Evidence map›Paper›PMID 39175803›Full record

ArticleFrontiers in language sciences2023

A reconceptualization of sentence production in post-stroke agrammatic aphasia: the synergistic processing bottleneck model.

Yasmeen Faroqi-Shah

Abstract read
In one paragraph

Article in Frontiers in language sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Characterizing Verb Argument Structure in Aphasia Using Dependency Parsers.Journal of speech, language, and hearing research : JSLHR · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Translanguaging in conversations for people with aphasia living in Greater Johannesburg, South Africa.The South African journal of communication disorders = Die Suid-Afrikaanse tydskrif vir Kommunikasieafwykings · 2025
    Article
  8. Article
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

1 author.

Yasmeen Faroqi-ShahDepartment of Hearing and Speech Sciences, University of Maryland, College Park, MD, USA.

Funding

Diagnostic markers of language impairment in bilingual adultsR21DC018916 · NIDCD · UNIV OF MARYLAND, COLLEGE PARK · PI FAROQI SHAH, YASMEEN · 2021 to 2022
$415k
NIDCD NIH HHS R21 DC018916
6 · The paper itself

Abstract

The language production deficit in post-stroke agrammatic aphasia (PSA-G) tends to result from lesions to the left inferior frontal gyrus (LIFG) and is characterized by a triad of symptoms: fragmented sentences, errors in functional morphology, and a dearth of verbs. Despite decades of research, the mechanisms underlying production patterns in PSA-G have been difficult to characterize. Two major impediments to progress may have been the view that it is a purely morphosyntactic disorder and the (sometimes overzealous) application of linguistic theory without interceding psycholinguistic evidence. In this paper, empirical evidence is examined to present an integrated portrait of language production in PSA-G and to evaluate the assumption of a syntax-specific syndrome. In light of extant evidence, it is proposed that agrammatic language production results from a combination of morphosyntactic, phonomotor, and processing capacity limitations that cause a cumulative processing bottleneck at the point of articulatory planning. This proposed Synergistic Processing Bottleneck model of PSA-G presents a testable framework for future research. The paper ends with recommendations for future research on PSA-G.

Indexed as

agrammatismaphasiamorphologyphonologyprocessing loadsyntaxverb

Identifiers

PMID39175803
PMCPMC11340809

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Registered trials

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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.