Evidence map›Paper›PMID 36251043›Full record

ArticleBrain structure & function2022

White matter microstructure and verbal fluency.

Natalia Egorova-Brumley, Chen Liang, Mohamed Salah Khlif, Amy Brodtmann

Open access · hybridAbstract read
In one paragraph

Article in Brain structure & function, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

11 citing papers in PubMed, 14 citations in OpenAlex.

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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

4 authors at 1 institution in 1 country.

Natalia Egorova-BrumleyMelbourne School of Psychological Sciences, University of Melbourne, Melbourne, Australia. natalia.egorova@unimelb.edu.au.ORCID http://orcid.org/0000-0002-9244-2900
Chen LiangDepartment of Speech Pathology, University of Melbourne, Melbourne, Australia.
Mohamed Salah KhlifCognitive Health Initiative, Central Clinical School, Monash University, Melbourne, Australia.
Amy BrodtmannCognitive Health Initiative, Central Clinical School, Monash University, Melbourne, Australia.
The University of Melbourne · AU

Funding

ARC DE180100893NHMRC APP1020526
6 · The paper itself

Abstract

Poor performance on verbal fluency tasks is associated with an increased risk of post-stroke cognitive impairment. Grey matter regions supporting verbal fluency have been identified via lesion-symptom mapping, but the links between verbal fluency and white matter structure remain less well described. We examined white matter correlates of semantic (Category Fluency Animals) and phonemic or lexical fluency (COWAT FAS) after stroke, accounting for stroke severity measured with the National Institutes of health Stroke Scale (NIHSS), age, sex, and level of education. White matter fibre density and cross-section measures were automatically extracted from 72 tracts, using MRtrix and TractSeg software in 72 ischaemic stroke survivors assessed 3 months after their event. We conducted regression analyses separately for phonemic and semantic fluency for each tract. Worse semantic fluency was associated with lower fibre density in several tracts, including the arcuate fasciculus, superior longitudinal fasciculus, inferior occipito-frontal fasciculus, inferior longitudinal fasciculus, optic radiation, striato-occipital, thalamo-occipital tracts, and inferior cerebellar peduncle. Our stroke sample was heterogenous with largely non-overlapping and predominantly right-lateralised lesions (lesion distribution: left N = 27, right N = 43, bilateral N = 2), dissimilar to previous studies of verbal fluency. Yet, the tracts we identified as correlates of semantic fluency were all left-lateralised. No associations between phonemic fluency performance and fibre density metrics in any of the white matter tracts we extracted survived correction for multiple comparisons, possibly due to the limitations in the selection of tracts and sample characteristics. We conclude that when accounting for the effects of stroke severity, sex, age, and education, semantic fluency is associated with white matter microstructure in the left arcuate fasciculus, superior longitudinal fasciculus, and several occipital tracts, possibly reflecting the disconnection in the sagittal stratum. Our results obtained with fixel-based analysis, complement previous findings obtained with lesions-symptom mapping and neurodegenerative approaches.

Indexed as

Brain IschemiaStrokeWhite MatterGray MatterHumansNeuropsychological TestsCategory fluency animalsCOWAT FASFixel-based analysis (FBA)Superior longitudinal fasciculusVerbal fluencyWhite matter

Identifiers

PMID36251043
PMCPMC9653311
OpenAlexW4306406885

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.