Researcher degrees of freedom and small sample sizes pose significant challenges to replicability in personality neuroscience. The CoScience EEG-Personality Project tackles these issues through an unprecedented large-scale, multi-laboratory effort (N ~ 800), bringing together ten research teams across Germany. All hypotheses were pre-registered and discussed in large collaborative teams to foster transparency and consensus building. To further enhance methodological rigor, the project employs cooperative forking path analysis (cFPA), a novel approach to systematically evaluate EEG preprocessing pipelines while limiting researchers’ degrees of freedom. This symposium will present first results from four subprojects, share insights from this multi-site EEG collaboration, and discuss both the challenges and opportunities of large-scale, consensus-driven research.

First, Katharina Paul will examine the Late Positive Potential in response to erotic images (same- and opposite-sex individuals), while considering the influence of gender and menstrual cycle phase on affective processing.

Second, Corinna Kührt associates dispositional willingness to invest cognitive effort with neurophysiological correlates of effort exertion (frontal midline theta power, N2, and P3 amplitudes) in a flanker task.

Third, Philipp Bierwirth reports findings on the association between dispositional anxiety and brain-heart communication, assessed via the feedback-triggered N300H during a gambling task.

Fourth, Johannes Rodrigues discusses the importance of cognitive effort and control to overcome default behavior in the ultimatum game considering: Reaction time,

electrocortical correlates, and relevant traits

Fifth, Christoph Frühlinger will investigate the predictability of fluid and crystallized intelligence from resting-state EEG and assess the CoScience dataset’s integrity by replicating reported associations between state sleepiness and brain power.

This study investigates gender differences in neural responses to erotic stimuli using the Late Positive Potential (LPP), an established EEG measure of emotional and motivational processing. Utilizing an extensive dataset from the multi-site CoScience EEG-Personality Project (N = 741), we examined the neural reactivity during a response matching task involving visual stimuli. Consistent with prior research, erotic images reliably elicited greater LPP amplitudes compared to non-erotic images, thus validating their motivational significance and salience. More notably, within this heterosexual sample men demonstrated significantly heightened LPP responses than women when viewing opposite-sex erotic images. Conversely, women exhibited somewhat larger LPP amplitudes to same-sex erotic images, consistent with theories suggesting greater sexual fluidity among women. These patterns were also reflected in subjective ratings, with women rating same-sex images as more positive and arousing than men. Modest effects of menstrual cycle phases on women's neural responses to erotic versus non-erotic images did not match expectations and were only observed in additional exploratory analyses. Furthermore, supplementary cooperative forking path analysis provided rich information on the robustness of these results. Overall, these results highlight the complexity of gender and hormonal influences on sexual responses, emphasizing the importance of large-scale studies for capturing subtle individual differences.

Individuals differ in their willingness and tendency to exert effortful control – a trait referred to as cognitive effort investment. The concept integrates the traits need for cognition, intellect, self-control and effortful control and predicts effort investment in goal-directed behavior. This study investigates the role of dispositional differences in cognitive effort investment during the processing of a flanker task. We focused on the effects on performance (i.e. reaction time, accuracy) and the amount of cognitive effort actually invested (i.e. frontal midline theta power, P3 and N2 amplitudes derived from EEG). Analyses of N ~ 780 participants reveal that differences between subjects explain 8 to 26 % of the variance. However, the results yield neither a main effect of cognitive effort investment nor an interaction effect between cognitive effort investment and demand. These results were robustly shown across the cooperative Forking Path Analysis (cFPA), i.e. independent of pre-processing and analytical choices. Data collection was distributed across ten different labs in Germany; data collection procedures were highly standardized (including material and training of experimenters). We will address how different sources of inter-laboratory variability influence the outcomes.

Communication between the brain and heart is generally adaptive. However, aberrant brain-heart coupling may contribute to pathological anxiety. This coupling can be assessed via the feedback-triggered N300H component, derived from EEG and ECG recordings. The N300H has been shown to be elevated in patients with panic disorder and to correlate with dispositional anxiety, making it a potential biomarker for anxiety in humans. However, the link between dispositional anxiety and brain-heart coupling has yet to be replicated.

To address this, 662 participants were examined as part of the multi-laboratory Coscience project. EEG and ECG were recorded during a gambling task in which participants could win or lose money on each trial, and the N300H was quantified in response to feedback presentation. Dispositional anxiety was assessed using the Behavioral Inhibition Scale. Additionally, a cooperative forking path analysis (cFPA) was employed to test the robustness of the results across different preprocessing pipelines, thereby reducing researchers’ degrees of freedom.

Although a robust N300H was observed in response to feedback, no association between dispositional anxiety and the N300H was found. Moreover, results from the cFPA suggest that this null finding is independent of the chosen preprocessing pipeline.

In sum, this study failed to replicate the previously reported association between dispositional anxiety and elevated brain-heart coupling. Potential reasons for this null finding and ways to bridge the gap between biological measures and personality traits will be discussed.

Decision-making in social bargaining scenarios, such as the Ultimatum Game (UG), are influenced by the offer fairness, but also by dispositional traits and neurophysiological processes representing evaluation (feedback negativity: FRN) and cognitive effort and cognitive control to overcome default behavior (midfrontal theta: MFT). However, the importance of the evaluation of the offer (FRN) has often been prioritized lately to predict behavior.

The present study investigated how offer fairness (high/middle/low), electrocortical correlates of cognitive effort / cognitive control (MFT) and offer evaluation (FRN) as well as individual differences in need for cognition (NFC) shape decision behavior and reaction time as a receiver in the UG. Data were collected as part of the CoScience EEG-Personality Project, a large-scale multi-site study comprising approximately 800 participants.

As preregistered, more unfair offers led to more rejection behavior, reaction times were slowest in the middle offer category and rejections were linked to longer reaction times. Also, partly matching predictions, MFT was a better predictor than FRN for offer rejection, high MFT led to rejection and NFC was linked to rejection of low offers.

These findings highlight the importance of the cognitive control and cognitive effort needed to overcome the behavioral default to accept all offers in the UG on several levels: Reaction time, electrocortical correlates of decision processes (MFT) and personality traits (NFC). They question fixation on outcome evaluation markers like FRN in the context of behavioral prediction.

Previous electroencephalogram (EEG) studies linked measures of spectral power under rest and fluid intelligence; however, subsequent high-powered studies challenged this relationship. The present study aimed to address previous limitations (low statistical power, lack of preregistration) and investigate the predictability of intelligence measures from resting-state EEG in the CoScience data set (N = 772). Support vector regressions were applied to analyze eight minutes of resting-state EEG with eyes open and closed before and after unrelated tasks. The decoding performance between the spectral power of 59 EEG channels within 30 frequency bins and fluid and crystallized intelligence, was evaluated with a 10-fold cross-validation. We could not identify any meaningful associations between resting-state EEG spectral power and either fluid or crystallized intelligence. However, we replicated the previously reported association between state sleepiness and theta power, attesting to the integrity of the CoScience data set. Furthermore, the decomposition of the EEG signal into its periodic and aperiodic components revealed that the aperiodic offset parameter is significantly correlated with state sleepiness, emphasizing the relevance of aperiodic signal components in understanding states of alertness versus sleepiness.