Evidence map›Paper›PMID 35265968›Full record

ArticleBrain : a journal of neurology2022

The multidimensional nature of aphasia recovery post-stroke.

James D Stefaniak, Fatemeh Geranmayeh, Matthew A Lambon Ralph

Open access · hybridAbstract read
In one paragraph

Article in Brain : a journal of neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed
4.9field-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

39 citing papers in PubMed, 64 citations in OpenAlex.

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  5. Acute-Phase Machine Learning Prediction of 12-Month Aphasia and Discourse Recovery.medRxiv : the preprint server for health sciences · 2026
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  9. The nonlinear trajectory of post-stroke aphasia recovery.Frontiers in human neuroscience · 2026
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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

3 authors at 2 institutions in 1 country.

James D StefaniakMRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, UK.ORCID 0000-0002-1362-0538
Fatemeh GeranmayehComputational Cognitive and Clinical Neuroimaging Laboratory, Department of Brain Sciences, Imperial College London, Hammersmith Hospital Campus, London W12 0NN, UK.
Matthew A Lambon RalphMRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, UK.ORCID 0000-0001-5907-2488
MRC Cognition and Brain Sciences Unit · GBHammersmith Hospital · GB

Funding

Medical Research Council MC_UU_00005/18Medical Research Council MC_UU_00030/9Medical Research Council MR/T001402/1Medical Research Council MR/X502959/1Wellcome Trust 093957
6 · The paper itself

Abstract

Language is not a single function, but instead results from interactions between neural representations and computations that can be damaged independently of each other. Although there is now clear evidence that the language profile in post-stroke aphasia reflects graded variations along multiple underlying dimensions ('components'), it is still entirely unknown if these distinct language components have different recovery trajectories and rely on the same, or different, neural regions during aphasia recovery. Accordingly, this study examined whether language components in the subacute stage: (i) mirror those observed in the chronic stage; (ii) recover together in a homogeneous manner; and (iii) have recovery trajectories that relate to changing activation in distinct or overlapping underlying brain regions. We analysed longitudinal data from 26 individuals with mild-moderate aphasia following left hemispheric infarct who underwent functional MRI and behavioural testing at ∼2 weeks and ∼4 months post-stroke. The language profiles in early post-stroke aphasia reflected three orthogonal principal components consisting of fluency, semantic/executive function and phonology. These components did not recover in a singular, homogeneous manner; rather, their longitudinal trajectories were uncorrelated, suggesting that aphasia recovery is heterogeneous and multidimensional. Mean regional brain activation during overt speech production in unlesioned areas was compared with patient scores on the three principal components of language at both the early and late time points. In addition, the change in brain activation over time was compared with the change on each of the principal component scores, both before and after controlling for baseline scores. We found that different language components were associated with changing activation in multiple, non-overlapping bilateral brain regions during aphasia recovery. Specifically, fluency recovery was associated with increasing activation in bilateral middle frontal gyri and right temporo-occipital middle temporal gyrus; semantic/executive recovery was associated with reducing activation in bilateral anterior temporal lobes; while phonology recovery was associated with reducing activation in bilateral precentral gyri, dorso-medial frontal poles and the precuneus. Overlapping clusters in the ventromedial prefrontal cortex were positively associated with fluency recovery but negatively associated with semantic/executive and phonology recovery. This combination of detailed behavioural and functional MRI data provides novel insights into the neural basis of aphasia recovery. Because different aspects of language seem to rely on different neural regions for recovery, treatment strategies that target the same neural region in all stroke survivors with aphasia might be entirely ineffective or even impair recovery, depending on the specific language profile of each individual patient.

Indexed as

AphasiaStrokeBrainHumansLanguageMagnetic Resonance ImagingRecovery of FunctionaphasiafMRIplasticitystroke

Identifiers

PMID35265968
PMCPMC9128817
OpenAlexW4205152336

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.