Visual search in neurodevelopmental disorders: evidence towards a continuum of impairment.

Disorders with neurodevelopmental aetiology such as Attention-Deficit/Hyperactivity Disorder (ADHD), Autism Spectrum Disorder (ASD) and Schizophrenia share commonalities at many levels of investigation despite phenotypic differences. Evidence of genetic overlap has led to the concept of a continuum of neurodevelopmental impairment along which these disorders can be positioned in aetiological, pathophysiological and developmental features. This concept requires their simultaneous comparison at different levels, which has not been accomplished so far. Given that cognitive impairments are core to the pathophysiology of these disorders, we provide for the first time differentiated head-to-head comparisons in a complex cognitive function, visual search, decomposing the task with eye movement-based process analyses. N = 103 late-adolescents with schizophrenia, ADHD, ASD and healthy controls took a serial visual search task, while their eye movements were recorded. Patients with schizophrenia presented the greatest level of impairment across different phases of search, followed by patients with ADHD, who shared with patients with schizophrenia elevated intra-subject variability in the pre-search stage. ASD was the least impaired group, but similar to schizophrenia in post-search processes and to schizophrenia and ADHD in pre-search processes and fixation duration while scanning the items. Importantly, the profiles of deviancy from controls were highly correlated between all three clinical groups, in line with the continuum idea. Findings suggest the existence of one common neurodevelopmental continuum of performance for the three disorders, while quantitative differences appear in the level of impairment. Given the relevance of cognitive impairments in these three disorders, we argue in favour of overlapping pathophysiological mechanisms.

Individual differences of conflict monitoring and feedback processing during reinforcement learning in a mock forensic context.

This study investigated individual differences of conflict monitoring (N2 component), feedback processing (feedback negativity component), and reinforcement learning in a discrimination learning task using a mock (fictitious) forensic scenario to set participants in a semantic task context. We investigated individual differences of anxiety-related, impulsivity-related traits and reasoning ability during trial-and-error learning of mock suspect and nonsuspect faces. Thereby, we asked how the differential investment of cognitive-motivational processes facilitates learning in a mock forensic context. As learning can be studied by means of time-on-task effects (i.e., variations of cognitive processes across task blocks), we investigated the differential investment of cognitive-motivational processes block-wise in N = 100 participants. By performing structural equation modeling, we demonstrate that conflict monitoring decreased across task blocks, whereas the percentage of correct responses increased across task blocks. Individuals with higher reasoning scores and higher impulsivity-related traits relied rather on feedback processing (i.e., external indicators) during reinforcement learning. Individuals with higher anxiety-related traits intensified their conflict monitoring throughout the task to learn successfully. Observation by relevant others intensified conflict monitoring more than nonobservation. Our data highlight that individual differences and social context modulate the intensity of information processing in a discrimination learning task using a mock forensic task scenario. We discuss our data with regard to recent cognitive-motivational approaches and in terms of reinforcement learning.

A meta-analysis of the P3 amplitude in tasks requiring deception in legal and social contexts.

In deception tasks the parietal P3 amplitude of the event-related potential indicates either recognition of salient stimuli (larger P3 following salient information) or mental effort (smaller P3 following demanding information). This meta-analysis (k = 77) investigated population effect sizes (δ) for conceptual and methodological a-priori moderators (study design, pre-task scenario, context of deception tasks, and P3 quantification). Within-subject designs show evidence of the underlying cognitive processes, between-subject designs allow for comparisons of cognitive processes in culprits vs. innocents. Committed vs. imagined mock crime scenarios yield larger δ. Deception tasks with a legal context result in almost twice as large δ than deception tasks with social-evaluative and social-biographical contexts. Peak-to-peak P3 quantification resulted in larger δ than other quantifications. Counter-measure techniques in 3-stimulus protocols reduce the discriminability of concealed vs. truthful P3 amplitudes. Depending on stimulus knowledge, deception tasks provide evidence for the salience hypothesis and the mental effort hypothesis, respectively.

Extending the Debate Between Spearman and Wilson 1929: When do Single Variables Optimally Reproduce the Common Part of the Observed Covariances?

