Very excited to share that my lab will be moving to Princeton (Neuroscience & Psychology) this fall. I'll be recruiting at all levels (more info to come soon), please share / get in touch if you're interested in joining!
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
Online Now: Bayesian efficient coding as a theory of perception: progress, controversies, and prospects
www.nature.com/articles/s44...
New research Article by @dobyrahnev.bsky.social ahnev.bsky.social & @kaixue98.bsky.social in the journal.
Now out in Developmental Science! @noraharhen.bsky.social, Rheza Budiono & @catehartley.bsky.social @hartleylabnyu.bsky.social use multi-patch foraging to identify a specific computational role for structure learning underlying developmental differences in exploration.
dx.doi.org/10.1111/desc...
New paper with Dan Burnston at @tulaneu.bsky.social
Part of a special issue on "Representation in the Neurosciences and AI" in Philosophy & the Mind Sciences
An alternative to encoding for thinking about neural representation.
philosophymindscience.org/index.php/ph...
direct.mit.edu/opmi/article...
maybe there's a way to study metacognitive monitoring w/o collecting confidence? could be handy for studying animals and infants?
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.
dlvr.it
Taylor Webb
Check out our latest profile! Dr. Megan Peters (@meganakpeters.bsky.social) studies how the brain represents & uses uncertainty and she also co-founded the online summer school, Neuromatch Academy. Learn more at the link below! #WomenInNeuroscience #StoriesOfWiN
www.storiesofwin.org/profiles/202...
A global perspective | Award-winning @ucirvine.bsky.social cognitive sciences Ph.D. student Sharanya Bashyam is advancing research on language, culture and children’s social cognition
@uofcalifornia.bsky.social @nadiachernyak.bsky.social
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, ...
Philosophy and the Mind Sciences (PhiMiSci) focuses on the interface between philosophy of mind, psychology, and cognitive neuroscience. PhiMiSci is a peer-reviewed, not-for-profit open-access journal...
Abstract. This study explores the use of response time (RT) data in type-2 receiver operating characteristic (ROC) analysis, a method traditionally used to examine the relationship between confidence ...
direct.mit.edu
Nico Schuck
Trends in Cognitive Sciences
Early in development, children can infer latent structure in the world from sparse and ambiguous evidence. Through a process known as structure learning, they extract statistical regularities, const...
Zheng et al. show that confidence (Type-2) judgments feature the same magnitude of computational noise as perceptual (Type-1) judgments, with important implications for the debate on whether Type-1 an...
🚨New pre-print out from our lab!!🚨 "Developmental differences in exploration reveal underlying differences in structure inference" by @noraharhen.bsky.social, Rheza Budiono, @catehartley.bsky.social, and
@aaronbornstein.bsky.social. Read here: osf.io/preprints/ps...
