Evidence map›Paper›PMID 33278802›Full record

ArticleBrain and language2021

Reliability of single-subject neural activation patterns in speech production tasks.

Saul A Frankford, Alfonso Nieto-Castañón, Jason A Tourville, Frank H Guenther

Open access · greenAbstract read
In one paragraph

Article in Brain and language, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.5field-weighted citation impact, top 39% 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

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. A Novel Candidate Neuromarker of Central Motor Dysfunction in Childhood Apraxia of Speech.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
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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.

Saul A FrankfordDepartment of Speech, Language, & Hearing Sciences, Boston University, Boston, MA 02215, USA. Electronic address: saulf@bu.edu.
Alfonso Nieto-CastañónDepartment of Speech, Language, & Hearing Sciences, Boston University, Boston, MA 02215, USA.
Jason A TourvilleDepartment of Speech, Language, & Hearing Sciences, Boston University, Boston, MA 02215, USA. Electronic address: jtour@bu.edu.
Frank H GuentherDepartment of Speech, Language, & Hearing Sciences, Boston University, Boston, MA 02215, USA; Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA; Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, USA. Electronic address: guenther@bu.edu.
Boston University · US

Funding

ULTRAHIGH FIELD TECHNOLOGY FOR FUNCTIONAL IMAGINGP41RR014075 · NCRR · MASSACHUSETTS GENERAL HOSPITAL · PI BOAS, DAVID A · 1999 to 2011
$16.4M
Sequencing and Initiation in Speech ProductionR01DC007683 · NIDCD · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI FRANK H GUENTHER · 2006 to 2026
$9.0M
NEURAL MODELING AND IMAGING OF SPEECHR01DC002852 · NIDCD · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI GUENTHER, FRANK H · 2001 to 2020
$7.2M
Advanced Research Training in Communication Sciences and DisordersT32DC013017 · NIDCD · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI Cara E. Stepp · 2016 to 2026
$4.9M
NCRR NIH HHS P41 RR014075NIDCD NIH HHS R01 DC002852NIDCD NIH HHS R01 DC007683NIDCD NIH HHS T32 DC013017
6 · The paper itself

Abstract

Speech neuroimaging research targeting individual speakers could help elucidate differences that may be crucial to understanding speech disorders. However, this research necessitates reliable brain activation across multiple speech production sessions. In the present study, we evaluated the reliability of speech-related brain activity measured by functional magnetic resonance imaging data from twenty neuro-typical subjects who participated in two experiments involving reading aloud simple speech stimuli. Using traditional methods like the Dice and intraclass correlation coefficients, we found that most individuals displayed moderate to high reliability. We also found that a novel machine-learning subject classifier could identify these individuals by their speech activation patterns with 97% accuracy from among a dataset of seventy-five subjects. These results suggest that single-subject speech research would yield valid results and that investigations into the reliability of speech activation in people with speech disorders are warranted.

Indexed as

Magnetic Resonance ImagingSpeechBrainBrain MappingHumansReproducibility of ResultsClassifierfMRIReliabilitySpeech production

Identifiers

PMID33278802
PMCPMC7781091
OpenAlexW3109292669

What OpenQuestion holds

Textmetadata
LicenceTDM
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.