolescents' heightened neural and physiological sensitivity to emotional stimuli. The present study examined the relations of ANS activity in the parasympathetic nervous system (PNS) and sympathetic nervous system (SNS) with brain activity during emotional face processing in adolescents. 135 adolescents (65 female; M = 17.15 yr, SD = 0.42) completed an emotional faces task during an fMRI scan while electrocardiography and skin conductance were recorded simultaneously. Using linear mixed-effect modelling, we tested the effect of change in respiratory sinus arrhythmia (RSA), a measure of PNS activity, and number of skin conductance responses (SCRs), a measure of SNS activity, on neural activity while adolescents viewed emotional faces. Greater RSA withdrawal, indicating decreased PNS activity, was associated with increased activation in the ventromedial prefrontal cortex (vmPFC). More SCRs, indicating greater SNS activity, were associated with decreased activation in several regions including the dorsomedial prefrontal cortex and increased activation in the left hippocampus. Left hippocampus-SCR coupling and vmPFC-RSA coupling predicted baseline SCR and RSA respectively. These findings implicate the hippocampus for potentiating SNS activity, document that regulation of SNS and PNS activity are coordinated with distinct regions of the medial prefrontal cortex, and suggest potential developmental differences in vmPFC regulation of PNS activity between adolescents and adults.

Age- and CGG repeat-related slowing of manual movement in fragile X carriers: A prodrome of fragile X-associated tremor ataxia syndrome?

BACKGROUND: Fragile X premutation carriers are at increased risk for fragile X-associated tremor ataxia syndrome (FXTAS), but to date we know little about prediction of onset and rate of progression and even less about treatment of this neurodegenerative disease. Thus, the longitudinal study of carriers, and the identification of potential biomarkers and prodromal states, is essential. Here we present results of baseline assessments from an ongoing longitudinal project. METHODS: The cohort consisted of 73 men, 48 with the fragile X mental retardation 1 (FMR1) premutation (55-200 cytosine-cytosine-guanine or CGG repeats) and 25 well-matched controls (< 40 repeats) aged between 40 and 75 years. At enrollment, none met criteria for FXTAS or had any clinically significant tremor or ataxia by blinded neurological examination. The battery consisted of measures of visual memory, spatial working memory, response inhibition, motor speed and control, planning and problem solving, sustained attention, and a standardized movement disorder evaluation. RESULTS: Contrary to expectations, there were no significant differences between premutation carriers and controls on any measure of executive function. However, the premutation carriers had significantly longer manual movement and reaction times than controls, and the significant interaction between CGG repeat and age revealed the slowest movement times among older carriers with higher CGG repeat alleles. A subset of premutation carriers had marginally lower scores on the ataxia evaluation, and they performed no differently from controls on the parkinsonism assessment. CONCLUSION: Early-developing cerebellar or fronto-motor tract white matter changes, previously documented in MRI studies, may underlie motor slowing that occurs before clinically observable neurological symptoms associated with FXTAS. © 2018 International Parkinson and Movement Disorder Society.

Effects of aggressive temperament on endogenous oxytocin levels in adult titi monkeys.

Coordination of oxytocin (OT) activity and partner interactions is important for the facilitation and maintenance of monogamous pair bonds. We used coppery titi monkeys (Callicebus cupreus) to identify the effects of male aggressive temperament on OT activity, affiliative partner-directed behaviors, aggressive partner-directed behaviors, anxiety-related behaviors, and hormone-behavior interactions. We used a mirror technique, simulating an intruder in the home territory of pairs to elicit behavioral responses, and quantified behaviors using an established ethogram. Plasma concentrations of OT (pg/ml) were quantified using enzyme immunoassay. We used general linear mixed models to predict 1) percent change in OT as a function of aggression score, and 2) percent change in behaviors as a function of aggression, OT, and OT by aggression interactions. High-aggressive males exhibited a significant drop in OT concentration relative to control when exposed to the front of the mirror (ß = -0.22, SE = 0.10, t = -2.20, p = 0.04). High-aggressive males spent significantly less time in contact with their mates (ß = -1.35, SE = 0.60, t = -2.26, p = 0.04) and lip-smacked less (ß = -1.02, SE = 0.44, t = -2.32, p = 0.03) relative to control. We also saw a trend toward an interaction effect between OT and proximity such that High-aggressive males displaying a drop in OT exhibited a smaller percent increase in social proximity (ß = 6.80, SE = 3.48, t = 1.96, p = 0.07). Males exhibiting a decrease in OT also trended toward back-arching and tail-lashing less in response to the mirror (ß = 4.53, SE = 2.5, t = 1.82, p = 0.09). To our knowledge, this is the first empirical study to examine interactions between OT and temperament in adult monogamous primates. Future studies should incorporate measures of pair-mate interactions and early-life experience to further understand variation in responses to social stressors and their effects on pair bonding.

Do Hostile School Environments Promote Social Deviance by Shaping Neural Responses to Social Exclusion?

The present study examined adolescents' neural responses to social exclusion as a mediator of past exposure to a hostile school environment (HSE) and later social deviance, and whether family connectedness buffered these associations. Participants (166 Mexican-origin adolescents, 54.4% female) reported on their HSE exposure and family connectedness across Grades 9-11. Six months later, neural responses to social exclusion were measured. Finally, social deviance was self-reported in Grades 9 and 12. The HSE-social deviance link was mediated by greater reactivity to social deviance in subgenual anterior cingulate cortex, a region from the social pain network also implicated in social susceptibility. However, youths with stronger family bonds were protected from this neurobiologically mediated path. These findings suggest a complex interplay of risk and protective factors that impact adolescent behavior through the brain.

A Mixed-Effects Location Scale Model for Dyadic Interactions.

We present a mixed-effects location scale model (MELSM) for examining the daily dynamics of affect in dyads. The MELSM includes person and time-varying variables to predict the location, or individual means, and the scale, or within-person variances. It also incorporates a submodel to account for between-person variances. The dyadic specification can accommodate individual and partner effects in both the location and the scale components, and allows random effects for all location and scale parameters. All covariances among the random effects, within and across the location and the scale are also estimated. These covariances offer new insights into the interplay of individual mean structures, intra-individual variability, and the influence of partner effects on such factors. To illustrate the model, we use data from 274 couples who provided daily ratings on their positive and negative emotions toward their relationship - up to 90 consecutive days. The model is fit using Hamiltonian Monte Carlo methods, and includes subsets of predictors in order to demonstrate the flexibility of this approach. We conclude with a discussion on the usefulness and the limitations of the MELSM for dyadic research.

Cross-Sectional Analysis of Longitudinal Mediation Processes.

Statistical mediation analysis can help to identify and explain the mechanisms behind psychological processes. Examining a set of variables for mediation effects is a ubiquitous process in the social sciences literature; however, despite evidence suggesting that cross-sectional data can misrepresent the mediation of longitudinal processes, cross-sectional analyses continue to be used in this manner. Alternative longitudinal mediation models, including those rooted in a structural equation modeling framework (cross-lagged panel, latent growth curve, and latent difference score models) are currently available and may provide a better representation of mediation processes for longitudinal data. The purpose of this paper is twofold: first, we provide a comparison of cross-sectional and longitudinal mediation models; second, we advocate using models to evaluate mediation effects that capture the temporal sequence of the process under study. Two separate empirical examples are presented to illustrate differences in the conclusions drawn from cross-sectional and longitudinal mediation analyses. Findings from these examples yielded substantial differences in interpretations between the cross-sectional and longitudinal mediation models considered here. Based on these observations, researchers should use caution when attempting to use cross-sectional data in place of longitudinal data for mediation analyses.