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Numerosity perception is foundational to mathematical learning, but itscomputational bases are strongly debated. Some investigators argue that humansare endowed with a specialized system supporting numerical representation;others argue that visual numerosity is estimated using continuous magnitudes,such as density or area, which usually co-vary with number. Here we reconcilethese contrasting perspectives by testing deep networks on the same numerositycomparison task that was administered to humans, using a stimulus space thatallows to measure the contribution of non-numerical features. Our modelaccurately simulated the psychophysics of numerosity perception and theassociated developmental changes: discrimination was driven by numerosityinformation, but non-numerical features had a significant impact, especiallyearly during development. Representational similarity analysis furtherhighlighted that both numerosity and continuous magnitudes were spontaneouslyencoded even when no task had to be carried out, demonstrating that numerosityis a major, salient property of our visual environment.

Perception of visual numerosity in humans and machines