Figure 3.

Sensitivity kernels and separability. (A) Group-averaged sensitivity kernels for each experimental condition: valid, neutral, and invalid. Each pixel represents a beta-weight that represents the degree of correlation between the noise at each SF and orientation component and the behavioral response. We refer to these weights as perceptual sensitivity; the higher the beta-weight, the higher the correlation between the noise and behavioral responses. The red boxes in the neutral kernel are a cartoon depiction of the slices we extracted to fit the tuning functions for each experimental condition. We fit the slice containing the orientation of the target (0°, vertical box) and the slice containing the spatial frequency of the target (1.5 cycles/°, horizontal box). (B) Separability test: correlation between the reconstructed sensitivity kernels and original kernels across all observers. A correlation close to 1 implies high separability.