Chronic post-stroke aphasia severity is determined by fragmentation of residual white matter networks
Open accessAbstract
Many stroke survivors with aphasia in the acute period experience spontaneous recovery within the first six months after the stroke. However, approximately 30–40% sustain permanent aphasia and the factors determining incomplete recovery are unclear. Suboptimal recovery may be influenced by disruption of areas seemingly spared by the stroke due to loss of white matter connectivity and network integrity. We reconstructed individual anatomical whole-brain connectomes from 90 left hemisphere stroke survivors using diffusion MR images. We measured the modularity of the residual white matter network organization, the probability of brain regions clustering together, and the degree of fragmentation of left hemisphere networks. Greater post-stroke left hemisphere network fragmentation and higher modularity index were associated with more severe chronic aphasia, controlling for the size of the stroke lesion. Even when the left hemisphere was relatively spared, subjects with disorganized community structure had significantly worse aphasia, particularly when key temporal lobe regions were isolated into segregated modules. These results suggest that white matter integrity and disorganization of neuronal networks could be important determinants of chronic aphasia severity. Connectome white matter organization measured through modularity and other topological features could be used as a personalized variable for clinical staging and aphasia treatment planning.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Aphasia severity is often correlated with post-stroke brain integrity, which ultimately determines the neural resources available to support recovery.
“Indeed, aphasia severity is often correlated with post-stroke brain integrity, which ultimately determines the neural resources available to support recovery55.”
From Machine Learning Predictions of Recovery in Bilingual Poststroke Aphasia: Aligning Insights With Clinical Evidence (2025) · cites this paper as [55]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Finding and evaluating community structure in networks
Newman, M. E. J., & Girvan, M. (2004) · Physical Review E · doi:10.1103/physreve.69.026113 · Cited by 13,931 · see citing works
Complex network measures of brain connectivity: Uses and interpretations
Rubinov, M., & Sporns, O. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.10.003 · Cited by 11,522 · see citing works
Heart Disease and Stroke Statistics—2010 Update: A Report From the American Heart Association
WRITING GROUP MEMBERS, Lloyd-Jones, D., Adams, R. J., Brown, T. M., Carnethon, M., Dai, S., De Simone, G., Ferguson, T. B., Ford, E., Furie, K., et al. (2010) · Circulation · doi:10.1161/circulationaha.109.192667 · Cited by 5,700 · see citing works
Probabilistic diffusion tractography with multiple fibre orientations: What can we gain?
Behrens, T. E. J., Berg, H. J., Jbabdi, S., Rushworth, M. F. S., & Woolrich, M. W. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2006.09.018 · Cited by 3,471 · see citing works
Andersson, J. L. R., Skare, S., & Ashburner, J. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00336-7 · Cited by 3,469 · see citing works
The economy of brain network organization
Bullmore, E., & Sporns, O. (2012) · Nature Reviews Neuroscience · doi:10.1038/nrn3214 · Cited by 3,284 · see citing works
Rich-club organization of the human connectome
van den Heuvel, M. P., & Sporns, O. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.3539-11.2011 · Cited by 2,354 · see citing works
Western Aphasia Battery--Revised
Kertesz, A. (2012) · PsycTESTS Dataset · doi:10.1037/t15168-000 · Cited by 1,367 · see citing works
Executive Summary: Heart Disease and Stroke Statistics—2010 Update
WRITING GROUP MEMBERS, Lloyd‐Jones, D. M., Adams, R. J., Brown, T. M., Carnethon, M. R., Dai, S., SIMONE, G. D., Ferguson, T. B., Ford, E. S., Furie, K. L., et al. (2010) · Circulation · doi:10.1161/circulationaha.109.192666 · Cited by 1,360 · see citing works
The rises and falls of disconnection syndromes
Catani, M., & ffytche, D. H. (2005) · Brain · doi:10.1093/brain/awh622 · Cited by 863 · see citing works
Mapping Human Whole-Brain Structural Networks with Diffusion MRI
Hagmann, P., Kurant, M., Gigandet, X., Thiran, P., Wedeen, V. J., Meuli, R., & Thiran, J.-P. (2007) · PLoS ONE · doi:10.1371/journal.pone.0000597 · Cited by 788 · see citing works
Reworking the language network
Fedorenko, E., & Thompson-Schill, S. L. (2014) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2013.12.006 · Cited by 615 · see citing works
Aphasia after stroke: natural history and associated deficits.
Wade, D. T., Hewer, R. L., DAVID, R. M., & Enderby, P. (1986) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp.49.1.11 · Cited by 417 · see citing works
Pure alexia as a disconnection syndrome: New diffusion imaging evidence for an old concept
Epelbaum, S., Pinel, P., Raphaël Gaillard, B., Delmaire, C., Perrin, M., Dupont, S., Dehaene, S., & Cohen, L. (2008) · Cortex · doi:10.1016/j.cortex.2008.05.003 · Cited by 283 · see citing works
Enantiomorphic normalization of focally lesioned brains
Nachev, P., Coulthard, E. J., Jäger, H. R., Christopher Kennard, C., & Masud Husain, B. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.10.002 · Cited by 276 · see citing works
Bonilha, L., Nesland, T., Martz, G. U., Joseph, J. E., Spampinato, M. V., Edwards, J. C., & Tabesh, A. (2012) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp-2012-302476 · Cited by 209 · see citing works
Self-citationYourganov, G., Fridriksson, J., Rorden, C., Gleichgerrcht, E. L., & Bonilha, L. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.4396-15.2016 · Cited by 170 · see citing works
Self-citationWhat is a disconnection syndrome?
