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Objects di er along many di erent dimensions: shape, size, color, etc. These dimensions help us categorize objects in the world. Through experience we learn that certain dimensions--say shape--are important for certain categories--say cars--and we develop a stable ability to preferentially discriminate those dimensions. But we also learn to flexibly alter the relative discriminability of dimensions based on the current demands of our environment. In both stable and flexible cases, relevant dimensions become easier to discriminate than irrelevant dimensions. This is a process known as dimensional modulation.

Category learning causes a stable advantage for category-relevant shape dimensions during a task requiring attention to all dimensions: ERP evidence