Table 2.

Model performance on different images and tasks in Experiment 1. Notes: For each image, we calculated the within-category similarity (CRT) and between-category similarity (NRT) using visual search data. We then fit the model either on all objects within a task (e.g., animals and nonanimals in the animal task) or for all objects of a given type (e.g., animal images in all three tasks) for various tasks and image types. The asterisk symbol beside each correlation coefficient indicates its statistical significance, with conventions as in Table 1.

Model fitted on:	Correlation between categorization & search	Model coefficients RT = a × NRT + b × CRT + c
		a	b	c
All tasks/items	0.85****	0.16	−0.04	0.61
Animal task	0.84****	0.09	−0.08	0.7
Dog task	0.89****	0.14	−0.03	0.61
Labrador task	0.77**	0.14	−0.02	0.61
Animals across tasks	0.91****	0.17	−0.02	0.55
Dogs across tasks	0.95****	0.21	−0.02	0.53
Labradors across tasks	0.96****	0.33	−0.13	0.63
Things across tasks	0.43*	0.11	−0.06	0.68