Interested in human replay and solid methods? Jointly with @skjerns.de we're releasing a benchmark dataset with known ground-truth neural sequences in MEG & fMRI, for developing & validating replay methods. First test: existing methods show similar effect sizes, but room to improve shorturl.at/6TgIr
What matters most for childhood brain organization?
We analyzed 649 variables.
The answer: Socioeconomics (SES); with brain patterns pointing at sleep & stress as drivers.
Even brain-IQ associations were better explained by SES.
In Science today: www.science.org/doi/10.1126/...
shorturl.at
Studies in rodents and humans using invasive electrophysiology have established that neural replay is a ubiquitous phenomenon in the brain that is associated with a wide range of cognitive functions, ...
The Group for Neural Theory is celebrating its 20th birthday this week with a party in Paris!
gnt20.github.io
One thing weâre celebrating is its remarkable training record
A threadâŠ
Online Now: Bayesian efficient coding as a theory of perception: progress, controversies, and prospects
Analysis of #acoustic #rhythms across nearly 100 species reveals a conserved slow tempo centered around 2.7 Hz, within the delta range, suggesting a constraint rooted in conserved #neural mechanisms of #auditory perception @plosbiology.org đ§Ș plos.io/4ejLRcl
Bayesian efficient coding unifies two foundational theories of sensory processing: efficient coding and Bayesian inference. Central to this account is the idea that natural environmental statistics shape both how sensory information is encoded and how it is perceptually interpreted. By unifying these principles, the framework accounts for counterintuitive perceptual biases and establishes lawful relationships between environmental statistics, bias, and discrimination thresholds. In this article, we review behavioural and neural evidence for this theory in perception and cognition, as well as how short- and long-term adaptation to the environment may be expressed within the framework. We further review theoretical developments that extend the original framework, focusing on how response biases can be decomposed into encoding- and decoding-related components. A decade after its introduction, Bayesian efficient coding continues to evolve as a powerful theory, with recent extensions addressing early limitations and opening new directions for investigating perception and cognition.
A new #bmm release is available on #CRAN. With this version, #bmm now covers basic response time models. This release contains three new models plus several usability features. Here's what's in it đ§”
venpopov.com/bmm/
#rstats #bayes #openscience
Thanks to the Weber School for inviting me to give a #TEDx talk!
I discuss how much people vary in their inner thought â from thinking mainly in words to thinking mostly abstractly â and the implications it has for understanding AI cognition.
youtu.be/WAm0XQIRBMw
Representations of geometric shapes have syntactic structure w/ @maxencepajot.bsky.social and @standehaene.bsky.social is out & open-access in JEP:General doi.org/10.1037/xge0.... For an overview, see thread below!
Multimodal mental imagery profiles and the prevalence of aphantasia and hyperphantasia in the general population
doi.org/10.1016/j.co...
Fit computational and measurement models using full Bayesian inference. The package provides a simple and accessible interface by translating complex domain-specific models into brms syntax, a powerfu...
Preprint alert (link below)! @maxencepajot.bsky.social, @standehaene.bsky.social, and I show that human adults, but not convolutional or transformer networks, encode geometric shapes in hierarchically structured representations. TL;DR: Geometric-shape representations have internal syntax! 1/8
