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However, the understanding of its cognitive substrates is limited. The present study used functional magnetic resonance imaging to examine the neural correlates of programming to understand the cognitive substrates of CT. Specifically, magnetic resonance imaging signals were collected while the participants were mentally solving programming problems, and we found that CT recruited distributed cortical regions, including the posterior parietal cortex, the medial frontal cortex, and the left lateral frontal cortex. These regions showed extensive univariate and multivariate resemblance with arithmetic, reasoning, and spatial cognition tasks. Based on the resemblance, clustering analyses revealed that cortical regions involved in CT can be divided into Reasoning, Calculation, Visuospatial, and Shared components. Further, connectivity increased during programming within the CT network constructed by these four components and decreased between the CT network and other cortical regions. In sum, our study revealed the cognitive components underlying CT and their neural correlates and further suggests that CT is not a simple sum of parallel cognitive processes, but a composite cognitive process integrating a set of intellectual abilities, particularly those in the science, technology, engineering, and math domains.<\/jats:p>","DOI":"10.1093\/cercor\/bhab182","type":"journal-article","created":{"date-parts":[[2021,5,31]],"date-time":"2021-05-31T11:32:22Z","timestamp":1622460742000},"page":"5579-5597","source":"Crossref","is-referenced-by-count":19,"title":["The Neural Correlates of Computational Thinking: Collaboration of Distinct Cognitive Components Revealed by fMRI"],"prefix":"10.1093","volume":"31","author":[{"given":"Shan","family":"Xu","sequence":"first","affiliation":[{"name":"Faculty of Psychology, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"Li","sequence":"additional","affiliation":[{"name":"Faculty of Psychology, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jia","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Psychology, Tsinghua Laboratory of Brain and Intelligence, Tsinghua University, Beijing 100086, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2021,7,13]]},"reference":[{"key":"2021110415164895100_ref1","doi-asserted-by":"crossref","first-page":"4909","DOI":"10.1073\/pnas.1603205113","article-title":"Origins of the brain networks for advanced mathematics in expert mathematicians","volume":"113","author":"Amalric","year":"2016","journal-title":"Proc Natl Acad Sci"},{"key":"2021110415164895100_ref2","first-page":"1","volume-title":"2014 IEEE Frontiers in Education Conference (FIE) Proceedings","author":"Ambr\u00f3sio","year":"2014"},{"key":"2021110415164895100_ref3","doi-asserted-by":"crossref","first-page":"241","DOI":"10.3758\/BF03196490","article-title":"An information-processing model of the BOLD response in symbol manipulation tasks","volume":"10","author":"Anderson","year":"2003","journal-title":"Psychon Bull Rev"},{"key":"2021110415164895100_ref4","doi-asserted-by":"crossref","first-page":"2382","DOI":"10.1016\/j.neuroimage.2010.10.009","article-title":"Is 2\u2009+\u20092\u2009=\u20094? 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