{"pk":29559,"title":"The “Fraction Sense” Emerges from a Deep Convolutional Neural Network","subtitle":null,"abstract":"Fractions are a critical building block for the development ofhuman mathematical cognition, but the origins of this conceptare not well-understood. Recent work has found that a wholenumber sense is present in deep convolutional neural networks(DCNNs) pre-trained for object recognition and uses them asa model for investigating human numerical cognition. Do DC-NNs also have a fraction sense? If so, is it dependent or in-dependent of whole number processing? We investigated theneural sensitivity of a pretrained DCNN to both whole num-bers and fractions. We replicated and extended previous re-search that the sense of whole number emerges in a differentDCNN architecture. Further, we showed that DCNN is alsosensitive to fraction value, i.e., the ratio of numerosities. Test-ing this model, our results suggest that the fraction sense relieson the whole number sense.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[{"word":"deep convolutional neural network; emergentsense of number; ratio-processing system; approximate num-ber system"}],"section":"Poster Session 1","is_remote":true,"remote_url":"https://escholarship.org/uc/item/8kd4t919","frozenauthors":[{"first_name":"Yun-Shiuan","middle_name":"","last_name":"Chuang","name_suffix":"","institution":"University of Wisconsin-Madison","department":""},{"first_name":"Edward","middle_name":"M.","last_name":"Hubbard","name_suffix":"","institution":"University of Wisconsin-Madison","department":""},{"first_name":"Joseph","middle_name":"L.","last_name":"Austerweil","name_suffix":"","institution":"University of Wisconsin-Madison","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2020-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/29559/galley/19419/download/"}]}