#EEGManyLabs @eegmanylabs.bsky.social · 15/05/2026Open data, transparent pipelines, better estimates. #EEGManyLabs #EEG #OpenScience 000
#EEGManyLabs @eegmanylabs.bsky.social · 15/05/2026Our replication study highlights why open science practices are essential for estimating effect sizes realistically. Preregistered, large-scale multi-site EEG work can help us separate robust neural phenomena from effects that can vary heavily on analytic choices or publication bias. 111
#EEGManyLabs @eegmanylabs.bsky.social · 15/05/2026The take-home: CDA appears to be a robust marker of visual working memory load, but its relationship with individual differences in capacity is much smaller and less reliable than previously assumed. 100
#EEGManyLabs @eegmanylabs.bsky.social · 15/05/2026We also looked back at the broader literature. Funnel-plot diagnostics suggested small-study effects and possible selective reporting, meaning earlier strong CDA-capacity correlations may have been overestimated. 110
#EEGManyLabs @eegmanylabs.bsky.social · 15/05/2026The original study reported a very large association, r = .78. In our multi-site replication, the estimate was much smaller, around r = .15 across pipelines and analyses, and non-significant in the preregistered meta-analytic tests. 101
#EEGManyLabs @eegmanylabs.bsky.social · 15/05/2026The more complicated news: The predicted correlation between the CDA increase from set size 2 to 4 and individual visual working memory capacity did not replicate in the preregistered analyses. 100
#EEGManyLabs @eegmanylabs.bsky.social · 15/05/2026The good news: CDA amplitude reliably increased from set size 2 to 4, and from set size 2 to 6. There was little evidence for a further increase from 4 to 6, consistent with the expected plateau. So CDA clearly tracks memory load. 100
#EEGManyLabs @eegmanylabs.bsky.social · 15/05/2026We ran a preregistered, multi-site replication of this key result across 10 laboratories, with 304 participants recruited, a common task, and shared analysis plans. The goal was not just “does CDA exist?”, but “how large and reliable are these effects?” 100
#EEGManyLabs @eegmanylabs.bsky.social · 15/05/2026Since Vogel & Machizawa’s Nature (2004) paper, the classic claim has had two parts: a. CDA amplitude increases as people hold more items in mind up to a certain limit - ~4 items. And b) the size of that CDA increase predicts who has higher visual working memory capacity. doi.org/10.1038/natu...doi.orgNeural activity predicts individual differences in visual working memory capacity - NatureNature - Neural activity predicts individual differences in visual working memory capacity 121
#EEGManyLabs @eegmanylabs.bsky.social · 15/05/2026CDA is a workhorse signal in visual working memory research. In lateralised change-detection tasks, activity contralateral to the remembered items becomes more negative during the delay period. That delay-period asymmetry is what we call the CDA. 100
#EEGManyLabs @eegmanylabs.bsky.social · 15/05/2026New #EEGManyLabs paper out in Cortex! We asked whether contralateral delay activity, or CDA, can serve as a reliable EEG marker of visual working memory capacity. doi.org/10.1016/j.co...doi.orgRedirecting 12815
Reposted by #EEGManyLabsEEG101 COST Action @eeg101costaction.bsky.social · 18/03/2026📢 EEG101 funding calls are now open Available grants: 🔬 Research visits (STSMs) – up to €4000 🎤 Conference dissemination grants – up to €2500 🌐 Virtual mobility grants – up to €1500 🗓 Deadline: 3 April 2026 – 17:00 CET Details & eligibility: www.eeg101.eu/grants #EEG #Neuroscience #OpenScienceeeg101.euGrantsEEG101 COST Action 066
#EEGManyLabs @eegmanylabs.bsky.social · 20/08/2025Follow #EEGManyLabs on X and Bluesky for updates, threads on specific studies, and new Stage 2 results as they appear. Share the site with your lab and collaborators. Let’s build better EEG together. 000
#EEGManyLabs @eegmanylabs.bsky.social · 20/08/2025Huge thanks to our community. Your contributions power inclusive, rigorous, high-impact EEG science. 100
#EEGManyLabs @eegmanylabs.bsky.social · 20/08/2025Cap-E will guide you through related projects, spin-offs, and associated initiatives. This includes EEG100 celebrating 100 years of EEG (see dx.doi.org/10.1038/s415...) and the pan-European network EEG101 COST Action (www.cost.eu/actions/CA24...).dx.doi.orgOne hundred years of EEG for brain and behaviour research - Nature Human BehaviourOn the centenary of the first human EEG recording, more than 500 experts reflect on the impact that this discovery has had on our understanding of the brain and behaviour. We document their priorities... 111
