Evidence map›Paper›PMID 32087372›Full record

ArticleNeuroImage2020

Principle ERP reduction and analysis: Estimating and using principle ERP waveforms underlying ERPs across tasks, subjects and electrodes.

Emilie Campos, Chad Hazlett, Patricia Tan, Holly Truong, Sandra Loo, Charlotte DiStefano, Shafali Jeste, Damla Şentürk

Open access · goldAbstract read
In one paragraph

Article in NeuroImage, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 21% 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, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Looking Back at the Next 40 Years of ASD Neuroscience Research.Journal of autism and developmental disorders · 2021
    Review
  5. 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

8 authors at 1 institution in 1 country.

Emilie CamposDepartment of Biostatistics, University of California, Los Angeles, USA.
Chad HazlettDepartments of Statistics and Political Science, University of California, Los Angeles, USA.
Patricia TanDepartment of Psychiatry, University of California, Los Angeles, USA.
Holly TruongDepartment of Psychiatry, University of California, Los Angeles, USA.
Sandra LooDepartment of Psychiatry, University of California, Los Angeles, USA.
Charlotte DiStefanoDepartment of Psychiatry, University of California, Los Angeles, USA.
Shafali JesteDepartment of Psychiatry, University of California, Los Angeles, USA.
Damla ŞentürkDepartment of Biostatistics, University of California, Los Angeles, USA. Electronic address: dsenturk@ucla.edu.
University of California, Los Angeles · US

Funding

A unified longitudinal functional data framework for the analysis of complex biomedical dataR01GM111378 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SENTURK, DAMLA, SUGAR, CATHERINE ANN · 2015 to 2018
$1.4M
NIGMS NIH HHS R01 GM111378
6 · The paper itself

Abstract

Event-related potentials (ERP) waveforms are the summation of many overlapping signals. Changes in the peak or mean amplitude of a waveform over a given time period, therefore, cannot reliably be attributed to a particular ERP component of ex ante interest, as is the standard approach to ERP analysis. Though this problem is widely recognized, it is not well addressed in practice. Our approach begins by presuming that any observed ERP waveform - at any electrode, for any trial type, and for any participant - is approximately a weighted combination of signals from an underlying set of what we refer to as principle ERPs, or pERPs. We propose an accessible approach to analyzing complete ERP waveforms in terms of their underlying pERPs. First, we propose the principle ERP reduction (pERP-RED) algorithm for investigators to estimate a suitable set of pERPs from their data, which may span multiple tasks. Next, we provide tools and illustrations of pERP-space analysis, whereby observed ERPs are decomposed into the amplitudes of the contributing pERPs, which can be contrasted across conditions or groups to reveal which pERPs differ (substantively and/or significantly) between conditions/groups. Differences on all pERPs can be reported together rather than selectively, providing complete information on all components in the waveform, thereby avoiding selective reporting or user discretion regarding the choice of which components or windows to use. The scalp distribution of each pERP can also be plotted for any group/condition. We demonstrate this suite of tools through simulations and on real data collected from multiple experiments on participants diagnosed with Autism Spectrum Disorder and Attention Deficit Hyperactivity Disorder. Software for conducting these analyses is provided in the pERPred package for R.

Indexed as

AlgorithmsSignal Processing, Computer-AssistedAttention Deficit Disorder with HyperactivityAutism Spectrum DisorderBrainChildChild, PreschoolElectrodesElectroencephalographyEvoked PotentialsFemaleHumansMaleAttention deficit hyperactivity disorder (ADHD)Autism spectrum disorder (ASD)EEGERPICAPCA

Identifiers

PMID32087372
PMCPMC7594508
OpenAlexW3007300315

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.