What's the deal with drift rate variability in the Diffusion Model of decision-making? Find out in our newest publication in Computational Brain and Behaviour Led by @jie-sun.bsky.social + @adamosth.bsky.social Come for the slow errors, stay for the joint modelling w/ EEG rdcu.be/e85Re

New paper in Psych Review on a model of false recognition in Deese-Roediger-McDermott DRM task. Not just recognition responses, but also associated RTs! And not just the semantic task, but also the structural task - where words overlap in orthography/phonology! A thread!

Never truly understood what people meant by 'stretched too thin' until I was stretched too thin.

Using EEG 🧠⚡ and representational similarity analysis, we mapped how the neural representations of food attributes (e.g., taste & health) unfold over time when viewing foods🍎🍰🥗 @danfeuerriegel.bsky.social @tgro.bsky.social theconversation.com/our-brains-e... doi.org/10.1016/j.ap...

Honey, we fixed Signal Detection Theory (SDT)! In this preprint, Constantin Meyer-Grant, David Kellen, Sam Harding, and I critically evaluate the (unequal-variance) Gaussian SDT model in recognition memory and pursue the Gumbel-min model as a principled alternative: doi.org/10.31234/osf... 🧵

Extreme-Value Signal Detection Theory for RecognitionMemory: The Parametric Road Not Taken

Signal Detection Theory has long served as a cornerstone of psychological research, particularly in recognition memory. Yet its conventional application hinges almost exclusively on the Gaussian…

doi.org

What if forgetting was not the result of time erasing memories but interference from new, similar experiences? It was what Dr Raina Zhang from the Complex Human Data Hub calls a “mind-blowing” theory that set her on the path to study the mechanisms behind memory. Learn more: go.unimelb.edu.au/ut7p

Meet Dr Raina Zhang: the researcher redefining how we understand memory and forgetting

Meet Dr Raina Zhang: the researcher redefining how we understand memory and forgetting

go.unimelb.edu.au

🧠 New preprint alert! In this study, using a joint modelling method with the Diffusion Decision Model, we offer a mechanistic reinterpretation of the Late Positive event-related potential Component (LPC) as a neural signature of mnemonic strength during evidence accumulation in recognition memory.

bioRxivpreprint@biorxivpreprint.bsky.social · last yr.

A Parietal Memory Strength Signal Linked to Evidence Accumulation in Recognition Decisions https://www.biorxiv.org/content/10.1101/2025.07.20.665783v1

We recently updated our preprint that explains how to deal with unidentifiability constraints when measuring participants' decision-making cognition as well as introducing new methods to measure participants' decision-making cognition from brain+behavioral data osf.io/preprints/ps...

🚨New Pre-print is out! What causes the drift rate to vary across trials? How much does the drift rate variability estimate in the Diffusion Decision Model reflect the true variability? Here, we critically examined this by including trial-level regressors of drift rate. osf.io/preprints/ps...