Evidence map›Paper›PMID 35709321›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2022

A syntax-lexicon trade-off in language production.

Neguine Rezaii, Kyle Mahowald, Rachel Ryskin, Bradford Dickerson, Edward Gibson

Open access · greenAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
4.5field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 40 citations in OpenAlex.

  1. Article
  2. Article
  3. Non-fluent agrammatic variant of primary progressive aphasia in a bilingual Mandarin/English speaker: a case report.Archives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists · 2026
    Article
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  7. Language abnormalities in Alzheimer's disease indicate reduced informativeness.Annals of clinical and translational neurology · 2024
    Article
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  9. Article
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  11. Automatic classification of AD pathology in FTD phenotypes using natural speech.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 5 institutions in 1 country.

Neguine RezaiiFrontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114.
Kyle MahowaldDepartment of Linguistics, The University of Texas at Austin, Austin, TX 78712.
Rachel RyskinDepartment of Cognitive & Information Sciences, University of California, Merced, CA 95343.
Bradford DickersonFrontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114.
Edward GibsonDepartment of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139.
Harvard University · USMassachusetts General Hospital · USMassachusetts Institute of Technology · USThe University of Texas at Austin · USUniversity of California, Merced · US

Funding

The Harvard Clinical and Translational Science CenterUL1TR002541 · NCATS · HARVARD MEDICAL SCHOOL · PI NADLER, LEE MARSHALL · 2018 to 2022
$93.0M
Research Education ComponentP30AG062421 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI STEVEN E ARNOLD · 2019 to 2026
$36.5M
Imaging tau, amyloid, and neurodegeneration in PPAR01DC014296 · NIDCD · MASSACHUSETTS GENERAL HOSPITAL · PI DICKERSON, BRADFORD C, JOHNSON, KEITH A. · 2016 to 2020
$4.3M
Use of machine learning to quantify cognitive function in AD, FTD, and DLBR21AG073744 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI DICKERSON, BRADFORD C, WOLFF, PHILLIP MARK · 2021 to 2022
$443k
Computational psycholinguistic analysis of speech samples in PPA and AD and FTDR21DC019567 · NIDCD · MASSACHUSETTS GENERAL HOSPITAL · PI DICKERSON, BRADFORD C, WOLFF, PHILLIP MARK · 2022 to 2023
$443k
NCATS NIH HHS UL1 TR002541NIA NIH HHS P30 AG062421NIA NIH HHS R21 AG073744NIDCD NIH HHS R01 DC014296
6 · The paper itself

Abstract

Spoken language production involves selecting and assembling words and syntactic structures to convey one's message. Here we probe this process by analyzing natural language productions of individuals with primary progressive aphasia (PPA) and healthy individuals. Based on prior neuropsychological observations, we hypothesize that patients who have difficulty producing complex syntax might choose semantically richer words to make their meaning clear, whereas patients with lexicosemantic deficits may choose more complex syntax. To evaluate this hypothesis, we first introduce a frequency-based method for characterizing the syntactic complexity of naturally produced utterances. We then show that lexical and syntactic complexity, as measured by their frequencies, are negatively correlated in a large (

Indexed as

LanguageSpeechAphasia, Primary ProgressiveHumansprimary progressive aphasiasyntactic complexitysyntax frequencysyntax–lexicon trade-offword frequency

Identifiers

PMID35709321
PMCPMC9231468
OpenAlexW4282974240

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.