{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T03:18:46Z","timestamp":1776741526729,"version":"3.51.2"},"reference-count":36,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2023,9,29]],"date-time":"2023-09-29T00:00:00Z","timestamp":1695945600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"STI2030-Major Projects","award":["2022ZD0208500"],"award-info":[{"award-number":["2022ZD0208500"]}]},{"name":"STI2030-Major Projects","award":["82071884"],"award-info":[{"award-number":["82071884"]}]},{"name":"STI2030-Major Projects","award":["62106285"],"award-info":[{"award-number":["62106285"]}]},{"name":"National Natural Science Foundation of China","award":["2022ZD0208500"],"award-info":[{"award-number":["2022ZD0208500"]}]},{"name":"National Natural Science Foundation of China","award":["82071884"],"award-info":[{"award-number":["82071884"]}]},{"name":"National Natural Science Foundation of China","award":["62106285"],"award-info":[{"award-number":["62106285"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Brain Sciences"],"abstract":"<jats:p>Recognizing highly occluded objects is believed to arise from the interaction between the brain\u2019s vision and cognition-controlling areas, although supporting neuroimaging data are currently limited. To explore the neural mechanism during this activity, we conducted an occlusion object recognition experiment using functional magnetic resonance imaging (fMRI). During magnet resonance examinations, 66 subjects engaged in object recognition tasks with three different occlusion degrees. Generalized linear model (GLM) analysis showed that the activation degree of the occipital lobe (inferior occipital gyrus, middle occipital gyrus, and occipital fusiform gyrus) and dorsal anterior cingulate cortex (dACC) was related to the occlusion degree of the objects. Multivariate pattern analysis (MVPA) further unearthed a considerable surge in classification precision when dACC activation was incorporated as a feature. This suggested the combined role of dACC and the occipital lobe in occluded object recognition tasks. Moreover, psychophysiological interaction (PPI) analysis disclosed that functional connectivity (FC) between the dACC and the occipital lobe was enhanced with increased occlusion, highlighting the necessity of FC between these two brain regions in effectively identifying exceedingly occluded objects. In conclusion, these findings contribute to understanding the neural mechanisms of highly occluded object recognition, augmenting our appreciation of how the brain manages incomplete visual data.<\/jats:p>","DOI":"10.3390\/brainsci13101387","type":"journal-article","created":{"date-parts":[[2023,9,29]],"date-time":"2023-09-29T05:48:13Z","timestamp":1695966493000},"page":"1387","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Brain Functional Representation of Highly Occluded Object Recognition"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-3191-6146","authenticated-orcid":false,"given":"Bao","family":"Li","sequence":"first","affiliation":[{"name":"Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou 450001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou 450001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Long","family":"Cao","sequence":"additional","affiliation":[{"name":"Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou 450001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Panpan","family":"Chen","sequence":"additional","affiliation":[{"name":"Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou 450001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-1174-8100","authenticated-orcid":false,"given":"Tianyuan","family":"Liu","sequence":"additional","affiliation":[{"name":"Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou 450001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Gao","sequence":"additional","affiliation":[{"name":"Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou 450001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1087-5911","authenticated-orcid":false,"given":"Linyuan","family":"Wang","sequence":"additional","affiliation":[{"name":"Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou 450001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bin","family":"Yan","sequence":"additional","affiliation":[{"name":"Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou 450001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4197-7999","authenticated-orcid":false,"given":"Li","family":"Tong","sequence":"additional","affiliation":[{"name":"Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou 450001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,9,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3752","DOI":"10.1038\/s41598-018-22160-9","article-title":"Deep Residual Network Predicts Cortical Representation and Organization of Visual Features for Rapid Categorization","volume":"8","author":"Wen","year":"2018","journal-title":"Sci. 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