The covariances of observed variables reproduced from conventional factor score predictors are generally not the same as the covariances reproduced from the common factors. We sought to find a factor score predictor that optimally reproduces the common part of the observed covariances. It was found algebraically that-under some conditions-the single observed variable with highest loading on a factor reproduces the non-diagonal elements of the observed covariance matrix more exactly than the conventional factor score predictors. This finding is linked to Spearman's and Wilson's 1929 debate on the use of single variables as factor score predictors. A population-based and a sample-based simulation study confirmed the algebraic result that taking a single variable can outperform conventional factor score predictors in reproducing the non-diagonal covariances when the nonzero loading size and the number of nonzero loadings per factor are small. The results indicated that a weighted aggregation of variables does not necessarily lead to an improvement of the score over the variable with the highest loading.

The Trade-Off Between Factor Score Determinacy and the Preservation of Inter-Factor Correlations.

Regression factor score predictors have the maximum factor score determinacy, that is, the maximum correlation with the corresponding factor, but they do not have the same inter-correlations as the factors. As it might be useful to compute factor score predictors that have the same inter-correlations as the factors, correlation-preserving factor score predictors have been proposed. However, correlation-preserving factor score predictors have smaller correlations with the corresponding factors (factor score determinacy) than regression factor score predictors. Thus, higher factor score determinacy goes along with bias of the inter-correlations and unbiased inter-correlations go along with lower factor score determinacy. The aim of the present study was therefore to investigate the size and conditions of the trade-off between factor score determinacy and bias of inter-correlations by means of algebraic considerations and a simulation study. It turns out that under several conditions very small gains of factor score determinacy of the regression factor score predictor go along with a large bias of inter-correlations. Instead of using the regression factor score predictor by default, it is proposed to check whether substantial bias of inter-correlations can be avoided without substantial loss of factor score determinacy using a correlation-preserving factor score predictor. A syntax that allows to compute correlation-preserving factor score predictors from regression factor score predictors, and to compare factor score determinacy and inter-correlations of the factor score predictors is given in the Appendix.

The association of dispositional anxiety with the NoGo N2 under relaxation instruction versus speed/accuracy instruction.

Prior research suggests that cognitive control, indicated by NoGo N2 amplitudes in Go/NoGo tasks, is associated with dispositional anxiety. This negative association tends to be reduced in anxiety-enhancing experimental conditions. However, anxiety-reducing conditions have not yet been investigated systematically. Thus, the present study compares the effect of a relaxation instruction with the conventional speed/accuracy instruction in a Go/NoGo task on the correlation of the NoGo N2 with two subconstructs of dispositional anxiety, namely anxious apprehension and anxious arousal. As the test of differences between correlations needs considerable statistical power, the present study was included into the multi-lab CoScience Project. The hypotheses, manipulation checks, and the main path of pre-processing and statistical analysis were preregistered. Complete data sets of 777 participants were available for data analysis. Preregistered general linear models revealed that the different instructions of the task (speed/accuracy vs. relaxation) had no effect on the association between dispositional anxiety and the NoGo N2 amplitude in general. This result was supported by Cooperative-Forking-Path analysis. In contrast, a preregistered latent growth model with categorical variables revealed that anxious arousal was a negative predictor of the NoGo N2 intercept and a positive predictor of the NoGo N2 slope. Non-preregistered growth models, allowing for correlations of anxious apprehension with anxious arousal, revealed that higher anxious apprehension scores were associated with more negative NoGo N2 amplitudes with increased relaxation. Results are discussed in the context of the compensatory error monitoring hypothesis and the revised Reinforcement Sensitivity Theory.

Inter-individual and intra-individual variability of the N2 component: on reliability and signal-to-noise ratio.

