ePoster · Computational Neuroscience
How sequential curricula enhance visual learning generalization: The role of subspace dimensionality
Charlotte Volk, Christopher C. Pack, Shahab Bakhtiari · COSYNE 2025
Practicing a visual task leads to long-lasting perceptual improvements in humans and other animals. However, the generalization of Visual Learning (VL) to unseen conditions varies across different tasks. Particularly, it has been shown that learning ‘easy’ visual tasks leads to better generalization than learning ‘hard’ ones. Moreover, experimental evidence suggests that greater generalizability in VL can be achieved through sequential curriculum training, specifically by training on ‘easier’ versions of a task before progressing to ‘harder’ versions. Yet, a neurocomputational explanation for