There is growing awareness across the neuroscience community that the replicability of findings about the relationship between brain activity and cognitive phenomena can be improved by conducting studies with high statistical power that adhere to welldefined and standardised analysis pipelines. Inspired by recent efforts from the psychological sciences, and with the desire to examine some of the foundational findings using electroencephalography (EEG), we have launched #EEGManyLabs, a large-scale international collaborative replication effort. Since its discovery in the early 20th century, EEG has had a profound influence on our understanding of human cognition, but there is limited evidence on the replicability of some of the most highly cited discoveries. After a systematic search and selection process, we have identified 27 of the most influential and continually cited studies in the field. We plan to directly test the replicability of key findings from 20 of these studies in teams of at least three independent laboratories. The design and protocol of each replication effort will be submitted as a Registered Report and peer-reviewed prior to data collection.Prediction markets, open to all EEG researchers, will be used as a forecasting tool to examine which findings the community expects to replicate. This project will update our confidence in some of the most influential EEG findings and generate a large open access database that can be used to inform future research practices. Finally, through this international effort, we hope to create a cultural shift towards inclusive, highpowered multi-laboratory collaborations.

Face cognition performance is related to individual differences in cognitive subprocesses, as reflected in the amplitudes and latencies of event-related brain potentials (ERPs; Herzmann, Kunina, Sommer, & Wilhelm, 2010). In order to replicate and extend these findings, 110 participants were tested on a comprehensive task battery measuring face cognition abilities and established cognitive abilities, followed by ERP recordings in a face-learning-and-recognition task. We replicated the links of the ERP components indicating the speed of structural face encoding (N170 latency) and access to structural representations in memory (early repetition effect [ERE]/N250r) with the accuracy and speed of face cognition and with established cognitive abilities. As a novel result, we differentiated between the accuracy of face perception and face memory on the behavioral and electrophysiological levels and report a relationship between basic visual processes (P100 amplitude) and face memory. Moreover, the brain-behavior relationships for the ERE/N250r held true, even though we eliminated pictorial and perceptual structural codes from the priming effects by using backward masking of the primes with novel unfamiliar faces. On a methodological level, we demonstrated the utility of the latent difference score modeling technique to parameterize ERP difference components (e.g., ERE/N250r) on a latent level and link them to face cognition abilities.

The rejection of unfair offers in the ultimatum game (UG) indicates negative reciprocity. The model of strong reciprocity claims that negative reciprocity reflects prosociality because the rejecting individual is sacrificing resources in order to punish unfair behavior. However, a recent study found that the rejection rate of unfair offers is linked to assertiveness (status defense model). To pursue the question what drives negative reciprocity, the present study investigated individual differences in the rejection of unfair offers along with their behavioral and neuronal determinants. We measured fairness preferences and event-related potentials (ERP) in 200 healthy participants playing a computerized version of the UG with pictures of unfair and fair proposers. Structural equation modeling (SEM) on the behavioral data corroborated both the strong reciprocity and the status defense models of human cooperation: Not only more prosocial but also more assertive individuals were more likely to show negative reciprocity by rejecting unfair offers. Experimental ERP results confirmed the feedback negativity (FN) as a neural signature of fairness processing. Multilevel SEM of brain-behavior relationships revealed that negative reciprocity was significantly associated with individual differences in FN amplitudes in response to proposers. Our results confirm stable individual differences in fairness processing at the behavioral and neuronal level.

Both emotion and reward are primary modulators of cognition: emotional word content enhances word processing, and reward expectancy similarly amplifies cognitive processing from the perceptual up to the executive control level. Here, we investigate how these primary regulators of cognition interact. We studied how the anticipation of gain or loss modulates the neural time course (event-related potentials, ERPs) related to processing of emotional words. Participants performed a semantic categorization task on emotional and neutral words, which were preceded by a cue indicating that performance could lead to monetary gain or loss. Emotion-related and reward-related effects occurred in different time windows, did not interact statistically, and showed different topographies. This speaks for an independence of reward expectancy and the processing of emotional word content. Therefore, privileged processing given to emotionally valenced words seems immune to short-term modulation of reward. Models of language comprehension should be able to incorporate effects of reward and emotion on language processing, and the current study argues for an architecture in which reward and emotion do not share a common neurobiological mechanism.

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