The nogo N2 component, an anterior negative peak supposed to be generated in the anterior cingulate cortex, has been used as an indicator of conflict monitoring and response conflict in basic and clinical research. Here, we investigate the reliability and the signal-to-noise ratio (SNR) of inter-individual differences of the N2 amplitudes as well as of intra-individual standard deviations of N2 amplitudes. Effects of the number of nogo epochs, type of summary measure (peak vs. average amplitude), and filter cut-offs (1-12 Hz vs. 1-30 Hz) are investigated. A sample of N=32 participants, performed a go/nogo task. Excellent Cronbach's alpha coefficients (> or = .90) were obtained for the fronto-central average N2 amplitude at 40 nogo epochs and for the peak N2 amplitude at 60 nogo epochs. The SNR was higher for the average nogo N2 amplitude compared to the peak N2 amplitude. Split-half reliability coefficients of the intra-individual standard deviation of the nogo N2 amplitudes were at least moderate. Based on these results we provide suggestions for a reliable N2 measurement. Moreover, although intra-individual variability has often been conceived as noise the present findings support the idea that intra-individual N2 variability incorporates systematic variance.

Robust oblique Target-rotation for small samples.

Introduction: Oblique Target-rotation in the context of exploratory factor analysis is a relevant method for the investigation of the oblique simple structure. It was argued that minimizing single cross-loadings by means of target rotation may lead to large effects of sampling error on the target rotated factor solutions. Method: In order to minimize effects of sampling error on results of Target-rotation we propose to compute the mean cross-loadings for each block of salient loadings of the independent clusters model and to perform Target-rotation for the block-wise mean cross-loadings. The resulting transformation-matrix is than applied to the complete unrotated loading matrix in order to produce mean Target-rotated factors. Results: A simulation study based on correlated independent clusters model and zero-mean cross-loading models revealed that mean oblique Target-rotation resulted in smaller bias of factor inter-correlations than conventional Target-rotation based on single loadings, especially when sample size was small and when the number of factors was large. An empirical example revealed that the similarity of Target-rotated factors computed for small subsamples with Target-rotated factors of the total sample was more pronounced for mean Target-rotation than for conventional Target-rotation. Discussion: Mean Target-rotation can be recommended in the context of oblique factor models based on simple structure, especially for small samples. An R-script and an SPSS-script for this form of Target-rotation are provided in the Supplementary Material.

Intra-Subject Variability, Intelligence, and ADHD Traits in a Community-Based Sample.

OBJECTIVE: The present study investigates the predictive validity of intra-subject variability (ISV) for ADHD traits in a community-based sample and the stability of the relationship between ISV and fluid intelligence (gf) across the continuum of ADHD traits. METHOD: Age-residualized data from 426 participants (8-18 years, 6% ADHD) was used to investigate whether ex-Gaussian and DDM parameters derived from simple choice-reaction-time tasks can predict continuously assessed ADHD traits. Multiple-Group-Analyses and Latent-Moderated-Structural-Equations were used to test whether ADHD traits moderate the relationship between ISV and gf. RESULTS: σ and µ of the ex-Gaussian model as well as DDM parameters drift rate (v) and boundary separation (a) significantly predicted general ADHD traits, while τ predicted attention difficulties specifically. Across the ADHD continuum, σ and v were significant predictors of gf. CONCLUSION: The results confirm the link between ISV and ADHD. The relationship between ISV and gf appears stable across the ADHD continuum.

Modulation of the conflict monitoring intensity: the role of aversive reinforcement, cognitive demand, and trait-BIS.

According to Botvinick's (2007) integrative account, conflict monitoring is aversive because individuals anticipate cognitive demand, whereas the revised reinforcement sensitivity theory (rRST) predicts that conflict processing is aversive because individuals anticipate aversive reinforcement of erroneous responses. Because these accounts give different reasons for the aversive aspects of conflict, we manipulated cognitive demand and the aversive reinforcement as a consequence of wrong choices in a go/no-go task. Thereby, we also aimed to investigate whether individual differences in conflict sensitivity (i.e., in trait anxiety, linked to high sensitivity of the behavioral inhibition system [trait-BIS]) represent the effects of aversive reinforcement and cognitive demand in conflict tasks. We expected that these manipulations would have effects on the frontal N2 component representing activity of the anterior cingulate cortex. Moreover, higher-trait-BIS individuals should be more sensitive than lower-trait-BIS individuals to aversive effects in conflict situations, resulting in a more negative frontal N2 for higher-trait-BIS individuals. In Study 1, with N = 104 students, and Study 2, with N = 47 students, aversive reinforcement was manipulated in three levels (within-subjects factor) and cognitive demand in two levels (between-subjects factor). The behavioral findings from the go/no-go task with noncounterbalanced reinforcement levels (Study 1) could be widely replicated in a task with counterbalanced reinforcement levels (Study 2). The frontal mean no-go N2 amplitude and the frontal no-go N2 dipole captured predicted reinforcement-related variations of conflict monitoring, indicating that the anticipation of aversive reinforcement induces variations in conflict monitoring intensity in frontal brain areas. The aversive nature of conflict was underlined by the more pronounced conflict monitoring in higher- than in lower-trait-BIS individuals.

