André Beauducel

Behavioral approach and reward processing: results on feedback-related negativity and P3 component.

This study examined the FRN, the P3, and individual differences in trait-BAS and trait-BIS in the context of reward expectation mismatch. A more negative FRN was predicted for higher vs. lower trait-BAS individuals and for higher vs. lower trait-BIS individuals. In the extinction-learning task, participants (N=102) chose between two response buttons to earn a maximum of points. In the acquisition phase, button 1 was continuously rewarded and button 2 was partially rewarded. In the extinction phase, one button was unexpectedly no longer rewarded. The FRN amplitude was more negative for higher vs. lower trait-BAS individuals and for lower vs. higher trait-BIS individuals within the extinction phase. The P3 was more positive in the extinction compared to the acquisition phase. Our results suggest that higher trait-BAS individuals have a more pronounced reward expectation mismatch.

Cognitive performance before and after the onset of subjective cognitive decline in old age

Our objectives were (1) to test the association between the report of subjective cognitive decline (SCD) and prospective objective cognitive performance in high age individuals and (2) to study the course of longitudinal cognitive performance before and after the first report of SCD.

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.

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 Cronbachs 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.

Modeling the construct validity of the Berlin Intelligence Structure Model

The Berlin Intelligence Structure Model is a hierarchical and faceted model which is originally based on an almost representative sample of tasks found in the literature. Therefore, the Berlin Intelligence Structure Model is an integrative model with a high degree of generality. The present paper investigates the construct validity of this model by using different confirmatory factor analysis models. The results show that the model assumptions are supported only in part by the data. Moreover, it is demonstrated that there are different possibilities to incorporate the Berlin Intelligence Structure Model assumptions into confirmatory factor analysis models. The results are discussed with regard to the validity of the Berlin Intelligence Structure Model test, and the validity of the model.

Have you ever seen this face? - individual differences and event-related potentials during deception

Deception studies emphasize on the importance of event-related potentials (ERP) for a reliable differentiation of the underlying neuro-cognitive processes. The stimulus-locked parietal P3 amplitude has been shown to reflect stimulus salience but also attentional control available for stimulus processing. Known stimuli requiring truthful responses (targets) and known stimuli requiring deceptive responses (probes) were hypothesized to be more salient than unknown stimuli. Thus, a larger P3 was predicted for known truthful and deceptive stimuli than for unknown stimuli. The Medial Frontal Negativity (MFN) represents the amount of required cognitive control and was expected to be more negative to known truthful and deceptive stimuli than to unknown stimuli. Moreover, we expected higher sensitivity to injustice (SI-perpetrator) and aversiveness (Trait-BIS) to result in more intense neural processes during deception. Nu2009=u2009102 participants performed a deception task with three picture types: probes requiring deceptive responses, targets requiring truthful responses to known stimuli, and irrelevants being associated with truthful responses to unknown stimuli. Repeated-measures ANOVA and fixed-links modeling suggested a more positive parietal P3 and a more negative frontal MFN to deceptive vs. irrelevant stimuli. Trait-BIS and SI-perpetrator predicted an increase of the P3 and a decrease of the MFN from irrelevants to probes. This suggested an intensification of stimulus salience and cognitive control across picture types in individuals scoring either higher on Trait-BIS or higher on SI-perpetrator. In contrast, individuals with both higher Trait-BIS and higher SI-perpetrator scores showed a less negative probe-MFN suggesting that this subgroup invests less cognitive control to probes. By extending prior research we demonstrate that personality modulates stimulus salience and control processes during deception.

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 Spearmans and Wilsons 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.

How do working-memory-related demand, reasoning ability and aversive reinforcement modulate conflict monitoring?

Conflict monitoring is a process of stimulus evaluation and a pre-requisite for subsequent recruitment of cognitive control and behavioral adaptations. This study investigated how experimentally manipulated working-memory-related cognitive demand and aversive reinforcement modulate individual differences of conflict monitoring intensity and behavioral adjustments. Individual differences were assessed by means of an anxiety-related trait dimension (trait-BIS) and by means of reasoning abilities—a core determinant of intelligence. Moreover, we investigated the special role of verbal reasoning ability and figural reasoning ability for the modulation of the conflict monitoring intensity. Ninety participants performed a go/nogo task with four conditions each comprising a combination of low vs. high working-memory-related cognitive demand and low vs. high aversive reinforcement. No effect of aversive reinforcement was observed for the N2 amplitude. The fronto-central nogo N2 amplitude was more pronounced for high demand vs. low demand suggesting that cognitive demand served as an aversive costly event. Higher total reasoning abilities were associated with more intense conflict monitoring and shorter response times with increasing aversive reinforcement (defined as verbal error-feedback vs. monetary loss). Individuals with higher trait-BIS scores demonstrated a more intense conflict monitoring even in conditions with low aversive reinforcement and also a more cautious responding (i.e., response times slowing) with increasing aversive reinforcement indicating a focus on negative feedback prevention. The findings provide evidence for the conflict monitoring theory and suggest that working-memory-related demand overrules the impact of aversive reinforcement on conflict monitoring intensity. Reasoning abilities and anxiety-related traits go along with an intensification of conflict monitoring but differences in the flexibility of behavioral adjustment.

Reliability Estimates for Three Factor Score Estimators

Estimates for the reliability of Thurstones regression factor score predictor, Bartletts factor score predictor, and McDonalds factor score predictor were proposed. As in Kuder-Richardsons formula, the reliability estimates are based on a hypothetical set of equivalent items. The reliability estimates were compared by means of simulation studies. Overall, the reliability estimates were largest for the regression score predictor, so that the reliability estimates for Bartletts and McDonalds factor score predictor should be compared with the reliability of the regression score predictor, whenever Bartletts or McDonalds factor score predictor are to be computed. An R-script and an SPSS-script for the computation of the respective reliability estimates is presented.

Taking the Error Term of the Factor Model into Account: The Factor Score Predictor Interval.

The problem of factor score indeterminacy implies that the factor and the error scores cannot be completely disentangled in the factor model. It is therefore proposed to compute Harman’s factor score predictor that contains an additive combination of factor and error variance. This additive combination is discussed in the framework of classical test theory. On this basis, a definition of reliability, standard error of measurement, and confidence intervals for the factor score predictor are proposed. It is argued that factor score predictor intervals should be used instead of single score predictors to account for the error term in the factor model. The calculation of reliabilities and factor score predictor intervals is illustrated by means of a small simulation study and an empirical example.