Evidence map›Paper›PMID 33927783›Full record

ArticleComputational and mathematical methods in medicine2021

Information Transfer and Multifractal Analysis of EEG in Mild Blast-Induced TBI.

Todd Zorick, Katy D Gaines, Gholam R Berenji, Mark A Mandelkern, Jason Smith

Abstract readComparative Study
In one paragraph

Article in Computational and mathematical methods in medicine, 2021. 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

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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.

  1. Article
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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

5 authors.

Todd ZorickDepartment of Psychiatry, Harbor-UCLA Medical Center and UCLA Geffen School of Medicine, USA.ORCID https://orcid.org/0000-0002-5851-785X
Katy D GainesNeuro Health Inc, University of California, Irvine, USA.
Gholam R BerenjiGreater Los Angeles VA Department of Nuclear Imaging, University of California, Irvine, USA.
Mark A MandelkernGreater Los Angeles VA Department of Nuclear Imaging, University of California, Irvine, USA.
Jason SmithThe Boeing Company, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mild, blast-induced traumatic brain injury (mbTBI) is a common combat brain injury characterized by typically normal neuroimaging findings, with unpredictable future cognitive recovery. Traditional methods of electroencephalography (EEG) analysis (e.g., spectral analysis) have not been successful in detecting the degree of cognitive and functional impairment in mbTBI. We therefore collected resting state EEG (5 minutes, 64 leads) from twelve patients with a history of mbTBI, along with repeat neuropsychological testing (D-KEFS Tower test) to compare two new methods for analyzing EEG (multifractal detrended fluctuation analysis (MF-DFA) and information transfer modeling (ITM)) with spectral analysis. For MF-DFA, we extracted relevant parameters from the resultant multifractal spectrum from all leads and compared with traditional power by frequency band for spectral analysis. For ITM, because the number of parameters from each lead far exceeded the number of subjects, we utilized a reduced set of 10 leads which were compared with spectral analysis. We utilized separate 30 second EEG segments for training and testing statistical models based upon regression tree analysis. ITM and MF-DFA models both generally had improved accuracy at correlating with relevant measures of cognitive performance as compared to spectral analytic models ITM and MF-DFA both merit additional research as analytic tools for EEG and cognition in TBI.

Indexed as

AdultBlast InjuriesBrain Injuries, TraumaticCognitionCognitive DysfunctionComputational BiologyElectroencephalographyExecutive FunctionFemaleFourier AnalysisFractalsHumansMaleModels, NeurologicalModels, PsychologicalNeuropsychological Tests

Identifiers

PMID33927783
PMCPMC8051525

What OpenQuestion holds

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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.