Coefficients of Factor Score Determinacy for Mean Plausible Values of Bayesian Factor Analysis.

In the context of Bayesian factor analysis, it is possible to compute plausible values, which might be used as covariates or predictors or to provide individual scores for the Bayesian latent variables. Previous simulation studies ascertained the validity of mean plausible values by the mean squared difference of the mean plausible values and the generating factor scores. However, the mean correlation of sets of single plausible values of different factors were shown to be an adequate estimator of the correlation between factors. Using sets of single plausible values to compute a mean prediction in secondary analysis implies that their determinacy should be known. Therefore, a plausible value-based determinacy coefficient allowing for estimation of the determinacy of single plausible values was proposed and evaluated by means of two simulation studies. The first simulation study demonstrated that the plausible value-based determinacy coefficient is an adequate estimate of the correlation of single plausible values with the population factor. It is also shown that the plausible value-based determinacy coefficient of mean plausible values approaches the conventional, model parameter-based determinacy coefficient with increasing number of imputations. The second simulation study revealed that the plausible value-based determinacy coefficient and the model parameter-based determinacy coefficient yield similar results even for misspecified models in small samples. It also revealed that for small sample sizes and a small salient loading size, the coefficients of determinacy overestimate the validity, so that it is recommended to report the determinacy coefficients together with a bias-correction to estimate the validity of plausible values in empirical settings.

Conditions affecting the association of general trait-anxiety with the ERN-Ne.

The ERN-Ne of the event-related potential indicates error monitoring. Even though enlarged ERN-Ne amplitudes have often been related to higher anxiety scores, a recent meta-analysis provided very small effect sizes for the association of trait-anxiety with the ERN-Ne. Conditions modulating this association were investigated in the present study: (1) The generality of the trait-anxiety factor, (2) gender, and (3) experimental conditions, i.e., worry induction and error aversiveness. Participants (48% men) completed a flanker task. Worries were induced before the task by giving participants (n = 61) a bogus feedback claiming their responses were slower than the average responses of participants, whereas other participants (n = 61) got the feedback that they responded as fast as other participants. Aversiveness of errors was varied by playing sinus tones after too slow responses in one part of the task (no-scream condition) and aversive screams after too slow responses in another part (scream condition). Increased ERN-Ne amplitudes of response time errors occurred for individuals higher on trait-anxiety in the condition with induced worries and screams. A multiple group model for women and men indicated that women are more sensitive to conditions altering the association of trait-anxiety with the ERN-Ne.

Evidence towards a continuum of impairment across neurodevelopmental disorders from basic ocular-motor tasks.

Findings of genetic overlap between Schizophrenia, Attention-Deficit/Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) contributed to a renewed conceptualization of these disorders as laying on a continuum based on aetiological, pathophysiological and neurodevelopmental features. Given that cognitive impairments are core to their pathophysiology, we compared patients with schizophrenia, ADHD, ASD, and controls on ocular-motor and manual-motor tasks, challenging crucial cognitive processes. Group comparisons revealed inhibition deficits common to all disorders, increased intra-subject variability in schizophrenia and, to a lesser extent, ADHD as well as slowed processing in schizophrenia. Patterns of deviancies from controls exhibited strong correlations, along with differences that posited schizophrenia as the most impaired group, followed by ASD and ADHD. While vector correlations point towards a common neurodevelopmental continuum of impairment, vector levels suggest differences in the severity of such impairment. These findings argue towards a dimensional approach to Neurodevelopmental Disorders' pathophysiological mechanisms.

