Obligatory coactive processing of color and luminance challenges strategic modulation by predictiveness

Area of Science:

• Cognitive Psychology
• Computational Neuroscience
• Visual Perception

Background:

• Accurate object categorization involves integrating multiple information sources.
• The predictiveness of features significantly influences categorization strategies.
• Color and luminance are typically considered integral features, processed interactively.

Purpose of the Study:

• To investigate how feature predictiveness modulates the processing of integral features like color and luminance.
• To test the strong version of the relative saliency hypothesis, predicting serial processing for highly predictive integral features.
• To determine if strategic adjustments in processing occur based on feature predictiveness.

Main Methods:

• Participants categorized visual stimuli varying in color and luminance under different mapping conditions (100% and 95% accuracy).
• Feature predictiveness was manipulated to be equal and unequal across experiments.
• System factorial technology (SFT) and computational modeling were used for non-parametric and parametric strategy inference.

Main Results:

• Robust evidence for coactive processing of color and luminance was found in aggregated group data.
• This coactive processing persisted regardless of stimulus-category mapping accuracy.
• Individual subject data showed some variability, but group trends supported obligatory coactive processing.

Conclusions:

• The processing of color and luminance is obligatory and coactive, challenging the strategic adjustment relative saliency hypothesis.
• Integral features may not be subject to strategic modulation of processing order based on predictiveness.
• Findings suggest a fundamental coactive mechanism for processing integral visual features.