Reverse-engineering what makes a symbol memorable

Symbols may represent the first form of human visual communication, yet little is known about the cognitive and neural mechanisms supporting memory for these pervasive graphics. By investigating memory for everyday symbols, we can understand how abstract concepts are concretized with simple referents and later processed in visual memory systems. Recently, symbols have been found to be highly memorable, especially relative to words, but it remains unclear what drives their heightened memorability. We identified the key visual and conceptual attributes driving high memorability for symbols. Participants were tested on their memory for conventional symbols (e.g., !@#$%) before sorting them based on visual or conceptual features. Principle component analyses performed on the sorting data revealed which of these features predict memory for symbols. Generative artificial intelligence was then used to accentuate or downplay these predictive features to create a set of memorable and forgettable novel symbols. A memory test revealed that symbols designed to be memorable were not only better recognized than those designed to be forgettable, but they also afforded superior recall of associated abstract words. This work demonstrates that certain features drive memory for images and offers clear evidence that memory can be intentionally engineered.