A Gaussian-process-based mixture model reveals that swap errors in visual working memory can depend on report-dimension (location) distance, pointing to a possible encoding-stage mechanism.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
q-bio.NC 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
A flexible Bayesian non-parametric mixture model reveals multiple dependencies of swap errors in visual working memory
A Gaussian-process-based mixture model reveals that swap errors in visual working memory can depend on report-dimension (location) distance, pointing to a possible encoding-stage mechanism.