Evidence map›Paper›PMID 36469170›Full record

ArticleApplied psychophysiology and biofeedback2023

EEG Connectivity in ADHD Compared to a Normative Database: A Cohort Analysis of 120 Subjects from the ICAN Study.

Cynthia Kerson, Joel Lubar, Roger deBeus, Xueliang Pan, Robert Rice, Theodore Allen, Maha Yazbeck, Shlok Sah, Yajat Dhawan, Wei Zong and 2 more

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Article in Applied psychophysiology and biofeedback, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

12 authors.

Cynthia Kerson *Department of Applied Psychophysiology, Saybrook University, Pasadena, USA. ckerson@saybrook.edu.ORCID 0000-0001-5861-1443
Joel Lubar *Southeastern Neurofeedback Institute, Pompano Beach, Florida, USA.
Roger deBeusUniversity of North Carolina at Asheville, Asheville, NC, USA.
Xueliang PanDepartment of Biomedical Informatics, Center for Biostatistics, Ohio State University, Columbus, USA.
Robert RiceDepartment of Psychiatry and Behavioral Health, Ohio State University, Nisonger Center, Columbus, USA.
Theodore AllenIntegrated Systems Engineering, The Ohio State University, Columbus, USA.
Maha YazbeckIntegrated Systems Engineering, The Ohio State University, Columbus, USA.
Shlok SahDepartment of Computer Science and Engineering, Ohio State University, Columbus, USA.
Yajat DhawanDepartment of Computer Science and Engineering, Ohio State University, Columbus, USA.
Wei ZongDepartment of Computer Science and Engineering, Ohio State University, Columbus, USA.
Michelle E Roley-RobertsDepartment of Psychiatry, Creighton University, CHI Health, Behavioral Health, Omaha, USA.
L Eugene ArnoldDepartment of Psychiatry and Behavioral Health, Ohio State University, Nisonger Center, Columbus, USA.

Funding

Double-Blind Randomized Clinical Trial of EEG Neurofeedback for ADHDR01MH100144 · NIMH · OHIO STATE UNIVERSITY · PI ARNOLD, L EUGENE · 2014 to 2018
$3.5M
NIMH NIH HHS R01 MH100144
6 · The paper itself

Abstract

This study explores how EEG connectivity measures in children with ADHD ages 7-10 (n = 140) differ from an age-matched nonclinical database. We differentiated connectivity in networks, Brodmann area pairs, and frequencies. Subjects were in the International Collaborative ADHD Neurofeedback study, which explored neurofeedback for ADHD. Inclusion criteria were mainly rigorously diagnosed ADHD and a theta/beta power ratio (TBR) ≤ 4.5. Using statistical and machine learning algorithms, connectivity values were extracted in coherence, phase, and lag coherence at all Brodmann, subcortical, and cerebellar areas within the main networks in all EEG frequencies and then compared with a normative database. There is a higher rate of dysregulation (more than ± 1.97SD), in some cases as much as 75%, of the Brodmann pairs observed in coherence and phase between BAs 7, 10, and 11 with secondary connections from these areas to BAs 21, 30, 35, 37, 39, and 40 in the ADHD children as compared to the normative database. Left and right Brodmann areas 10 and 11 are highly disconnected to each other. The most dysregulated Brodmann Areas in ADHD are 7, 10, and 11, relevant to ADHD executive-function deficits and provide important considerations when developing interventions for ADHD children.

Indexed as

Attention Deficit Disorder with HyperactivityNeurofeedbackCerebral CortexChildCohort StudiesElectroencephalographyHumansADHDBrodmann areaCoherenceEEGEEG connectivity

Identifiers

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Registered trials

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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.