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BackgroundCognitive dysfunction is a major feature of Parkinson’s disease (PD), but the pathophysiology remains unknown. One potential mechanism is abnormal low-frequency cortical rhythms which engage cognitive functions and are deficient in PD. We tested the hypothesis that mid-frontal delta/theta rhythms predict cognitive dysfunction in PD.MethodWe recruited 100 patients with PD and 49 demographically similar control participants who completed a series of cognitive control tasks, including the Simon, oddball and interval-timing tasks. We focused on cue-evoked delta (1–4 Hz) and theta (4–7 Hz) rhythms from a single mid-frontal EEG electrode (cranial vertex (Cz)) in patients with PD who were either cognitively normal, with mild-cognitive impairments (Parkinson’s disease with mild-cognitive impairment) or had dementia (Parkinson’s disease dementia).ResultsWe found that PD-related cognitive dysfunction was associated with increased response latencies and decreased mid-frontal delta power across all tasks. Within patients with PD, the first principal component of evoked electroencephalography features from a single electrode (Cz) strongly correlated with clinical metrics such as the Montreal Cognitive Assessment score (r=0.34) and with National Institutes of Health Toolbox Executive Function score (r=0.46).ConclusionsThese data demonstrate that cue-evoked mid-frontal delta/theta rhythms directly relate to cognition in PD. Our results provide insight into the nature of low-frequency frontal rhythms and suggest that PD-related cognitive dysfunction results from decreased delta/theta activity. These findings could facilitate the development of new biomarkers and targeted therapies for cognitive symptoms of PD.

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.

Unexpected events can have internal causes (action errors) as well as external causes (perceptual novelty). Both events call for adaptations of ongoing behavior, resulting, amongst other things, in post-error and post-novelty slowing (PES/PNS) of reaction times (RT). Both types of events are processed in prefrontal brain areas, indexed by event-related potentials (ERPs): Errors are followed by a complex of ERPs comprised of the error-related negativity (ERN) and error positivity (Pe), whereas novels are followed by a N2/P3 complex. However, despite those overlapping properties, past neuroscientific studies of both types of events resulted in largely separate branches of research. Only recently have theoretical efforts proposed overlapping neuronal networks for the computation of ‘unexpectedness’ in general. Crucially, in a recent study, we have shown that both errors and novelty are indeed processed in the same neuronal network in the human brain: the prefrontal-cingulate performance-monitoring network (PCMN) underlying the ERN also explained significant parts of the N2/P3 complex.