Catani, M., & Mesulam, M. M. (2008) · Cortex · doi:10.1016/j.cortex.2008.05.001 · Cited by 167 · see citing works
Faria, A. V., Joel, S. E., Zhang, Y., Oishi, K., van Zjil, P. C. M., Miller, M. I., Pekar, J. J., & Mori, S. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.03.078 · Cited by 163 · see citing works
Regional white matter damage predicts speech fluency in chronic post-stroke aphasia
Basilakos, A., Fillmore, P. T., Rorden, C., Guo, D., Bonilha, L., & Fridriksson, J. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00845 · Cited by 122 · see citing works
Self-citationBonilha, L., Gleichgerrcht, E. L., Nesland, T., Rorden, C., & Fridriksson, J. (2015) · Neurorehabilitation and neural repair · doi:10.1177/1545968315593808 · Cited by 113 · see citing works
Self-citationReproducibility of the Structural Brain Connectome Derived from Diffusion Tensor Imaging
Bonilha, L., Gleichgerrcht, E. L., Fridriksson, J., Rorden, C., Breedlove, J. L., Nesland, T., Paulus, W., Helms, G., & Focke, N. K. (2015) · PLoS ONE · doi:10.1371/journal.pone.0135247 · Cited by 98 · see citing works
Self-citationAssessing the Clinical Effect of Residual Cortical Disconnection After Ischemic Strokes
Bonilha, L., Rorden, C., & Fridriksson, J. (2014) · Stroke · doi:10.1161/strokeaha.113.004137 · Cited by 68 · see citing works
Self-citationPreservation of structural brain network hubs is associated with less severe post-stroke aphasia
Gleichgerrcht, E. L., Kocher, M., Nesland, T., Rorden, C., Fridriksson, J., & Bonilha, L. (2015) · Restorative Neurology and Neuroscience · doi:10.3233/rnn-150511 · Cited by 48 · see citing works
Self-citationSubcortical damage and white matter disconnection associated with non-fluent speech
Bonilha, L., & Fridriksson, J. (2008) · Brain · doi:10.1093/brain/awn200 · Cited by 34 · see citing works
Self-citationDrawing on the right brain for aphasia recovery
Barrett, A. M., & Hamilton, R. H. (2016) · Neurology · doi:10.1212/wnl.0000000000002619 · Cited by 5 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Structural disconnections explain brain network dysfunction after stroke
Griffis, J. C., Metcalf, N. V., Corbetta, M., & Shulman, G. L. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.07.100 · Cited by 213 · see citing works
Mapping language networks using the structural and dynamic brain connectomes
Del Gaizo, J., Fridriksson, J., Yourganov, G., Hillis, A. E., Hickok, G., Misic, B., Rorden, C., & Bonilha, L. (2017) · eneuro · doi:10.1523/eneuro.0204-17.2017 · Cited by 62 · see citing works
Self-citationMachine<scp>learning‐based</scp>multimodal prediction of language outcomes in chronic aphasia
Kristinsson, S., Zhang, W., Rorden, C., Newman‐Norlund, R., Basilakos, A., Bonilha, L., Yourganov, G., Xiao, F., Hillis, A., & Fridriksson, J. (2021) · Human Brain Mapping · doi:10.1002/hbm.25321 · Cited by 64 · see citing works
Self-citationMarte, M. J., Carpenter, E., Scimeca, M., Russell-Meill, M., Peñaloza, C., Grasemann, U., Miikkulainen, R., & Kiran, S. (2025) · Stroke · doi:10.1161/strokeaha.124.047867 · Cited by 9 · see citing works
“55 Notably, our findings also emphasize the importance of baseline nonverbal cognitive function in predicting treatment outcomes, particularly for CLG.”
- Authors
- Marebwa, B. K., Fridriksson, J., Yourganov, G., Feenaughty, L., Rorden, C., & Bonilha, L.
- Affiliations
- Medical University of South Carolina (US)
- University of South Carolina (US)
- University of Memphis (US)
- Corresponding author
- Bonilha, Leonardo
- Venue
- Scientific Reports
- Published
- 2017-08-15
- Volume
- 7
- Issue
- 1
- Pages
- 8188-8188
- ISSN
- 2045-2322 (ISSN-L)
- PMC
- PMC5558035
- OpenAlex
- W2742760950
- Cited by
- 64
- References
- 26
- Citations by year
- 2026: 9 · 2025: 7 · 2024: 7 · 2023: 6 · 2022: 11 · 2021: 3 · 2020: 6 · 2019: 13 · 2018: 1 · 2017: 1
- FWCI
- 3.29
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Scientific Reports (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- American Heart Association (SFDRN26030003)
- National Institutes of Health (DC014664)
- National Institute on Deafness and Other Communication Disorders (DC014021, DC011739, R01DC014021, DC014664)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- post-stroke aphasia, white matter connectivity, network modularity, connectome, diffusion MRI, left hemisphere stroke, temporal lobe, community structure, aphasia recovery
- MeSH terms
- Adult, Aged, Aphasia, Brain Mapping, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Middle Aged, Severity of Illness Index, Stroke, Connectome, White Matter
About these checks
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
