Evidence map›Paper›PMID 39536158›Full record

ArticleJournal of cognitive neuroscience2025

How Can Graph Theory Inform the Dual-stream Model of Speech Processing? A Resting-state Functional Magnetic Resonance Imaging Study of Stroke and Aphasia Symptomology.

Haoze Zhu, Megan C Fitzhugh, Lynsey M Keator, Lisa Johnson, Chris Rorden, Leonardo Bonilha, Julius Fridriksson, Corianne Rogalsky

Abstract read
In one paragraph

Article in Journal of cognitive neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

What it found

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Haoze ZhuArizona State University.
Megan C FitzhughUniversity of California, San Diego.
Lynsey M KeatorUniversity of Delaware.
Lisa JohnsonUniversity of South Carolina.
Chris RordenUniversity of South Carolina.
Leonardo BonilhaEmory University, Atlanta.
Julius FridrikssonUniversity of South Carolina.
Corianne RogalskyArizona State University.

Funding

Telerehab for Aphasia (TERRA)P50DC014664 · NIDCD · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI BONILHA, LEONARDO F · 2016 to 2025
$25.0M
Arizona State UniversityNIDCD NIH HHS P50 DC014664
6 · The paper itself

Abstract

The dual-stream model of speech processing describes a cortical network involved in speech processing. However, it is not yet known if the dual-stream model represents actual intrinsic functional brain networks. Furthermore, it is unclear how disruptions after a stroke to the functional connectivity of the dual-stream model's regions are related to speech production and comprehension impairments seen in aphasia. To address these questions, in the present study, we examined two independent resting-state fMRI data sets: (1) 28 neurotypical matched controls and (2) 28 chronic left-hemisphere stroke survivors collected at another site. We successfully identified an intrinsic functional network among the dual-stream model's regions in the control group using functional connectivity. We then used both standard functional connectivity analyses and graph theory approaches to determine how this connectivity may predict performance on clinical aphasia assessments. Our findings provide evidence that the dual-stream model of speech processing is an intrinsic network as measured via resting-state MRI and that functional connectivity of the hub nodes of the dual-stream network defined by graph theory methods, but not overall average network connectivity, is weaker in the stroke group than in the control participants. In addition, the functional connectivity of the hub nodes predicted linguistic impairments on clinical assessments. In particular, the relative strength of connectivity of the right hemisphere's homologues of the left dorsal stream hubs to the left dorsal hubs, versus to the right ventral stream hubs, is a particularly strong predictor of poststroke aphasia severity and symptomology.

Indexed as

AphasiaBrainSpeechStrokeAdultAgedBrain MappingFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedNeural PathwaysRest

Identifiers

PMID39536158
PMCPMC13557152

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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.