If you need to combine old and new information, you need to remember how much to weigh one vs the other. If you're imprecise about it, but with a (Bayesian) central tendency, you'll overweight past evidence at the beginning, and new information at the end. ⇒ primacy + recency.
I have posted on OSF the data for the numerosity estimation and discrimination tasks discussed in my paper with Mike Woodford "Endogenous Precision of the Number Sense". https://t.co/lVcRfnTnQA Btw it's now on eLife as a reviewed, not-revised preprint https://t.co/AiMm5TEMd3
"This raises the crucial question to what extent variability in risky choices really reflects subjective valuation (as opposed to noisy perception), as usually assumed in standard economic models." Very cool!
Important work by @GillesdeH and @ChristianCRuff's group! Perceptual processes account for risk preferences, and their reversal. "inter- and intra-individual variability in risky choice behaviour can be explained by fluctuations in basic perceptual neurocognitive representations"
🎉 Thrilled to announce that the first project I worked on from start to finish in Zurich is now on bioRxiv! We show how risk preferences are fundamentally shaped by how we process choice variables, and how these can be measured in the parietal cortex.
https://t.co/qrTYXkv7Nh
Arthur Prat-Carrabin has some new work on numerosity perception showing that Weber's law can be broken by manipulations of the stimulus distribution and reward function: https://t.co/Om6lB4CQSO
The pattern of results is broadly consistent with a Bayesian observer model.
"I think that, actually, the brain is pretty clever."
Cognitive neuroscientist @KiaNobre of @WuTsaiYale explains why she doesn't believe limited resources drive the brain's behavior.
Watch Neuroscience Perspectives🎙️ w/@JohnnyFoxe ➡️https://t.co/ZVkD38mdVc
The question of how we represent stuff is fundamental and comes with many implications. This sheds some principled light on how it happens for simple stuff (1D variables), while exhibiting interesting experimental results.
Last month I posted a preprint that presents experimental and theoretical results about the brain's representation of magnitudes. We looked at the variability of subjects in both an estimation task and a discrimination task, and with different priors. https://t.co/lfeoEruL43
The cost we deduce is not found in other studies but it is the only one that explains all our results simultaneously. And it turns out that it makes a lot of sense: you "pay" for getting more signals about what you want to represent.
Applications are open for the CNeuro2024 summer school in computational neuroscience to be held in Beijing, 8-15 July 2024. Rolling admissions starting March 1. See https://t.co/5aaVG2zQdZ for details on program and application process.