Evidence map›Paper›PMID 32705146›Full record

Observational studyBrain : a journal of neurology2020

Structural white matter connectometry of word production in aphasia: an observational study.

William D Hula, Sandip Panesar, Michelle L Gravier, Fang-Cheng Yeh, Haley C Dresang, Michael Walsh Dickey, Juan C Fernandez-Miranda

Open access · hybridAbstract readObservational Study
In one paragraph

Observational study in Brain : a journal of neurology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed
5.0field-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

40 citing papers in PubMed, 69 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Neural pathways underlying the production of pitch and rhythm in aphasia.Annals of the New York Academy of Sciences · 2025
    Article
  11. Article
  12. Article
  13. The Relationship between White Matter Architecture and Language Lateralization in the Healthy Brain.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024
    Article
  14. Article
  15. Assessing Relative Linguistic Impairment With Model-Based Item Selection.Journal of speech, language, and hearing research : JSLHR · 2024
    Article
  16. Review
  17. Article
  18. Observational
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 6 institutions in 1 country.

William D HulaGeriatric Research, Education, and Clinical Center and Audiology and Speech Pathology Service, VA Pittsburgh Healthcare System, Pittsburgh PA, USA.
Sandip PanesarDepartment of Neurosurgery, Stanford University, Palo Alto, CA, USA.
Michelle L GravierDepartment of Speech, Language, and Hearing Sciences, California State East Bay, Hayward, CA, USA.
Fang-Cheng YehDepartment of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA.
Haley C DresangDepartment of Communication Science and Disorders, University of Pittsburgh, Pittsburgh PA, USA.
Michael Walsh DickeyGeriatric Research, Education, and Clinical Center and Audiology and Speech Pathology Service, VA Pittsburgh Healthcare System, Pittsburgh PA, USA.
Juan C Fernandez-MirandaDepartment of Neurosurgery, Stanford University, Palo Alto, CA, USA.
Stanford University · USCalifornia State University, East Bay · USGeriatric Research Education and Clinical Center · USNeurological Surgery · USUniversity of Pittsburgh · USVA Pittsburgh Healthcare System · US

Funding

Language connectivity pathways and neuroplasticity in aphasic stroke patientsR01DC013803 · NIDCD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI FERNANDEZ-MIRANDA, JUAN CARLOS, HULA, WILLIAM D. · 2015 to 2019
$1.9M
NIDCD NIH HHS R01 DC013803
6 · The paper itself

Abstract

While current dual-steam neurocognitive models of language function have coalesced around the view that distinct neuroanatomical networks subserve semantic and phonological processing, respectively, the specific white matter components of these networks remain a matter of debate. To inform this debate, we investigated relationships between structural white matter connectivity and word production in a cross-sectional study of 42 participants with aphasia due to unilateral left hemisphere stroke. Specifically, we reconstructed a local connectome matrix for each participant from diffusion spectrum imaging data and regressed these matrices on indices of semantic and phonological ability derived from their responses to a picture-naming test and a computational model of word production. These connectometry analyses indicated that both dorsally located (arcuate fasciculus) and ventrally located (inferior frontal-occipital, uncinate, and middle longitudinal fasciculi) tracts were associated with semantic ability, while associations with phonological ability were more dorsally situated, including the arcuate and middle longitudinal fasciculi. Associations with limbic pathways including the posterior cingulum bundle and the fornix were also found. All analyses controlled for total lesion volume and all results showing positive associations obtained false discovery rates < 0.05. These results challenge dual-stream accounts that deny a role for the arcuate fasciculus in semantic processing, and for ventral-stream pathways in language production. They also illuminate limbic contributions to both semantic and phonological processing for word production.

Indexed as

AdultAgedAged, 80 and overAphasiaBrainConnectomeCross-Sectional StudiesDiffusion Tensor ImagingFemaleHumansMaleMiddle AgedNeural PathwaysSpeechStrokeWhite Matteraphasiadiffusion spectrum imagingdual-streamstructural connectometrywhite matter

Identifiers

PMID32705146
PMCPMC7447522
OpenAlexW3044040952

What OpenQuestion holds

Textmetadata
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.