Evidence map›Paper›PMID 26150785›Full record

ArticleFrontiers in neuroinformatics2015

The PREP pipeline: standardized preprocessing for large-scale EEG analysis.

Nima Bigdely-Shamlo, Tim Mullen, Christian Kothe, Kyung-Min Su, Kay A Robbins

Abstract read
In one paragraph

Article in Frontiers in neuroinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 525 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
525citing papers in PubMed, 1 pooled it
–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

525 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Trial
  4. Trial
  5. Trial
  6. Trial
  7. Trial
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Rhythmic stimulation elicits multiple, concurrent neural responses.Cerebral cortex (New York, N.Y. : 1991) · 2026
    Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

465 more citing papers are in PubMed but not listed here.

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.

Nima Bigdely-ShamloSyntrogi Inc. San Diego, CA, USA.
Tim MullenSyntrogi Inc. San Diego, CA, USA.
Christian KotheSyntrogi Inc. San Diego, CA, USA ; Swartz Center for Computational Neuroscience, University of California San Diego, La Jolla, CA, USA.
Kyung-Min SuDepartment of Computer Science, University of Texas at San Antonio San Antonio, TX, USA.
Kay A RobbinsDepartment of Computer Science, University of Texas at San Antonio San Antonio, TX, USA.

Funding

A Human Electrophysiology, Associated Anatomic Data and Integrated Tool ResourceR01MH084819 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI GRETHE, JEFFREY S., MAKEIG, SCOTT · 2009 to 2011
$1.0M
NIMH NIH HHS R01 MH084819
6 · The paper itself

Abstract

The technology to collect brain imaging and physiological measures has become portable and ubiquitous, opening the possibility of large-scale analysis of real-world human imaging. By its nature, such data is large and complex, making automated processing essential. This paper shows how lack of attention to the very early stages of an EEG preprocessing pipeline can reduce the signal-to-noise ratio and introduce unwanted artifacts into the data, particularly for computations done in single precision. We demonstrate that ordinary average referencing improves the signal-to-noise ratio, but that noisy channels can contaminate the results. We also show that identification of noisy channels depends on the reference and examine the complex interaction of filtering, noisy channel identification, and referencing. We introduce a multi-stage robust referencing scheme to deal with the noisy channel-reference interaction. We propose a standardized early-stage EEG processing pipeline (PREP) and discuss the application of the pipeline to more than 600 EEG datasets. The pipeline includes an automatically generated report for each dataset processed. Users can download the PREP pipeline as a freely available MATLAB library from http://eegstudy.org/prepcode.

Indexed as

artifactBCILABbig dataEEGEEGLABmachine learningpreprocessing

Identifiers

PMID26150785
PMCPMC4471356

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.