Frequency tagging of syntactic structure or lexical properties; a registered MEG study.

A traditional view on sentence comprehension holds that the listener parses linguistic input using hierarchical syntactic rules. Recently, physiological evidence for such a claim has been provided by Ding et al.'s (2016) MEG study that demonstrated, using a frequency-tagging paradigm, that regularly occurring syntactic constituents were spontaneously tracked by listeners. Even more recently, this study's results have been challenged as artifactual by Frank and Yang (2018) who successfully re-created Ding's results using a distributional semantic vector model that relied exclusively on lexical information and did not appeal to any hierarchical syntactic representations. The current MEG study was designed to dissociate the two interpretations of Ding et al.'s results. Taking advantage of the morphological richness of Russian, we constructed two types of sentences of different syntactic structure; critically, this was achieved by manipulating a single affix on one of the words while all other lexical roots and affixes in the sentence were kept the same. In Experiment 1, we successfully verified the intuition that due to almost complete lexical overlap the two types of sentences should yield the same activity pattern according to Frank and Yang's (2018) lexico-semantic model. In Experiment 2, we recorded Russian listeners' MEG activity while they listened to the two types of sentences. Contradicting the hierarchical syntactic account and consistent with the lexico-semantic one, we observed no difference across the conditions in the way participants tracked the stimuli properties. Corroborated by other recent evidence, our findings show that peaks interpreted by Ding et al. as reflecting higher-level syntactic constituency may stem from non-syntactic factors.

#EEGManyLabs: Investigating the replicability of influential EEG experiments.

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 well-defined 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, high-powered multi-laboratory collaborations.

Slow and Fast Responses: Two Mechanisms of Trial Outcome Processing Revealed by EEG Oscillations.

Cognitive control includes maintenance of task-specific processes related to attention, and non-specific regulation of motor threshold. Depending upon the nature of the behavioral tasks, these mechanisms may predispose to different kinds of errors, with either increased or decreased response time (RT) of erroneous responses relative to correct responses. Specifically, slow responses are related to attentional lapses and decision uncertainty, these conditions tending to delay RTs of both erroneous and correct responses. Here we studied if RT may be a valid approximation distinguishing trials with high and low levels of sustained attention and decision uncertainty. We analyzed response-related and feedback-related modulations in theta, alpha and beta band activity in the auditory version of the two-choice condensation task, which is highly demanding for sustained attention while involves no inhibition of prepotent responses. Depending upon response speed and accuracy, trials were divided into slow correct, slow erroneous, fast correct and fast erroneous. We found that error-related frontal midline theta (FMT) was present only on fast erroneous trials. The feedback-related FMT was equally strong on slow erroneous and fast erroneous trials. Late post-response posterior alpha suppression was stronger on erroneous slow trials. Feedback-related frontal beta was present only on slow correct trials. The data obtained cumulatively suggests that RT allows distinguishing the two types of trials, with fast trials related to higher levels of attention and low uncertainty, and slow trials related to lower levels of attention and higher uncertainty.