John P Grogan
@johnpgrogan1.bsky.social
96 followers 140 following 9 posts
Cognitive neuroscience postdoc at Trinity College Dublin, developing models of neural activity during decision making. @[email protected]. @JohnPGrogan1 on twitter
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Reposted by John P Grogan
masudhusain.bsky.social
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...
Reposted by John P Grogan
epares.bsky.social
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:
Perceptual glimpses are locally accumulated and globally maintained at distinct processing levels
elifesciences.org
Reposted by John P Grogan
kobedesender.bsky.social
"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
Reposted by John P Grogan
kobedesender.bsky.social
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
Reposted by John P Grogan
hakwan.bsky.social
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🧠📈
johnpgrogan1.bsky.social
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.
johnpgrogan1.bsky.social
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...
CPP and model-DVs for confidence Speed-pressure effects. CPP is larger in Speed condition, but model-DVs predict the opposite effect
johnpgrogan1.bsky.social
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...
observed CPP and model-simulated Decision Variables, for different Certainty ratings, showing Boundary-Single model replicated CPP effect better
johnpgrogan1.bsky.social
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...
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.
johnpgrogan1.bsky.social
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...
Illustration of the four confidence models we tested - Time or Boundary based stopping rules, and Single or Distinct pre- and post-decision accumulation processes.
johnpgrogan1.bsky.social
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...
Reposted by John P Grogan
brianodegaard.bsky.social
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/
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
academic.oup.com
Reposted by John P Grogan
janelleshane.com
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.
daviddlevine.com
LLMs hallucinating nonexistent software packages with plausible names leads to a new malware vulnerability: "slopsquatting."
LLMs can't stop making up software dependencies and sabotaging everything
: Hallucinated package names fuel 'slopsquatting'
www.theregister.com
Reposted by John P Grogan
kobedesender.bsky.social
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
PhD position in cognitive computational neuroscience
PhD position in cognitive computational neuroscience
www.kuleuven.be
Reposted by John P Grogan
masudhusain.bsky.social
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...
Reposted by John P Grogan
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....
The Role of Visual Feedback in Metacognitive Judgments of Motor Performance
Predicting the outcome of one’s actions is crucial for effective behaviour. The mechanical underpinnings of this metacognitive ability are, however, poorly unde
papers.ssrn.com
Reposted by John P Grogan
jie-sun.bsky.social
🚨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...
OSF
osf.io
Reposted by John P Grogan
kobedesender.bsky.social
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