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To address this question, we examined the influence of two well-established principles of language organization\u2014frequency and concreteness\u2014on naming accuracy in a post-stroke bilingual individual with anomic aphasia (PWA). The participant, a highly proficient Basque-Spanish bilingual, underwent MRI scanning to delineate the extent and location of the lesion and completed a naming-by-definition task in both languages, along with a control group of 24 age-matched bilinguals. Stimuli were orthogonally varied by frequency (high\/low) and concreteness (high\/low). Generalized linear mixed models revealed main effects of both frequency and concreteness on naming accuracy. Notably, while healthy controls showed a robust concreteness effect\u2014with concrete words yielding higher accuracy\u2014the PWA exhibited a disproportionately larger impairment for low-frequency words. This pattern, consistent with the lesion\u2019s location to the inferior temporal gyrus, highlights a specific vulnerability of frequency-based lexical representations following temporal lobe damage. Importantly, the bilingual PWA demonstrated strikingly similar error rates across languages, yet an item-level analysis revealed that the specific words affected differed between the two languages. These findings (i) clarify the role of the inferior temporal gyrus in lexical organization, (ii) suggest that bilinguals possess an integrated lexical system governed by general cognitive principles, and (iii) challenge the notion that language itself is the dominant axis of organization in the bilingual mind\/brain.<\/jats:p>","DOI":"10.1162\/nol_a_00170","type":"journal-article","created":{"date-parts":[[2025,4,10]],"date-time":"2025-04-10T20:03:06Z","timestamp":1744315386000},"update-policy":"https:\/\/doi.org\/10.1162\/mitpressjournals.corrections.policy","source":"Crossref","is-referenced-by-count":3,"title":["Basque-Spanish Bilingual Aphasia: A Case-Study to Reveal Frequency-Based, Language-Agnostic Lexical Organization in Bilinguals"],"prefix":"10.1162","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2983-5880","authenticated-orcid":true,"given":"Esti","family":"Blanco-Elorrieta","sequence":"first","affiliation":[{"name":"Department of Psychology, New York University, New York, NY, USA"},{"name":"Department of Neural Science, New York University, New York, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5429-8066","authenticated-orcid":true,"given":"Miren","family":"Arantzeta","sequence":"additional","affiliation":[{"name":"Department of Linguistics and Basque Studies, University of the Basque Country (UPV-EHU), Bizkaia, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"281","published-online":{"date-parts":[[2025,6,23]]},"reference":[{"key":"2025062614154570200_bib1","doi-asserted-by":"publisher","first-page":"Article 14","DOI":"10.3389\/fninf.2014.00014","article-title":"Machine learning for neuroimaging with scikit-learn. 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