Evidence map›Paper›PMID 39230061›Full record

ArticleHuman brain mapping2024

Generalized models for estimating cerebral lateralisation of young children using functional transcranial Doppler ultrasound.

Josephine E Quin-Conroy, Paul A Thompson, Donna M Bayliss, Nicholas A Badcock

Abstract read
In one paragraph

Article in Human brain mapping, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Josephine E Quin-ConroySchool of Psychological Science, University of Western Australia, Western Australia, Australia.ORCID 0000-0001-9961-5301
Paul A ThompsonSchool of Education, Learning and Communication Sciences, University of Warwick, Coventry, UK.ORCID 0000-0001-9940-6913
Donna M BaylissSchool of Psychological Science, University of Western Australia, Western Australia, Australia.ORCID 0000-0001-5940-5211
Nicholas A BadcockSchool of Psychological Science, University of Western Australia, Western Australia, Australia.ORCID 0000-0001-6862-4694

Funding

Australian Government Research Training Program (RTP) Offset 10306140
6 · The paper itself

Abstract

Thompson et al., 2023 (Generalized models for quantifying laterality using functional transcranial Doppler ultrasound. Human Brain Mapping, 44(1), 35-48) introduced generalised model-based analysis methods for determining cerebral lateralisation from functional transcranial Doppler ultrasound (fTCD) data which substantially decreased the uncertainty of individual lateralisation estimates across several large adult samples. We aimed to assess the suitability of these methods for increasing precision in lateralisation estimates for child fTCD data. We applied these methods to adult fTCD data to establish the validity of two child-friendly language and visuospatial tasks. We also applied the methods to fTCD data from 4- to 7-year-old children. For both samples, the laterality estimates from the complex generalised additive model (GAM) approach correlated strongly with the traditional methods while also decreasing individual standard errors compared to the popular period-of-interest averaging method. We recommend future research using fTCD with young children consider using GAMs to reduce the noise in their LI estimates.

Indexed as

Functional LateralityUltrasonography, Doppler, TranscranialAdultCerebral CortexChildChild, PreschoolFemaleHumansMaleYoung AdultchildfTCDgeneralized additive model (GAM)generalized linear model (GLM)laterality

Identifiers

PMID39230061
PMCPMC11372819

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.