A distinct cortical network for mathematical knowledge in the human brain
Open accessAbstract
How does the brain represent and manipulate abstract mathematical concepts? Recent evidence suggests that mathematical processing relies on specific brain areas and dissociates from language. Here, we investigate this dissociation in two fMRI experiments in which professional mathematicians had to judge the truth value of mathematical and nonmathematical spoken statements. Sentences with mathematical content systematically activated bilateral intraparietal sulci and inferior temporal regions, regardless of math domain, problem difficulty, and strategy for judging truth value (memory retrieval, calculation or mental imagery). Second, classical language areas were only involved in the parsing of both nonmathematical and mathematical statements, and their activation correlated with syntactic complexity, not mathematical content. Third, the mere presence, within a sentence, of elementary logical operators such as quantifiers or negation did not suffice to activate math-responsive areas. Instead, quantifiers and negation impacted on activity in right angular gyrus and left inferior frontal gyrus, respectively. Overall, these results support the existence of a distinct, non-linguistic cortical network for mathematical knowledge in the human brain.
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Neuroimaging studies have consistently shown that the language network remains largely inactive during various reasoning tasks.
“Neuroimaging studies have consistently shown that the language network -a set of brain regions responsible for language comprehension and production -remains largely inactive during various reasoning tasks”
From Training Large Language Models to Reason in a Continuous Latent Space (2024) · cites this paper as Amalric and Dehaene, 2019
The Discussion reports no activation in some language regions during spoken algebra problems, supporting a limited version of the claim. But the General Discussion says mathematical statements activated core language areas in proportion to syntactic complexity. The paper does not establish that the language network remains largely inactive across various reasoning tasks. No page numbers are available in our copy. (LLM, conf=0.86)
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- Authors
- Amalric, M., & Dehaene, S.
- Affiliations
- Université Paris-Sud (FR)
- Corresponding author
- Amalric, Marie
- Dehaene, Stanislas
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2019-04
- Volume
- 189
- Pages
- 19-31
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2907706060
- Cited by
- 126
- References
- 5
- Citations by year
- 2026: 21 · 2025: 18 · 2024: 20 · 2023: 19 · 2022: 14 · 2021: 18 · 2020: 11 · 2019: 4 · 2018: 1
- FWCI
- 9.20
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- NeuroImage (acceptedVersion)
- PubMed (publishedVersion)
- HAL (submittedVersion, cc-by-nc)
- Funders
- Inserm
- CEA, Collège de France
- Université Paris-Sud
- the Bettencourt-Schueller Foundation
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Cognitive and developmental aspects of mathematical skills
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neuroscience and Music Perception
- Keywords
- mathematical cognition, mathematical knowledge, mathematical processing, language processing, intraparietal sulcus, inferior temporal cortex, angular gyrus, inferior frontal gyrus, negation, syntactic analysis, truth value judgment
- MeSH terms
- Adult, Brain Mapping, Cerebral Cortex, Humans, Language, Magnetic Resonance Imaging, Mathematics, Nerve Net, Semantics, Thinking, Mathematical Concepts
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