On the Detection of the Correct Number of Factors in Two-Facet Models by Means of Parallel Analysis.

Methods for optimal factor rotation of two-facet loading matrices have recently been proposed. However, the problem of the correct number of factors to retain for rotation of two-facet loading matrices has rarely been addressed in the context of exploratory factor analysis. Most previous studies were based on the observation that two-facet loading matrices may be rank deficient when the salient loadings of each factor have the same sign. It was shown here that full-rank two-facet loading matrices are, in principle, possible, when some factors have positive and negative salient loadings. Accordingly, the current simulation study on the number of factors to extract for two-facet models was based on rank-deficient and full-rank two-facet population models. The number of factors to extract was estimated from traditional parallel analysis based on the mean of the unreduced eigenvalues as well as from nine other rather traditional versions of parallel analysis (based on the 95th percentile of eigenvalues, based on reduced eigenvalues, based on eigenvalue differences). Parallel analysis based on the mean eigenvalues of the correlation matrix with the squared multiple correlations of each variable with the remaining variables inserted in the main diagonal had the highest detection rates for most of the two-facet factor models. Recommendations for the identification of the correct number of factors are based on the simulation results, on the results of an empirical example data set, and on the conditions for approximately rank-deficient and full-rank two-facet models.

Bayesian and Maximum-Likelihood Modeling and Higher-Level Scores of Interpersonal Problems With Circumplex Structure.

Difficulties in interpersonal behavior are often measured by the circumplex-based Inventory of Interpersonal Problems. Its eight scales can be represented by a three-factor structure with two circumplex factors, Dominance and Love, and a general problem factor, Distress. Bayesian confirmatory factor analysis is well-suited to evaluate the higher-level structure of interpersonal problems because circumplex loading priors allow for data-driven adjustments and a more flexible investigation of the ideal circumplex pattern than conventional maximum likelihood confirmatory factor analysis. Using a non-clinical sample from an online questionnaire study (N = 822), we replicated the three-factor structure of the IIP by maximum likelihood and Bayesian confirmatory factor analysis and found great proximity of the Bayesian loadings to perfect circumplexity. We found additional support for the validity of the three-factor model of the IIP by including external criteria-Agreeableness, Extraversion, and Neuroticism from the Big Five and subclinical grandiose narcissism-in the analysis. We also investigated higher-level scores for Dominance, Love, and Distress using traditional regression factor scores and weighted sum scores. We found excellent reliability (with R tt ≥ 0.90) for Dominance, Love, and Distress for the two scoring methods. We found high congruence of the higher-level scores with the underlying factors and good circumplex properties of the scoring models. The correlational pattern with the external measures was in line with theoretical expectations and similar to the results from the factor analysis. We encourage the use of Bayesian modeling when dealing with circumplex structure and recommend the use of higher-level scores for interpersonal problems as parsimonious, reliable, and valid measures.

The P300 and MFN as indicators of concealed knowledge in situations with negative and positive moral valence.

Many studies on concealed knowledge involve mock-thefts. The present study compares ERPs of participants concealing knowledge of a morally negative behavior (mock-theft) with ERPs of participants concealing knowledge of a morally positive behavior. Some participants (n= 33) stole a candy box out of an office, whereas others (n= 28) put the candy box into an office as a present. During a concealed information test, participants concealed knowledge of the candy box and a key they had seen in the office (probe stimuli) and honestly indicated not knowing similar irrelevant stimuli. P300s were enlarged for probe, compared to irrelevant stimuli in both conditions, revealing that probe stimuli were more salient than irrelevant stimuli regardless of their moral valence. Likewise, medial frontal negativities were enlarged for probe versus irrelevant stimuli in both conditions, indicating response conflicts when answering deceptively to probe items in both situations.

Psychometric Properties of a German Online Version of the Gudjonsson Suggestibility Scale 1.

