Evidence map›Paper›PMID 33783669›Full record

ArticleNeuroinformatics2022

Biomarkers Based on Comprehensive Hierarchical EEG Coherence Analysis: Example Application to Social Competence in Autism (Preliminary Results).

Mo Modarres, David Cochran, David N Kennedy, Richard Schmidt, Paula Fitzpatrick, Jean A Frazier

Open access · hybridAbstract read
In one paragraph

Article in Neuroinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 60% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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

6 authors at 4 institutions in 1 country.

Mo ModarresThe Eunice Kennedy Shriver Center Department of Psychiatry, University of Massachusetts Medical School, 55 Lake Avenue North, Room S3-312, Worcester, MA, 01655, USA. mo.modarres@umassmed.edu.ORCID http://orcid.org/0000-0002-0454-8546
David CochranThe Eunice Kennedy Shriver Center Department of Psychiatry, University of Massachusetts Medical School, 55 Lake Avenue North, Room S3-312, Worcester, MA, 01655, USA.
David N KennedyThe Eunice Kennedy Shriver Center Department of Psychiatry, University of Massachusetts Medical School, 55 Lake Avenue North, Room S3-312, Worcester, MA, 01655, USA.
Richard SchmidtPsychology Department, College of the Holy Cross, Worcester, MA, USA.
Paula FitzpatrickPsychology Department, Assumption University, Worcester, MA, USA.
Jean A FrazierThe Eunice Kennedy Shriver Center Department of Psychiatry, University of Massachusetts Medical School, 55 Lake Avenue North, Room S3-312, Worcester, MA, 01655, USA.
UMass Memorial Health Care · USUniversity of Massachusetts Chan Medical School · USAssumption College · USCollege of the Holy Cross · US

Funding

Resource DiscoveryP41EB019936 · NIBIB · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI David Nelson Kennedy · 2016 to 2026
$15.2M
Exposing the Deep Content of the Publication: Knowledge Extraction for Neuroimaging in Child PsychiatryR01MH083320 · NIMH · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI FRAZIER, JEAN A, KENNEDY, DAVID NELSON · 2009 to 2020
$6.3M
Modeling the Behavioral Dynamics of Social Action and CoordinationR01GM105045 · NIGMS · UNIVERSITY OF CINCINNATI · PI SCHMIDT, RICHARD C, SHOCKLEY, KEVIN · 2013 to 2017
$1.5M
NIBIB NIH HHS P41 EB019936NIGMS NIH HHS R01 GM105045NIMH NIH HHS R01 MH083320
6 · The paper itself

Abstract

Electroencephalography (EEG) coherence analysis, based on measurement of synchronous oscillations of neuronal clusters, has been used extensively to evaluate functional connectivity in brain networks. EEG coherence studies have used a variety of analysis variables (e.g., time and frequency resolutions corresponding to the analysis time period and frequency bandwidth), regions of the brain (e.g., connectivity within and between various cortical lobes and hemispheres) and experimental paradigms (e.g., resting state with eyes open or closed; performance of cognitive tasks). This variability in study designs has resulted in difficulties in comparing the findings from different studies and assimilating a comprehensive understanding of the underlying brain activity and regions with abnormal functional connectivity in a particular disorder. In order to address the variability in methods across studies and to facilitate the comparison of research findings between studies, this paper presents the structure and utilization of a comprehensive hierarchical electroencephalography (EEG) coherence analysis that allows for formal inclusion of analysis duration, EEG frequency band, cortical region, and experimental test condition in the computation of the EEG coherences. It further describes the method by which this EEG coherence analysis can be utilized to derive biomarkers related to brain (dys)function and abnormalities. In order to document the utility of this approach, the paper describes the results of the application of this method to EEG and behavioral data from a social synchrony paradigm in a small cohort of adolescents with and without Autism Spectral Disorder.

Indexed as

Autistic DisorderAdolescentBiomarkersBrainElectroencephalographyHumansSocial SkillsBiomarkersAutismEEG coherenceFunctional connectivityMotor coordinationSocial synchrony

Identifiers

PMID33783669
PMCPMC13034563
OpenAlexW3150578927

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.