A neural geometry approach comprehensively explains apparently conflicting models of visual perceptual learning.

ABSTRACT: Visual perceptual learning (VPL), defined as long-term improvement in a visual task, is considered a crucial tool for elucidating underlying visual and brain plasticity. Previous studies have proposed several neural models of VPL, including changes in neural tuning or in noise correlations. Here, to adjudicate different models, we propose that all neural changes at single units can be conceptualized as geometric transformations of population response manifolds in a high-dimensional neural space. Following this neural geometry approach, we identified neural manifold shrinkage due to reduced trial-by-trial population response variability, rather than tuning or correlation changes, as the primary mechanism of VPL. Furthermore, manifold shrinkage successfully explains VPL effects across artifi

SUBMITTER: Cheng YA 

PROVIDER: S-EPMC12106082 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature