Evidence map›Paper›PMID 26962070›Full record

ArticleNeurology2016

Network dysfunction predicts speech production after left hemisphere stroke.

Fatemeh Geranmayeh, Robert Leech, Richard J S Wise

Abstract read
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Article in Neurology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.

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50citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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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

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3 · Its place in the literature

Who cites it

50 citing papers in PubMed.

  1. Article
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  7. Hubs and interaction: the brain's meta-loop.Cerebral cortex (New York, N.Y. : 1991) · 2025
    Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Recovery from aphasia in the first year after stroke.Brain : a journal of neurology · 2023
    Article
  14. Targeted neurorehabilitation strategies in post-stroke aphasia.Restorative neurology and neuroscience · 2023
    Review
  15. Article
  16. Review
  17. Article
  18. Article
  19. Observational
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4 · The record

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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

3 authors.

Fatemeh GeranmayehFrom the Computational Cognitive and Clinical Neuroimaging Laboratory, Imperial College, Hammersmith Hospital Campus, London, UK. fatemeh.geranmayeh00@imperial.ac.uk.
Robert LeechFrom the Computational Cognitive and Clinical Neuroimaging Laboratory, Imperial College, Hammersmith Hospital Campus, London, UK.
Richard J S WiseFrom the Computational Cognitive and Clinical Neuroimaging Laboratory, Imperial College, Hammersmith Hospital Campus, London, UK.

Funding

Medical Research Council MR/K014129/1
6 · The paper itself

Abstract

objectiveTo investigate the role of multiple distributed brain networks, including the default mode, fronto-temporo-parietal, and cingulo-opercular networks, which mediate domain-general and task-specific processes during speech production after aphasic stroke.

methodsWe conducted an observational functional MRI study to investigate the effects of a previous left hemisphere stroke on functional connectivity within and between distributed networks as patients described pictures. Study design included various baseline tasks, and we compared results to those of age-matched healthy participants performing the same tasks. We used independent component and psychophysiological interaction analyses.

resultsAlthough activity within individual networks was not predictive of speech production, relative activity between networks was a predictor of both within-scanner and out-of-scanner language performance, over and above that predicted from lesion volume, age, sex, and years of education. Specifically, robust functional imaging predictors were the differential activity between the default mode network and both the left and right fronto-temporo-parietal networks, respectively activated and deactivated during speech. We also observed altered between-network functional connectivity of these networks in patients during speech production.

conclusionsSpeech production is dependent on complex interactions among widely distributed brain networks, indicating that residual speech production after stroke depends on more than the restoration of local domain-specific functions. Our understanding of the recovery of function following focal lesions is not adequately captured by consideration of ipsilesional or contralesional brain regions taking over lost domain-specific functions, but is perhaps best considered as the interaction between what remains of domain-specific networks and domain-general systems that regulate behavior.

Identifiers

PMID26962070
PMCPMC4826341

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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.