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The Adaptive Attention Representation Model (AARM), for example, provides an account in which categorization decisions are based on the perceptual similarity of a new stimulus to stored exemplars, and dimension-wise attention is updated on every trial in the direction of a feedback-based error gradient. As such, attention modulation as described by AARM requires interactions among processes of orienting, visual perception, memory retrieval, prediction error, and goal maintenance to facilitate learning. The current study explored the neural bases of attention mechanisms using quantitative predictions from AARM to analyze behavioral and fMRI data collected while participants learned novel categories. Generalized linear model analyses revealed patterns of BOLD activation in the parietal cortex (orienting), visual cortex (perception), medial temporal lobe (memory retrieval), basal ganglia (prediction error), and pFC (goal maintenance) that covaried with the magnitude of model-predicted attentional tuning. Results are consistent with AARM's specification of attention modulation as a dynamic property of distributed cognitive systems.<\/jats:p>","DOI":"10.1162\/jocn_a_01882","type":"journal-article","created":{"date-parts":[[2022,6,15]],"date-time":"2022-06-15T17:48:13Z","timestamp":1655315293000},"page":"1761-1779","update-policy":"https:\/\/doi.org\/10.1162\/mitpressjournals.corrections.policy","source":"Crossref","is-referenced-by-count":6,"title":["Distributed Neural Systems Support Flexible Attention Updating during Category Learning"],"prefix":"10.1162","volume":"34","author":[{"given":"Emily R.","family":"Weichart","sequence":"first","affiliation":[{"name":"Ohio State University, Columbus"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel G.","family":"Evans","sequence":"additional","affiliation":[{"name":"Ohio State University, Columbus"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Matthew","family":"Galdo","sequence":"additional","affiliation":[{"name":"Ohio State University, Columbus"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Giwon","family":"Bahg","sequence":"additional","affiliation":[{"name":"Ohio State University, Columbus"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Brandon M.","family":"Turner","sequence":"additional","affiliation":[{"name":"Ohio State University, Columbus"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"281","published-online":{"date-parts":[[2022,9,1]]},"reference":[{"key":"2023090100051425300_bib1","doi-asserted-by":"publisher","first-page":"E420","DOI":"10.1073\/pnas.1518931113","article-title":"Attention promotes episodic encoding by stabilizing hippocampal representations","volume":"113","author":"Aly","year":"2016","journal-title":"Proceedings of the National Academy of Sciences, 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