The boundaries of language and thought in deductive inference
Open accessAbstract
Is human thought fully embedded in language, or do some forms of thought operate independently? To directly address this issue, we focus on inference-making, a central feature of human cognition. In a 3T fMRI study we compare logical inferences relying on sentential connectives (e.g., not, or, if … then) to linguistic inferences based on syntactic transformation of sentences involving ditransitive verbs (e.g., give, say, take). When contrasted with matched grammaticality judgments, logic inference alone recruited “core” regions of deduction [Brodmann area (BA) 10p and 8m], whereas linguistic inference alone recruited perisylvian regions of linguistic competence, among others (BA 21, 22, 37, 39, 44, and 45 and caudate). In addition, the two inferences commonly recruited a set of general “support” areas in frontoparietal cortex (BA 6, 7, 8, 40, and 47). The results indicate that logical inference is not embedded in natural language and confirm the relative modularity of linguistic processes.
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Previous studies have shown that sentences with content words lead to larger responses in the perisylvian fronto-temporal language network than spoken equations or logical statements with variables.
“Although all of the tasks in the language/math/logic localizer contain language stimuli, previous studies have shown that sentences with content words lead to larger responses in the perisylvian fronto-temporal language network than spoken equations or logical statements with variables (Kanjlia et al., 2016; Monti et al., 2009; Monti et al., 2012).”
From Computer code comprehension shares neural resources with formal logical inference in the fronto-parietal network (2020) · cites this paper as Monti et al., 2009
Previous studies have found that responses to language, logic and math when compared to each other were similar to what was observed for each domain relative to independent control conditions.
“Furthermore, previous studies have found that responses to language, logic and math when compared to each other were similar to what was observed for each domain relative to independent control conditions (e.g. sentences relative to lists of non-words for language, and easy vs. hard logic problems; Kanjlia et al., 2016; Monti et al., 2009, Monti et al., 2012).”
From Computer code comprehension shares neural resources with formal logical inference in the fronto-parietal network (2020) · cites this paper as Monti et al., 2009
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- Authors
- Monti, M. M., Parsons, L. M., & Osherson, D. N.
- Affiliations
- MRC Cognition and Brain Sciences Unit (GB)
- University of Sheffield (GB)
- Princeton University (US)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2009-07-28
- Volume
- 106
- Issue
- 30
- Pages
- 12554-12559
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC2718391
- OpenAlex
- W2110980037
- Cited by
- 170
- References
- 63
- Citations by year
- 2026: 8 · 2025: 13 · 2024: 13 · 2023: 6 · 2022: 5 · 2021: 12 · 2020: 8 · 2019: 6 · 2018: 32 · 2017: 5 · 2016: 8 · 2015: 11 · 2014: 10 · 2013: 7 · 2012: 14
- FWCI
- 4.21
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Categorization, perception, and language
- Social Sciences › Arts and Humanities › Language and Linguistics › Syntax, Semantics, Linguistic Variation
- Keywords
- language and thought, deductive reasoning, logical inference, linguistic inference, syntactic transformation, ditransitive verbs, modularity of language, frontoparietal cortex, perisylvian cortex, Brodmann area 10, caudate nucleus, grammaticality judgment, language of thought
- MeSH terms
- Cognition, Female, Humans, Language, Logic, Magnetic Resonance Imaging, Male, Psycholinguistics, Psychomotor Performance, Semantics, Young Adult
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