John P Grogan

Modeling Speed–Accuracy Trade-Offs in the Stopping Rule for Confidence Judgments! Now out in #PsychologicalReview (aka we can finally say we do comp models)! Led by @stefherregods.bsky.social @lucvermeylen.bsky.social @pierreledenmat.bsky.social

Paper: desenderlab.com/wp-content/u... Thread ↓↓↓

Reformation of science publishing: the Stockholm Declaration | Royal Society Open Science Science relies on integrity and trustworthiness. But scientists under career pressure are lured to purchase fake publications from ‘paper mills’ that use AI-generated data, text and image fabrication....

Newly released Stockholm Declaration recommends the following reforms to publishing:

1. Academia resumes control of publishing

2. Incentive systems to merit quality, not quantity

3. Independent fraud detection and prevention

4. Legislation and policies to protect science quality and integrity

The current environment is making it near impossible to run clinical trials in the UK.
One key issue discussed in @brain1878.bsky.social
is the duplication - or worse - of regulatory oversight at NHS hospitals & universities.

My views on how to change the system
academic.oup.com/brain/articl...

Check out our reviewed preprint, now out in eLife!
With @spk3lly.bsky.social, @redmondoconnell.bsky.social and Anna Geuzebroek

elifesciences.org/reviewed-pre...

While we work on improving the [solid] paper based on the reviews, here are the key take-home messages:

"Learning to be confident: How agents learn confidence based on prediction errors"! Now out in @cognitionjournal.bsky.social led by @pierreledenmat.bsky.social

Paper: desenderlab.com/wp-content/u... Thread ↓↓↓

#AcademicSky #PsychSciSky #Neuroscience #Neuroskyence

Introducing hMFC: A Bayesian hierarchical model of trial-to-trial fluctuations in decision criterion! Now out in @plos.org Comp Bio.
led by Robin Vloeberghs with @anne-urai.bsky.social Scott Linderman

Paper: desenderlab.com/wp-content/u... Thread ↓↓↓

#PsychSciSky #Neuroscience #Neuroskyence

does someone good at coding & analysis want to work remotely w/ us in the coming few months (before end of 2025), as a paid consultant? project will be on neurofeedback (fMRI, ECoG, calcium imaging). we'll work towards developing the experiments & analysis pipelines together. if so pls DM me ur CV🧠📈

Neurally-informed modelling unravels a single evidence accumulation process for choices and subsequent confidence reports Subjective confidence in perceptual choices depends on computations occurring prior to and after choice commitment. However, the nature of these computations remains unclear. Current models disagree o...

Read the paper to see how assumptions about initial-decisions (e.g. collapsing-boundaries) influence post-decision confidence model computations and comparisons, and how we went about simulating a CPP proxy signal (doi.org/10.1101/2025...)

Overall, we found and that post-decision confidence can be explained by a Single accumulation process that continues from initial decision until reaching a post-decision collapsing confidence-boundary, and comparing models' decision-dynamics to the CPP can distinguish behaviourall-similar models.

CPP and model-DVs for confidence Speed-pressure effects. CPP is larger in Speed condition, but model-DVs predict the opposite effect

to get Certainty effects before the initial choice, as we have seen previously (e.g. Grogan et al., 2023).

No model could replicate a surprising result; that the CPP was larger when speed-pressure (short deadline) was applied to the confidence-ratings, suggesting additional mechanisms at play...

observed CPP and model-simulated Decision Variables, for different Certainty ratings, showing Boundary-Single model replicated CPP effect better

Boundary-Single models could replicate the effects of Certainty we saw on the CPP, while Boundary-Distinct could not, especially for pre-choice effects.
Having pre- and post-choice as a Single process allows evidence-info to carry over and inform certainty ratings, which seems to be necessary...

behavioural data and model-fit data, showing Time-based models cannot replication decreasing accuracy or certainty for slower confidence-RTs, while Boundary-models give similarly good fits.

there was little difference between Boundary models where the pre- and post-decision accumulation processes were Distinct or a Single process, when looking at behavioural fits.
However, simulating Decision-Variable accumulation traces allowed us to compare these different mechanisms directly...