#EEGManyLabs @eegmanylabs.bsky.social · 20/08/2025We are also introducing our new mascot, Professor Cap-E (thank you to Aleksei Medvedev for the design). 130
#EEGManyLabs @eegmanylabs.bsky.social · 20/08/2025 It is not too late to join a replication team. Several projects are still recruiting new labs. You will find sign-up forms on the Replications page. 100
#EEGManyLabs @eegmanylabs.bsky.social · 20/08/2025You will find Stage 1 protocols and Stage 2 results, with links to data, code, and materials. Including a recently completed 22-lab replication of the foundational N2pc study by Eimer (1996): dx.doi.org/10.1016/j.co...dx.doi.orgRedirecting 100
#EEGManyLabs @eegmanylabs.bsky.social · 20/08/2025#EEGManyLabs website is now live: eegmanylabs.org A home for our global effort to test the replicability of influential EEG findings, share resources, improve methods in cognitive neuroscience, and grow an open, connected community.eegmanylabs.orgeegmanylabs 15536
Reposted by #EEGManyLabsThe Transmitter @thetransmitter.bsky.social · 30/05/2025The first published paper to emerge from @eegmanylabs.bsky.social settles a debate 20 years in the making. Read more in this month’s Null and Noteworthy. By @ldattaro.bsky.social www.thetransmitter.org/null-and-not...thetransmitter.orgNull and Noteworthy—Learning theory validated 20 years laterThe first published paper from EEGManyLabs’ replication project nullifies a null result that had complicated a famous reinforcement learning theory. 0106
#EEGManyLabs @eegmanylabs.bsky.social · 07/02/2025This is just the first in our #EEGManyLabs series—showing how collaborative EEG science can refine major theories. Watch this space for more. In the meantime, read the full paper for the deep dive: doi.org/10.1016/j.co... Huge thanks to all labs involved!doi.orgRedirecting 000
#EEGManyLabs @eegmanylabs.bsky.social · 07/02/2025One of the best parts? ✅ Minimal heterogeneity. ✅Across different EEG systems & participant samples, the pattern held strong, suggesting we have a robust and generalizable result. 110
#EEGManyLabs @eegmanylabs.bsky.social · 07/02/2025The P300 also wasn’t as simple as “expectancy-only: we found both expectancy and valence effects. This implies that feedback evaluation is spread across multiple stages, rather than being sharply split into “FRN for valence” and “P300 for expectancy.” 100
#EEGManyLabs @eegmanylabs.bsky.social · 07/02/2025The original study had only 17 participants—typical for its time but underpowered (~40% power). Our larger sample detected the small-to-moderate expectancy effect (ηp² = .08—identical to the original!). 🚫 Reminder: Absence of evidence ≠ Evidence of absence! 100
#EEGManyLabs @eegmanylabs.bsky.social · 07/02/2025🚨 Results: The FRN isn’t just about valence! 🚨 It was significantly modulated by both: ✅ Valence (reward vs. no reward) ✅ Expectancy (expected vs. unexpected) These results align more with Holroyd & Coles’ prediction error theory than Hajcak et al.’s original conclusion. 100
#EEGManyLabs @eegmanylabs.bsky.social · 07/02/2025We put this to the test across 13 labs with 359 participants worldwide—a massive jump from the original n=17! Our goal? 🧐 🔍 Does the FRN really ignore expectancy? 🔍 Is the P300 only about surprises? 100
#EEGManyLabs @eegmanylabs.bsky.social · 07/02/2025A new “two-stage” model proposed: ✅ FRN tracks valence (good vs. bad outcome) ✅ P300 tracks expectancy (surprise factor) With 600+ citations, this study has shaped how researchers interpret feedback-locked ERPs. 100
#EEGManyLabs @eegmanylabs.bsky.social · 07/02/2025But Hajcak et al. (2005) found something different: They found the FRN only distinguished reward vs. no reward, NOT whether an outcome was expected. 🤯 This challenged Holroyd & Coles’ reinforcement-learning theory and led to a new interpretation of feedback processing. 100
#EEGManyLabs @eegmanylabs.bsky.social · 07/02/2025The original study (Hajcak, Holroyd, Moser, & Simons, 2005) tested a highly influential idea: Holroyd & Coles (2002) reinforcement learning model proposed that the FRN (feedback-related negativity) signals a better/worse-than-expected dopamine-driven prediction error. 110
#EEGManyLabs @eegmanylabs.bsky.social · 07/02/2025🚨Exciting news! We now have the first-ever complete #EEGManyLabs replication. This large-scale multi-site study revisits a key debate in EEG & reinforcement learning. A thread! 🧵👇 📄 Full paper: doi.org/10.1016/j.co...doi.orgRedirecting 2156