کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5630822 1580849 2017 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A brain-based account of “basic-level” concepts
ترجمه فارسی عنوان
یک حساب مبتنی بر مغز از یک سطح اولیه؟ مفاهیم
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی علوم اعصاب شناختی
چکیده انگلیسی


- A brain-based account of the advantage of “basic-level” object concepts is proposed.
- The basic-level representation encompasses concrete and abstract semantic content.
- Basic-level concepts are neurally similar to their typical subordinate-level concepts.

This study provides a brain-based account of how object concepts at an intermediate (basic) level of specificity are represented, offering an enriched view of what it means for a concept to be a basic-level concept, a research topic pioneered by Rosch and others (Rosch et al., 1976). Applying machine learning techniques to fMRI data, it was possible to determine the semantic content encoded in the neural representations of object concepts at basic and subordinate levels of abstraction. The representation of basic-level concepts (e.g. bird) was spatially broad, encompassing sensorimotor brain areas that encode concrete object properties, and also language and heteromodal integrative areas that encode abstract semantic content. The representation of subordinate-level concepts (robin) was less widely distributed, concentrated in perceptual areas that underlie concrete content. Furthermore, basic-level concepts were representative of their subordinates in that they were neurally similar to their typical but not atypical subordinates (bird was neurally similar to robin but not woodpecker). The findings provide a brain-based account of the advantages that basic-level concepts enjoy in everyday life over subordinate-level concepts: the basic level is a broad topographical representation that encompasses both concrete and abstract semantic content, reflecting the multifaceted yet intuitive meaning of basic-level concepts.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: NeuroImage - Volume 161, 1 November 2017, Pages 196-205
نویسندگان
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