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Once our CNN model was fine\u2010tuned using a pre\u2010trained VGG16 model to recognize the visual stimuli from the digit and object categories, representational similarity analysis (RSA) was conducted using neural activations from fMRI and feature representations from the CNN model across all 16 classes. The encoded neural representation of the CNN model exhibited the hierarchical topography mapping of the human visual system. The feature representations in the lower convolutional (Conv) layers showed greater similarity with the neural representations in the early visual areas and parietal cortices, including the posterior cingulate cortex. The feature representations in the higher Conv layers were encoded in the higher\u2010order visual areas, including the ventral\/medial\/dorsal stream and middle temporal complex. The neural representations in the classification layers were observed mainly in the ventral stream visual cortex (including the inferior temporal cortex), superior parietal cortex, and prefrontal cortex. There was a surprising similarity between the neural representations from the CNN model and the neural representations for human visual perception in the context of the perception of digits versus objects, particularly in the primary visual and associated areas. This study also illustrates the uniqueness of human visual perception. Unlike the CNN model, the neural representation of digits and objects for humans is more widely distributed across the whole brain, including the frontal and temporal areas.<\/jats:p>","DOI":"10.1002\/hbm.26189","type":"journal-article","created":{"date-parts":[[2023,1,13]],"date-time":"2023-01-13T17:15:01Z","timestamp":1673630101000},"page":"2018-2038","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Neural representations of the perception of handwritten digits and visual objects from a convolutional neural network compared to humans"],"prefix":"10.1002","volume":"44","author":[{"given":"Juhyeon","family":"Lee","sequence":"first","affiliation":[{"name":"Department of Brain and Cognitive Engineering Korea University  Seoul Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Minyoung","family":"Jung","sequence":"additional","affiliation":[{"name":"Department of Brain and Cognitive Engineering Korea University  Seoul Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Niv","family":"Lustig","sequence":"additional","affiliation":[{"name":"Department of Brain and Cognitive Engineering Korea University  Seoul Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8902-6009","authenticated-orcid":false,"given":"Jong\u2010Hwan","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Brain and Cognitive Engineering Korea University  Seoul Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2023,1,13]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tics.2020.10.009"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1162\/jocn.2007.19.11.1845"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.dcn.2017.08.002"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2010.10.009"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cortex.2007.08.008"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tics.2015.07.002"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1162\/089892903770007380"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2007.04.042"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.1714-18.2019"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2013.10.049"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1003963"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1038\/srep27755"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-14578-5"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2020.117139"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-vision-091517-034202"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2011.04.016"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuron.2020.11.021"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1608434113"},{"key":"e_1_2_10_20_1","doi-asserted-by":"publisher","DOI":"10.1093\/cercor\/bhv111"},{"key":"e_1_2_10_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/0010-0277(92)90049-N"},{"issue":"1","key":"e_1_2_10_22_1","first-page":"83","article-title":"Towards an anatomical and functional model of number processing","volume":"1","author":"Dehaene S.","year":"1995","journal-title":"Mathematical Cognition"},{"key":"e_1_2_10_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"e_1_2_10_24_1","first-page":"ArXiv 1810.0480","article-title":"Bert: Pre\u2010training of deep bidirectional transformers for language understanding","author":"Devlin J.","year":"2018","journal-title":"ArXiv Preprint"},{"key":"e_1_2_10_25_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pbio.0050294"},{"key":"e_1_2_10_26_1","doi-asserted-by":"publisher","DOI":"10.1152\/jn.2001.86.4.1991"},{"key":"e_1_2_10_27_1","doi-asserted-by":"publisher","DOI":"10.1016\/s0896-6273(03)00036-9"},{"key":"e_1_2_10_28_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2016.10.001"},{"key":"e_1_2_10_29_1","unstructured":"Erhan D. 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