Illustration of the four confidence models we tested - Time or Boundary based stopping rules, and Single or Distinct pre- and post-decision accumulation processes.

on a task with long or short post-decision deadlines to rate confidence, which induced a post-decision/confidence speed-accuracy trade-off.
Post-decision accumulation was better explained by accumulation to collapsing confidence-boundaries, than by a Time-based stopping rule, but...

Different confidence models can give very similar behavioural predictions, making it hard to compare them, but they often make different predictions for the decision dynamics. We simulated Decision Variable traces, and compared them to a neural metric of evidence accumulation, the CPP...

Neurally-informed modelling unravels a single evidence accumulation process for choices and subsequent confidence reports Subjective confidence in perceptual choices depends on computations occurring prior to and after choice commitment. However, the nature of these computations remains unclear. Current models disagree o...

Our newest preprint is out (doi.org/10.1101/2025.06.05.658071), with @lucvermeylen.bsky.social,Dasha Monakhovych, Cameron McCabe, Sarah-Louise Mannion, @kobedesender.bsky.social, @redmondoconnell.bsky.social, comparing post-decision confidence models against behaviour and neural decision signals...

Metacognitive sensitivity: The key to calibrating trust and optimal decision making with AI Abstract. Knowing when to trust and incorporate the advice from artificially intelligent (AI) systems is of increasing importance in the modern world. Rese

Led by postdoc Doyeon Lee and grad student Joseph Pruitt, our lab has a new Perspectives piece in PNAS Nexus:

"Metacognitive sensitivity: The key to calibrating trust and optimal decision-making with AI"

academic.oup.com/pnasnexus/ar...

With co-authors Tianyu Zhou and Eric Du 1/

Dissociable encoding of evolving beliefs and momentary belief updates in distinct neural decision signals - Nature Communications People are capable of making near-optimal decisions in volatile, changing environments. Here, the authors show how two neural decision signals encode distinct aspects of the belief updating process un...

Very happy to share this paper, now published in
@natcomms.nature.com! nature.com/articles/s41...
With @spk3lly.bsky.social and @neuromurphy.bsky.social, we investigated the neural computations that allow us to make near-optimal decisions in changing environments. Here's a short summary:

1. LLM-generated code tries to run code from online software packages. Which is normal but
2. The packages don’t exist. Which would normally cause an error but
3. Nefarious people have made malware under the package names that LLMs make up most often. So
4. Now the LLM code points to malware.

PhD position in cognitive computational neuroscience PhD position in cognitive computational neuroscience

PhD position in cognitive computational neuroscience! Join us, & investigate how we can endow domain-specific models of vision (eg DNNs) with domain-general processes such as metacognition or working memory.
All details => www.kuleuven.be/personeel/jo...
#PsychSciSky #Neuroscience #Neuroskyence

Why academia is sleepwalking into self-destruction. My editorial @brain1878.bsky.social If you agree with the sentiments please repost. It's important for all our sakes to stop the madness
academic.oup.com/brain/articl...

Ever wondered how basketball players know when their throws are in/out?
L. Brun & @perrineporte.bsky.social asked players to rate confidence in their throws under variable visual feedback.
Turns out vision helps adjust confidence in successful, but not failed throws:
papers.ssrn.com/sol3/papers....

🚨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...

How is confidence related to confidence RTs? @stefherregods.bsky.social @lucvermeylen.bsky.social and I showcase how our recent EAM of confidence accounts for various relationships observed in empirical data.

link: pmc.ncbi.nlm.nih.gov/articles/PMC...
#PsychSciSky #Neuroscience #Neuroskyence

Muscarinic receptors mediate motivation via preparatory neural activity in humans Muscarinic antagonism is causally involved in motivation and incentivisation in healthy human participants, partially mediated via preparatory neural signatures, with implications for cholinergic trea...

Pleased that our work from my previous postdoc with Sanjay Manohar is finally published!
Muscarinic antagonism reduces motivation & invigoration in humans, mediated by changes in preparatory EEG signals: doi.org/10.7554/eLif...