Evidence map›Paper›PMID 33043903›Full record

ArticleJournal of neural engineering2020

Adaptive virtual referencing for the extraction of extracellularly recorded action potentials in noisy environments.

Corey E Cruttenden, Wei Zhu, Yi Zhang, Soo Han Soon, Xiao-Hong Zhu, Wei Chen, Rajesh Rajamani

Abstract read
In one paragraph

Article in Journal of neural engineering, 2020. 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
–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

1 citing paper in PubMed.

  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

7 authors.

Corey E CruttendenDepartment of Mechanical Engineering, University of Minnesota, Minneapolis, MN, United States of America.
Wei ZhuCenter for Magnetic Resonance Research (CMRR), Radiology Department, University of Minnesota, Minneapolis, MN, United States of America.
Yi ZhangCenter for Magnetic Resonance Research (CMRR), Radiology Department, University of Minnesota, Minneapolis, MN, United States of America.
Soo Han SoonCenter for Magnetic Resonance Research (CMRR), Radiology Department, University of Minnesota, Minneapolis, MN, United States of America.
Xiao-Hong ZhuCenter for Magnetic Resonance Research (CMRR), Radiology Department, University of Minnesota, Minneapolis, MN, United States of America.
Wei ChenCenter for Magnetic Resonance Research (CMRR), Radiology Department, University of Minnesota, Minneapolis, MN, United States of America.
Rajesh RajamaniDepartment of Mechanical Engineering, University of Minnesota, Minneapolis, MN, United States of America.ORCID 0000-0001-9931-7419

Funding

TRD4 - Ultrahigh Field Engineering and SafetyP41EB027061 · NIBIB · UNIVERSITY OF MINNESOTA · PI Gregory John Metzger · 2019 to 2026
$11.7M
Integrated fMRI Methods to Study Neurophysiology and Circuit Dynamics at Laminar and Columnar LevelR01MH111413 · NIMH · UNIVERSITY OF MINNESOTA · PI CHEN, WEI · 2016 to 2020
$4.4M
Institutional Center Cores for Advanced NeuroimagingP30NS076408 · NINDS · UNIVERSITY OF MINNESOTA · PI UGURBIL, KAMIL · 2012 to 2020
$4.2M
Ultra High Field (16.4 Tesla) Animal MRI/MRS SystemS10RR025031 · NCRR · UNIVERSITY OF MINNESOTA · PI GARWOOD, MICHAEL · 2008 to 2008
$2.0M
NCRR NIH HHS S10 RR025031NIBIB NIH HHS P41 EB027061NIMH NIH HHS R01 MH111413NINDS NIH HHS P30 NS076408
6 · The paper itself

Abstract

objectiveRemoval of common mode noise and artifacts from extracellularly measured action potentials, herein referred to as spikes, recorded with multi-electrode arrays (MEAs) which included severe noise and artifacts generated by an ultrahigh field (UHF) 16.4 Tesla magnetic resonance imaging (MRI) scanner. APPROACH: An adaptive virtual referencing (AVR) algorithm is used to remove artifacts and thus enable extraction of neural spike signals from extracellular recordings in anesthetized rat brains. A 16-channel MEA with 150-micron inter-site spacing is used, and a virtual reference is created by spatially averaging the 16 signal channels which results in a reference signal without extracellular spiking activity while preserving common mode noise and artifacts. This virtual reference signal is then used as the input to an adaptive FIR filter which optimally scales and time-shifts the reference to each specific electrode site to remove the artifacts and noise. MAIN

resultsBy removing artifacts and reducing noise, the neural spikes at each electrode site can be well extracted, even from data originally recorded with a high noise floor due to electromagnetic interference and artifacts generated by a 16.4T MRI scanner. The AVR method enables many more spikes to be detected than would otherwise be possible. Further, the filtered spike waveforms can be well separated from each other using PCA feature extraction and semi-supervised k-means clustering. While data in a 16.4T MRI scanner contains significantly more noise and artifacts, the developed AVR method enables similar data quality to be extracted as recorded on benchtop experiments outside the MRI scanner. SIGNIFICANCE: AVR of extracellular spike signals recorded with MEAs has not been previously reported and fills a technical need by enabling low-noise extracellular spike extraction in noisy and challenging environments such as UHF MRI that will enable further study of neuro-vascular coupling at UHF.

Indexed as

Action PotentialsAlgorithmsArtifactsBrainAnimalsFemaleRatsRats, Sprague-DawleySignal Processing, Computer-Assisted

Identifiers

PMID33043903
PMCPMC8118086

What OpenQuestion holds

Textmetadata
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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.