Reframing Memory: Shape-Dependent Boundary Features Drive Processing Efficiency Under High Load.

Poster Session XI

Keyword: Memory

Abstract: Using a modified change detection paradigm, we investigated how boundary shapes influence visual working memory performance. Forty participants performed local feature detection with varying boundary conditions. Results revealed shape-dependent enhancement of processing efficiency (up to 107%), emerged during maintenance under high memory load, suggesting dynamic optimization of visual information processing.

• Craig Tomlin (Presenting Author)