Paul Bays

Computational cognitive scientist, Professor at University of Cambridge.

[Paul Bays @BaysLab]

Our review of Bayesian efficient coding as a theory of perception is out now in TICS – with Ivan Tomić and Máté Lengyel. https://t.co/mEpyKjjvfv

[Paul Bays @BaysLab]

Just published open access in 𝘗𝘴𝘺𝘤𝘩𝘰𝘭𝘰𝘨𝘪𝘤𝘢𝘭 𝘔𝘦𝘵𝘩𝘰𝘥𝘴: “𝗪𝗼𝗿𝗸𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗖𝗶𝗿𝗰𝘂𝗹𝗮𝗿 𝗗𝗮𝘁𝗮: 𝗔 𝗧𝘂𝘁𝗼𝗿𝗶𝗮𝗹 𝗳𝗼𝗿 𝗖𝗼𝗴𝗻𝗶𝘁𝗶𝘃𝗲 𝗮𝗻𝗱 𝗕𝗲𝗵𝗮𝘃𝗶𝗼𝗿𝗮𝗹 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵”

🔗 https://t.co/tXR8jY2EuI

#CircularStatistics

[Paul Bays @BaysLab]

#WorkingMemory #ReinforcementLearning #Cognition #Vision

[Paul Bays @BaysLab]

The rich get richer in visual processing: latest study with Ivan Tomic shows that we allocate resources preferentially to stimuli that we feel confident in estimating, which makes us better at estimating them...even if the initial confidence was misplaced https://t.co/xkRfsZ28pq

[Paul Bays @BaysLab]

Do the contents of visual working memory deteriorate more quickly when more items are being remembered? Seems a straightforward question but we had to bring together 13 studies and >120,000 trials to get definitive answers... https://t.co/EKLtQUjpfC

[Paul Bays @BaysLab]

Our lab is at ECVP this week, giving one talk and presenting three posters. Come and say hi!

[Paul Bays @BaysLab]

Our lab is now on LinkedIn: https://t.co/5eeRSp95bJ

[Paul Bays @BaysLab]

New work on sensory prediction resolves some long-standing puzzles about attenuation of self-touch https://t.co/xEzPIib3GV

[Paul Bays @BaysLab]

Now out in Comms Psych: the "anti-Bayesian" size-weight illusion is a consequence of the brain focusing resources on encoding typical combinations of size and weight (i.e. "efficient coding"). Explains the material-weight illusion too https://t.co/lM6K8Rhdxn

[Paul Bays @BaysLab]

We have an opening for a postdoc to work on a collaborative project with @lengyel_m (UCambridge Engineering) combining machine learning methods with human experiments on visual perception and memory https://t.co/x7DrFzxRhg

[Ethan Mollick @emollick]

👀Claude handles an insane request:
“Remove the squid”

“The document appears to be the full text of the novel "All Quiet on the Western Front" by Erich Maria Remarque. It doesn't contain any mention of squid that I can see.”

“Figure out a way to remove the 🦑​​​​​​​​​​​​​​​​“

[Paul Bays @BaysLab]

A systematic dissection of the analogue report methodology and comparison with "gold-standard" 2AFC. Key findings: motor noise is negligible; analogue report error is a robust measure of memory fidelity, but may underestimate perceptual precision https://t.co/PQ9BleY2Az

[Paul Bays @BaysLab]

Almost two years in the making!

[Paul Bays @BaysLab]

Out now in NHB (finally!), a review of visual working memory from a computational perspective, with @weijima01 @timothyfbrady and Sebastian Schneegans. https://t.co/IypKOGd427

[Paul Bays @BaysLab]

Nice commentary from @salinas_urgent and @mangosheikh_B on our new eLife paper https://t.co/6d0scJC6Dg

[Paul Bays @BaysLab]

@gershbrain @PhilCorlett1 @chazfirestone Yes, I believe so. It's a dramatic demo (I tried it at VSS once) but doesn't need any extra mechanism to explain it over the standard illusion.

[Paul Bays @BaysLab]

The size-weight illusion is a by-product of efficient sensory coding adapted to the combinations of volume and mass found in everyday objects. New preprint https://t.co/RSBE8KT6Oh

[John B. Holbein @JohnHolbein1]

“Among articles stating that data was available upon request, only 17% shared data upon request.”

https://t.co/L84lnKMgPn

[Paul Bays @BaysLab]

We measured how effectively observers can reallocate working memory resources to new visual items when old ones become obsolete - people are surprisingly good at it! New paper with @ivntmc @dataforyounz @DAagtenMurphy https://t.co/EOS8mgu3LV

[Chaz Firestone @chazfirestone]

The difference between saccades and smooth pursuit eye movements, as demonstrated by sticking gross plastic thingies on your eyeballs

https://t.co/vuiWBgFTh4