The language network is not engaged in object categorization
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Abstract
The relationship between language and thought is the subject of long-standing debate. One claim states that language facilitates categorization of objects based on a certain feature (e.g. color) through the use of category labels that reduce interference from other, irrelevant features. Therefore, language impairment is expected to affect categorization of items grouped by a single feature (low-dimensional categories, e.g. “Yellow Things”) more than categorization of items that share many features (high-dimensional categories, e.g. “Animals”). To test this account, we conducted two behavioral studies with individuals with aphasia and an fMRI experiment with healthy adults. The aphasia studies showed that selective low-dimensional categorization impairment was present in some, but not all, individuals with severe anomia and was not characteristic of aphasia in general. fMRI results revealed little activity in language-responsive brain regions during both low- and high-dimensional categorization; instead, categorization recruited the domain-general multiple-demand network (involved in wide-ranging cognitive tasks). Combined, results demonstrate that the language system is not implicated in object categorization. Instead, selective low-dimensional categorization impairment might be caused by damage to brain regions responsible for cognitive control. Our work adds to the growing evidence of the dissociation between the language system and many cognitive tasks in adults.
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fMRI reveals that the language network responds reliably when people listen to, read, or generate sentences, but not when they perform arithmetic tasks, engage in logical reasoning, understand computer programs, listen to music, categorize objects or events, reason about people's mental states, or process non-verbal communicative information like facial expressions or gestures.
“it responds reliably when people listen to, read, or generate sentences, but not when they perform arithmetic tasks, engage in logical reasoning, understand computer programs, listen to music, categorize objects or events, reason about people’s mental states, or process non-verbal communicative information like facial expressions or gestures [37, 41, 42, 43, 44, 45, 46, 47, 48].”
From Dissociating language and thought in large language models (2024) · cites this paper as [42]
Individuals with language deficits may struggle to produce grammatical utterances and retrieve contextually appropriate words, but their ability to reason about objects and events presented non-linguistically often remains intact.
“Individuals with language deficits may struggle to produce grammatical utterances and retrieve contextually appropriate words, but their ability to reason about objects and events presented non-linguistically often remains intact [42, 151].”
From Dissociating language and thought in large language models (2024) · cites this paper as [42]
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Dissociating language and thought in large language models
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Self-citation
- Authors
- Benn, Y., Ivanova, A. A., Clark, O., Mineroff, Z., Seikus, C., Silva, J. S., Varley, R., & Fedorenko, E.
- Affiliations
- Manchester Metropolitan University (GB)
- McGovern Institute for Brain Research (US)
- University College London (GB)
- Corresponding author
- Benn, Yael
- Venue
- Cerebral Cortex
- Publisher
- Oxford University Press (OUP)
- Published
- 2023-08-09
- Volume
- 33
- Issue
- 19
- Pages
- 10380-10400
- ISSN
- 1047-3211 (ISSN-L)
- 1460-2199
- PMC
- PMC10545444
- OpenAlex
- W4385690887
- Cited by
- 14
- References
- 157
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 5 · 2023: 2 · 2022: 1 · 2021: 1
- FWCI
- 1.79
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Cerebral Cortex (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- e-space (Manchester Metropolitan University) (submittedVersion)
- UCL Discovery (University College London) (submittedVersion, cc-by)
- OSF Preprints (OSF Preprints) (submittedVersion)
- Funders
- National Institutes of Health (R00-HD057522, R01-DC016607, R01-DC016950)
- Simons Foundation
- Simons Center for the Social Brain
- Brain and Cognitive Sciences Department and the McGovern Institute for Brain Research
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Categorization, perception, and language
- Social Sciences › Psychology › Developmental and Educational Psychology › Reading and Literacy Development
- Keywords
- object classification, language and thought, aphasia, anomia, multiple-demand network, cognitive control, language impairment, feature-based classification
- MeSH terms
- Adult, Aphasia, Brain, Humans, Language
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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