Suggestibility is a trait dimension that has been differentiated into Yield and Shift dimensions. Yield refers to the susceptibility to suggestive item content in a first question series (Yield 1) and a second question series following negative feedback (Yield 2). Shift describes the tendency to change answers over the two series of questions depending on social pressure. This study aimed at investigating the psychometric properties and the factor structure of a German online version of the Gudjonsson Suggestibility Scale 1 (GSS 1) and measurement invariance of suggestibility scores for gender and research institution. A total of N=560 (n=287 female; age: M=24.20, SD=4.60years) students participated in the study. We present Stanine norms for the application of the online GSS 1. Results supported the theoretical basis of the GSS by revealing the two expected suggestibility factors: Yield and Shift. As expected, a leading factor and a non-leading factor were identified for Yield 1 and Yield 2 and a single factor for Shift. We report psychometric properties (e.g., item difficulty, part-whole corrected item-total correlations, reliability coefficients). We compare the factorial structure of the German online GSS 1 with former versions of the GSS 1. Our data suggest widely measurement invariance for gender and research institution on Yield 1 and Yield 2.

Identification of Facet Models by Means of Factor Rotation: A Simulation Study and Data Analysis of a Test for the Berlin Model of Intelligence Structure.

We investigated by means of a simulation study how well methods for factor rotation can identify a two-facet simple structure. Samples were generated from orthogonal and oblique two-facet population factor models with 4 (2 factors per facet) to 12 factors (6 factors per facet). Samples drawn from orthogonal populations were submitted to factor analysis with subsequent Varimax, Equamax, Parsimax, Factor Parsimony, Tandem I, Tandem II, Infomax, and McCammon's minimum entropy rotation. Samples drawn from oblique populations were submitted to factor analysis with subsequent Geomin rotation and a Promax-based Tandem II rotation. As a benchmark, we investigated a target rotation of the sample loadings toward the corresponding faceted population loadings. The three conditions were sample size (n = 400, 1,000), number of factors (q = 4-12), and main loading size (l = .40, .50, .60). For less than six orthogonal factors Infomax and McCammon's minimum entropy rotation and for six and more factors Tandem II rotation yielded the highest congruence of sample loading matrices with faceted population loading matrices. For six and more oblique factors Geomin rotation and a Promax-based Tandem II rotation yielded the highest congruence with faceted population loadings. Analysis of data of 393 participants that performed a test for the Berlin Model of Intelligence Structure revealed that the faceted structure of this model could be identified by means of a Promax-based Tandem II rotation of task aggregates corresponding to the cross-products of the facets. Implications for the identification of faceted models by means of factor rotation are discussed.

Individual differences in ERPs during deception: Observing vs. demonstrating behavior leading to a small social conflict.

The present study investigated individual differences modulating P300 and MFN amplitudes in a concealed information test (CIT). Some participants were offered candy and either denied (n = 41) or ate it (n = 31), while others witnessed an examiner eating it (informed condition; n = 34). Afterwards it was suggested that the candy was not meant for them. During the CIT, participants saw the candy (probe) and similar unknown items (irrelevants) and indicated that they did not know them. P300 and MFN amplitudes differed for probe and irrelevant items, revealing that known items were more salient and deception was accompanied by response conflicts. Larger differences between P300s for probe versus irrelevant items occurred for women. Furthermore, especially for women, response conflicts diminished when being in the informed condition. Different patterns of MFN amplitudes appeared for informed women depending on the Machiavellianism score, suggesting that gender and Machiavellianism could be related to different cognitive processing during deception.

Model-related factor score predictors for confirmatory factor analysis.

The present paper introduces model-related (MR) factor score predictors, which reflect specific aspects of confirmatory factor models. The development is mainly based on Schönemann and Steiger's regression score components, but it can also be applied to the factor score coefficients. It is shown that the rotation of factor score predictors has no impact on the covariance matrix reproduced from the corresponding regression component patterns. Thus, regression score components or factor score coefficients can be rotated in order to obtain the required properties. This idea is the basis for MR factor score predictors, which are computed by means of a partial Procrustes rotation towards a target pattern representing the interesting properties of a confirmatory factor model. Two examples demonstrate the construction of MR factor score predictors reflecting specific constraints of a factor model.